From 27f4778f9edb6a05110e2d661b24219b669d12cd Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 24 Apr 2020 12:51:53 +0200 Subject: [PATCH 01/93] first version of spec 3 --- spec/baseline.spec.json | 101 ++ spec/deployment.spec.json | 268 +++++ spec/detections.spec.json | 161 +++ spec/{v2 => }/lookups.spec.json | 0 spec/{v2 => }/macros.spec.json | 0 spec/response.spec.json | 120 ++ spec/response_task.spec.json | 151 +++ spec/stories.spec.json | 109 ++ spec/v1/analytic_story.json.spec | 163 --- spec/v1/contextual_search.json.spec | 202 ---- spec/v1/detection_search.json.spec | 638 ---------- spec/v1/investigative_search.json.spec | 220 ---- spec/v1/support_search.json.spec | 218 ---- spec/v2/baselines.spec.json | 499 -------- spec/v2/detections.spec.json | 1526 ------------------------ spec/v2/investigations.spec.json | 401 ------- spec/v2/responses.spec.json | 340 ------ spec/v2/story.spec.json | 271 ----- 18 files changed, 910 insertions(+), 4478 deletions(-) create mode 100644 spec/baseline.spec.json create mode 100644 spec/deployment.spec.json create mode 100644 spec/detections.spec.json rename spec/{v2 => }/lookups.spec.json (100%) rename spec/{v2 => }/macros.spec.json (100%) create mode 100644 spec/response.spec.json create mode 100644 spec/response_task.spec.json create mode 100644 spec/stories.spec.json delete mode 100644 spec/v1/analytic_story.json.spec delete mode 100644 spec/v1/contextual_search.json.spec delete mode 100644 spec/v1/detection_search.json.spec delete mode 100644 spec/v1/investigative_search.json.spec delete mode 100644 spec/v1/support_search.json.spec delete mode 100644 spec/v2/baselines.spec.json delete mode 100644 spec/v2/detections.spec.json delete mode 100644 spec/v2/investigations.spec.json delete mode 100644 spec/v2/responses.spec.json delete mode 100644 spec/v2/story.spec.json diff --git a/spec/baseline.spec.json b/spec/baseline.spec.json new file mode 100644 index 0000000000..258ebee0ea --- /dev/null +++ b/spec/baseline.spec.json @@ -0,0 +1,101 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema", + "$id": "http://example.com/example.json", + "type": "object", + "title": "Baseline Schema", + "description": "schema for baselines", + "default": {}, + "additionalProperties": true, + "required": [ + "name", + "id", + "version", + "date", + "description", + "author", + "search", + "tags" + ], + "properties": { + "name": { + "$id": "#/properties/name", + "type": "string", + "title": "Name of baseline", + "default": "", + "examples": [ + "Previously Seen AWS Regions" + ] + }, + "id": { + "$id": "#/properties/id", + "type": "string", + "description": "UUID as unique identifier", + "default": "", + "examples": [ + "fc0edc95-ff2b-48b0-9f6f-63da3789fd63" + ] + }, + "version": { + "$id": "#/properties/version", + "type": "integer", + "description": "version of baseline, e.g. 1 or 2 ...", + "default": 0, + "examples": [ + 1 + ] + }, + "date": { + "$id": "#/properties/date", + "type": "string", + "description": "date of creation or modification, format yyyy-mm-dd", + "default": "", + "examples": [ + "2019-12-06" + ] + }, + "description": { + "$id": "#/properties/description", + "type": "string", + "description": "A detailed description of the baseline ", + "default": "", + "examples": [ + "This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days" + ] + }, + "author": { + "$id": "#/properties/author", + "type": "string", + "description": "Author of the baseline", + "default": "", + "examples": [ + "Bahvin Patel, Splunk" + ] + }, + "search": { + "$id": "#/properties/search", + "type": "string", + "description": "The Splunk search for the baseline", + "default": "", + "examples": [ + "sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" + ] + }, + "tags": { + "$id": "#/properties/tags", + "type": "object", + "description": "An array of key value pairs for tagging", + "default": {}, + "examples": [ + { + "custom_key": "custom_value", + "analytics_story": "suspicious_aws_ec2_activities" + } + ], + "additionalProperties": true, + "required": [], + "properties": null, + "minItems": 1, + "uniqueItems": true + } + } +} diff --git a/spec/deployment.spec.json b/spec/deployment.spec.json new file mode 100644 index 0000000000..aa9a2aac43 --- /dev/null +++ b/spec/deployment.spec.json @@ -0,0 +1,268 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema", + "$id": "http://example.com/example.json", + "type": "object", + "title": "Deployment Schema", + "description": "schema for deployment", + "default": {}, + "additionalProperties": true, + "required": [ + "name", + "id", + "date", + "description", + "scheduling", + "tags" + ], + "properties": { + "name": { + "$id": "#/properties/name", + "type": "string", + "description": "Name of deployment configuration", + "default": "", + "examples": [ + "Deployment Configuration all Detections" + ] + }, + "id": { + "$id": "#/properties/id", + "type": "string", + "description": "uuid as unique identifier", + "default": "", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ] + }, + "date": { + "$id": "#/properties/date", + "type": "string", + "description": "date of creation or modification, format yyyy-mm-dd", + "default": "", + "examples": [ + "2019-12-06" + ] + }, + "description": { + "$id": "#/properties/description", + "type": "string", + "description": "description of the deployment configuration", + "default": "", + "examples": [ + "This deployment configuration provides a standard scheduling policy over all rules." + ] + }, + "scheduling": { + "$id": "#/properties/scheduling", + "type": "object", + "description": "allows to set scheduling parameter", + "default": {}, + "examples": [ + { + "latest_time": "now", + "cron_schedule": "*/10 * * * *", + "earliest_time": "-10m", + "schedule_window": "auto" + } + ], + "additionalProperties": true, + "required": [ + "cron_schedule", + "earliest_time", + "latest_time" + ], + "properties": { + "cron_schedule": { + "$id": "#/properties/scheduling/properties/cron_schedule", + "type": "string", + "description": "Cron schedule to schedule the Splunk searches.", + "default": "", + "examples": [ + "*/10 * * * *" + ] + }, + "earliest_time": { + "$id": "#/properties/scheduling/properties/earliest_time", + "type": "string", + "description": "earliest time of search", + "default": "", + "examples": [ + "-10m" + ] + }, + "latest_time": { + "$id": "#/properties/scheduling/properties/latest_time", + "type": "string", + "description": "latest time of search", + "default": "", + "examples": [ + "now" + ] + }, + "schedule_window": { + "$id": "#/properties/scheduling/properties/schedule_window", + "type": "string", + "description": "schedule window for search", + "default": "", + "examples": [ + "auto" + ] + } + } + }, + "alert_action": { + "$id": "#/properties/alert_action", + "type": "object", + "description": "Set alert action parameter for search", + "default": {}, + "examples": [ + { + "email": { + "to": "test@test.com", + "subject": "Splunk Alert $name$", + "message": "Splunk Alert $name$ triggered %fields%" + }, + "index": { + "name": "asx" + }, + "notable": { + "rule_description": "%description%", + "rule_title": "%name%" + } + } + ], + "additionalProperties": true, + "required": [ + "index" + ], + "properties": { + "index": { + "$id": "#/properties/alert_action/properties/index", + "type": "object", + "description": "By enabling it, the results are stored in another index", + "default": {}, + "examples": [ + { + "name": "asx" + } + ], + "additionalProperties": true, + "required": [ + "name" + ], + "properties": { + "name": { + "$id": "#/properties/alert_action/properties/index/properties/name", + "type": "string", + "description": "Name of the index", + "default": "", + "examples": [ + "asx" + ] + } + } + }, + "notable": { + "$id": "#/properties/alert_action/properties/notable", + "type": "object", + "description": "By enabling it, a notable is generated", + "default": {}, + "examples": [ + { + "rule_title": "%name%", + "rule_description": "%description%" + } + ], + "additionalProperties": true, + "required": [ + "rule_title", + "rule_description" + ], + "properties": { + "rule_title": { + "$id": "#/properties/alert_action/properties/notable/properties/rule_title", + "type": "string", + "description": "Rule title of the notable event", + "default": "", + "examples": [ + "%name%" + ] + }, + "rule_description": { + "$id": "#/properties/alert_action/properties/notable/properties/rule_description", + "type": "string", + "description": "Rule description of the notable event", + "default": "", + "examples": [ + "%description%" + ] + } + } + }, + "email": { + "$id": "#/properties/alert_action/properties/email", + "type": "object", + "description": "By enabling it, an email is sent with the results", + "default": {}, + "examples": [ + { + "subject": "Splunk Alert $name$", + "message": "Splunk Alert $name$ triggered %fields%", + "to": "test@test.com" + } + ], + "additionalProperties": true, + "required": [ + "to", + "subject", + "message" + ], + "properties": { + "to": { + "$id": "#/properties/alert_action/properties/email/properties/to", + "type": "string", + "description": "Recipient of email", + "default": "", + "examples": [ + "test@test.com" + ] + }, + "subject": { + "$id": "#/properties/alert_action/properties/email/properties/subject", + "type": "string", + "description": "Subject of email", + "default": "", + "examples": [ + "Splunk Alert $name$" + ] + }, + "message": { + "$id": "#/properties/alert_action/properties/email/properties/message", + "type": "string", + "description": "message of email", + "default": "", + "examples": [ + "Splunk Alert $name$ triggered %fields%" + ] + } + } + } + } + }, + "tags": { + "$id": "#/properties/tags", + "type": "object", + "description": "An array of key value pairs for tagging", + "default": {}, + "examples": [ + { + "analytics_story": "credential_dumping" + } + ], + "additionalProperties": true, + "required": [], + "properties": null, + "minItems": 1, + "uniqueItems": true + } + } +} diff --git a/spec/detections.spec.json b/spec/detections.spec.json new file mode 100644 index 0000000000..af19e8233f --- /dev/null +++ b/spec/detections.spec.json @@ -0,0 +1,161 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema", + "$id": "http://example.com/example.json", + "type": "object", + "title": "Detection Schema", + "description": "schema for detections", + "default": {}, + "additionalProperties": true, + "required": [ + "name", + "id", + "version", + "date", + "description", + "type", + "references", + "author", + "search", + "knwon_false_positives", + "tags" + ], + "properties": { + "name": { + "$id": "#/properties/name", + "type": "string", + "title": "Name of detection", + "default": "", + "examples": [ + "Access LSASS Memory for Dump Creation" + ] + }, + "id": { + "$id": "#/properties/id", + "type": "string", + "description": "UUID as unique identifier", + "default": "", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ] + }, + "version": { + "$id": "#/properties/version", + "type": "integer", + "description": "version of detection, e.g. 1 or 2 ...", + "default": 0, + "examples": [ + 2 + ] + }, + "date": { + "$id": "#/properties/date", + "type": "string", + "description": "date of creation or modification, format yyyy-mm-dd", + "default": "", + "examples": [ + "2019-12-06" + ] + }, + "description": { + "$id": "#/properties/description", + "type": "string", + "description": "A detailed description of the detection", + "default": "", + "examples": [ + "dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump." + ] + }, + "how_to_implement": { + "$id": "#/properties/how_to_implement", + "type": "string", + "description": "information about how to implement. Only needed for non standard implementations.", + "default": "", + "examples": [ + "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." + ] + }, + "type": { + "$id": "#/properties/type", + "type": "string", + "description": "type of detection", + "default": "", + "examples": [ + "ESCU" + ], + "items": { + "enum": [ + "ESCU", + "SSE", + "RBA" + ] + "type": "string" + } + }, + "references": { + "$id": "#/properties/references", + "type": "array", + "description": "A list of references for this detection", + "default": [], + "examples": [ + [ + "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" + ] + ], + "additionalItems": true, + "items": { + "$id": "#/properties/references/items", + "type": "string", + "title": "The Items Schema", + "description": "An explanation about the purpose of this instance.", + "default": "", + "examples": [ + "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" + ] + } + }, + "author": { + "$id": "#/properties/author", + "type": "string", + "description": "Author of the detection", + "default": "", + "examples": [ + "Patrick Bareiss, Splunk" + ] + }, + "search": { + "$id": "#/properties/search", + "type": "string", + "description": "The Splunk search for the detection", + "default": "", + "examples": [ + "`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter`" + ] + }, + "knwon_false_positives": { + "$id": "#/properties/knwon_false_positives", + "type": "string", + "description": "known false postives", + "default": "", + "examples": [ + "Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual." + ] + }, + "tags": { + "$id": "#/properties/tags", + "type": "object", + "description": "An array of key value pairs for tagging", + "default": {}, + "examples": [ + { + "custom_key": "custom_value", + "analytics_story": "credential_dumping" + } + ], + "additionalProperties": true, + "required": [], + "properties": null, + "minItems": 1, + "uniqueItems": true + } + } +} diff --git a/spec/v2/lookups.spec.json b/spec/lookups.spec.json similarity index 100% rename from spec/v2/lookups.spec.json rename to spec/lookups.spec.json diff --git a/spec/v2/macros.spec.json b/spec/macros.spec.json similarity index 100% rename from spec/v2/macros.spec.json rename to spec/macros.spec.json diff --git a/spec/response.spec.json b/spec/response.spec.json new file mode 100644 index 0000000000..9015969b59 --- /dev/null +++ b/spec/response.spec.json @@ -0,0 +1,120 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema", + "$id": "http://example.com/example.json", + "type": "object", + "title": "Response Schema", + "description": "schema for response", + "default": {}, + "additionalProperties": true, + "required": [ + "name", + "id", + "version", + "date", + "description", + "author", + "response_tasks", + "tags" + ], + "properties": { + "name": { + "$id": "#/properties/name", + "type": "string", + "description": "Name of response", + "default": "", + "examples": [ + "Response Example" + ] + }, + "id": { + "$id": "#/properties/id", + "type": "string", + "description": "UUID as unique identifier", + "default": "", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ] + }, + "version": { + "$id": "#/properties/version", + "type": "integer", + "description": "version of detection, e.g. 1 or 2 ...", + "default": 0, + "examples": [ + 1 + ] + }, + "date": { + "$id": "#/properties/date", + "type": "string", + "description": "version of detection, e.g. 1 or 2 ...", + "default": "", + "examples": [ + "2019-12-06" + ] + }, + "description": { + "$id": "#/properties/description", + "type": "string", + "description": "Description of response", + "default": "", + "examples": [ + "Response example." + ] + }, + "author": { + "$id": "#/properties/author", + "type": "string", + "description": "Author of the response", + "default": "", + "examples": [ + "Rico Valdez, Patrick Bareiß, Splunk" + ] + }, + "response_tasks": { + "$id": "#/properties/response_tasks", + "type": "object", + "description": "Response tasks divided into phases", + "default": {}, + "examples": [ + { + "identification": [ + { + "id": "c36f3f48-e0bb-4c20-a62a-cdc8f6418892", + "name": "Investigate Indicator of Compromise Hash" + }, + { + "name": "Investigate Domains", + "id": "0dc849b2-2eb4-4fd2-add1-b6cc475765f0" + } + ], + "another_phase": [ + { + "id": "7c72d944-3995-4485-8e57-67b4c353989b", + "name": "Another investigation" + } + ] + } + ], + "additionalProperties": true, + "required": [], + "properties": null + }, + "tags": { + "$id": "#/properties/tags", + "type": "object", + "description": "An array of key value pairs for tagging", + "default": {}, + "examples": [ + { + "analytics_story": "credential_dumping" + } + ], + "additionalProperties": true, + "required": [], + "properties": null, + "minItems": 1, + "uniqueItems": true + } + } +} diff --git a/spec/response_task.spec.json b/spec/response_task.spec.json new file mode 100644 index 0000000000..9e86cfe949 --- /dev/null +++ b/spec/response_task.spec.json @@ -0,0 +1,151 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema", + "$id": "http://example.com/example.json", + "type": "object", + "title": "Response Task Schema", + "description": "schema for response tasks", + "default": {}, + "additionalProperties": true, + "required": [ + "name", + "id", + "version", + "date", + "description", + "author", + "inputs" + ], + "properties": { + "name": { + "$id": "#/properties/name", + "type": "string", + "description": "Namo fo response task", + "default": "", + "examples": [ + "Response Tas Example" + ] + }, + "id": { + "$id": "#/properties/id", + "type": "string", + "description": "UUID as unique identifier", + "default": "", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ] + }, + "version": { + "$id": "#/properties/version", + "type": "integer", + "description": "version of detection, e.g. 1 or 2 ...", + "default": 0, + "examples": [ + 3 + ] + }, + "date": { + "$id": "#/properties/date", + "type": "string", + "description": "date of creation or modification, format yyyy-mm-dd", + "default": "", + "examples": [ + "2019-12-06" + ] + }, + "description": { + "$id": "#/properties/description", + "type": "string", + "description": "Description of response task", + "default": "", + "examples": [ + "Response Task example description" + ] + }, + "author": { + "$id": "#/properties/author", + "type": "string", + "description": "Author of response task", + "default": "", + "examples": [ + "Patrick Bareiß, Splunk" + ] + }, + "inputs": { + "$id": "#/properties/inputs", + "type": "array", + "description": "Inputs used from the response task", + "default": [], + "examples": [ + [ + "lookup_file" + ] + ] + }, + "search": { + "$id": "#/properties/search", + "type": "string", + "description": "Search as response task", + "default": "", + "examples": [ + "`sysmon` EventCode=1 | search [| inputlookup %lookup_file% ] | stats count by dest user process_name" + ] + }, + "playbook": { + "$id": "#/properties/playbook", + "type": "object", + "description": "A phantom playbook as response task", + "default": {}, + "examples": [ + { + "url_json": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json", + "url_python": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py", + "name": "lets_encrypt_domain_investigate.json" + } + ], + "additionalProperties": true, + "required": [ + "name", + "url_json", + "url_python" + ], + "properties": { + "name": { + "$id": "#/properties/playbook/properties/name", + "type": "string", + "description": "Name of Phantom Playbook", + "default": "", + "examples": [ + "lets_encrypt_domain_investigate.json" + ] + }, + "url_json": { + "$id": "#/properties/playbook/properties/url_json", + "type": "string", + "description": "URL for phantom playbook json file", + "default": "", + "examples": [ + "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json" + ] + }, + "url_python": { + "$id": "#/properties/playbook/properties/url_python", + "type": "string", + "description": "URL for phantom playbook python file", + "default": "", + "examples": [ + "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py" + ] + } + } + }, + "dashboard": { + "$id": "#/properties/dashboard", + "type": "string", + "description": "Name of dashboard used as response task", + "default": "", + "examples": [ + "process_chain_analysis.json" + ] + } + } +} diff --git a/spec/stories.spec.json b/spec/stories.spec.json new file mode 100644 index 0000000000..508a21e5c0 --- /dev/null +++ b/spec/stories.spec.json @@ -0,0 +1,109 @@ +{ + "$schema": "http://json-schema.org/draft-07/schema", + "$id": "http://example.com/example.json", + "type": "object", + "title": "Analytics Story Schema", + "description": "schema analytics story", + "default": {}, + "additionalProperties": true, + "required": [ + "name", + "id", + "version", + "date", + "description", + "narrative", + "author", + "tags" + ], + "properties": { + "name": { + "$id": "#/properties/name", + "type": "string", + "description": "Name of the Analytics Story", + "default": "", + "examples": [ + "Credential Dumping" + ] + }, + "id": { + "$id": "#/properties/id", + "type": "string", + "description": "UUID as unique identifier", + "default": "", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ] + }, + "version": { + "$id": "#/properties/version", + "type": "integer", + "description": "version of analytics story, e.g. 1 or 2 ...", + "default": 0, + "examples": [ + 1 + ] + }, + "date": { + "$id": "#/properties/date", + "type": "string", + "description": "date of creation or modification, format yyyy-mm-dd", + "default": "", + "examples": [ + "2019-12-06" + ] + }, + "description": { + "$id": "#/properties/description", + "type": "string", + "description": "description of the analytics story", + "default": "", + "examples": [ + "Uncover activity consistent with credential dumping, a technique where attackers compromise systems and attempt to obtain and exfiltrate passwords." + ] + }, + "narrative": { + "$id": "#/properties/narrative", + "type": "string", + "description": "narrative of the analytics story", + "default": "", + "examples": [ + "gathering credentials from a target system, often hashed or encrypted, is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems." + ] + }, + "author": { + "$id": "#/properties/author", + "type": "string", + "description": "Author of the analytics story", + "default": "", + "examples": [ + "Rico Valdez, Patrick Bareiß, Splunk" + ] + }, + "search": { + "$id": "#/properties/search", + "type": "string", + "description": "An additional Splunk search, which uses the result of the detections", + "default": "", + "examples": [ + "index=asx mitre_id=t1003 | stats values(source) as detections values(process) as processes values(user) as users values(_time) as time count by dest" + ] + }, + "tags": { + "$id": "#/properties/tags", + "type": "object", + "description": "An explanation about the purpose of this instance.", + "default": {}, + "examples": [ + { + "analytics_story": "credential_dumping" + } + ], + "additionalProperties": true, + "required": [], + "properties": null, + "minItems": 1, + "maxItems": 1 + } + } +} diff --git a/spec/v1/analytic_story.json.spec b/spec/v1/analytic_story.json.spec deleted file mode 100644 index aff21a1eb0..0000000000 --- a/spec/v1/analytic_story.json.spec +++ /dev/null @@ -1,163 +0,0 @@ -{ - "$schema": "http://json-schema.org/draft-04/schema#", - "title": "Analytic Story Manifest", - "description": "The fields that make up the manifest of a version 1 Analytic Story", - "type": "object", - "properties": { - "category": { - "description": "The category to which the Analytic Story belongs", - "enum": ["Abuse", "Adversary Tactics", "Best Practices", "Cloud Security", "Malware", "Vulnerability"] - }, - "channel": { - "description": "A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Content Updates are in the ESCU channel", - "type": "string" - }, - "creation_date": { - "description": "The date this story was created", - "type": "string" - }, - "description": { - "description": "A high-level description or goal of the Analytic Story", - "type": "string" - }, - "id": { - "description": "A unique identifier for the Analytic Story", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person maintaining this Analytic Story" - }, - "email": { - "type": "string", - "description": "Email address of the person maintaining this Analytic Story" - }, - "name": { - "type": "string", - "description": "Name of the person maintaining this Analytic Story" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "modification_date": { - "description": "The date of the most recent modification to this Analytic Story", - "type": "string" - }, - "name": { - "description": "The name of the Analytic Story", - "type": "string" - }, - "narrative": { - "description": "Long-form text that describes the Analytic Story and the rationale behind it, as well as an overview of the included searches, and how they enable the story", - "type": "string" - }, - "original_authors": { - "description": "An array of the original authors of the Analytic Story", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person who originally authored the Analytic Story" - }, - "email": { - "type": "string", - "description": "Email address of the person who originally authored the Analytic Story" - }, - "name": { - "type": "string", - "description": "Name of the person who originally authored the Analytic Story" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "references": { - "description": "An array of URLs that give information about the problem the story is addressing", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "searches": { - "type": "object", - "description": "The different types of searches", - "properties": { - "contextual_searches": { - "description": "The names of the searches used to help scope and provide context to the detection searches", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "detection_searches": { - "description": "The names of the searches used to detect the behaviors detailed within the Analytic Story", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "investigative_searches": { - "description": "The names of the searches used to investigate further after a detection search uncovers events", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "support_searches": { - "description": "The names of the searches that create intermediate data used by the other searches or to provide baseline information to better understand your environment", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - } - }, - "additionalProperties": false - }, - "spec_version": { - "description": "The version of the Analytic Story specification this manifest follows", - "type": "integer" - }, - "version": { - "description": "The version of the Analytic Story", - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "category", - "channel", - "creation_date", - "description", - "id", - "maintainers", - "modification_date", - "narrative", - "original_authors", - "name", - "references", - "searches", - "spec_version", - "version" - ] -} \ No newline at end of file diff --git a/spec/v1/contextual_search.json.spec b/spec/v1/contextual_search.json.spec deleted file mode 100644 index 16bee6a7b0..0000000000 --- a/spec/v1/contextual_search.json.spec +++ /dev/null @@ -1,202 +0,0 @@ -{ - "$schema": "http://json-schema.org/draft-04/schema#", - "title": "Contextual Search Manifest", - "description": "The fields that make up the manifest of a version 1 contextual search", - "type": "object", - "properties": { - "channel": { - "description": "A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Updates are in the ESCU channel", - "type": "string" - }, - "creation_date": { - "description": "The date the story manifest was created", - "type": "string" - }, - "data_metadata": { - "type": "object", - "description": "Information about the date being ingested", - "properties": { - "data_models": { - "description": "A list of data models, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "type": "array", - "items": { - "enum": ["Apache", "AWS", "Bro", "Microsoft Windows", "Linux", "macOS", "Netbackup", "Splunk Enterprise", "Splunk Enterprise Security", "Splunk Stream", "Active Directory", "Bluecoat", "Carbon Black Response", "Carbon Black Protect", "CrowdStrike Falcon", "Microsoft Exchange", "Nessus", "Palo Alto Firewall", "Qualys" , "Sysmon", "Tanium", "Ziften"] - }, - "minItems": 0, - "uniqueItems": true - } - }, - "additionalProperties": false, - "required": ["data_source", "providing_technologies"] - }, - "fields_required": { - "description": "A list of fields that need to be in the result of the detection search for the search to be successful", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person maintaining this search" - }, - "email": { - "type": "string", - "description": "Email address of the person maintaining this search" - }, - "name": { - "type": "string", - "description": "Name of the person maintaining this search" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person who originally authored the search" - }, - "email": { - "type": "string", - "description": "Email address of the person who originally authored the search" - }, - "name": { - "type": "string", - "description": "Name of the person who originally authored the search" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "search": { - "description": "The search (in SPL) executed within core Splunk", - "type": "string" - }, - "search_description": { - "description": "A description of what the search is designed to detect", - "type": "string" - }, - "search_id": { - "description": "The unique identifier for the search", - "type": "string" - }, - "search_name": { - "description": "The name of the search", - "type": "string" - }, - "search_type": { - "description": "The type of the search", - "enum": ["detection", "investigative", "contextual", "support"] - }, - "search_window": { - "type": "object", - "description": "The fields associated on when this search should run relative to the detection event", - "properties": { - "earliest_time_offset": { - "description": "The number of seconds into the past from the event time the search should cover", - "type": "integer" - }, - "latest_time_offset": { - "description": "The number of seconds into the future from the event time the search should cover", - "type": "integer" - } - }, - "additionalProperties": false, - "required": ["latest_time_offset", "earliest_time_offset"] - }, - "spec_version": { - "description": "The version of the contextual search specification this manifest follows", - "type": "integer" - }, - "status": { - "description": "The current status of the search - development, experimental, production", - "enum": ["development", "experimental", "production"] - }, - "team_notes": { - "description": "Notes for the team about the search", - "type": "string" - }, - "version": { - "description": "The version of the search", - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "channel", - "creation_date", - "data_metadata", - "fields_required", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "search", - "search_description", - "search_id", - "search_type", - "search_window", - "spec_version", - "version" - ] -} diff --git a/spec/v1/detection_search.json.spec b/spec/v1/detection_search.json.spec deleted file mode 100644 index 94e8ed943d..0000000000 --- a/spec/v1/detection_search.json.spec +++ /dev/null @@ -1,638 +0,0 @@ -{ - "$schema": "http://json-schema.org/draft-04/schema#", - "title": "Detection Search Manifest", - "description": "The fields that make up the manifest of a version 1 detection search", - "type": "object", - "properties": { - "asset_type": { - "description": "Designates the type of asset being investigated", - "type": "string" - }, - "channel": { - "description": "A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Updates are in the ESCU channel", - "type": "string" - }, - "confidence": { - "description": "Confidence that detected behavior is malicious", - "type": "string" - }, - "correlation_rule": { - "type": "object", - "description": "Various fields to enhance usability in Enterprise Security", - "properties": { - "notable": { - "type": "object", - "description": "Various fields associated with creating a notable event", - "properties": { - "rule_description": { - "description": "Description of the notable event that will display in Incident Review", - "type": "string" - }, - "rule_title": { - "description": "Title of the notable event that will display in Incident Review", - "type": "string" - }, - "nes_fields": { - "description": "A list of suggested fields to be used for notable-event suppression", - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "rule_description", - "rule_title", - "nes_fields" - ] - }, - "risk": { - "type": "object", - "description": "Fields associated with assigning risk to objects", - "properties": { - "risk_object": { - "description": "TThe field to which you are assigning risk", - "type": "string" - }, - "risk_object_type": { - "description": "The type of object to which you’re assigning risk", - "type": "array", - "items": { - "type": "string", - "enum": [ - "system", - "user", - "other" - ] - }, - "minItems": 0, - "maxItems": 1, - "uniqueItems": true - }, - "risk_score": { - "description": "Score assigned to risk_object", - "type": "integer" - } - }, - "additionalProperties": false, - "required": [ - "risk_score", - "risk_object", - "risk_object_type" - ] - }, - "suppress": { - "type": "object", - "description": "Fields associated with suppressing the creation of multiple alerts", - "properties": { - "suppress_fields": { - "description": "The fields to base the suppression on", - "type": "string" - }, - "suppress_period": { - "description": "The length of time the suppression should be in effect", - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "suppress_fields", - "suppress_period" - ] - } - }, - "additionalProperties": false - }, - "creation_date": { - "description": "The date the story manifest was created", - "type": "string" - }, - "phantom_playbooks": { - "description": "Array of recommended playbooks", - "type": "array", - "items": { - "type": "object", - "properties": { - "phantom_server": { - "type": "string", - "description": "IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname)" - }, - "playbook_name": { - "type": "string", - "description": "Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment" - }, - "playbook_display_name": { - "type": "string", - "description": "Display Name of the playbook. Capitalize each letter and remove underscores from playbook_name field. Eg: Simple Network Enrichment" - }, - "playbook_url": { - "type": "string", - "description": "Url of the playbook on Phantom website." - }, - "sensitivity": { - "type": "string", - "description": "TLP colors (White, Green, Amber or Red)" - }, - "severity": { - "type": "string", - "description": "Severity in phantom (High, Medium, Low)" - } - }, - "additionalProperties": false, - "required": [ - "phantom_server", - "playbook_name", - "sensitivity", - "severity", - "playbook_url", - "playbook_display_name" - ] - } - }, - "data_metadata": { - "type": "object", - "description": "Information about the date being ingested", - "properties": { - "data_models": { - "description": "A list of data models, if any, used by this search", - "type": "array", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "uniqueItems": true - }, - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "type": "array", - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "OSquery" - ] - }, - "minItems": 0, - "uniqueItems": true - } - }, - "additionalProperties": false, - "required": [ - "data_source", - "providing_technologies" - ] - }, - "eli5": { - "description": "Explain it like I’m 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert", - "type": "string" - }, - "how_to_implement": { - "description": "A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications", - "type": "string" - }, - "known_false_positives": { - "description": "Scenarios in which detected behavior is benig, coupled with suggestions on how to verify the behavior", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "type": "array", - "items": { - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person maintaining this search" - }, - "email": { - "type": "string", - "description": "Email address of the person maintaining this search" - }, - "name": { - "type": "string", - "description": "Name of the person maintaining this search" - } - }, - "additionalProperties": false, - "required": [ - "name", - "email", - "company" - ] - } - }, - "mappings": { - "type": "object", - "description": "Mappings to various industry standards and frameworks", - "properties": { - "cis20": { - "description": "A list of critical security controls this search helps you implement", - "type": "array", - "items": { - "enum": [ - "CIS 1", - "CIS 2", - "CIS 3", - "CIS 4", - "CIS 5", - "CIS 6", - "CIS 7", - "CIS 8", - "CIS 9", - "CIS 10", - "CIS 11", - "CIS 12", - "CIS 13", - "CIS 14", - "CIS 15", - "CIS 16", - "CIS 17", - "CIS 18", - "CIS 19", - "CIS 20" - ] - }, - "minItems": 0, - "uniqueItems": true - }, - "kill_chain_phases": { - "description": "A list of kill-chain phases to which the search applies", - "type": "array", - "items": { - "enum": [ - "Reconnaissance", - "Weaponization", - "Delivery", - "Exploitation", - "Installation", - "Command and Control", - "Actions on Objectives" - ] - }, - "minItems": 0, - "uniqueItems": true - }, - "mitre_attack": { - "description": "A list of the techniques and tactics identified by the search", - "type": "array", - "items": { - "enum": [ - "Initial Access", - "AppInit DLLs", - "Authentication Package", - "Change Default File Association", - "Credential Dumping", - "Application Shimming", - "Account Discovery", - "Accessibility Features", - "Command-Line Interface", - "Execution", - "Persistence", - "Privilege Escalation", - "Defense Evasion", - "Credential Access", - "Discovery", - "Lateral Movement", - "Collection", - "Exfiltration", - "Command and Control", - "Command and Control Protocol", - "Commonly Used Port", - "Custom Cryptographic Protocol", - "DLL Injection", - "DLL Search Order Hijacking", - "DLL Side-Loading", - "Data Compressed", - "Data Encrypted", - "Data Obfuscation", - "Data Staged", - "Data Transfer Size Limits", - "Data from Local System", - "Data from Network Shared Drive", - "Data from Removable Media", - "Disabling Security Tools", - "Email Collection", - "Execution through API", - "Exfiltration Over Alternative Protocol", - "Exfiltration Over Command and Control Channel", - "Exfiltration Over Other Network Medium", - "Exfiltration Over Physical Medium", - "Exploitation of Vulnerability", - "Fallback Channels", - "File Deletion", - "File System Logical Offsets", - "File System Permissions Weakness", - "File and Directory Discovery", - "Graphical User Interface", - "Hypervisor", - "Indicator Blocking", - "Indicator Removal from Tools", - "Indicator Removal on Host", - "Input Capture", - "InstallUtil", - "Legitimate Credentials", - "Local Network Configuration Discovery", - "Local Network Connections Discovery", - "Local Port Monitor", - "Logon Scripts", - "MSBuild", - "Masquerading", - "Modify Existing Service", - "Modify Registry", - "Multi-Stage Channels", - "Multiband Communication", - "Multilayer Encryption", - "NTFS Extended Attributes", - "Network Service Scanning", - "Network Share Connection Removal", - "Network Sniffing", - "New Service", - "Obfuscated Files or Information", - "Pass the Hash", - "Pass the Ticket", - "Path Interception", - "Peripheral Device Discovery", - "Permission Groups Discovery", - "PowerShell", - "Process Discovery", - "Process Hollowing", - "Query Registry", - "Redundant Access", - "Registry Run Keys / Start Folder", - "Regsvcs/Regasm", - "Regsvr32", - "Remote Desktop Protocol", - "Create Account", - "Remote File Copy", - "Remote Services", - "Remote System Discovery", - "Replication Through Removable Media", - "Rootkit", - "Rundll32", - "Scheduled Task", - "Scheduled Transfer", - "Screen Capture", - "Scripting", - "Security Software Discovery", - "Security Support Provider", - "Service Execution", - "Service Registry Permissions Weakness", - "Shared Webroot", - "Shortcut Modification", - "Software Packing", - "Standard Application Layer Protocol", - "Standard Cryptographic Protocol", - "Standard Non-Application Layer Protocol", - "System Information Discovery", - "System Owner/User Discovery", - "System Service Discovery", - "System Time Discovery", - "Taint Shared Content", - "Third-party Software", - "Timestomp", - "Two-Factor Authentication Interception", - "Uncommonly Used Port", - "Video Capture", - "Valid Accounts", - "Web Service", - "Web Shell", - "Windows Admin Shares", - "Windows Management Instrumentation Event Subscription", - "Windows Management Instrumentation", - "Windows Remote Management", - "Winlogon Helper DLL", - "Exploitation for Privilege Escalation" - ] - }, - "minItems": 0, - "uniqueItems": true - }, - "nist": { - "description": "A list of the NIST controls the search helps you implement", - "type": "array", - "items": { - "enum": [ - "ID.AM", - "ID.RA", - "PR.DS", - "PR.IP", - "PR.AC", - "PR.PT", - "PR.AT", - "PR.MA", - "DE.CM", - "DE.DP", - "DE.AE", - "RS.MI", - "RS.AN", - "RS.RP", - "RS.IM", - "RS.CO", - "RC.IM", - "RC.CO" - ] - }, - "minItems": 0, - "uniqueItems": true - } - }, - "additionalProperties": false - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "type": "array", - "items": { - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person who originally authored the search" - }, - "email": { - "type": "string", - "description": "Email address of the person who originally authored the search" - }, - "name": { - "type": "string", - "description": "Name of the person who originally authored the search" - } - }, - "additionalProperties": false, - "required": [ - "name", - "email", - "company" - ] - } - }, - "references": { - "description": "A list of URLs that give more information about the search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "scheduling": { - "type": "object", - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "type": "string" - } - }, - "additionalProperties": false - }, - "search": { - "description": "The search (in SPL) executed within core Splunk", - "type": "string" - }, - "search_description": { - "description": "A description of what the search is designed to detect", - "type": "string" - }, - "search_id": { - "description": "The unique identifier for the search", - "type": "string" - }, - "search_name": { - "description": "The name of the search", - "type": "string" - }, - "search_type": { - "description": "The type of the search", - "enum": [ - "detection", - "investigative", - "contextual", - "support" - ] - }, - "security_domain": { - "description": "The high-level security area to which the search belongs", - "enum": [ - "access", - "endpoint", - "network", - "threat" - ] - }, - "spec_version": { - "description": "The version of the detection search specification this manifest follows", - "type": "integer" - }, - "status": { - "description": "The current status of the search - development, experimental, production", - "enum": [ - "development", - "experimental", - "production" - ] - }, - "team_notes": { - "description": "Notes for the team about the search", - "type": "string" - }, - "version": { - "description": "The version of the search", - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "channel", - "confidence", - "creation_date", - "data_metadata", - "eli5", - "how_to_implement", - "known_false_positives", - "maintainers", - "modification_date", - "original_authors", - "search", - "search_description", - "search_id", - "search_type", - "security_domain", - "scheduling", - "version" - ] -} \ No newline at end of file diff --git a/spec/v1/investigative_search.json.spec b/spec/v1/investigative_search.json.spec deleted file mode 100644 index 908809e8bd..0000000000 --- a/spec/v1/investigative_search.json.spec +++ /dev/null @@ -1,220 +0,0 @@ -{ - "$schema": "http://json-schema.org/draft-04/schema#", - "title": "Investigative Search Manifest", - "description": "The fields that make up the manifest of a version 1 investigative earch", - "type": "object", - "properties": { - "channel": { - "description": "A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Updates are in the ESCU channel", - "type": "string" - }, - "creation_date": { - "description": "The date the story manifest was created", - "type": "string" - }, - "data_metadata": { - "type": "object", - "description": "Information about the date being ingested", - "properties": { - "data_models": { - "description": "A list of data models, if any, used by this search", - "type": "array", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "type": "array", - "items": { - "enum": ["Apache", "AWS", "Bro", "Microsoft Windows", "Linux", "macOS", "Netbackup", "Splunk Enterprise", "Splunk Enterprise Security", "Splunk Stream", "Active Directory", "Bluecoat", "Carbon Black Response", "Carbon Black Protect", "CrowdStrike Falcon", "Microsoft Exchange", "Nessus", "Palo Alto Firewall", "Qualys" , "Sysmon", "Tanium", "Ziften"] - }, - "minItems": 0, - "uniqueItems": true - } - }, - "additionalProperties": false, - "required": ["data_source", "providing_technologies"] - }, - "fields_required": { - "description": "A list of fields that need to be in the result of the detection search for the search to be successful", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person maintaining this search" - }, - "email": { - "type": "string", - "description": "Email address of the person maintaining this search" - }, - "name": { - "type": "string", - "description": "Name of the person maintaining this search" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person who originally authored the search" - }, - "email": { - "type": "string", - "description": "Email address of the person who originally authored the search" - }, - "name": { - "type": "string", - "description": "Name of the person who originally authored the search" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "search": { - "description": "The search (in SPL) executed within core Splunk", - "type": "string" - }, - "search_description": { - "description": "A description of what the search is designed to detect", - "type": "string" - }, - "search_id": { - "description": "The unique identifier for the search", - "type": "string" - }, - "search_name": { - "description": "The name of the search", - "type": "string" - }, - "search_type": { - "description": "The type of the search", - "enum": ["detection", "investigative", "contextual", "support"] - }, - "search_window": { - "type": "object", - "description": "The fields associated on when this search should run relative to the detection event", - "properties": { - "earliest_time_offset": { - "description": "The number of seconds into the past from the event time the search should cover", - "type": "integer" - }, - "latest_time_offset": { - "description": "The number of seconds into the future from the event time the search should cover", - "type": "integer" - } - }, - "additionalProperties": false, - "required": ["latest_time_offset", "earliest_time_offset"] - }, - "spec_version": { - "description": "The version of the investigative search specification this manifest follows", - "type": "integer" - }, - "status": { - "description": "The current status of the search - development, experimental, production", - "enum": ["development", "experimental", "production"] - }, - "team_notes": { - "description": "Notes for the team about the search", - "type": "string" - }, - "version": { - "description": "The version of the search", - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "channel", - "creation_date", - "data_metadata", - "fields_required", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "search", - "search_description", - "search_id", - "search_type", - "search_window", - "spec_version", - "version" - ] -} diff --git a/spec/v1/support_search.json.spec b/spec/v1/support_search.json.spec deleted file mode 100644 index fdeee988b6..0000000000 --- a/spec/v1/support_search.json.spec +++ /dev/null @@ -1,218 +0,0 @@ -{ - "$schema": "http://json-schema.org/draft-04/schema#", - "title": "Support Search Manifest", - "description": "The fields that make up the manifest of a version 1 support search", - "type": "object", - "properties": { - "channel": { - "description": "A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Updates are in the ESCU channel", - "type": "string" - }, - "creation_date": { - "description": "The date the story manifest was created", - "type": "string" - }, - "data_metadata": { - "type": "object", - "description": "Information about the date being ingested", - "properties": { - "data_models": { - "description": "A list of data models, if any, used by this search", - "type": "array", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "type": "array", - "items": { - "enum": ["Apache", "AWS", "Bro", "Microsoft Windows", "Linux", "macOS", "Netbackup", "Splunk Enterprise", "Splunk Enterprise Security", "Splunk Stream", "Active Directory", "Bluecoat", "Carbon Black Response", "Carbon Black Protect", "CrowdStrike Falcon", "Microsoft Exchange", "Nessus", "Palo Alto Firewall", "Qualys" , "Sysmon", "Tanium", "Ziften"] - }, - "minItems": 0, - "uniqueItems": true - } - }, - "additionalProperties": false, - "required": ["data_source", "providing_technologies"] - }, - "eli5": { - "description": "Explain it like I’m 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert", - "type": "string" - }, - "how_to_implement": { - "description": "A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person maintaining this search" - }, - "email": { - "type": "string", - "description": "Email address of the person maintaining this search" - }, - "name": { - "type": "string", - "description": "Name of the person maintaining this search" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "type": "array", - "items" :{ - "type": "object", - "properties": { - "company": { - "type": "string", - "description": "Company associated with the person who originally authored the search" - }, - "email": { - "type": "string", - "description": "Email address of the person who originally authored the search" - }, - "name": { - "type": "string", - "description": "Name of the person who originally authored the search" - } - }, - "additionalProperties": false, - "required": ["name", "email", "company"] - } - }, - "scheduling": { - "type": "object", - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run against in Splunk format", - "type": "string" - } - }, - "additionalProperties": false - }, - "search": { - "description": "The search (in SPL) executed within core Splunk", - "type": "string" - }, - "search_description": { - "description": "A description of what the search is designed to detect", - "type": "string" - }, - "search_id": { - "description": "The unique identifier for the search", - "type": "string" - }, - "search_name": { - "description": "The name of the search", - "type": "string" - }, - "search_type": { - "description": "The type of the search", - "enum": ["detection", "investigative", "contextual", "support"] - }, - "spec_version": { - "description": "The version of the detection search specification this manifest follows", - "type": "integer" - }, - "status": { - "description": "The current status of the search - development, experimental, production", - "enum": ["development", "experimental", "production"] - }, - "team_notes": { - "description": "Notes for the team about the search", - "type": "string" - }, - "version": { - "description": "The version of the search", - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "channel", - "creation_date", - "data_metadata", - "eli5", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "scheduling", - "search", - "search_description", - "search_id", - "search_type", - "spec_version", - "version" - ] -} \ No newline at end of file diff --git a/spec/v2/baselines.spec.json b/spec/v2/baselines.spec.json deleted file mode 100644 index b4d1eab4b1..0000000000 --- a/spec/v2/baselines.spec.json +++ /dev/null @@ -1,499 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/baselines.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "definitions": { - "phantom": { - "properties": { - "phantom_server": { - "description": "IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname)", - "examples": [ - "automation (hostname)" - ], - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment", - "examples": [ - "community/dns_hijack_investigation" - ], - "type": "string" - }, - "playbook_url": { - "description": "Url of the playbook on Phantom website.", - "examples": [ - "https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" - ], - "type": "string" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "examples": [ - "0 * * * *" - ], - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "examples": [ - "-70m@m" - ], - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "examples": [ - "-10m@m" - ], - "type": "string" - } - }, - "type": "object" - }, - "sensitivity": { - "description": "TLP colors (White, Green, Amber or Red)", - "examples": [ - "green" - ], - "type": "string" - }, - "severity": { - "description": "Severity in phantom (High, Medium, Low)", - "examples": [ - "medium" - ], - "type": "string" - } - }, - "required": [ - "phantom_server", - "playbook_name", - "playbook_url" - ], - "type": "object" - }, - "splunk": { - "properties": { - "lookups": { - "description": "A list of lookups in the search", - "examples": [ - "detection_search_lookup" - ], - "items": { - "type": "string" - }, - "type": "array" - }, - "macros": { - "description": "A list of macros in the search", - "examples": [ - "detection_search_output_filter" - ], - "items": { - "type": "string" - }, - "type": "array" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "examples": [ - "0 * * * *" - ], - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "examples": [ - "-70m@m" - ], - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "examples": [ - "-10m@m" - ], - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search (in SPL) executed within core Splunk for investgation.", - "examples": [ - "| inputlookup discovered_dns_records.csv | rename answer as discovered_answer | join domain[|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n)" - ], - "type": "string" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - } - }, - "description": "The fields that make up the manifest of a version 2 baseline search", - "properties": { - "baseline": { - "anyOf": [ - { - "required": [ - "splunk" - ] - }, - { - "required": [ - "phantom" - ] - } - ], - "properties": { - "phantom": { - "$ref": "#/definitions/phantom" - }, - "splunk": { - "$ref": "#/definitions/splunk" - } - }, - "type": "object" - }, - "creation_date": { - "description": "The date the baseline manifest was created", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "data_metadata": { - "description": "Information about the date being ingested", - "properties": { - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "examples": [ - "wineventlog" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_models": { - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "examples": [ - "DNS" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "examples": [ - "stream:dns" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Azure", - "Bro", - "GCP", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "Censys", - "Passive Total", - "WHOIS", - "Okta" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "required": [ - "data_source", - "providing_technologies" - ], - "type": "object" - }, - "description": { - "description": "A description of what the search is is doing to create a baseline", - "examples": [ - "The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Traffic` datamodel, then stores the output under the `discovered_dns_records.csv` lookup" - ], - "type": "string" - }, - "eli5": { - "description": "Explain it like I am 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert", - "examples": [ - "Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named `discovered_dns_records.csv`" - ], - "type": "string" - }, - "entities": { - "description": "A list of entities that will used in the story flow or are relevant to the security investigation.", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "parent_process_id", - "process_id", - "process_name", - "process", - "recipient", - "Region", - "region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "query", - "answer", - "domain" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications", - "examples": [ - "To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation" - ], - "type": "string" - }, - "id": { - "description": "The unique identifier for the search", - "examples": [ - "c096f721-8842-42ce-bfc7-74bd8c72b7c3" - ], - "type": "string" - }, - "known_false_positives": { - "description": "Describe the known false postives while the analyst builds the baseline.", - "examples": [ - "Please vet the lookup created by this baseline search." - ], - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "items": { - "properties": { - "company": { - "description": "Company associated with the person maintaining this search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "name": { - "description": "The name of the search that creates the baseline", - "examples": [ - "Discover DNS records" - ], - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "items": { - "properties": { - "company": { - "description": "Company associated with the person who originally authored the search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "spec_version": { - "description": "The version of the detection search specification this manifest follows", - "examples": [ - "2.0" - ], - "type": "integer" - }, - "type": { - "description": "The type of baseline", - "enum": [ - "splunk", - "phantom", - "uba" - ], - "examples": [ - "splunk" - ] - }, - "version": { - "description": "The version of the search", - "examples": [ - "1", - "2" - ], - "type": "string" - } - }, - "required": [ - "id", - "creation_date", - "data_metadata", - "eli5", - "known_false_positives", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "name", - "description", - "type", - "spec_version", - "version", - "baseline" - ], - "title": "Baseline Manifest", - "type": "object" -} diff --git a/spec/v2/detections.spec.json b/spec/v2/detections.spec.json deleted file mode 100644 index f6d4f4d3c3..0000000000 --- a/spec/v2/detections.spec.json +++ /dev/null @@ -1,1526 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/detections.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "definitions": { - "phantom": { - "properties": { - "correlation_rule": { - "description": "Various fields to enhance usability in Enterprise Security", - "properties": { - "notable": { - "description": "Various fields associated with creating a notable event", - "properties": { - "nes_fields": { - "description": "A list of suggested fields to be used for notable-event suppression", - "examples": [ - "src" - ], - "type": "string" - }, - "rule_description": { - "description": "Description of the notable event that will display in Incident Review", - "examples": [ - "The table represents a list of DNS records and their responses for corporate domains that have recently changed" - ], - "type": "string" - }, - "rule_title": { - "description": "Title of the notable event that will display in Incident Review. Add tokenized fieldnames", - "examples": [ - "DNS record changed on $src$" - ], - "type": "string" - } - }, - "required": [ - "rule_description", - "rule_title", - "nes_fields" - ], - "type": "object" - }, - "risk": { - "description": "Fields associated with assigning risk to objects", - "properties": { - "risk_object": { - "description": "TThe field to which you are assigning risk", - "examples": [ - "src" - ], - "type": "string" - }, - "risk_object_type": { - "description": "The type of object to which you are assigning risk", - "examples": [ - "system" - ], - "items": { - "enum": [ - "system", - "user", - "other" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "risk_score": { - "description": "Score assigned to risk_object", - "examples": [ - "40" - ], - "type": "integer" - } - }, - "required": [ - "risk_score", - "risk_object", - "risk_object_type" - ], - "type": "object" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "examples": [ - "0 * * * *" - ], - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "examples": [ - "-70m@m" - ], - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "examples": [ - "-10m@m" - ], - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search that will trigger phantom playbook", - "examples": [ - "| sendalert runphantomplaybook" - ], - "type": "string" - }, - "suppress": { - "description": "Fields associated with suppressing the creation of multiple alerts", - "properties": { - "suppress_fields": { - "description": "The fields to base the suppression on", - "examples": [ - "src" - ], - "type": "string" - }, - "suppress_period": { - "description": "The length of time the suppression should be in effect", - "examples": [ - "28800s" - ], - "type": "string" - } - }, - "required": [ - "suppress_fields", - "suppress_period" - ], - "type": "object" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - }, - "phantom_server": { - "description": "IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname)", - "examples": [ - "automation (hostname)" - ], - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment", - "examples": [ - "community/dns_hijack_detect_playbook" - ], - "type": "string" - }, - "playbook_url": { - "description": "Url of the playbook on Phantom website.", - "examples": [ - "https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" - ], - "type": "string" - }, - "sensitivity": { - "description": "TLP colors (white, green, amber or red)", - "examples": [ - "green" - ], - "type": "string" - }, - "severity": { - "description": "Severity in phantom (High, Medium, Low)", - "examples": [ - "high" - ], - "type": "string" - } - }, - "required": [ - "correlation_rule", - "playbook_name", - "phantom_server", - "playbook_url" - ], - "type": "object" - }, - "splunk": { - "correlation_rule": { - "description": "Various fields to enhance usability in Enterprise Security", - "properties": { - "lookups": { - "description": "A list of lookups in the search", - "examples": [ - "detection_search_lookup" - ], - "items": { - "type": "string" - }, - "type": "array" - }, - "macros": { - "description": "A list of macros in the search", - "examples": [ - "detection_search_output_filter" - ], - "items": { - "type": "string" - }, - "type": "array" - }, - "notable": { - "description": "Various fields associated with creating a notable event", - "properties": { - "drilldown_name": { - "description": "The text for the drilldown hyperlink within the Incident Review dashboard", - "type": "string" - }, - "drilldown_search": { - "description": "The actual drilldown search", - "type": "string" - }, - "nes_fields": { - "description": "A list of suggested fields to be used for notable-event suppression", - "type": "string" - }, - "rule_description": { - "description": "Description of the notable event that will display in Incident Review", - "type": "string" - }, - "rule_title": { - "description": "Title of the notable event that will display in Incident Review", - "type": "string" - } - }, - "required": [ - "rule_description", - "rule_title", - "nes_fields" - ], - "type": "object" - }, - "risk": { - "description": "Fields associated with assigning risk to objects", - "properties": { - "risk_object": { - "description": "TThe field to which you are assigning risk", - "type": "string" - }, - "risk_object_type": { - "description": "The type of object to which you are assigning risk", - "items": { - "enum": [ - "system", - "user", - "other" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "risk_score": { - "description": "Score assigned to risk_object", - "type": "integer" - } - }, - "required": [ - "risk_score", - "risk_object", - "risk_object_type" - ], - "type": "object" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search that will trigger phantom playbook", - "type": "string" - }, - "suppress": { - "description": "Fields associated with suppressing the creation of multiple alerts", - "properties": { - "suppress_fields": { - "description": "The fields to base the suppression on", - "type": "string" - }, - "suppress_period": { - "description": "The length of time the suppression should be in effect", - "type": "string" - } - }, - "required": [ - "suppress_fields", - "suppress_period" - ], - "type": "object" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - }, - "type": "object" - }, - "uba": { - "properties": { - "correlation_rule": { - "description": "Various fields to enhance usability in Enterprise Security", - "properties": { - "notable": { - "description": "Various fields associated with creating a notable event", - "properties": { - "nes_fields": { - "description": "A list of suggested fields to be used for notable-event suppression", - "type": "string" - }, - "rule_description": { - "description": "Description of the notable event that will display in Incident Review", - "type": "string" - }, - "rule_title": { - "description": "Title of the notable event that will display in Incident Review", - "type": "string" - } - }, - "required": [ - "rule_description", - "rule_title", - "nes_fields" - ], - "type": "object" - }, - "risk": { - "description": "Fields associated with assigning risk to objects", - "properties": { - "risk_object": { - "description": "TThe field to which you are assigning risk", - "type": "string" - }, - "risk_object_type": { - "description": "The type of object to which you are assigning risk", - "items": { - "enum": [ - "system", - "user", - "other" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "risk_score": { - "description": "Score assigned to risk_object", - "type": "integer" - } - }, - "required": [ - "risk_score", - "risk_object", - "risk_object_type" - ], - "type": "object" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search (in SPL) executed within core Splunk", - "type": "string" - }, - "suppress": { - "description": "Fields associated with suppressing the creation of multiple alerts", - "properties": { - "suppress_fields": { - "description": "The fields to base the suppression on", - "type": "string" - }, - "suppress_period": { - "description": "The length of time the suppression should be in effect", - "type": "string" - } - }, - "required": [ - "suppress_fields", - "suppress_period" - ], - "type": "object" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - }, - "event_type": { - "description": "An anomaly or threat.", - "examples": [ - "anomaly" - ], - "type": "string" - }, - "model": { - "description": "The name of the Splunk UBA model that detected the anomaly.", - "examples": [ - "UBA Model" - ], - "type": "string" - }, - "model_version": { - "description": "Url of the playbook on Phantom website.", - "examples": [ - "2.0" - ], - "type": "string" - }, - "threat_category": { - "description": "The category of a threat in Splunk UBA.", - "examples": [ - "Malware" - ], - "type": "string" - } - }, - "required": [ - "correlation_rule", - "event_type", - "model", - "model_version", - "threat_category" - ], - "type": "object" - } - }, - "description": "A object that defines the parameters for detecting things using various Splunk capabilities", - "properties": { - "asset_type": { - "description": "Designates the type of asset being investigated", - "examples": [ - "Endpoint" - ], - "type": "string" - }, - "baselines": { - "description": "An array of the baseline objects to exectute before the detection ", - "items": { - "properties": { - "id": { - "description": "UUID of the baseline object", - "examples": [ - "c096f721-8842-42ce-bfc7-74bd8c72b7c3" - ], - "type": "string" - }, - "name": { - "description": "name of baseline object", - "examples": [ - "Discover DNS records" - ], - "type": "string" - }, - "type": { - "description": "Type of baseline to execute", - "enum": [ - "phantom", - "splunk", - "uba" - ], - "examples": [ - "splunk" - ], - "type": "string" - } - }, - "required": [ - "type", - "name", - "id" - ], - "type": "object" - }, - "type": "array" - }, - "confidence": { - "description": "Confidence that detected behavior is malicious", - "enum": [ - "high", - "medium", - "low" - ], - "examples": [ - "high" - ] - }, - "creation_date": { - "description": "The date the story manifest was created", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "data_metadata": { - "description": "Information about the date being ingested", - "properties": { - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "examples": [ - "wineventlog" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_models": { - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint", - "UEBA" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "examples": [ - "DNS" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "examples": [ - "stream:dns" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Azure", - "Bro", - "GCP", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "OSquery", - "Okta" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "required": [ - "data_source", - "providing_technologies" - ], - "type": "object" - }, - "description": { - "description": "A description of what the detection is designed to find", - "examples": [ - "The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day." - ], - "type": "string" - }, - "detect": { - "anyOf": [ - { - "required": [ - "splunk" - ] - }, - { - "required": [ - "phantom" - ] - }, - { - "required": [ - "uba" - ] - } - ], - "properties": { - "phantom": { - "$ref": "#/definitions/phantom" - }, - "splunk": { - "$ref": "#/definitions/splunk" - }, - "uba": { - "$ref": "#/definitions/uba" - } - }, - "type": "object" - }, - "eli5": { - "description": "Explain it like I am 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert", - "examples": [ - "Using a lookup `discover_dns_records` generated by support search \"Discover DNS records\" we check previous network traffic and make sure the responses have not changed." - ], - "type": "string" - }, - "entities": { - "description": "A list of entities that is outputed by the search...", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "app", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "parent_process_id", - "parent_process_name", - "process_id", - "process_name", - "process", - "recipient", - "Region", - "region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "query", - "host", - "dest_ip", - "userName", - "dest_user", - "url", - "domain", - "cluster_name" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications", - "examples": [], - "type": "string" - }, - "id": { - "description": "The unique identifier for the detection", - "examples": [ - "To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search \"Discover DNS record\"." - ], - "type": "string" - }, - "investigations": { - "description": "An array of the investigation objects to exectute on the detection results ", - "items": { - "properties": { - "id": { - "description": "UUID of the investigation object", - "examples": [ - "bc11a8cf-35e7-4bb2-8140-e756cc06fd72" - ], - "type": "string" - }, - "name": { - "description": "Name of investigation object ", - "examples": [ - "Get DNS Server History for a host" - ], - "type": "string" - }, - "type": { - "description": "Type of investigation object", - "enum": [ - "phantom", - "splunk", - "uba" - ], - "examples": [ - "splunk" - ], - "type": "string" - } - }, - "required": [ - "type", - "name", - "id" - ], - "type": "object" - }, - "type": "array" - }, - "known_false_positives": { - "description": "Scenarios in which detected behavior is benig, coupled with suggestions on how to verify the behavior", - "examples": [ - "Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate." - ], - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "items": { - "properties": { - "company": { - "description": "Company associated with the person maintaining this search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "mappings": { - "description": "Mappings to various industry standards and frameworks", - "properties": { - "cis20": { - "description": "A list of critical security controls this search helps you implement", - "examples": [ - "CIS 12" - ], - "items": { - "enum": [ - "CIS 1", - "CIS 2", - "CIS 3", - "CIS 4", - "CIS 5", - "CIS 6", - "CIS 7", - "CIS 8", - "CIS 9", - "CIS 10", - "CIS 11", - "CIS 12", - "CIS 13", - "CIS 14", - "CIS 15", - "CIS 16", - "CIS 17", - "CIS 18", - "CIS 19", - "CIS 20" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "kill_chain_phases": { - "description": "A list of kill-chain phases to which the search applies", - "examples": [ - "Reconnaissance" - ], - "items": { - "enum": [ - "Reconnaissance", - "Weaponization", - "Delivery", - "Exploitation", - "Installation", - "Command and Control", - "Actions on Objectives" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "mitre_attack": { - "description": "A list of the techniques and tactics identified by the search", - "examples": [ - "Defense Evasion", - "Initial Access" - ], - "items": { - "enum": [ - "Initial Access", - "Impact", - "Execution", - "Persistence", - "Spearphishing Attachment", - "Spearphishing Link", - "Privilege Escalation", - "Defense Evasion", - "Credential Access", - "Discovery", - "Lateral Movement", - "Collection", - "Exfiltration", - "Accessibility Features", - "Account Discovery", - "AppInit DLLs", - "Application Shimming", - "Authentication Package", - "Change Default File Association", - "Command and Control", - "Command and Control Protocol", - "Command-Line Interface", - "Commonly Used Port", - "Credential Dumping", - "Custom Cryptographic Protocol", - "DLL Injection", - "DLL Search Order Hijacking", - "DLL Side-Loading", - "Data Compressed", - "Data Encrypted", - "Data Obfuscation", - "Data Staged", - "Data Transfer Size Limits", - "Data from Local System", - "Data from Network Shared Drive", - "Data from Removable Media", - "Disabling Security Tools", - "Email Collection", - "Execution through API", - "Exfiltration Over Alternative Protocol", - "Exfiltration Over Command and Control Channel", - "Exfiltration Over Other Network Medium", - "Exfiltration Over Physical Medium", - "Exploitation of Vulnerability", - "Fallback Channels", - "File Deletion", - "File System Logical Offsets", - "File System Permissions Weakness", - "File and Directory Discovery", - "Graphical User Interface", - "Hypervisor", - "Indicator Blocking", - "Indicator Removal from Tools", - "Indicator Removal on Host", - "Input Capture", - "InstallUtil", - "Legitimate Credentials", - "Local Network Configuration Discovery", - "Local Network Connections Discovery", - "Local Port Monitor", - "Logon Scripts", - "MSBuild", - "Masquerading", - "Modify Existing Service", - "Modify Registry", - "Multi-Stage Channels", - "Multiband Communication", - "Multilayer Encryption", - "NTFS Extended Attributes", - "Network Service Scanning", - "Network Share Connection Removal", - "Network Sniffing", - "New Service", - "Obfuscated Files or Information", - "Pass the Hash", - "Pass the Ticket", - "Path Interception", - "Peripheral Device Discovery", - "Permission Groups Discovery", - "PowerShell", - "Process Discovery", - "Process Hollowing", - "Query Registry", - "Redundant Access", - "Registry Run Keys / Start Folder", - "Regsvcs/Regasm", - "Regsvr32", - "Remote Desktop Protocol", - "Create Account", - "Remote File Copy", - "Remote Services", - "Remote System Discovery", - "Replication Through Removable Media", - "Rootkit", - "Rundll32", - "Scheduled Task", - "Scheduled Transfer", - "Screen Capture", - "Scripting", - "Security Software Discovery", - "Security Support Provider", - "Service Execution", - "Service Registry Permissions Weakness", - "Shared Webroot", - "Shortcut Modification", - "Software Packing", - "Standard Application Layer Protocol", - "Standard Cryptographic Protocol", - "Standard Non-Application Layer Protocol", - "System Information Discovery", - "System Owner/User Discovery", - "System Service Discovery", - "System Time Discovery", - "Taint Shared Content", - "Third-party Software", - "Timestomp", - "Two-Factor Authentication Interception", - "Uncommonly Used Port", - "Video Capture", - "Valid Accounts", - "Web Service", - "Web Shell", - "Windows Admin Shares", - "Windows Management Instrumentation Event Subscription", - "Windows Management Instrumentation", - "Windows Remote Management", - "Winlogon Helper DLL", - "Exploitation for Privilege Escalation" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "mitre_technique_id": { - "description": "MITRE Technique ID identified by the search", - "examples": [ - "T1001", - "T1002", - "T1003" - ], - "items": { - "enum": [ - "T1001", - "T1002", - "T1003", - "T1004", - "T1005", - "T1006", - "T1007", - "T1008", - "T1009", - "T1010", - "T1011", - "T1012", - "T1013", - "T1014", - "T1015", - "T1016", - "T1017", - "T1018", - "T1019", - "T1020", - "T1021", - "T1022", - "T1023", - "T1024", - "T1025", - "T1026", - "T1027", - "T1028", - "T1029", - "T1030", - "T1031", - "T1032", - "T1033", - "T1034", - "T1035", - "T1036", - "T1037", - "T1038", - "T1039", - "T1040", - "T1041", - "T1042", - "T1043", - "T1044", - "T1045", - "T1046", - "T1047", - "T1048", - "T1049", - "T1050", - "T1051", - "T1052", - "T1053", - "T1054", - "T1055", - "T1056", - "T1057", - "T1058", - "T1059", - "T1060", - "T1061", - "T1062", - "T1063", - "T1064", - "T1065", - "T1066", - "T1067", - "T1068", - "T1069", - "T1070", - "T1071", - "T1072", - "T1073", - "T1074", - "T1075", - "T1076", - "T1077", - "T1078", - "T1079", - "T1080", - "T1081", - "T1082", - "T1083", - "T1084", - "T1085", - "T1086", - "T1087", - "T1088", - "T1089", - "T1090", - "T1091", - "T1092", - "T1093", - "T1094", - "T1095", - "T1096", - "T1097", - "T1098", - "T1099", - "T1100", - "T1101", - "T1102", - "T1103", - "T1104", - "T1105", - "T1106", - "T1107", - "T1108", - "T1109", - "T1110", - "T1111", - "T1112", - "T1113", - "T1114", - "T1115", - "T1116", - "T1117", - "T1118", - "T1119", - "T1120", - "T1121", - "T1122", - "T1123", - "T1124", - "T1125", - "T1126", - "T1127", - "T1128", - "T1129", - "T1130", - "T1131", - "T1132", - "T1133", - "T1134", - "T1135", - "T1136", - "T1137", - "T1138", - "T1139", - "T1140", - "T1141", - "T1142", - "T1143", - "T1144", - "T1145", - "T1146", - "T1147", - "T1148", - "T1149", - "T1150", - "T1151", - "T1152", - "T1153", - "T1154", - "T1155", - "T1156", - "T1157", - "T1158", - "T1159", - "T1160", - "T1161", - "T1162", - "T1163", - "T1164", - "T1165", - "T1166", - "T1167", - "T1168", - "T1169", - "T1170", - "T1171", - "T1172", - "T1173", - "T1174", - "T1175", - "T1176", - "T1177", - "T1178", - "T1179", - "T1180", - "T1181", - "T1182", - "T1183", - "T1184", - "T1185", - "T1186", - "T1187", - "T1188", - "T1189", - "T1190", - "T1191", - "T1192", - "T1193", - "T1194", - "T1195", - "T1196", - "T1197", - "T1198", - "T1199", - "T1200", - "T1201", - "T1202", - "T1203", - "T1204", - "T1205", - "T1206", - "T1207", - "T1208", - "T1209", - "T1210", - "T1211", - "T1212", - "T1213", - "T1214", - "T1215", - "T1216", - "T1217", - "T1218", - "T1219", - "T1220", - "T1221", - "T1222", - "T1223", - "T1480", - "T1482", - "T1483", - "T1484", - "T1485", - "T1486", - "T1487", - "T1488", - "T1489", - "T1490", - "T1491", - "T1492", - "T1493", - "T1494", - "T1495", - "T1496", - "T1497", - "T1498", - "T1499", - "T1500", - "T1501", - "T1502", - "T1503", - "T1504", - "T1505", - "T1506", - "T1514", - "T1518", - "T1519", - "T1522", - "T1525", - "T1526", - "T1527", - "T1528", - "T1529", - "T1530", - "T1531", - "T1534", - "T1535", - "T1536", - "T1537", - "T1538", - "T1539" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "nist": { - "description": "A list of the NIST controls the search helps you implement", - "examples": [ - "ID.AM", - "PR.PT" - ], - "items": { - "enum": [ - "ID.AM", - "ID.RA", - "PR.DS", - "PR.IP", - "PR.AC", - "PR.PT", - "PR.AT", - "PR.MA", - "DE.CM", - "DE.DP", - "DE.AE", - "RS.MI", - "RS.AN", - "RS.RP", - "RS.IM", - "RS.CO", - "RC.IM", - "RC.CO" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "type": "object" - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "name": { - "description": "The name of the detection", - "examples": [ - "DNS record changed" - ], - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "items": { - "properties": { - "company": { - "description": "Company associated with the person who originally authored the search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "references": { - "description": "A list of URLs that give more information about the search", - "examples": [ - "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "responses": { - "description": "An array of the response objects to exectute on the detection results", - "items": { - "properties": { - "id": { - "description": "UUID of the Respose object", - "examples": [ - "1169w17b-ef78-4b59-aae8-5369073014e1" - ], - "type": "string" - }, - "name": { - "description": "Name of Response Object", - "examples": [ - "DNS Hijack Reponse" - ], - "type": "string" - }, - "type": { - "description": "Type of baseline to execute", - "enum": [ - "phantom", - "splunk", - "uba" - ], - "examples": [ - "phantom" - ], - "type": "string" - } - }, - "required": [ - "type", - "name", - "id" - ], - "type": "object" - }, - "type": "array" - }, - "security_domain": { - "description": "The high-level security area to which the search belongs", - "enum": [ - "access", - "endpoint", - "network", - "threat", - "cloud" - ], - "examples": [ - "endpoint" - ] - }, - "spec_version": { - "description": "The version of the detection specification this manifest follows", - "examples": [ - "2.0" - ], - "type": "integer" - }, - "type": { - "description": "The type of detection", - "enum": [ - "uba", - "splunk", - "phantom" - ], - "examples": [ - "phantom" - ] - }, - "version": { - "description": "The version of the detection", - "examples": [ - "1" - ], - "type": "string" - } - }, - "required": [ - "confidence", - "creation_date", - "data_metadata", - "eli5", - "how_to_implement", - "known_false_positives", - "maintainers", - "modification_date", - "original_authors", - "description", - "id", - "type", - "security_domain", - "version", - "detect" - ], - "title": "Detection Manifest", - "type": "object" -} diff --git a/spec/v2/investigations.spec.json b/spec/v2/investigations.spec.json deleted file mode 100644 index bf07e97947..0000000000 --- a/spec/v2/investigations.spec.json +++ /dev/null @@ -1,401 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/investigations.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "definitions": { - "phantom": { - "properties": { - "phantom_server": { - "description": "IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname)", - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment", - "type": "string" - }, - "playbook_url": { - "description": "Url of the playbook on Phantom website.", - "type": "string" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "sensitivity": { - "description": "TLP colors (White, Green, Amber or Red)", - "type": "string" - }, - "severity": { - "description": "Severity in phantom (High, Medium, Low)", - "type": "string" - } - }, - "required": [ - "playbook_name", - "phantom_server", - "playbook_url" - ], - "type": "object" - }, - "splunk": { - "properties": { - "fields_required": { - "description": "A list of data models, if any, used by this search", - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "lookups": { - "description": "A list of lookups in the search", - "examples": [ - "detection_search_lookup" - ], - "items": { - "type": "string" - }, - "type": "array" - }, - "macros": { - "description": "A list of macros in the search", - "examples": [ - "detection_search_output_filter" - ], - "items": { - "type": "string" - }, - "type": "array" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search (in SPL) executed within core Splunk for investgation.", - "type": "string" - } - }, - "required": [ - "search", - "fields_required", - "schedule" - ], - "type": "object" - } - }, - "description": "The fields that make up the manifest of a version 2 investigative object", - "properties": { - "creation_date": { - "description": "The date the story manifest was created", - "type": "string" - }, - "data_metadata": { - "description": "Information about the date being ingested", - "properties": { - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_models": { - "description": "A list of data models, if any, used by this search", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "items": { - "enum": [ - "Apache", - "AWS", - "Azure", - "Bro", - "GCP", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "Censys", - "OSquery", - "SMTP", - "Cuckoo", - "VirusTotal", - "DeepSight", - "Okta" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "required": [ - "data_source", - "providing_technologies" - ], - "type": "object" - }, - "description": { - "description": "A description of what the search is designed to detect", - "type": "string" - }, - "eli5": { - "description": "Explain it like I\u2019m 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert", - "type": "string" - }, - "entities": { - "description": "A list of entities that will used in the story flow or are relevant to the security investigation. ", - "items": { - "enum": [ - "accessKeyId", - "arn", - "app", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "parent_process_id", - "process_id", - "process_name", - "process", - "recipient", - "Region", - "region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "dest_ip", - "domain" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications", - "type": "string" - }, - "id": { - "description": "The unique identifier for the search", - "type": "string" - }, - "investigate": { - "anyOf": [ - { - "required": [ - "splunk" - ] - }, - { - "required": [ - "phantom" - ] - } - ], - "properties": { - "phantom": { - "$ref": "#/definitions/phantom" - }, - "splunk": { - "$ref": "#/definitions/splunk" - } - }, - "type": "object" - }, - "known_false_positives": { - "description": "Scenarios in which detected behavior is benig, coupled with suggestions on how to verify the behavior", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person maintaining this search", - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this search", - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this search", - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "type": "string" - }, - "name": { - "description": "The name of the search", - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person who originally authored the search", - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the search", - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the search", - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "spec_version": { - "description": "The version of the investigative search specification this manifest follows", - "type": "integer" - }, - "type": { - "description": "Type of product that will support this investigate object.", - "enum": [ - "phantom", - "splunk", - "uba" - ] - }, - "version": { - "description": "The version of the search", - "type": "string" - } - }, - "required": [ - "creation_date", - "data_metadata", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "description", - "id", - "type", - "spec_version", - "version", - "investigate" - ], - "title": "Investigative Search Manifest", - "type": "object" -} diff --git a/spec/v2/responses.spec.json b/spec/v2/responses.spec.json deleted file mode 100644 index 887209b025..0000000000 --- a/spec/v2/responses.spec.json +++ /dev/null @@ -1,340 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/responses.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "definitions": { - "phantom": { - "properties": { - "phantom_server": { - "description": "IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname)", - "type": "string" - }, - "playbook_display_name": { - "description": "Display Name of the playbook. Capitalize each letter and remove underscores from playbook_name field. Eg: Simple Network Enrichment", - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment", - "type": "string" - }, - "playbook_url": { - "description": "Url of the playbook on Phantom website.", - "type": "string" - }, - "sensitivity": { - "description": "TLP colors (White, Green, Amber or Red)", - "type": "string" - }, - "severity": { - "description": "Severity in phantom (High, Medium, Low)", - "type": "string" - }, - "type": { - "description": "Type of baseline to execute", - "enum": [ - "phantom", - "splunk", - "uba" - ], - "type": "string" - } - }, - "type": "object" - }, - "splunk": { - "properties": { - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time tes search should run against in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "A reponse action exectued in splunk", - "type": "string" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - } - }, - "description": "The fields that make up the manifest of a version 1 response spec", - "properties": { - "creation_date": { - "description": "The date the story manifest was created", - "type": "string" - }, - "data_metadata": { - "additionalProperties": false, - "description": "Information about the date being used to run the response", - "properties": { - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_models": { - "description": "A list of data models, if any, used by this search", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Censys", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "Censys", - "Passive Total", - "WHOIS" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "required": [ - "data_source", - "providing_technologies" - ], - "type": "object" - }, - "description": { - "description": "A description of what this reponse object will do ", - "type": "string" - }, - "entities": { - "description": "A list of entities that is either an input or an output for the security workflow.", - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "query", - "answer", - "domain" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "fields_required": { - "description": "A list of fields that need to be in the result of the detection search for the search to be successful", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion on how to implement this reponse object, the config files, etc", - "type": "string" - }, - "id": { - "description": "The unique identifier for the search", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the reponse spec", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person maintaining this search", - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this search", - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this search", - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "type": "string" - }, - "name": { - "description": "The name of the search", - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the reponse object", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person who originally authored the search", - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the search", - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the search", - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "response": { - "anyOf": [ - { - "required": [ - "splunk" - ] - }, - { - "required": [ - "phantom" - ] - } - ], - "properties": { - "phantom": { - "$ref": "#/definitions/phantom" - }, - "splunk": { - "$ref": "#/definitions/splunk" - } - }, - "type": "object" - }, - "spec_version": { - "description": "The version of the investigative search specification this manifest follows", - "type": "integer" - }, - "type": { - "description": "The type of detection", - "enum": [ - "splunk", - "phantom" - ] - }, - "version": { - "description": "The version of the search", - "type": "string" - } - }, - "required": [ - "creation_date", - "data_metadata", - "entity", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "search", - "description", - "id", - "type", - "spec_version", - "version", - "response" - ], - "title": "Response Manifest", - "type": "object" -} diff --git a/spec/v2/story.spec.json b/spec/v2/story.spec.json deleted file mode 100644 index b5141f9388..0000000000 --- a/spec/v2/story.spec.json +++ /dev/null @@ -1,271 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/story.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "description": "The fields that make up the manifest of a version 2 Analytic Story", - "meta:license": [ - "This file is licensed to you under the Apache License, Version 2.0 (the 'License');", - "you may not use this file except in compliance with the License. You may obtain a copy", - "of the License at http://www.apache.org/licenses/LICENSE-2.0" - ], - "properties": { - "category": { - "description": "The category to which the Analytic Story belongs", - "items": { - "enum": [ - "Abuse", - "Account Compromise", - "Account Sharing", - "Adversary Tactics", - "Best Practices", - "Cloud Security", - "Command and Control", - "Compliance", - "Data Exfiltration", - "Denial of Service", - "Endpoint Compromise", - "GDPR", - "IAM Analytics", - "Insider Threat", - "Lateral Movement", - "Malware", - "Network Attack", - "Operations", - "Other", - "Privilege Escalation", - "Phishing", - "Ransomware", - "SaaS", - "Scanning", - "Shadow IT", - "Threat Intelligence", - "Unauthorized Software", - "Vulnerability", - "Web Attack" - ], - "examples": [ - "Adversary Tactics" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "channel": { - "description": "A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Content Updates are in the ESCU channel", - "examples": [ - "ESCU" - ], - "type": "string" - }, - "creation_date": { - "description": "The date this story was created", - "examples": [ - "2017-11-21" - ], - "type": "string" - }, - "description": { - "description": "A high-level description or goal of the Analytic Story", - "examples": [ - "Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records." - ], - "type": "string" - }, - "detections": { - "description": "An array of detection mechanisms from Splunk, UBA and phantom. ", - "items": { - "additionalProperties": false, - "properties": { - "detection_id": { - "description": "unique identifier of the detection, in the form of UUID", - "examples": [ - "1169w17b-ef78-4b59-aae8-5369073014e1" - ], - "type": "string" - }, - "name": { - "description": "Name of the Detection. It can be a name of a Splunk correlation search name, a UBA threat or a Phantom detection playbook.", - "examples": [ - "DNS record changed" - ], - "type": "string" - }, - "type": { - "description": "What product gives you a detection", - "enum": [ - "splunk", - "uba", - "phantom" - ], - "examples": [ - "splunk", - "uba", - "phantom" - ], - "type": "string" - } - }, - "required": [ - "detection_id", - "type", - "name" - ], - "type": "object" - }, - "type": "array" - }, - "id": { - "description": "A unique identifier for the Analytic Story", - "examples": [ - "8169f17b-ef68-4b59-aae8-5869073014e1" - ], - "format": "uuid", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person maintaining this Analytic Story", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this Analytic Story", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this Analytic Story", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "modification_date": { - "description": "The date of the most recent modification to this Analytic Story", - "examples": [ - "2018-09-06" - ], - "type": "string" - }, - "name": { - "description": "The name of the Analytic Story", - "examples": [ - "DNS Hijacking" - ], - "type": "string" - }, - "narrative": { - "description": "Long-form text that describes the Analytic Story and the rationale behind it, as well as an overview of the included searches, and how they enable the story", - "examples": [ - "Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.

The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous." - ], - "type": "string" - }, - "original_authors": { - "description": "An array of the original authors of the Analytic Story", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person who originally authored the Analytic Story", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the Analytic Story", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the Analytic Story", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "references": { - "description": "An array of URLs that give information about the problem the story is addressing", - "examples": [ - "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "spec_version": { - "description": "The version of the Analytic Story specification this manifest follows", - "examples": [ - 2 - ], - "type": "integer" - }, - "usecase": { - "description": "The usecase to which the Analytic Story belongs to.", - "enum": [ - "Security Monitoring", - "Advanced Threat Detection", - "Insider Threat", - "Compliance", - "Fraud Detection" - ], - "examples": [ - "Advanced Threat Detection" - ] - }, - "version": { - "description": "The version of the Analytic Story, bump the version number when the story gets an update", - "examples": [ - "1.0" - ], - "type": "string" - } - }, - "required": [ - "id", - "category", - "usecase", - "name", - "description", - "detections", - "version" - ], - "title": "Analytic Story Manifest", - "type": "object" -} From a569e55051b5187e85b95ac6e3934b847614c96b Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 24 Apr 2020 12:52:33 +0200 Subject: [PATCH 02/93] first version of spec 3 --- spec/baseline.spec.json | 194 ++++++------- spec/deployment.spec.json | 528 +++++++++++++++++------------------ spec/macros.spec.json | 80 +++--- spec/response.spec.json | 232 +++++++-------- spec/response_task.spec.json | 294 +++++++++---------- spec/stories.spec.json | 210 +++++++------- 6 files changed, 769 insertions(+), 769 deletions(-) diff --git a/spec/baseline.spec.json b/spec/baseline.spec.json index 258ebee0ea..a60e5415a7 100644 --- a/spec/baseline.spec.json +++ b/spec/baseline.spec.json @@ -1,101 +1,101 @@ { - "$schema": "http://json-schema.org/draft-07/schema", - "$id": "http://example.com/example.json", - "type": "object", - "title": "Baseline Schema", - "description": "schema for baselines", - "default": {}, - "additionalProperties": true, - "required": [ - "name", - "id", - "version", - "date", - "description", - "author", - "search", - "tags" - ], - "properties": { - "name": { - "$id": "#/properties/name", - "type": "string", - "title": "Name of baseline", - "default": "", - "examples": [ - "Previously Seen AWS Regions" - ] - }, - "id": { - "$id": "#/properties/id", - "type": "string", - "description": "UUID as unique identifier", - "default": "", - "examples": [ - "fc0edc95-ff2b-48b0-9f6f-63da3789fd63" - ] - }, - "version": { - "$id": "#/properties/version", - "type": "integer", - "description": "version of baseline, e.g. 1 or 2 ...", - "default": 0, - "examples": [ - 1 - ] - }, - "date": { - "$id": "#/properties/date", - "type": "string", - "description": "date of creation or modification, format yyyy-mm-dd", - "default": "", - "examples": [ - "2019-12-06" - ] - }, - "description": { - "$id": "#/properties/description", - "type": "string", - "description": "A detailed description of the baseline ", - "default": "", - "examples": [ - "This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days" - ] - }, - "author": { - "$id": "#/properties/author", - "type": "string", - "description": "Author of the baseline", - "default": "", - "examples": [ - "Bahvin Patel, Splunk" - ] - }, - "search": { - "$id": "#/properties/search", - "type": "string", - "description": "The Splunk search for the baseline", - "default": "", - "examples": [ - "sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" - ] - }, - "tags": { - "$id": "#/properties/tags", - "type": "object", - "description": "An array of key value pairs for tagging", - "default": {}, - "examples": [ - { - "custom_key": "custom_value", - "analytics_story": "suspicious_aws_ec2_activities" - } - ], - "additionalProperties": true, - "required": [], - "properties": null, - "minItems": 1, - "uniqueItems": true + "$id": "http://example.com/example.json", + "$schema": "http://json-schema.org/draft-07/schema", + "additionalProperties": true, + "default": {}, + "description": "schema for baselines", + "properties": { + "author": { + "$id": "#/properties/author", + "default": "", + "description": "Author of the baseline", + "examples": [ + "Bahvin Patel, Splunk" + ], + "type": "string" + }, + "date": { + "$id": "#/properties/date", + "default": "", + "description": "date of creation or modification, format yyyy-mm-dd", + "examples": [ + "2019-12-06" + ], + "type": "string" + }, + "description": { + "$id": "#/properties/description", + "default": "", + "description": "A detailed description of the baseline ", + "examples": [ + "This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days" + ], + "type": "string" + }, + "id": { + "$id": "#/properties/id", + "default": "", + "description": "UUID as unique identifier", + "examples": [ + "fc0edc95-ff2b-48b0-9f6f-63da3789fd63" + ], + "type": "string" + }, + "name": { + "$id": "#/properties/name", + "default": "", + "examples": [ + "Previously Seen AWS Regions" + ], + "title": "Name of baseline", + "type": "string" + }, + "search": { + "$id": "#/properties/search", + "default": "", + "description": "The Splunk search for the baseline", + "examples": [ + "sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" + ], + "type": "string" + }, + "tags": { + "$id": "#/properties/tags", + "additionalProperties": true, + "default": {}, + "description": "An array of key value pairs for tagging", + "examples": [ + { + "analytics_story": "suspicious_aws_ec2_activities", + "custom_key": "custom_value" } + ], + "minItems": 1, + "properties": null, + "required": [], + "type": "object", + "uniqueItems": true + }, + "version": { + "$id": "#/properties/version", + "default": 0, + "description": "version of baseline, e.g. 1 or 2 ...", + "examples": [ + 1 + ], + "type": "integer" } + }, + "required": [ + "name", + "id", + "version", + "date", + "description", + "author", + "search", + "tags" + ], + "title": "Baseline Schema", + "type": "object" } diff --git a/spec/deployment.spec.json b/spec/deployment.spec.json index aa9a2aac43..ebcd2ddd87 100644 --- a/spec/deployment.spec.json +++ b/spec/deployment.spec.json @@ -1,268 +1,268 @@ { - "$schema": "http://json-schema.org/draft-07/schema", - "$id": "http://example.com/example.json", - "type": "object", - "title": "Deployment Schema", - "description": "schema for deployment", - "default": {}, - "additionalProperties": true, - "required": [ - "name", - "id", - "date", - "description", - "scheduling", - "tags" - ], - "properties": { - "name": { - "$id": "#/properties/name", - "type": "string", - "description": "Name of deployment configuration", - "default": "", - "examples": [ - "Deployment Configuration all Detections" - ] - }, - "id": { - "$id": "#/properties/id", - "type": "string", - "description": "uuid as unique identifier", - "default": "", - "examples": [ - "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" - ] - }, - "date": { - "$id": "#/properties/date", - "type": "string", - "description": "date of creation or modification, format yyyy-mm-dd", - "default": "", - "examples": [ - "2019-12-06" - ] - }, - "description": { - "$id": "#/properties/description", - "type": "string", - "description": "description of the deployment configuration", - "default": "", - "examples": [ - "This deployment configuration provides a standard scheduling policy over all rules." - ] - }, - "scheduling": { - "$id": "#/properties/scheduling", - "type": "object", - "description": "allows to set scheduling parameter", - "default": {}, - "examples": [ - { - "latest_time": "now", - "cron_schedule": "*/10 * * * *", - "earliest_time": "-10m", - "schedule_window": "auto" - } - ], - "additionalProperties": true, - "required": [ - "cron_schedule", - "earliest_time", - "latest_time" - ], - "properties": { - "cron_schedule": { - "$id": "#/properties/scheduling/properties/cron_schedule", - "type": "string", - "description": "Cron schedule to schedule the Splunk searches.", - "default": "", - "examples": [ - "*/10 * * * *" - ] - }, - "earliest_time": { - "$id": "#/properties/scheduling/properties/earliest_time", - "type": "string", - "description": "earliest time of search", - "default": "", - "examples": [ - "-10m" - ] - }, - "latest_time": { - "$id": "#/properties/scheduling/properties/latest_time", - "type": "string", - "description": "latest time of search", - "default": "", - "examples": [ - "now" - ] - }, - "schedule_window": { - "$id": "#/properties/scheduling/properties/schedule_window", - "type": "string", - "description": "schedule window for search", - "default": "", - "examples": [ - "auto" - ] - } - } - }, - "alert_action": { - "$id": "#/properties/alert_action", - "type": "object", - "description": "Set alert action parameter for search", - "default": {}, - "examples": [ - { - "email": { - "to": "test@test.com", - "subject": "Splunk Alert $name$", - "message": "Splunk Alert $name$ triggered %fields%" - }, - "index": { - "name": "asx" - }, - "notable": { - "rule_description": "%description%", - "rule_title": "%name%" - } - } - ], - "additionalProperties": true, - "required": [ - "index" - ], - "properties": { - "index": { - "$id": "#/properties/alert_action/properties/index", - "type": "object", - "description": "By enabling it, the results are stored in another index", - "default": {}, - "examples": [ - { - "name": "asx" - } - ], - "additionalProperties": true, - "required": [ - "name" - ], - "properties": { - "name": { - "$id": "#/properties/alert_action/properties/index/properties/name", - "type": "string", - "description": "Name of the index", - "default": "", - "examples": [ - "asx" - ] - } - } - }, - "notable": { - "$id": "#/properties/alert_action/properties/notable", - "type": "object", - "description": "By enabling it, a notable is generated", - "default": {}, - "examples": [ - { - "rule_title": "%name%", - "rule_description": "%description%" - } - ], - "additionalProperties": true, - "required": [ - "rule_title", - "rule_description" - ], - "properties": { - "rule_title": { - "$id": "#/properties/alert_action/properties/notable/properties/rule_title", - "type": "string", - "description": "Rule title of the notable event", - "default": "", - "examples": [ - "%name%" - ] - }, - "rule_description": { - "$id": "#/properties/alert_action/properties/notable/properties/rule_description", - "type": "string", - "description": "Rule description of the notable event", - "default": "", - "examples": [ - "%description%" - ] - } - } - }, - "email": { - "$id": "#/properties/alert_action/properties/email", - "type": "object", - "description": "By enabling it, an email is sent with the results", - "default": {}, - "examples": [ - { - "subject": "Splunk Alert $name$", - "message": "Splunk Alert $name$ triggered %fields%", - "to": "test@test.com" - } - ], - "additionalProperties": true, - "required": [ - "to", - "subject", - "message" - ], - "properties": { - "to": { - "$id": "#/properties/alert_action/properties/email/properties/to", - "type": "string", - "description": "Recipient of email", - "default": "", - "examples": [ - "test@test.com" - ] - }, - "subject": { - "$id": "#/properties/alert_action/properties/email/properties/subject", - "type": "string", - "description": "Subject of email", - "default": "", - "examples": [ - "Splunk Alert $name$" - ] - }, - "message": { - "$id": "#/properties/alert_action/properties/email/properties/message", - "type": "string", - "description": "message of email", - "default": "", - "examples": [ - "Splunk Alert $name$ triggered %fields%" - ] - } - } - } - } - }, - "tags": { - "$id": "#/properties/tags", - "type": "object", - "description": "An array of key value pairs for tagging", - "default": {}, - "examples": [ - { - "analytics_story": "credential_dumping" - } - ], - "additionalProperties": true, - "required": [], - "properties": null, - "minItems": 1, - "uniqueItems": true + "$id": "http://example.com/example.json", + "$schema": "http://json-schema.org/draft-07/schema", + "additionalProperties": true, + "default": {}, + "description": "schema for deployment", + "properties": { + "alert_action": { + "$id": "#/properties/alert_action", + "additionalProperties": true, + "default": {}, + "description": "Set alert action parameter for search", + "examples": [ + { + "email": { + "message": "Splunk Alert $name$ triggered %fields%", + "subject": "Splunk Alert $name$", + "to": "test@test.com" + }, + "index": { + "name": "asx" + }, + "notable": { + "rule_description": "%description%", + "rule_title": "%name%" + } } + ], + "properties": { + "email": { + "$id": "#/properties/alert_action/properties/email", + "additionalProperties": true, + "default": {}, + "description": "By enabling it, an email is sent with the results", + "examples": [ + { + "message": "Splunk Alert $name$ triggered %fields%", + "subject": "Splunk Alert $name$", + "to": "test@test.com" + } + ], + "properties": { + "message": { + "$id": "#/properties/alert_action/properties/email/properties/message", + "default": "", + "description": "message of email", + "examples": [ + "Splunk Alert $name$ triggered %fields%" + ], + "type": "string" + }, + "subject": { + "$id": "#/properties/alert_action/properties/email/properties/subject", + "default": "", + "description": "Subject of email", + "examples": [ + "Splunk Alert $name$" + ], + "type": "string" + }, + "to": { + "$id": "#/properties/alert_action/properties/email/properties/to", + "default": "", + "description": "Recipient of email", + "examples": [ + "test@test.com" + ], + "type": "string" + } + }, + "required": [ + "to", + "subject", + "message" + ], + "type": "object" + }, + "index": { + "$id": "#/properties/alert_action/properties/index", + "additionalProperties": true, + "default": {}, + "description": "By enabling it, the results are stored in another index", + "examples": [ + { + "name": "asx" + } + ], + "properties": { + "name": { + "$id": "#/properties/alert_action/properties/index/properties/name", + "default": "", + "description": "Name of the index", + "examples": [ + "asx" + ], + "type": "string" + } + }, + "required": [ + "name" + ], + "type": "object" + }, + "notable": { + "$id": "#/properties/alert_action/properties/notable", + "additionalProperties": true, + "default": {}, + "description": "By enabling it, a notable is generated", + "examples": [ + { + "rule_description": "%description%", + "rule_title": "%name%" + } + ], + "properties": { + "rule_description": { + "$id": "#/properties/alert_action/properties/notable/properties/rule_description", + "default": "", + "description": "Rule description of the notable event", + "examples": [ + "%description%" + ], + "type": "string" + }, + "rule_title": { + "$id": "#/properties/alert_action/properties/notable/properties/rule_title", + "default": "", + "description": "Rule title of the notable event", + "examples": [ + "%name%" + ], + "type": "string" + } + }, + "required": [ + "rule_title", + "rule_description" + ], + "type": "object" + } + }, + "required": [ + "index" + ], + "type": "object" + }, + "date": { + "$id": "#/properties/date", + "default": "", + "description": "date of creation or modification, format yyyy-mm-dd", + "examples": [ + "2019-12-06" + ], + "type": "string" + }, + "description": { + "$id": "#/properties/description", + "default": "", + "description": "description of the deployment configuration", + "examples": [ + "This deployment configuration provides a standard scheduling policy over all rules." + ], + "type": "string" + }, + "id": { + "$id": "#/properties/id", + "default": "", + "description": "uuid as unique identifier", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ], + "type": "string" + }, + "name": { + "$id": "#/properties/name", + "default": "", + "description": "Name of deployment configuration", + "examples": [ + "Deployment Configuration all Detections" + ], + "type": "string" + }, + "scheduling": { + "$id": "#/properties/scheduling", + "additionalProperties": true, + "default": {}, + "description": "allows to set scheduling parameter", + "examples": [ + { + "cron_schedule": "*/10 * * * *", + "earliest_time": "-10m", + "latest_time": "now", + "schedule_window": "auto" + } + ], + "properties": { + "cron_schedule": { + "$id": "#/properties/scheduling/properties/cron_schedule", + "default": "", + "description": "Cron schedule to schedule the Splunk searches.", + "examples": [ + "*/10 * * * *" + ], + "type": "string" + }, + "earliest_time": { + "$id": "#/properties/scheduling/properties/earliest_time", + "default": "", + "description": "earliest time of search", + "examples": [ + "-10m" + ], + "type": "string" + }, + "latest_time": { + "$id": "#/properties/scheduling/properties/latest_time", + "default": "", + "description": "latest time of search", + "examples": [ + "now" + ], + "type": "string" + }, + "schedule_window": { + "$id": "#/properties/scheduling/properties/schedule_window", + "default": "", + "description": "schedule window for search", + "examples": [ + "auto" + ], + "type": "string" + } + }, + "required": [ + "cron_schedule", + "earliest_time", + "latest_time" + ], + "type": "object" + }, + "tags": { + "$id": "#/properties/tags", + "additionalProperties": true, + "default": {}, + "description": "An array of key value pairs for tagging", + "examples": [ + { + "analytics_story": "credential_dumping" + } + ], + "minItems": 1, + "properties": null, + "required": [], + "type": "object", + "uniqueItems": true } + }, + "required": [ + "name", + "id", + "date", + "description", + "scheduling", + "tags" + ], + "title": "Deployment Schema", + "type": "object" } diff --git a/spec/macros.spec.json b/spec/macros.spec.json index 48c5a2f37f..cd0f5cafe1 100644 --- a/spec/macros.spec.json +++ b/spec/macros.spec.json @@ -1,43 +1,43 @@ { - "$id": "https://api.splunkresearch.com/schemas/macros.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "description": "An object that defines the parameters for a Splunk Macro", - "properties": { - "arguments": { - "description": "A list of the arguments being passed to this macro", - "type": "array", - "items": { - "type": "string" - }, - "minItems": 0, - "uniqueItems": true - }, - "name": { - "description": "The name of the macro", - "examples": [ - "detection_search_output_filter" - ], - "type": "string" - }, - "definition": { - "description": "The macro definition", - "examples": [ - "(query=fls-na* AND query = www* AND query=images*)" - ], - "type": "string" - }, - "description": { - "description": "What the macro is intended to filter", - "examples": [ - "Use this macro to filter out known good objects" - ], - "type": "string" - } + "$id": "https://api.splunkresearch.com/schemas/macros.json", + "$schema": "http://json-schema.org/draft-07/schema#", + "description": "An object that defines the parameters for a Splunk Macro", + "properties": { + "arguments": { + "description": "A list of the arguments being passed to this macro", + "items": { + "type": "string" + }, + "minItems": 0, + "type": "array", + "uniqueItems": true }, - "required": [ - "name", - "description" - ], - "title": "Macro Manifest", - "type": "object" + "definition": { + "description": "The macro definition", + "examples": [ + "(query=fls-na* AND query = www* AND query=images*)" + ], + "type": "string" + }, + "description": { + "description": "What the macro is intended to filter", + "examples": [ + "Use this macro to filter out known good objects" + ], + "type": "string" + }, + "name": { + "description": "The name of the macro", + "examples": [ + "detection_search_output_filter" + ], + "type": "string" + } + }, + "required": [ + "name", + "description" + ], + "title": "Macro Manifest", + "type": "object" } diff --git a/spec/response.spec.json b/spec/response.spec.json index 9015969b59..2ff8650157 100644 --- a/spec/response.spec.json +++ b/spec/response.spec.json @@ -1,120 +1,120 @@ { - "$schema": "http://json-schema.org/draft-07/schema", - "$id": "http://example.com/example.json", - "type": "object", - "title": "Response Schema", - "description": "schema for response", - "default": {}, - "additionalProperties": true, - "required": [ - "name", - "id", - "version", - "date", - "description", - "author", - "response_tasks", - "tags" - ], - "properties": { - "name": { - "$id": "#/properties/name", - "type": "string", - "description": "Name of response", - "default": "", - "examples": [ - "Response Example" - ] - }, - "id": { - "$id": "#/properties/id", - "type": "string", - "description": "UUID as unique identifier", - "default": "", - "examples": [ - "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" - ] - }, - "version": { - "$id": "#/properties/version", - "type": "integer", - "description": "version of detection, e.g. 1 or 2 ...", - "default": 0, - "examples": [ - 1 - ] - }, - "date": { - "$id": "#/properties/date", - "type": "string", - "description": "version of detection, e.g. 1 or 2 ...", - "default": "", - "examples": [ - "2019-12-06" - ] - }, - "description": { - "$id": "#/properties/description", - "type": "string", - "description": "Description of response", - "default": "", - "examples": [ - "Response example." - ] - }, - "author": { - "$id": "#/properties/author", - "type": "string", - "description": "Author of the response", - "default": "", - "examples": [ - "Rico Valdez, Patrick Bareiß, Splunk" - ] - }, - "response_tasks": { - "$id": "#/properties/response_tasks", - "type": "object", - "description": "Response tasks divided into phases", - "default": {}, - "examples": [ - { - "identification": [ - { - "id": "c36f3f48-e0bb-4c20-a62a-cdc8f6418892", - "name": "Investigate Indicator of Compromise Hash" - }, - { - "name": "Investigate Domains", - "id": "0dc849b2-2eb4-4fd2-add1-b6cc475765f0" - } - ], - "another_phase": [ - { - "id": "7c72d944-3995-4485-8e57-67b4c353989b", - "name": "Another investigation" - } - ] - } - ], - "additionalProperties": true, - "required": [], - "properties": null - }, - "tags": { - "$id": "#/properties/tags", - "type": "object", - "description": "An array of key value pairs for tagging", - "default": {}, - "examples": [ - { - "analytics_story": "credential_dumping" - } - ], - "additionalProperties": true, - "required": [], - "properties": null, - "minItems": 1, - "uniqueItems": true + "$id": "http://example.com/example.json", + "$schema": "http://json-schema.org/draft-07/schema", + "additionalProperties": true, + "default": {}, + "description": "schema for response", + "properties": { + "author": { + "$id": "#/properties/author", + "default": "", + "description": "Author of the response", + "examples": [ + "Rico Valdez, Patrick Barei\u00df, Splunk" + ], + "type": "string" + }, + "date": { + "$id": "#/properties/date", + "default": "", + "description": "version of detection, e.g. 1 or 2 ...", + "examples": [ + "2019-12-06" + ], + "type": "string" + }, + "description": { + "$id": "#/properties/description", + "default": "", + "description": "Description of response", + "examples": [ + "Response example." + ], + "type": "string" + }, + "id": { + "$id": "#/properties/id", + "default": "", + "description": "UUID as unique identifier", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ], + "type": "string" + }, + "name": { + "$id": "#/properties/name", + "default": "", + "description": "Name of response", + "examples": [ + "Response Example" + ], + "type": "string" + }, + "response_tasks": { + "$id": "#/properties/response_tasks", + "additionalProperties": true, + "default": {}, + "description": "Response tasks divided into phases", + "examples": [ + { + "another_phase": [ + { + "id": "7c72d944-3995-4485-8e57-67b4c353989b", + "name": "Another investigation" + } + ], + "identification": [ + { + "id": "c36f3f48-e0bb-4c20-a62a-cdc8f6418892", + "name": "Investigate Indicator of Compromise Hash" + }, + { + "id": "0dc849b2-2eb4-4fd2-add1-b6cc475765f0", + "name": "Investigate Domains" + } + ] } + ], + "properties": null, + "required": [], + "type": "object" + }, + "tags": { + "$id": "#/properties/tags", + "additionalProperties": true, + "default": {}, + "description": "An array of key value pairs for tagging", + "examples": [ + { + "analytics_story": "credential_dumping" + } + ], + "minItems": 1, + "properties": null, + "required": [], + "type": "object", + "uniqueItems": true + }, + "version": { + "$id": "#/properties/version", + "default": 0, + "description": "version of detection, e.g. 1 or 2 ...", + "examples": [ + 1 + ], + "type": "integer" } + }, + "required": [ + "name", + "id", + "version", + "date", + "description", + "author", + "response_tasks", + "tags" + ], + "title": "Response Schema", + "type": "object" } diff --git a/spec/response_task.spec.json b/spec/response_task.spec.json index 9e86cfe949..820f124be5 100644 --- a/spec/response_task.spec.json +++ b/spec/response_task.spec.json @@ -1,151 +1,151 @@ { - "$schema": "http://json-schema.org/draft-07/schema", - "$id": "http://example.com/example.json", - "type": "object", - "title": "Response Task Schema", - "description": "schema for response tasks", - "default": {}, - "additionalProperties": true, - "required": [ - "name", - "id", - "version", - "date", - "description", - "author", - "inputs" - ], - "properties": { - "name": { - "$id": "#/properties/name", - "type": "string", - "description": "Namo fo response task", - "default": "", - "examples": [ - "Response Tas Example" - ] - }, - "id": { - "$id": "#/properties/id", - "type": "string", - "description": "UUID as unique identifier", - "default": "", - "examples": [ - "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" - ] - }, - "version": { - "$id": "#/properties/version", - "type": "integer", - "description": "version of detection, e.g. 1 or 2 ...", - "default": 0, - "examples": [ - 3 - ] - }, - "date": { - "$id": "#/properties/date", - "type": "string", - "description": "date of creation or modification, format yyyy-mm-dd", - "default": "", - "examples": [ - "2019-12-06" - ] - }, - "description": { - "$id": "#/properties/description", - "type": "string", - "description": "Description of response task", - "default": "", - "examples": [ - "Response Task example description" - ] - }, - "author": { - "$id": "#/properties/author", - "type": "string", - "description": "Author of response task", - "default": "", - "examples": [ - "Patrick Bareiß, Splunk" - ] - }, - "inputs": { - "$id": "#/properties/inputs", - "type": "array", - "description": "Inputs used from the response task", - "default": [], - "examples": [ - [ - "lookup_file" - ] - ] - }, - "search": { - "$id": "#/properties/search", - "type": "string", - "description": "Search as response task", - "default": "", - "examples": [ - "`sysmon` EventCode=1 | search [| inputlookup %lookup_file% ] | stats count by dest user process_name" - ] - }, - "playbook": { - "$id": "#/properties/playbook", - "type": "object", - "description": "A phantom playbook as response task", - "default": {}, - "examples": [ - { - "url_json": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json", - "url_python": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py", - "name": "lets_encrypt_domain_investigate.json" - } - ], - "additionalProperties": true, - "required": [ - "name", - "url_json", - "url_python" - ], - "properties": { - "name": { - "$id": "#/properties/playbook/properties/name", - "type": "string", - "description": "Name of Phantom Playbook", - "default": "", - "examples": [ - "lets_encrypt_domain_investigate.json" - ] - }, - "url_json": { - "$id": "#/properties/playbook/properties/url_json", - "type": "string", - "description": "URL for phantom playbook json file", - "default": "", - "examples": [ - "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json" - ] - }, - "url_python": { - "$id": "#/properties/playbook/properties/url_python", - "type": "string", - "description": "URL for phantom playbook python file", - "default": "", - "examples": [ - "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py" - ] - } - } - }, - "dashboard": { - "$id": "#/properties/dashboard", - "type": "string", - "description": "Name of dashboard used as response task", - "default": "", - "examples": [ - "process_chain_analysis.json" - ] + "$id": "http://example.com/example.json", + "$schema": "http://json-schema.org/draft-07/schema", + "additionalProperties": true, + "default": {}, + "description": "schema for response tasks", + "properties": { + "author": { + "$id": "#/properties/author", + "default": "", + "description": "Author of response task", + "examples": [ + "Patrick Barei\u00df, Splunk" + ], + "type": "string" + }, + "dashboard": { + "$id": "#/properties/dashboard", + "default": "", + "description": "Name of dashboard used as response task", + "examples": [ + "process_chain_analysis.json" + ], + "type": "string" + }, + "date": { + "$id": "#/properties/date", + "default": "", + "description": "date of creation or modification, format yyyy-mm-dd", + "examples": [ + "2019-12-06" + ], + "type": "string" + }, + "description": { + "$id": "#/properties/description", + "default": "", + "description": "Description of response task", + "examples": [ + "Response Task example description" + ], + "type": "string" + }, + "id": { + "$id": "#/properties/id", + "default": "", + "description": "UUID as unique identifier", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ], + "type": "string" + }, + "inputs": { + "$id": "#/properties/inputs", + "default": [], + "description": "Inputs used from the response task", + "examples": [ + [ + "lookup_file" + ] + ], + "type": "array" + }, + "name": { + "$id": "#/properties/name", + "default": "", + "description": "Namo fo response task", + "examples": [ + "Response Tas Example" + ], + "type": "string" + }, + "playbook": { + "$id": "#/properties/playbook", + "additionalProperties": true, + "default": {}, + "description": "A phantom playbook as response task", + "examples": [ + { + "name": "lets_encrypt_domain_investigate.json", + "url_json": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json", + "url_python": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py" } + ], + "properties": { + "name": { + "$id": "#/properties/playbook/properties/name", + "default": "", + "description": "Name of Phantom Playbook", + "examples": [ + "lets_encrypt_domain_investigate.json" + ], + "type": "string" + }, + "url_json": { + "$id": "#/properties/playbook/properties/url_json", + "default": "", + "description": "URL for phantom playbook json file", + "examples": [ + "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json" + ], + "type": "string" + }, + "url_python": { + "$id": "#/properties/playbook/properties/url_python", + "default": "", + "description": "URL for phantom playbook python file", + "examples": [ + "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py" + ], + "type": "string" + } + }, + "required": [ + "name", + "url_json", + "url_python" + ], + "type": "object" + }, + "search": { + "$id": "#/properties/search", + "default": "", + "description": "Search as response task", + "examples": [ + "`sysmon` EventCode=1 | search [| inputlookup %lookup_file% ] | stats count by dest user process_name" + ], + "type": "string" + }, + "version": { + "$id": "#/properties/version", + "default": 0, + "description": "version of detection, e.g. 1 or 2 ...", + "examples": [ + 3 + ], + "type": "integer" } + }, + "required": [ + "name", + "id", + "version", + "date", + "description", + "author", + "inputs" + ], + "title": "Response Task Schema", + "type": "object" } diff --git a/spec/stories.spec.json b/spec/stories.spec.json index 508a21e5c0..410ef8b596 100644 --- a/spec/stories.spec.json +++ b/spec/stories.spec.json @@ -1,109 +1,109 @@ { - "$schema": "http://json-schema.org/draft-07/schema", - "$id": "http://example.com/example.json", - "type": "object", - "title": "Analytics Story Schema", - "description": "schema analytics story", - "default": {}, - "additionalProperties": true, - "required": [ - "name", - "id", - "version", - "date", - "description", - "narrative", - "author", - "tags" - ], - "properties": { - "name": { - "$id": "#/properties/name", - "type": "string", - "description": "Name of the Analytics Story", - "default": "", - "examples": [ - "Credential Dumping" - ] - }, - "id": { - "$id": "#/properties/id", - "type": "string", - "description": "UUID as unique identifier", - "default": "", - "examples": [ - "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" - ] - }, - "version": { - "$id": "#/properties/version", - "type": "integer", - "description": "version of analytics story, e.g. 1 or 2 ...", - "default": 0, - "examples": [ - 1 - ] - }, - "date": { - "$id": "#/properties/date", - "type": "string", - "description": "date of creation or modification, format yyyy-mm-dd", - "default": "", - "examples": [ - "2019-12-06" - ] - }, - "description": { - "$id": "#/properties/description", - "type": "string", - "description": "description of the analytics story", - "default": "", - "examples": [ - "Uncover activity consistent with credential dumping, a technique where attackers compromise systems and attempt to obtain and exfiltrate passwords." - ] - }, - "narrative": { - "$id": "#/properties/narrative", - "type": "string", - "description": "narrative of the analytics story", - "default": "", - "examples": [ - "gathering credentials from a target system, often hashed or encrypted, is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems." - ] - }, - "author": { - "$id": "#/properties/author", - "type": "string", - "description": "Author of the analytics story", - "default": "", - "examples": [ - "Rico Valdez, Patrick Bareiß, Splunk" - ] - }, - "search": { - "$id": "#/properties/search", - "type": "string", - "description": "An additional Splunk search, which uses the result of the detections", - "default": "", - "examples": [ - "index=asx mitre_id=t1003 | stats values(source) as detections values(process) as processes values(user) as users values(_time) as time count by dest" - ] - }, - "tags": { - "$id": "#/properties/tags", - "type": "object", - "description": "An explanation about the purpose of this instance.", - "default": {}, - "examples": [ - { - "analytics_story": "credential_dumping" - } - ], - "additionalProperties": true, - "required": [], - "properties": null, - "minItems": 1, - "maxItems": 1 + "$id": "http://example.com/example.json", + "$schema": "http://json-schema.org/draft-07/schema", + "additionalProperties": true, + "default": {}, + "description": "schema analytics story", + "properties": { + "author": { + "$id": "#/properties/author", + "default": "", + "description": "Author of the analytics story", + "examples": [ + "Rico Valdez, Patrick Barei\u00df, Splunk" + ], + "type": "string" + }, + "date": { + "$id": "#/properties/date", + "default": "", + "description": "date of creation or modification, format yyyy-mm-dd", + "examples": [ + "2019-12-06" + ], + "type": "string" + }, + "description": { + "$id": "#/properties/description", + "default": "", + "description": "description of the analytics story", + "examples": [ + "Uncover activity consistent with credential dumping, a technique where attackers compromise systems and attempt to obtain and exfiltrate passwords." + ], + "type": "string" + }, + "id": { + "$id": "#/properties/id", + "default": "", + "description": "UUID as unique identifier", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ], + "type": "string" + }, + "name": { + "$id": "#/properties/name", + "default": "", + "description": "Name of the Analytics Story", + "examples": [ + "Credential Dumping" + ], + "type": "string" + }, + "narrative": { + "$id": "#/properties/narrative", + "default": "", + "description": "narrative of the analytics story", + "examples": [ + "gathering credentials from a target system, often hashed or encrypted, is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems." + ], + "type": "string" + }, + "search": { + "$id": "#/properties/search", + "default": "", + "description": "An additional Splunk search, which uses the result of the detections", + "examples": [ + "index=asx mitre_id=t1003 | stats values(source) as detections values(process) as processes values(user) as users values(_time) as time count by dest" + ], + "type": "string" + }, + "tags": { + "$id": "#/properties/tags", + "additionalProperties": true, + "default": {}, + "description": "An explanation about the purpose of this instance.", + "examples": [ + { + "analytics_story": "credential_dumping" } + ], + "maxItems": 1, + "minItems": 1, + "properties": null, + "required": [], + "type": "object" + }, + "version": { + "$id": "#/properties/version", + "default": 0, + "description": "version of analytics story, e.g. 1 or 2 ...", + "examples": [ + 1 + ], + "type": "integer" } + }, + "required": [ + "name", + "id", + "version", + "date", + "description", + "narrative", + "author", + "tags" + ], + "title": "Analytics Story Schema", + "type": "object" } From d6e5dbc4788c7e12a9704e72089f44f8bfd38d00 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 29 Apr 2020 12:54:27 +0200 Subject: [PATCH 03/93] spec 3 update --- spec/baseline.spec.json | 9 +++++++++ spec/deployment.spec.json | 1 + spec/response_task.spec.json | 12 ++++++++++-- 3 files changed, 20 insertions(+), 2 deletions(-) diff --git a/spec/baseline.spec.json b/spec/baseline.spec.json index a60e5415a7..6367ae093e 100644 --- a/spec/baseline.spec.json +++ b/spec/baseline.spec.json @@ -32,6 +32,15 @@ ], "type": "string" }, + "how_to_implement": { + "$id": "#/properties/how_to_implement", + "type": "string", + "description": "information about how to implement. Only needed for non standard implementations.", + "default": "", + "examples": [ + "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." + ] + }, "id": { "$id": "#/properties/id", "default": "", diff --git a/spec/deployment.spec.json b/spec/deployment.spec.json index ebcd2ddd87..2576677bc5 100644 --- a/spec/deployment.spec.json +++ b/spec/deployment.spec.json @@ -261,6 +261,7 @@ "date", "description", "scheduling", + "alert_action", "tags" ], "title": "Deployment Schema", diff --git a/spec/response_task.spec.json b/spec/response_task.spec.json index 820f124be5..28b0688e1c 100644 --- a/spec/response_task.spec.json +++ b/spec/response_task.spec.json @@ -41,6 +41,15 @@ ], "type": "string" }, + "how_to_implement": { + "$id": "#/properties/how_to_implement", + "type": "string", + "description": "information about how to implement. Only needed for non standard implementations.", + "default": "", + "examples": [ + "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." + ] + }, "id": { "$id": "#/properties/id", "default": "", @@ -143,8 +152,7 @@ "version", "date", "description", - "author", - "inputs" + "author" ], "title": "Response Task Schema", "type": "object" From d2e82224b0a235c8cf02a26e1de9db4417ae3563 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 29 Apr 2020 13:01:45 +0200 Subject: [PATCH 04/93] Converted all objects to new spec --- ...bited_processes_to_enterprise_security.yml | 20 ++ baselines/add_prohibited_processes_to_es.yml | 43 ---- baselines/approved_aws_service_accounts.yml | 45 ----- baselines/assets_sorted_by_category.yml | 40 ---- baselines/baseline_api_calls_per_user_arn.yml | 47 ----- baselines/baseline_aws_regions.yml | 45 ----- baselines/baseline_blocked_vpc_traffic.yml | 54 ------ baselines/baseline_cloud_compute_regions.yml | 50 ----- .../baseline_network_acl_modifications.yml | 49 ----- .../baseline_of_api_calls_per_user_arn.yml | 22 +++ ...e_of_blocked_outbound_traffic_from_aws.yml | 28 +++ ...aseline_of_command_line_length___mltk.yml} | 61 ++---- ...> baseline_of_dns_query_length___mltk.yml} | 54 ++---- ..._aws_instances_launched_by_user___mltk.yml | 33 ++++ ...ws_instances_terminated_by_user___mltk.yml | 33 ++++ ...aseline_of_network_acl_activity_by_arn.yml | 23 +++ ..._of_s3_bucket_deletion_activity_by_arn.yml | 22 +++ ...line_of_security_group_activity_by_arn.yml | 23 +++ ...yml => baseline_of_smb_traffic___mltk.yml} | 62 ++---- baselines/baseline_s3_deletion_by_arn.yml | 48 ----- ...aseline_security_group_activity_by_arn.yml | 49 ----- baselines/brand_abuse_dnstwist_domains.yml | 43 ---- baselines/count_of_assets_by_category.yml | 19 ++ ...ount_of_unique_ips_connecting_to_ports.yml | 13 ++ ..._list_of_approved_aws_service_accounts.yml | 21 ++ baselines/discover_dns_records.yml | 62 ++---- baselines/dnstwist_domain_names.yml | 21 ++ baselines/identify_ports_on_network.yml | 39 ---- .../identify_systems_creating_rdp_traffic.yml | 38 ---- ...ystems_creating_remote_desktop_traffic.yml | 13 ++ ...identify_systems_receiving_rdp_traffic.yml | 39 ---- ...stems_receiving_remote_desktop_traffic.yml | 14 ++ .../identify_systems_using_remote_desktop.yml | 48 +---- baselines/monitor_successful_backups.yml | 47 ++--- .../monitor_successful_windows_updates.yml | 38 ---- baselines/monitor_unsuccessful_backups.yml | 47 ++--- .../monitor_unsuccessful_windows_updates.yml | 38 ---- ..._api_call_per_user_roles_in_cloudtrail.yml | 22 +++ ...iously_seen_aws_cross_account_activity.yml | 54 ++---- ...seen_aws_provisioning_activity_sources.yml | 23 +++ baselines/previously_seen_aws_regions.yml | 21 ++ baselines/previously_seen_aws_users.yml | 56 ------ ...y_seen_cloud_compute_creations_by_user.yml | 55 ++---- .../previously_seen_cloud_compute_images.yml | 55 ++---- ...usly_seen_cloud_compute_instance_types.yml | 58 ++---- baselines/previously_seen_cloud_regions.yml | 20 ++ baselines/previously_seen_cmd_arguments.yml | 48 ----- ...previously_seen_command_line_arguments.yml | 30 +++ baselines/previously_seen_ec2_amis.yml | 49 ++--- .../previously_seen_ec2_instance_types.yml | 51 ++--- .../previously_seen_ec2_launches_by_user.yml | 49 ++--- .../previously_seen_ec2_modifications.yml | 42 ---- ...viously_seen_ec2_modifications_by_user.yml | 19 ++ ...viously_seen_provisioning_activity_src.yml | 43 ---- ...eviously_seen_running_windows_services.yml | 20 ++ ...sly_seen_s3_bucket_access_by_remote_ip.yml | 21 ++ baselines/previously_seen_s3_remote_ip.yml | 45 ----- baselines/previously_seen_user_roles.yml | 47 ----- .../previously_seen_users_in_cloudtrail.yml | 26 +++ ...previously_seen_windows_service_starts.yml | 37 ---- ...stems_ready_for_spectre_meltdown_patch.yml | 47 ----- ...ady_for_spectre_meltdown_windows_patch.yml | 23 +++ .../train_ec2_excessive_runinstances.yml | 60 ------ ...train_ec2_excessive_terminateinstances.yml | 60 ------ .../update_previously_seen_aws_users.yml | 50 ----- ...te_previously_seen_users_in_cloudtrail.yml | 26 +++ .../windows_updates_install_failures.yml | 13 ++ .../windows_updates_install_successes.yml | 13 ++ dashboards/.gitkeep | 0 deployment/deployment.yml | 17 ++ ...ly_high_aws_instances_launched_by_user.yml | 35 ++++ ..._aws_instances_launched_by_user___mltk.yml | 31 +++ ..._high_aws_instances_terminated_by_user.yml | 35 ++++ ...ws_instances_terminated_by_user___mltk.yml | 30 +++ ...abnormally_high_ec2_instances_launched.yml | 108 ----------- .../abnormally_high_instance_termination.yml | 106 ---------- .../access_lsass_memory_for_dump_creation.yml | 117 +++-------- detections/account_harvesting.yml | 105 ---------- detections/acl_with_open_ports.yml | 95 --------- .../activity_related_to_pass_the_hash.yml | 109 ----------- detections/add_to_untrust_cert_store.yml | 115 ----------- ..._eks_kubernetes_cluster_scan_detection.yml | 25 +++ ...azon_eks_kubernetes_pod_scan_detection.yml | 26 +++ detections/anomalous_webclick.yml | 101 ---------- ...ivity_from_previously_unseen_user_role.yml | 97 ---------- ..._scanning_for_vulnerable_jboss_servers.yml | 89 --------- ..._to_add_certificate_to_untrusted_store.yml | 36 ++++ ...ution_policy_to_unrestricted_or_bypass.yml | 128 ++++-------- .../attempt_to_stop_security_service.yml | 44 +++++ ..._credential_dump_from_registry_via_reg.yml | 103 ---------- ...dential_dump_from_registry_via_reg_exe.yml | 34 ++++ detections/attrib_to_hide_files.yml | 108 ----------- ...ws_activity_from_non_approved_accounts.yml | 118 ----------- detections/aws_activity_in_new_region.yml | 110 ----------- ...ovisioning_from_previously_unseen_city.yml | 105 +++------- ...sioning_from_previously_unseen_country.yml | 106 +++------- ...provisioning_from_previously_unseen_ip.yml | 100 ---------- ...ning_from_previously_unseen_ip_address.yml | 44 +++++ ...isioning_from_previously_unseen_region.yml | 106 +++------- ...ross_account_activity_from_new_account.yml | 128 ------------ ...ctivity_from_previously_unseen_account.yml | 45 +++++ ...ntrol_list_created_with_all_open_ports.yml | 30 +++ ...ws_network_access_control_list_deleted.yml | 31 +++ detections/aws_spike_acl_activity.yml | 151 --------------- detections/badrabbit_schtasks.yml | 111 ----------- detections/batch_file_write_system32.yml | 105 ---------- detections/batch_file_write_to_system32.yml | 36 ++++ detections/brand_abuse_dns.yml | 98 ---------- detections/brand_abuse_email.yml | 106 ---------- detections/brand_abuse_web.yml | 97 ---------- detections/change_file_association.yml | 121 ------------ detections/child_processes_of_spoolsv_exe.yml | 39 ++++ detections/children_of_spoolsv.yml | 112 ----------- ...nts_connecting_to_multiple_dns_servers.yml | 105 +++------- .../cloud_compute_activity_in_new_region.yml | 107 ---------- ...ance_created_by_previously_unseen_user.yml | 123 +++--------- ...e_created_with_previously_unseen_image.yml | 32 +++ ...reated_with_previously_unseen_image_id.yml | 96 --------- ...d_with_previously_unseen_instance_type.yml | 122 +++--------- ...ce_started_in_previously_unused_region.yml | 36 ++++ detections/common_ransomware_extensions.yml | 119 ++---------- detections/common_ransomware_notes.yml | 121 ++---------- .../container_implant_aws_detection.yml | 65 ------- .../container_implant_gcp_detection.yml | 57 ------ ...ate_local_admin_accounts_using_net_exe.yml | 34 ++++ detections/create_local_admin_via_net.yml | 111 ----------- .../create_or_delete_network_shares.yml | 120 ------------ ...or_delete_windows_shares_using_net_exe.yml | 35 ++++ .../create_remote_thread_into_lsass.yml | 115 +++-------- detections/creation_of_shadow_copy.yml | 117 +++-------- ...f_shadow_copy_with_wmic_and_powershell.yml | 116 +++-------- .../cred_dump_via_copy_from_shadowcopy.yml | 90 --------- .../cred_dump_via_symlink_shadowcopy.yml | 89 --------- ...ping_via_copy_command_from_shadow_copy.yml | 34 ++++ ...ial_dumping_via_symlink_to_shadow_copy.yml | 32 +++ detections/cscript_via_cmd.yml | 114 ----------- detections/delete_shadow_copies.yml | 115 ----------- detections/deleting_shadow_copies.yml | 37 ++++ detections/deletion_network_acl.yml | 88 --------- ...ivity_related_to_pass_the_hash_attacks.yml | 34 ++++ ...ct_api_activity_from_users_without_mfa.yml | 54 ++++++ ..._scanning_for_vulnerable_jboss_servers.yml | 27 +++ ...pi_activities_from_unapproved_accounts.yml | 57 ++++++ ...ws_console_login_by_user_from_new_city.yml | 39 ++++ ...console_login_by_user_from_new_country.yml | 39 ++++ ..._console_login_by_user_from_new_region.yml | 39 ++++ ...redential_dumping_through_LSASS_access.yml | 134 ++++--------- ...to_phishing_sites_leveraging_evilginx2.yml | 52 +++++ ...cessive_account_lockouts_from_endpoint.yml | 38 ++++ ...detect_excessive_user_account_lockouts.yml | 29 +++ ...onnecting_to_dynamic_domain_providers.yml} | 102 +++------- .../detect_large_outbound_icmp_packets.yml | 46 +++++ .../detect_long_dns_txt_record_response.yml | 45 +++++ ...ious_requests_to_exploit_jboss_servers.yml | 37 ++++ .../detect_mimikatz_using_loaded_images.yml | 119 ++++-------- ...katz_via_powershell_and_eventcode_4703.yml | 39 ++++ ...ning_scripts_in_command_line_arguments.yml | 35 ++++ .../detect_new_api_calls_from_user_roles.yml | 34 ++++ detections/detect_new_local_admin_account.yml | 55 ++++++ .../detect_new_login_attempts_to_routers.yml | 31 +++ detections/detect_new_open_s3_buckets.yml | 33 ++++ .../detect_new_user_aws_console_login.yml | 37 ++++ .../detect_oulook_exe_writing_a__zip_file.yml | 44 +++++ detections/detect_outbound_smb_traffic.yml | 48 +++++ ...nterception_by_creation_of_program_exe.yml | 32 +++ ...system_network_configuration_discovery.yml | 37 ++++ ...ohibited_applications_spawning_cmd_exe.yml | 35 ++++ .../detect_psexec_with_accepteula_flag.yml | 42 ++++ detections/detect_rare_executables.yml | 44 +++++ detections/detect_s3_access_from_a_new_ip.yml | 38 ++++ .../detect_spike_in_aws_api_activity.yml | 62 ++++++ ...blocked_outbound_traffic_from_your_aws.yml | 55 ++++++ .../detect_spike_in_network_acl_activity.yml | 47 +++++ .../detect_spike_in_s3_bucket_deletion.yml | 46 +++++ ...etect_spike_in_security_group_activity.yml | 47 +++++ ...ect_unauthorized_assets_by_mac_address.yml | 40 ++++ detections/detect_usb_device_insertion.yml | 37 ++++ ..._cmd_exe_to_launch_script_interpreters.yml | 34 ++++ ...eb_traffic_to_dynamic_domain_providers.yml | 45 +++++ detections/detection_of_dns_tunnels.yml | 54 ++++++ .../detection_of_tools_built_by_nirsoft.yml | 34 ++++ detections/disable_remote_uac.yml | 106 ---------- .../disabling_remote_user_account_control.yml | 34 ++++ detections/dns_amplification_any_query.yml | 87 --------- detections/dns_evilginx_subdomains.yml | 108 ----------- detections/dns_query_length_mltk.yml | 151 --------------- .../dns_query_length_outliers___mltk.yml | 63 ++++++ ...ry_length_with_high_standard_deviation.yml | 136 +++---------- ...s_resolved_by_unauthorized_dns_servers.yml | 37 ++++ detections/dns_record_changed.yml | 120 +++--------- detections/dns_tunnelling.yml | 128 ------------ detections/dragonfly_schtasks.yml | 109 ----------- detections/dump_lsass_via_comsvcs_dll.yml | 112 +++-------- detections/dyn_dns_web_traffic.yml | 125 ------------ .../ec2_excessive_runinstances_mltk.yml | 107 ---------- .../ec2_excessive_terminateinstances_mltk.yml | 107 ---------- ...ance_created_by_previously_unseen_user.yml | 103 ---------- ...nce_modified_by_previously_unseen_user.yml | 93 --------- ...e_modified_with_previously_unseen_user.yml | 33 ++++ ...ce_started_in_previously_unseen_region.yml | 34 ++++ ...nce_started_with_previously_unseen_ami.yml | 100 +++------- ...d_with_previously_unseen_instance_type.yml | 105 +++------- ...ce_started_with_previously_unseen_user.yml | 34 ++++ .../email_attachments_with_lots_of_spaces.yml | 39 ++++ detections/email_attachments_with_spaces.yml | 90 --------- .../email_files_not_in_outlook_directory.yml | 109 ----------- ...itten_outside_of_the_outlook_directory.yml | 34 ++++ ...s_sending_high_volume_traffic_to_hosts.yml | 48 +++++ ..._high_volume_outbound_traffic_to_hosts.yml | 120 ------------ detections/excessive_dns_failures.yml | 127 +++--------- .../excessive_lockouts_from_endpoint.yml | 91 --------- .../excessive_user_account_lockouts.yml | 99 ---------- ...ution_of_file_with_multiple_extensions.yml | 35 ++++ ...n_of_file_with_spaces_before_extension.yml | 34 ++++ detections/execution_of_nirsoft_tools.yml | 116 ----------- ...d_without_successful_netbackup_backups.yml | 27 +++ detections/file_with_samsam_extension.yml | 32 +++ detections/file_write_spikes.yml | 109 ----------- detections/first_time_seen_cmd_line.yml | 141 -------------- .../first_time_seen_command_line_argument.yml | 54 ++++++ ...irst_time_seen_running_windows_service.yml | 129 ++++-------- detections/fsutil_deleting_journals.yml | 116 ----------- detections/gcp_gcr_container_uploaded.yml | 25 +++ .../gcp_kubernetes_cluster_scan_detection.yml | 29 +++ ..._files_and_directories_with_attrib_exe.yml | 33 ++++ detections/hosts_file_modification.yml | 106 ---------- ...ume_network_traffic_from_email_servers.yml | 122 ------------ ...e_of_network_traffic_from_email_server.yml | 47 +++++ detections/identify_new_user_accounts.yml | 29 +++ .../kubernetes_aws_scan_fingerprint.yml | 74 ------- ...kubernetes_gcp_scan_fingerprint_attack.yml | 72 ------- .../kubernetes_pods_aws_scan_fingerprint.yml | 72 ------- detections/large_icmp_outbound.yml | 112 ----------- .../large_volume_of_dns_any_queries.yml | 29 +++ detections/lnk_executing_a_process.yml | 94 --------- detections/local_admin_account_creation.yml | 126 ------------ detections/long_dns_text_response.yml | 120 ------------ detections/macos___re_opened_applications.yml | 34 ++++ detections/macos_re-opened_applications.yml | 71 ------- ...ious_application_shimming_via_registry.yml | 113 ----------- ...connect_to_internet_with_hidden_window.yml | 44 +++++ ...s_powershell_process___encoded_command.yml | 39 ++++ ...hell_process___execution_policy_bypass.yml | 42 ++++ ...iple_suspicious_command_line_arguments.yml | 43 ++++ ...connect_to_internet_with_hidden_window.yml | 125 ------------ ...ous_powershell_process_encoded_command.yml | 113 ----------- ...alicious_powershell_process_execpolicy.yml | 121 ------------ ..._process_multiple_suspicious_arguments.yml | 123 ------------ ...ershell_process_obfuscation_techniques.yml | 117 ----------- ...ll_process_with_obfuscation_techniques.yml | 41 ++++ ...ious_requests_to_exploit_jboss_servers.yml | 100 ---------- detections/monitor_dns_for_brand_abuse.yml | 26 +++ detections/monitor_email_for_brand_abuse.yml | 31 +++ ...nitor_registry_keys_for_print_monitors.yml | 38 ++++ .../monitor_web_traffic_for_brand_abuse.yml | 26 +++ detections/mshta_launching_scripts.yml | 109 ----------- ...h_invalid_credentails_from_the_same_ip.yml | 29 +++ detections/netbackup_failed_backup.yml | 86 -------- .../netbackup_no_backups_in_time_period.yml | 83 -------- detections/netsh_launching_process.yml | 108 ----------- detections/new_aws_console_login_by_user.yml | 97 ---------- .../new_aws_console_login_city_by_user.yml | 105 ---------- .../new_aws_console_login_country_by_user.yml | 103 ---------- .../new_aws_console_login_region_by_user.yml | 104 ---------- detections/new_connections_to_routers.yml | 97 ---------- .../new_container_uploaded_to_aws_ecr.yml | 24 +++ detections/new_open_s3_buckets.yml | 102 ---------- detections/new_user_accounts.yml | 90 --------- detections/no_win_updates_in_timeframe.yml | 91 --------- .../no_windows_updates_in_a_time_frame.yml | 34 ++++ detections/okta_account_lockout_events.yml | 25 +++ detections/okta_failed_sso_attempt.yml | 69 ------- detections/okta_failed_sso_attempts.yml | 24 +++ ...tiple_users_with_auth_failures_from_ip.yml | 66 ------- detections/okta_user_lockouts.yml | 66 ------- .../okta_user_logins_from_multiple_cities.yml | 94 +++------ detections/open_redirect_in_splunk_web.yml | 102 +++------- .../osquery_pack___coldroot_detection.yml | 30 +++ detections/osx_coldroot_pack.yml | 99 ---------- detections/osx_keyboard_taps.yml | 97 ---------- detections/outbound_smb_connections.yml | 123 ------------ detections/outlook_writing_zip.yml | 103 ---------- .../overwrite_accessibility_binaries.yml | 109 ----------- .../overwriting_accessibility_binaries.yml | 37 ++++ detections/password_sharing.yml | 90 --------- detections/path_interception_program.exe.yml | 110 ----------- detections/port_monitor_via_registry.yml | 115 ----------- detections/powershell_get_sedebug.yml | 113 ----------- detections/process_execution_via_wmi.yml | 34 ++++ detections/process_launching_netsh.yml | 118 ----------- detections/process_with_double_extension.yml | 107 ---------- .../process_with_spaces_before_extension.yml | 105 ---------- detections/processes_created_by_netsh.yml | 37 ++++ detections/processes_launching_netsh.yml | 37 ++++ .../processes_tapping_keyboard_events.yml | 33 ++++ detections/prohibited_allowed_through_fw.yml | 116 ----------- .../prohibited_apps_spawning_cmdprompt.yml | 128 ------------ .../prohibited_network_traffic_allowed.yml | 40 ++++ .../prohibited_software_on_endpoint.yml | 135 +++---------- detections/protocol_mismatch.yml | 117 ----------- detections/protocol_or_port_mismatch.yml | 40 ++++ .../protocols_authenticating_in_cleartext.yml | 101 ---------- ...ls_passing_authentication_in_cleartext.yml | 35 ++++ detections/psexec_accepteula.yml | 108 ----------- detections/rare_executables_on_endpoint.yml | 124 ------------ ...ulating_windows_services_registry_keys.yml | 45 +++++ ...de_files_directories_via_registry_keys.yml | 32 +++ detections/reg_manipulating_services.yml | 124 ------------ detections/reg_used_to_hide_files.yml | 111 ----------- ...istry_keys_for_creating_shim_databases.yml | 34 ++++ .../registry_keys_used_for_persistence.yml | 47 +++++ ...try_keys_used_for_privilege_escalation.yml | 39 ++++ detections/registry_persistence.yml | 115 ----------- detections/registry_privilege_escalation.yml | 105 ---------- detections/remote_desktop_bruteforce.yml | 104 ---------- .../remote_desktop_network_bruteforce.yml | 36 ++++ detections/remote_desktop_network_traffic.yml | 137 +++---------- ...mote_desktop_process_running_on_system.yml | 134 +++---------- .../remote_process_instantiation_via_wmi.yml | 39 ++++ .../remote_registry_key_modifications.yml | 32 +++ detections/remote_registry_modifications.yml | 112 ----------- detections/remote_wmi_command_attempt.yml | 125 +++--------- .../remote_wmi_process_instantiation.yml | 113 ----------- detections/rundll_loading_dll_by_ordinal.yml | 113 +++-------- detections/s3_access_from_new_ip.yml | 115 ----------- detections/samsam_payload_extensions.yml | 104 ---------- detections/samsam_test_file_write.yml | 116 +++-------- .../sc_exe_manipulating_windows_services.yml | 46 +++++ detections/sc_manipulating_services.yml | 118 ----------- ...k_name_used_by_dragonfly_threat_actors.yml | 32 +++ ...led_tasks_used_in_badrabbit_ransomware.yml | 33 ++++ detections/schtasks_forced_reboot.yml | 109 ----------- ...htasks_scheduling_job_on_remote_system.yml | 121 +++--------- .../schtasks_used_for_forcing_a_reboot.yml | 32 +++ detections/script_execution_via_wmi.yml | 34 ++++ detections/shim_database_file_creation.yml | 115 ++--------- detections/shim_database_installation.yml | 107 ---------- ...nstallation_with_suspicious_parameters.yml | 34 ++++ detections/short_lived_accounts.yml | 99 ---------- detections/short_lived_windows_accounts.yml | 30 +++ detections/single_letter_executables.yml | 103 ---------- .../single_letter_process_on_endpoint.yml | 31 +++ detections/smb_traffic_spike.yml | 138 +++---------- detections/smb_traffic_spike___mltk.yml | 56 ++++++ detections/smb_traffic_spike_mltk.yml | 147 -------------- detections/sncd_processes.yml | 112 ----------- ...pectre_and_meltdown_vulnerable_systems.yml | 27 +++ .../spectre_meltdown_vulnerabilities.yml | 91 --------- detections/spike_aws_api_call_per_account.yml | 155 --------------- .../spike_aws_security_group_activity.yml | 142 -------------- detections/spike_in_file_writes.yml | 34 ++++ detections/spike_s3_deletion.yml | 152 --------------- detections/spike_vpc_blocked_traffic.yml | 183 ------------------ ...lunk_enterprise_information_disclosure.yml | 35 ++++ detections/splunk_information_disclosure.yml | 96 --------- detections/sql_injection_with_long_urls.yml | 132 ++++--------- detections/stop_security_services.yml | 117 ----------- ...uspicious_changes_to_file_associations.yml | 41 ++++ detections/suspicious_email___uba_anomaly.yml | 32 +++ ...suspicious_email_attachment_extensions.yml | 39 ++++ detections/suspicious_email_attachments.yml | 93 --------- detections/suspicious_file_write.yml | 38 ++++ detections/suspicious_file_writes.yml | 113 ----------- detections/suspicious_java_classes.yml | 116 ++--------- ...uspicious_lnk_file_launching_a_process.yml | 41 ++++ detections/suspicious_reg_exe_process.yml | 43 ++++ detections/suspicious_reg_process.yml | 118 ----------- detections/suspicious_wevtutil_usage.yml | 138 +++---------- detections/suspicious_write_to_recycler.yml | 107 ---------- detections/suspicious_write_to_sysvol.yml | 103 ---------- ...us_writes_to_system_volume_information.yml | 28 +++ ...spicious_writes_to_windows_recycle_bin.yml | 33 ++++ ...rocesses_run_from_unexpected_locations.yml | 131 +++---------- detections/tor_traffic.yml | 117 +++-------- detections/uba_email_anomaly.yml | 84 -------- .../unauthorized_assets_via_mac_address.yml | 100 ---------- detections/unauthorized_dns_servers.yml | 89 --------- detections/uncommon_processes.yml | 112 ----------- detections/uncommon_processes_on_endpoint.yml | 35 ++++ detections/unload_sysmon_filter_driver.yml | 128 +++--------- detections/unsigned_image_loaded_by_LSASS.yml | 112 +++-------- detections/unsuccessful_netbackup_backups.yml | 24 +++ detections/unusually_long_command_line.yml | 35 ++++ .../unusually_long_command_line___mltk.yml | 48 +++++ detections/unusually_long_commandlines.yml | 112 ----------- .../unusually_long_commandlines_mltk.yml | 123 ------------ .../unusually_long_content-type_length.yml | 98 ---------- .../unusually_long_content_type_length.yml | 35 ++++ detections/usb_insertion.yml | 106 ---------- detections/users_without_mfa.yml | 111 ----------- detections/usn_journal_deletion.yml | 41 ++++ detections/web_fraud___account_harvesting.yml | 47 +++++ .../web_fraud___anomalous_user_clickspeed.yml | 42 ++++ ...aud___password_sharing_across_accounts.yml | 32 +++ ...servers_executing_suspicious_processes.yml | 118 +++-------- detections/windows_event_log_cleared.yml | 127 +++--------- .../windows_hosts_file_modification.yml | 37 ++++ detections/wmi_perm_event_subscription.yml | 105 ---------- .../wmi_perm_event_subscription_sysmon.yml | 103 ---------- .../wmi_permanent_event_subscription.yml | 34 ++++ ..._permanent_event_subscription___sysmon.yml | 33 ++++ detections/wmi_process_launch.yml | 109 ----------- detections/wmi_script_execution.yml | 109 ----------- detections/wmi_temp_event_subscription.yml | 108 ----------- .../wmi_temporary_event_subscription.yml | 38 ++++ investigations/aws_activity_via_region.yml | 40 ---- .../aws_network_interface_details.yml | 42 ---- investigations/aws_s3_bucket_details.yml | 42 ---- .../aws_user_activities_by_user_field.yml | 42 ---- .../aws_user_activity_by_accesskeyid.yml | 40 ---- .../aws_user_activity_by_src_user.yml | 40 ---- .../container_listing_aws_investigation.yml | 35 ---- investigations/dns_server_history.yml | 40 ---- investigations/dns_traffic_stats.yml | 45 ----- .../email_sent_to_hidden_cobra_actors.yml | 44 ----- .../first_occurrence_mac_address.yml | 44 ----- investigations/get_acl_details.yml | 39 ---- .../get_all_aws_activitiy_from_city.yml | 44 ----- .../get_all_aws_activitiy_from_country.yml | 44 ----- .../get_all_aws_activitiy_from_region.yml | 44 ----- .../get_all_aws_activitiy_from_src_ip.yml | 44 ----- .../get_all_backup_data_for_host.yml | 37 ---- .../get_authentication_logs_for_endpoint.yml | 41 ---- .../get_backup_logs_for_endpoint.yml | 37 ---- investigations/get_certificate_for_domain.yml | 45 ----- .../get_ec2_details_by_instance_id.yml | 45 ----- investigations/get_ec2_launch_details.yml | 42 ---- investigations/get_email_info.yml | 37 ---- investigations/get_emails_from_sender.yml | 38 ---- investigations/get_emails_from_source.yml | 41 ---- ...ogon_rights_modifications_for_endpoint.yml | 39 ---- ...et_logon_rights_modifications_for_user.yml | 39 ---- .../get_network_traffic_from_src_ip.yml | 39 ---- .../get_notable_history_for_endpoint.yml | 37 ---- investigations/get_notable_info.yml | 37 ---- investigations/get_okta_activity_by_app.yml | 34 ---- investigations/get_okta_activity_by_ip.yml | 34 ---- investigations/get_okta_user_activity.yml | 34 ---- investigations/get_parent_process_info.yml | 49 ----- .../get_process_creating_dns_traffic.yml | 50 ----- investigations/get_process_file_activity.yml | 47 ----- investigations/get_process_info.yml | 47 ----- investigations/get_process_info_for_port.yml | 47 ----- .../get_process_registry_activity.yml | 47 ----- investigations/get_rdp_authentications.yml | 43 ---- investigations/get_registry_activities.yml | 49 ----- investigations/get_risk_for_endpoint.yml | 40 ---- investigations/get_risk_for_user.yml | 40 ---- .../get_update_logs_for_endpoint.yml | 39 ---- .../get_user_info_from_identity_table.yml | 35 ---- .../get_vulnerability_logs_for_endpoint.yml | 36 ---- investigations/get_web_activity.yml | 41 ---- investigations/get_web_activity_by_src_ip.yml | 41 ---- investigations/get_web_posts_by_src.yml | 43 ---- investigations/get_web_session_info.yml | 41 ---- investigations/get_wmi_sysmon_events.yml | 42 ---- ...gate_cloud_compute_instance_activities.yml | 38 ---- ...ailed_logins_for_multiple_destinations.yml | 41 ---- .../investigate_pass_the_hash_attempts.yml | 39 ---- .../investigate_pass_the_ticket_attempts.yml | 43 ---- .../investigate_previous_unseen_user.yml | 44 ----- ...e_user_activities_in_all_cloud_regions.yml | 40 ---- ...user_activities_in_single_cloud_region.yml | 40 ---- .../kubernetes_aws_activity_by_src_ip.yml | 37 ---- .../kubernetes_gcp_activity_by_src_ip.yml | 35 ---- ...mail_attachment_investigate_and_delete.yml | 49 ----- .../suspicious_strings_in_HTTP_header.yml | 49 ----- .../user_activity_via_cloudtrail.yml | 44 ----- response_tasks/all_backup_logs_for_host.yml | 12 ++ ...azon_eks_kubernetes_activity_by_src_ip.yml | 17 ++ response_tasks/analyze_malicious_file.yml | 6 + ...stigate_user_activities_by_accesskeyid.yml | 15 ++ ...aws_investigate_user_activities_by_arn.yml | 17 ++ ...stigate_user_activities_by_source_user.yml | 15 ++ .../aws_network_acl_details_from_id.yml | 14 ++ ...twork_interface_details_via_resourceid.yml | 17 ++ .../aws_s3_bucket_details_via_bucketname.yml | 17 ++ .../dns_hijack_enrichment.yml | 42 +--- .../domain_certificate_investigation.yml | 46 +---- ...count_lockouts_enrichment_and_response.yml | 42 +--- .../gcp_kubernetes_activity_by_src_ip.yml | 21 ++ .../get_all_aws_activity_from_city.yml | 19 ++ .../get_all_aws_activity_from_country.yml | 19 ++ .../get_all_aws_activity_from_ip_address.yml | 19 ++ .../get_all_aws_activity_from_region.yml | 19 ++ .../get_authentication_logs_for_endpoint.yml | 14 ++ .../get_backup_logs_for_endpoint.yml | 12 ++ .../get_certificate_logs_for_a_domain.yml | 19 ++ .../get_dns_server_history_for_a_host.yml | 16 ++ response_tasks/get_dns_traffic_ratio.yml | 18 ++ ...get_ec2_instance_details_by_instanceid.yml | 20 ++ response_tasks/get_ec2_launch_details.yml | 17 ++ response_tasks/get_email_info.yml | 12 ++ .../get_emails_from_specific_sender.yml | 13 ++ ...e_and_last_occurrence_of_a_mac_address.yml | 17 ++ .../get_history_of_email_sources.yml | 17 ++ ...ogon_rights_modifications_for_endpoint.yml | 14 ++ ...et_logon_rights_modifications_for_user.yml | 14 ++ response_tasks/get_notable_history.yml | 14 ++ response_tasks/get_notable_info.yml | 14 ++ ...d_emails_to_hidden_cobra_threat_actors.yml | 18 ++ response_tasks/get_parent_process_info.yml | 19 ++ response_tasks/get_process_file_activity.yml | 17 ++ response_tasks/get_process_info.yml | 17 ++ ..._process_information_for_port_activity.yml | 19 ++ .../get_process_registry_activity.yml | 17 ++ ...rocess_responsible_for_the_dns_traffic.yml | 21 ++ response_tasks/get_registry_activities.yml | 20 ++ .../get_risk_modifiers_for_endpoint.yml | 15 ++ .../get_risk_modifiers_for_user.yml | 15 ++ .../get_sysmon_wmi_activity_for_host.yml | 16 ++ .../get_update_logs_for_endpoint.yml | 12 ++ ...t_user_information_from_identity_table.yml | 12 ++ .../get_vulnerability_logs_for_endpoint.yml | 11 ++ ...web_session_information_via_session_id.yml | 16 ++ ...stigate_aws_activities_via_region_name.yml | 15 ++ ...ate_aws_ecr_container_listing_activity.yml | 20 ++ ...gate_aws_user_activities_by_user_field.yml | 16 ++ ...gate_cloud_compute_instance_activities.yml | 12 ++ ...ailed_logins_for_multiple_destinations.yml | 16 ++ ...nvestigate_network_traffic_from_src_ip.yml | 12 ++ .../investigate_okta_activity_by_app.yml | 12 ++ ...nvestigate_okta_activity_by_ip_address.yml | 12 ++ .../investigate_pass_the_hash_attempts.yml | 17 ++ .../investigate_pass_the_ticket_attempts.yml | 18 ++ .../investigate_previous_unseen_user.yml | 19 ++ ...cessful_remote_desktop_authentications.yml | 18 ++ ...gate_suspicious_strings_in_http_header.yml | 23 +++ ...e_user_activities_in_all_cloud_regions.yml | 14 ++ .../investigate_user_activities_in_okta.yml | 12 ++ ...user_activities_in_single_cloud_region.yml | 14 ++ .../investigate_web_activity_from_host.yml | 13 ++ .../investigate_web_activity_from_src_ip.yml | 13 ++ .../investigate_web_posts_from_src.yml | 15 ++ response_tasks/malware_hunt_and_contain.yml | 10 + response_tasks/process_chain_analysis.yml | 9 + response_tasks/quarantaine_infected_host.yml | 6 + ...mail_attachment_investigate_and_delete.yml | 17 ++ responses/README.md | 2 - responses/credential_dumping_attack.yml | 19 ++ stories/account_monitoring.yml | 50 ----- stories/account_monitoring_and_controls.yml | 24 +++ ...ts.yml => apache_struts_vulnerability.yml} | 41 ++-- stories/asset_tracking.yml | 35 ++-- stories/aws_cross_account_activity.yml | 35 ++-- stories/aws_cryptomining.yml | 47 ++--- stories/aws_ec2.yml | 51 ----- stories/aws_network_acl.yml | 44 ----- stories/aws_network_acl_activity.yml | 24 +++ stories/aws_suspcious_logins.yml | 44 ----- ...ws_suspicious_provisioning_activities.yml} | 44 ++--- stories/aws_user_monitoring.yml | 49 ++--- stories/brand_monitoring.yml | 45 ++--- stories/cloud_cryptomining.yml | 59 ++---- .../{coldroot.yml => coldroot_macos_rat.yml} | 42 ++-- stories/collection_and_staging.yml | 49 ++--- stories/command_and_control.yml | 73 ++----- stories/common_phishing_frameworks.yml | 39 ++-- stories/container_implant_story.yml | 38 ---- ...mplantation_monitoring_&_investigation.yml | 26 +++ stories/credential_dumping.yml | 73 ++----- stories/data_protection.yml | 45 ++--- stories/defense_evasion.yml | 44 ----- stories/dhs_report_TA18-074A.yml | 88 --------- stories/dhs_report_ta18_074a.yml | 38 ++++ stories/disable_security_tools.yml | 54 ------ stories/disabling_security_tools.yml | 28 +++ stories/dns_amplification_attacks.yml | 37 ++-- stories/dns_hijacking.yml | 50 ++--- stories/dynamic_dns.yml | 44 ++--- ...emotet_malware_(dhs_report_ta18_201a).yml} | 63 ++---- stories/hidden_cobra_malware.yml | 64 ++---- stories/host_redirection.yml | 41 ++-- ...rabilities.yml => jboss_vulnerability.yml} | 38 ++-- stories/kubernetes_scanning_activity.yml | 47 ++--- stories/lateral_movement.yml | 46 ++--- stories/malicious_powershell.yml | 49 ++--- ...ackups.yml => monitor_backup_solution.yml} | 38 ++-- ... => monitor_for_unauthorized_software.yml} | 35 ++-- stories/monitor_for_updates.yml | 35 ++-- stories/netsh_abuse.yml | 42 ++-- ...geworm.yml => orangeworm_attack_group.yml} | 43 ++-- stories/phishing_payloads.yml | 38 ++-- ...ated_with_mudcarp_espionage_campaigns.yml} | 49 ++--- ..._traffic_allowed_or_protocol_mismatch.yml} | 44 ++--- stories/ransomware.yml | 88 ++------- ...l => router_&_infrastructure_security.yml} | 37 ++-- stories/{samsam.yml => samsam_ransomware.yml} | 75 ++----- ... spectre_and_meltdown_vulnerabilities.yml} | 35 ++-- ...ml => splunk_enterprise_vulnerability.yml} | 37 ++-- ...terprise_vulnerability_cve_2018_11409.yml} | 39 ++-- stories/sql_injection.yml | 37 ++-- stories/suspicious_aws_ec2_activities.yml | 25 +++ stories/suspicious_aws_login_activities.yml | 21 ++ ...3.yml => suspicious_aws_s3_activities.yml} | 43 ++-- ...traffic.yml => suspicious_aws_traffic.yml} | 35 ++-- stories/suspicious_cmd_line_executions.yml | 54 ------ .../suspicious_command_line_executions.yml | 28 +++ stories/suspicious_dns_traffic.yml | 60 ++---- stories/suspicious_emails.yml | 44 ++--- ...ties.yml => suspicious_mshta_activity.yml} | 45 ++--- stories/suspicious_okta_activities.yml | 55 ------ stories/suspicious_okta_activity.yml | 36 ++++ ...suspicious_windows_registry_activities.yml | 58 ++---- ...picious_wmi.yml => suspicious_wmi_use.yml} | 55 ++---- ....yml => unusual_aws_ec2_modifications.yml} | 35 ++-- stories/unusual_processes.yml | 57 ++---- ...ons.yml => use_of_cleartext_protocols.yml} | 35 ++-- ...{web_fraud.yml => web_fraud_detection.yml} | 43 ++-- stories/windows_defense_evasion_tactics.yml | 21 ++ ..._file_extension_and_association_abuse.yml} | 43 ++-- ...ivity.yml => windows_log_manipulation.yml} | 48 ++--- stories/windows_persistence.yml | 74 ------- stories/windows_persistence_techniques.yml | 24 +++ stories/windows_privilege_escalation.yml | 44 ++--- ...ce_abuse.yml => windows_service_abuse.yml} | 43 ++-- 616 files changed, 9499 insertions(+), 26495 deletions(-) create mode 100644 baselines/add_prohibited_processes_to_enterprise_security.yml delete mode 100644 baselines/add_prohibited_processes_to_es.yml delete mode 100644 baselines/approved_aws_service_accounts.yml delete mode 100644 baselines/assets_sorted_by_category.yml delete mode 100644 baselines/baseline_api_calls_per_user_arn.yml delete mode 100644 baselines/baseline_aws_regions.yml delete mode 100644 baselines/baseline_blocked_vpc_traffic.yml delete mode 100644 baselines/baseline_cloud_compute_regions.yml delete mode 100644 baselines/baseline_network_acl_modifications.yml create mode 100644 baselines/baseline_of_api_calls_per_user_arn.yml create mode 100644 baselines/baseline_of_blocked_outbound_traffic_from_aws.yml rename baselines/{train_unusually_long_commandlines.yml => baseline_of_command_line_length___mltk.yml} (51%) rename baselines/{train_dns_query_length.yml => baseline_of_dns_query_length___mltk.yml} (52%) create mode 100644 baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml create mode 100644 baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml create mode 100644 baselines/baseline_of_network_acl_activity_by_arn.yml create mode 100644 baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml create mode 100644 baselines/baseline_of_security_group_activity_by_arn.yml rename baselines/{train_smb_traffic_spike.yml => baseline_of_smb_traffic___mltk.yml} (53%) delete mode 100644 baselines/baseline_s3_deletion_by_arn.yml delete mode 100644 baselines/baseline_security_group_activity_by_arn.yml delete mode 100644 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detections/abnormally_high_ec2_instances_launched.yml delete mode 100644 detections/abnormally_high_instance_termination.yml delete mode 100644 detections/account_harvesting.yml delete mode 100644 detections/acl_with_open_ports.yml delete mode 100644 detections/activity_related_to_pass_the_hash.yml delete mode 100644 detections/add_to_untrust_cert_store.yml create mode 100644 detections/amazon_eks_kubernetes_cluster_scan_detection.yml create mode 100644 detections/amazon_eks_kubernetes_pod_scan_detection.yml delete mode 100644 detections/anomalous_webclick.yml delete mode 100644 detections/api_acitivity_from_previously_unseen_user_role.yml delete mode 100644 detections/attackers_scanning_for_vulnerable_jboss_servers.yml create mode 100644 detections/attempt_to_add_certificate_to_untrusted_store.yml create mode 100644 detections/attempt_to_stop_security_service.yml delete mode 100644 detections/attempted_credential_dump_from_registry_via_reg.yml create mode 100644 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delete mode 100644 detections/create_or_delete_network_shares.yml create mode 100644 detections/create_or_delete_windows_shares_using_net_exe.yml delete mode 100644 detections/cred_dump_via_copy_from_shadowcopy.yml delete mode 100644 detections/cred_dump_via_symlink_shadowcopy.yml create mode 100644 detections/credential_dumping_via_copy_command_from_shadow_copy.yml create mode 100644 detections/credential_dumping_via_symlink_to_shadow_copy.yml delete mode 100644 detections/cscript_via_cmd.yml delete mode 100644 detections/delete_shadow_copies.yml create mode 100644 detections/deleting_shadow_copies.yml delete mode 100644 detections/deletion_network_acl.yml create mode 100644 detections/detect_activity_related_to_pass_the_hash_attacks.yml create mode 100644 detections/detect_api_activity_from_users_without_mfa.yml create mode 100644 detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml create mode 100644 detections/detect_aws_api_activities_from_unapproved_accounts.yml create mode 100644 detections/detect_aws_console_login_by_user_from_new_city.yml create mode 100644 detections/detect_aws_console_login_by_user_from_new_country.yml create mode 100644 detections/detect_aws_console_login_by_user_from_new_region.yml create mode 100644 detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml create mode 100644 detections/detect_excessive_account_lockouts_from_endpoint.yml create mode 100644 detections/detect_excessive_user_account_lockouts.yml rename detections/{dyn_dns_queries.yml => detect_hosts_connecting_to_dynamic_domain_providers.yml} (53%) create mode 100644 detections/detect_large_outbound_icmp_packets.yml create mode 100644 detections/detect_long_dns_txt_record_response.yml create mode 100644 detections/detect_malicious_requests_to_exploit_jboss_servers.yml create mode 100644 detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml create mode 100644 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stories/defense_evasion.yml delete mode 100644 stories/dhs_report_TA18-074A.yml create mode 100644 stories/dhs_report_ta18_074a.yml delete mode 100644 stories/disable_security_tools.yml create mode 100644 stories/disabling_security_tools.yml rename stories/{emotet.yml => emotet_malware_(dhs_report_ta18_201a).yml} (50%) rename stories/{jboss_vulnerabilities.yml => jboss_vulnerability.yml} (89%) rename stories/{monitor_backups.yml => monitor_backup_solution.yml} (57%) rename stories/{detect_unauthorized_processes.yml => monitor_for_unauthorized_software.yml} (71%) rename stories/{orangeworm.yml => orangeworm_attack_group.yml} (70%) rename stories/{mudcarp.yml => possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml} (69%) rename stories/{prohibited_traffic_and_protocol_mismatch.yml => prohibited_traffic_allowed_or_protocol_mismatch.yml} (53%) rename stories/{routers_and_infrastructure.yml => router_&_infrastructure_security.yml} (64%) rename stories/{samsam.yml => samsam_ransomware.yml} (55%) rename stories/{spectre_meltdown.yml => spectre_and_meltdown_vulnerabilities.yml} (53%) rename stories/{splunk_vulnerabilities.yml => splunk_enterprise_vulnerability.yml} (72%) rename stories/{splunk_information_disclosure.yml => splunk_enterprise_vulnerability_cve_2018_11409.yml} (75%) create mode 100644 stories/suspicious_aws_ec2_activities.yml create mode 100644 stories/suspicious_aws_login_activities.yml rename stories/{aws_s3.yml => suspicious_aws_s3_activities.yml} (59%) rename stories/{aws_suspcious_traffic.yml => suspicious_aws_traffic.yml} (74%) delete mode 100644 stories/suspicious_cmd_line_executions.yml create mode 100644 stories/suspicious_command_line_executions.yml rename stories/{suspicious_mshta_activities.yml => suspicious_mshta_activity.yml} (59%) delete mode 100644 stories/suspicious_okta_activities.yml create mode 100644 stories/suspicious_okta_activity.yml rename stories/{suspicious_wmi.yml => suspicious_wmi_use.yml} (50%) rename stories/{aws_ec2_modifications.yml => unusual_aws_ec2_modifications.yml} (68%) rename stories/{non-secure_communications.yml => use_of_cleartext_protocols.yml} (61%) rename stories/{web_fraud.yml => web_fraud_detection.yml} (74%) create mode 100644 stories/windows_defense_evasion_tactics.yml rename stories/{file_extension_abuse.yml => windows_file_extension_and_association_abuse.yml} (75%) rename stories/{suspicious_event_log_activity.yml => windows_log_manipulation.yml} (59%) delete mode 100644 stories/windows_persistence.yml create mode 100644 stories/windows_persistence_techniques.yml rename stories/{service_abuse.yml => windows_service_abuse.yml} (58%) diff --git a/baselines/add_prohibited_processes_to_enterprise_security.yml b/baselines/add_prohibited_processes_to_enterprise_security.yml new file mode 100644 index 0000000000..7d56b81d78 --- /dev/null +++ b/baselines/add_prohibited_processes_to_enterprise_security.yml @@ -0,0 +1,20 @@ +name: Add Prohibited Processes to Enterprise Security +id: 251930a5-1451-4428-bb13-eed5775be0ce +version: '1.0' +date: '2017-09-15' +description: This search takes the existing interesting process table from ES, filters + out any existing additions added by ESCU and then updates the table with processes + identified by ESCU that should be prohibited on your endpoints. +how_to_implement: This search should be run on each new install of ESCU. +author: David Dorsey, Splunk +search: '| inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup + append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull + value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup + interesting_processes_lookup | stats count' +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - Monitor for Unauthorized Software + - SamSam Ransomware + detections: + - Prohibited Software On Endpoint diff --git a/baselines/add_prohibited_processes_to_es.yml b/baselines/add_prohibited_processes_to_es.yml deleted file mode 100644 index e240f49f8a..0000000000 --- a/baselines/add_prohibited_processes_to_es.yml +++ /dev/null @@ -1,43 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup - append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain - | fillnull value=false is_required is_secure | fillnull value=true is_prohibited - | outputlookup interesting_processes_lookup | stats count' -creation_date: '2017-06-27' -data_metadata: - data_models: [] - data_source: - - Splunk Enterprise - providing_technologies: - - Splunk Enterprise Security -description: This search takes the existing interesting process table from ES, filters - out any existing additions added by ESCU and then updates the table with processes - identified by ESCU that should be prohibited on your endpoints. -eli5: This search outputs the interesting processes lookup table and filters out all - processes in the table that haven't already been inserted by ESCU. It then appends - to those results all the processes currently identified by ESCU that should be prohibited. - Next, it fills in the required fields with processes identified by ESCU, and then - writes the results back to the interesting process lookup table. This is done so - any new processes identified that should be prohibited will be added to the lookup - table without creating any duplicate entries. -how_to_implement: This search should be run on each new install of ESCU. -id: 251930a5-1451-4428-bb13-eed5775be0ce -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-15' -name: Add Prohibited Processes to Enterprise Security -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/approved_aws_service_accounts.yml b/baselines/approved_aws_service_accounts.yml deleted file mode 100644 index 65f5338fe8..0000000000 --- a/baselines/approved_aws_service_accounts.yml +++ /dev/null @@ -1,45 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail errorCode=success | rename userName as identity - | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats - count by identity | table identity | outputlookup aws_service_accounts | stats - count -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for successful API activity in CloudTrail within the - last 30 days, filters out known users from the identity table, and outputs values - of users into `aws_service_accounts.csv` lookup file. -eli5: We first look for all successful CloudTrail API activity caused by types of - user accounts and then remove all the events caused by users in the Identity table. - This generates a list of accounts--typically service accounts--configured in your - AWS environment. We output this list of service accounts to `aws_service_accounts.csv`. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Please validate the service account entires in `aws_service_accounts.csv`, - which is a lookup file created as a result of running this support search. Please - remove the entries of service accounts that are not legitimate. -id: fc0edc95-ff2b-48b1-5f6f-63ga3789fd43 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-12-03' -name: Create a list of approved AWS service accounts -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/baselines/assets_sorted_by_category.yml b/baselines/assets_sorted_by_category.yml deleted file mode 100644 index 770e29c9a6..0000000000 --- a/baselines/assets_sorted_by_category.yml +++ /dev/null @@ -1,40 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| from datamodel Identity_Management.All_Assets | stats count values(nt_host) - by category | sort -count' -creation_date: '2017-06-11' -data_metadata: - data_models: - - Identity_Management - data_source: - - Splunk Enterprise Security - providing_technologies: - - Splunk Enterprise Security -description: This search shows you every asset category you have and the assets that - belong to those categories. -eli5: This search gives you the number and the names of the hosts of each host in - your environment by category. It will then sort them by the count. -how_to_implement: To successfully implement this search you must first leverage the - Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv - file which should then be mapped to the Identity_Management data model. The Identity_Management - data model will contain a list of known authorized company assets. Ensure that all - inventoried systems are constantly vetted and updated. -id: dcfd6b40-42f9-469d-a433-2e53f7489ff9 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-13' -name: Count of assets by category -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/baseline_api_calls_per_user_arn.yml b/baselines/baseline_api_calls_per_user_arn.yml deleted file mode 100644 index ab8128d0e7..0000000000 --- a/baselines/baseline_api_calls_per_user_arn.yml +++ /dev/null @@ -1,47 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn - | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) - as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, - stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, - avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats - count -creation_date: '2018-04-09' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search establishes, on a per-hour basis, the average and the standard - deviation of the number of API calls made by each user. Also recorded is the number - of data points for each user. This table is then outputted to a lookup file to allow - the detection search to operate quickly. -eli5: This search returns all log events that are API calls, pulls out the ARN that - initiated each call, and collects them in one-hour groupings. Next, it calculates - the number of API calls made per ARN per hour. For each ARN, it calculates the average - and standard deviation of this count on a per-hour basis. It also includes the - number of data points each ARN had. This table is then stored in a lookup file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail - inputs. -id: fc0edc96-ff2b-48b0-9f6f-63da3783fd63 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-04-09' -name: Baseline of API Calls per User ARN -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/baseline_aws_regions.yml b/baselines/baseline_aws_regions.yml deleted file mode 100644 index cebfa4c5a9..0000000000 --- a/baselines/baseline_aws_regions.yml +++ /dev/null @@ -1,45 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest - latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv - | stats count -creation_date: '2018-01-08' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where an AWS instance is started - and creates a baseline of most recent time (latest) and the first time (earliest) - we've seen this region in our dataset grouped by the value awsRegion for the last - 30 days -eli5: In this support search, we create a table of the first time (earliest) and most - recent time (latest) that this region has been seen in our dataset, grouped by the - value `awsRegion`. We only look for those events where an instance has been started. - All of these entries will be added to the `previously_seen_aws_regions.csv` lookup - file, which will act like a baseline for detections. Please validate the entries - of region names in the lookup file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail - inputs. -id: fc0edc95-ff2b-48b0-9f6f-63da3789fd63 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-01-08' -name: Previously Seen AWS Regions -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/baseline_blocked_vpc_traffic.yml b/baselines/baseline_blocked_vpc_traffic.yml deleted file mode 100644 index fa151bc2ce..0000000000 --- a/baselines/baseline_blocked_vpc_traffic.yml +++ /dev/null @@ -1,54 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 - OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND - dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | - stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) - as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) - as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections - by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, - stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections - | stats count -creation_date: '2018-04-26' -data_metadata: - data_source: - - AWS VPC Flow Logs - data_sourcetypes: - - aws:cloudwatchlogs:vpcflow - providing_technologies: - - AWS -description: This search establishes, on a per-hour basis, the average and the standard - deviation of the number of outbound connections blocked in your VPC flow logs by - each source IP address (IP address of your EC2 instances). Also recorded is the - number of data points for each source IP. This table outputs to a lookup file to - allow the detection search to operate quickly. -eli5: Use this search to create a baseline of blocked outbound network connections - by each source IP in your AWS environment. This search returns all log events that - correspond to a blocked outbound network connection, extracts the source IP from - where the outbound connection was initiated, and collects the events in one-hour - groupings. Next, it calculates the number of outbound connections blocked per hour. - For each source IP, it calculates the average and standard deviation of this count - on a per-hour basis. It also includes the number of data points each source IP - had. This table is then stored in a lookup file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow - logs.`. -id: fc0edd96-ff2b-48b0-9f1f-63da3782fd63 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-05-07' -name: Baseline of blocked outbound traffic from AWS -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/baseline_cloud_compute_regions.yml b/baselines/baseline_cloud_compute_regions.yml deleted file mode 100644 index d3a6f872fa..0000000000 --- a/baselines/baseline_cloud_compute_regions.yml +++ /dev/null @@ -1,50 +0,0 @@ -baseline: - splunk: - lookups: - - previously_seen_cloud_regions - macros: - - previously_seen_cloud_regions_input_filter - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from - datamodel=Cloud_Infrastructure.Compute where Compute.action=start `previously_seen_cloud_regions_input_filter` - by Compute.region | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_regions - | stats count' -creation_date: '2019-10-02' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: This search looks for cloud compute events where a compute instance is - started and creates a baseline of most recent time, `lastTime` and the first time - `firstTime` we've seen this region in our dataset grouped by the region for the - last 30 days -eli5: In this support search, we create a table of the first time `firstTime` and - most recent time `lastTime` that this region has been seen in our dataset, grouped - by the region. We only look for those events where an instance has been started. - All of these entries will be added to the `previously_seen_cloud_regions` lookup - file, which will act like a baseline for detections. -how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs - and have the Security Research cloud data model installed. -id: b5e232db-dec6-4db8-aaa1-dd5474521e40 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-10-02' -name: Previously Seen Cloud Regions -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/baseline_network_acl_modifications.yml b/baselines/baseline_network_acl_modifications.yml deleted file mode 100644 index 9b97d69b7d..0000000000 --- a/baselines/baseline_network_acl_modifications.yml +++ /dev/null @@ -1,49 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail `network_acl_events` | spath output=arn path=userIdentity.arn - | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) - as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, - stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, - avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats - count -creation_date: '2018-05-21' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search establishes, on a per-hour basis, the average and the standard - deviation of the number of API calls that were related to network ACLs made by each - user. Also recorded is the number of data points for each user. This table is then - outputted to a lookup file to allow the detection search to operate quickly. -eli5: Use this search to create a baseline for API calls related to network ACLs for - the users who initiated this activity. It returns all logged API calls for network - activity, pulls out the ARN that initiated each call, and collects the `eventNames` - in one-hour groupings. Next, it calculates the number of API calls made per ARN - per-hour. For each ARN, it calculates the average and standard deviation of this - count on a per-hour basis. It also includes the number of data points for each ARN. - This table is stored in a lookup file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail - inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. -id: fc0edd96-ff2b-4810-9f1f-63da3783fd63 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-05-21' -name: Baseline of Network ACL Activity by ARN -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/baseline_of_api_calls_per_user_arn.yml b/baselines/baseline_of_api_calls_per_user_arn.yml new file mode 100644 index 0000000000..73f1346346 --- /dev/null +++ b/baselines/baseline_of_api_calls_per_user_arn.yml @@ -0,0 +1,22 @@ +name: Baseline of API Calls per User ARN +id: fc0edc96-ff2b-48b0-9f6f-63da3783fd63 +version: '1.0' +date: '2018-04-09' +description: This search establishes, on a per-hour basis, the average and the standard + deviation of the number of API calls made by each user. Also recorded is the number + of data points for each user. This table is then outputted to a lookup file to allow + the detection search to operate quickly. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail + inputs. +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn + | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) + as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, + stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, + avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count +tags: + analytics_story: + - AWS User Monitoring + detections: + - Detect Spike in AWS API Activity diff --git a/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml b/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml new file mode 100644 index 0000000000..8ab019c3de --- /dev/null +++ b/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml @@ -0,0 +1,28 @@ +name: Baseline of blocked outbound traffic from AWS +id: fc0edd96-ff2b-48b0-9f1f-63da3782fd63 +version: '1.0' +date: '2018-05-07' +description: This search establishes, on a per-hour basis, the average and the standard + deviation of the number of outbound connections blocked in your VPC flow logs by + each source IP address (IP address of your EC2 instances). Also recorded is the + number of data points for each source IP. This table outputs to a lookup file to + allow the detection search to operate quickly. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow + logs.`. +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR + src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 + AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections + by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) + as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) + as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, + avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections + | stats count +tags: + analytics_story: + - AWS Network ACL Activity + - Command and Control + - Suspicious AWS Traffic + detections: + - Detect Spike in blocked Outbound Traffic from your AWS diff --git a/baselines/train_unusually_long_commandlines.yml b/baselines/baseline_of_command_line_length___mltk.yml similarity index 51% rename from baselines/train_unusually_long_commandlines.yml rename to baselines/baseline_of_command_line_length___mltk.yml index f41188949c..32c0717762 100644 --- a/baselines/train_unusually_long_commandlines.yml +++ b/baselines/baseline_of_command_line_length___mltk.yml @@ -1,34 +1,12 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -31d@d - latest_time: -1d@d - search: '| tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as - end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest - Processes.process_name Processes.process | `drop_dm_object_name(Processes)` - | search user!=unknown | `security_content_ctime(start_time)`| `security_content_ctime(end_time)`| eval processlen=len(process) - | fit DensityFunction processlen by user into cmdline_pdfmodel' -creation_date: '2019-05-08' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Baseline of Command Line Length - MLTK +id: d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459 +version: '1.0' +date: '2019-05-08' description: This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. -eli5: Create a machine-learning (ML) model to characterize the length of the command - lines used in your environment. This can help you identify unusually long ones that - may indicate that attackers are executing commands on yout systems. how_to_implement: You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number @@ -39,18 +17,19 @@ how_to_implement: You must be ingesting endpoint data and populating the Endpoin a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -id: d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459 -known_false_positives: '' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2019-05-08' -name: Baseline of Command Line Length - MLTK -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as start_time + max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest + Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search + user!=unknown | `security_content_ctime(start_time)`| `security_content_ctime(end_time)`| + eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel' +tags: + analytics_story: + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Ransomware + - Suspicious Command-Line Executions + - Suspicious MSHTA Activity + - Unusual Processes + detections: + - Unusually Long Command Line - MLTK + - Detect Prohibited Applications Spawning cmd.exe diff --git a/baselines/train_dns_query_length.yml b/baselines/baseline_of_dns_query_length___mltk.yml similarity index 52% rename from baselines/train_dns_query_length.yml rename to baselines/baseline_of_dns_query_length___mltk.yml index 3a796e39b7..7dc237389b 100644 --- a/baselines/train_dns_query_length.yml +++ b/baselines/baseline_of_dns_query_length___mltk.yml @@ -1,31 +1,12 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -31d@d - latest_time: -1d@d - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query - DNS.record_type | search DNS.record_type=* | `drop_dm_object_name("DNS")` | - eval query_length = len(query) | fit DensityFunction query_length by record_type - into dns_query_pdfmodel' -creation_date: '2019-05-08' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro +name: Baseline of DNS Query Length - MLTK +id: c914844c-0ff5-4efc-8d44-c063443129ba +version: '1.0' +date: '2019-05-08' description: This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. -eli5: Create a machine-learning (ML) model to characterize the length of DNS requests - seen in your environment to help identify unusually long ones that may be indicative - of attacker infrastrucutre or the use of DNS as a command-and-control channel in - your environment. how_to_implement: To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any @@ -34,18 +15,15 @@ how_to_implement: To successfully implement this search, you will need to ensure period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -id: c914844c-0ff5-4efc-8d44-c063443129ba -known_false_positives: '' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2019-05-08' -name: Baseline of DNS Query Length - MLTK -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution + by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name("DNS")` + | eval query_length = len(query) | fit DensityFunction query_length by record_type + into dns_query_pdfmodel' +tags: + analytics_story: + - Command and Control + - Hidden Cobra Malware + - Suspicious DNS Traffic + detections: + - DNS Query Length Outliers - MLTK diff --git a/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml b/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml new file mode 100644 index 0000000000..3c8ac68b0d --- /dev/null +++ b/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml @@ -0,0 +1,33 @@ +name: Baseline of Excessive AWS Instances Launched by User - MLTK +id: fa5634df-fb05-4b4b-aba0-6115138bb1ba +version: '1.0' +date: '2019-11-14' +description: This search is used to build a Machine Learning Toolkit (MLTK) model + for how many RunInstances users do in the environment. By default, the search uses + the last 90 days of data to build the model. The model created by this search is + then used in the corresponding detection search, which identifies subsequent outliers + in the number of RunInstances performed by a user in a small time window. +how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs.\ + + In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, + along with any required dependencies. Depending on the number of users in your environment, + you may also need to adjust the value for max_inputs in the MLTK settings for the + DensityFunction algorithm, then ensure that the search completes in a reasonable + timeframe. By default, the search builds the model using the past 30 days of data. + You can modify the search window to build the model over a longer period of time, + which may give you better results. You may also want to periodically re-run this + search to rebuild the model with the latest data.\ + + More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.' +author: Jason Brewer, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` + | bucket span=10m _time | stats count as instances_launched by _time src_user | + fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 +tags: + analytics_story: + - Cloud Cryptomining + - Suspicious AWS EC2 Activities + detections: + - Abnormally High AWS Instances Launched by User - MLTK diff --git a/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml b/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml new file mode 100644 index 0000000000..aa37ff0640 --- /dev/null +++ b/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml @@ -0,0 +1,33 @@ +name: Baseline of Excessive AWS Instances Terminated by User - MLTK +id: b28ed6de-e4ba-40f7-ae0a-93a088c774ab +version: '1.0' +date: '2019-11-14' +description: This search is used to build a Machine Learning Toolkit (MLTK) model + for how many TerminateInstances users do in the environment. By default, the search + uses the last 90 days of data to build the model. The model created by this search + is then used in the corresponding detection search, which identifies subsequent + outliers in the number of TerminateInstances performed by a user in a small time + window. +how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs.\ + + In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, + along with any required dependencies. Depending on the number of users in your environment, + you may also need to adjust the value for max_inputs in the MLTK settings for the + DensityFunction algorithm, then ensure that the search completes in a reasonable + timeframe. By default, the search builds the model using the past 30 days of data. + You can modify the search window to build the model over a longer period of time, + which may give you better results. You may also want to periodically re-run this + search to rebuild the model with the latest data.\ + + More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.' +author: Jason Brewer, Splunk +search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` + | bucket span=10m _time | stats count as instances_terminated by _time src_user + | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 +tags: + analytics_story: + - Suspicious AWS EC2 Activities + detections: + - Abnormally High AWS Instances Terminated by User - MLTK diff --git a/baselines/baseline_of_network_acl_activity_by_arn.yml b/baselines/baseline_of_network_acl_activity_by_arn.yml new file mode 100644 index 0000000000..b9bf21a4cc --- /dev/null +++ b/baselines/baseline_of_network_acl_activity_by_arn.yml @@ -0,0 +1,23 @@ +name: Baseline of Network ACL Activity by ARN +id: fc0edd96-ff2b-4810-9f1f-63da3783fd63 +version: '1.0' +date: '2018-05-21' +description: This search establishes, on a per-hour basis, the average and the standard + deviation of the number of API calls that were related to network ACLs made by each + user. Also recorded is the number of data points for each user. This table is then + outputted to a lookup file to allow the detection search to operate quickly. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail + inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail `network_acl_events` | spath output=arn path=userIdentity.arn + | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) + as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, + stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, + avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats + count +tags: + analytics_story: + - AWS Network ACL Activity + detections: + - Detect Spike in Network ACL Activity diff --git a/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml b/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml new file mode 100644 index 0000000000..4270200846 --- /dev/null +++ b/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml @@ -0,0 +1,22 @@ +name: Baseline of S3 Bucket deletion activity by ARN +id: fc0edd96-ff2b-48b0-9f1f-63eq3783fd63 +version: '1.0' +date: '2018-07-17' +description: This search establishes, on a per-hour basis, the average and standard + deviation for the number of API calls related to deleting an S3 bucket by each user. + Also recorded is the number of data points for each user. This table is then outputted + to a lookup file to allow the detection search to operate quickly. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail + inputs. +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventName=DeleteBucket | spath output=arn path=userIdentity.arn + | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) + as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, + stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, + avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count +tags: + analytics_story: + - Suspicious AWS S3 Activities + detections: + - Detect Spike in S3 Bucket deletion diff --git a/baselines/baseline_of_security_group_activity_by_arn.yml b/baselines/baseline_of_security_group_activity_by_arn.yml new file mode 100644 index 0000000000..673f34c8e4 --- /dev/null +++ b/baselines/baseline_of_security_group_activity_by_arn.yml @@ -0,0 +1,23 @@ +name: Baseline of Security Group Activity by ARN +id: fc0edd96-ff2b-48b0-9f1f-63da3783fd63 +version: '1.0' +date: '2018-04-17' +description: This search establishes, on a per-hour basis, the average and the standard + deviation for the number of API calls related to security groups made by each user. + Also recorded is the number of data points for each user. This table is then outputted + to a lookup file to allow the detection search to operate quickly. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail + inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail `security_group_api_calls` | spath output=arn path=userIdentity.arn + | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) + as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, + stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, + avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats + count +tags: + analytics_story: + - AWS User Monitoring + detections: + - Detect Spike in Security Group Activity diff --git a/baselines/train_smb_traffic_spike.yml b/baselines/baseline_of_smb_traffic___mltk.yml similarity index 53% rename from baselines/train_smb_traffic_spike.yml rename to baselines/baseline_of_smb_traffic___mltk.yml index 0217269002..fbd3fef0cd 100644 --- a/baselines/train_smb_traffic_spike.yml +++ b/baselines/baseline_of_smb_traffic___mltk.yml @@ -1,35 +1,13 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -31d@d - latest_time: -1d@d - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 - OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src - | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") - | `drop_dm_object_name("All_Traffic")` | fit DensityFunction count by "HourOfDay,DayOfWeek" - into smb_pdfmodel' -creation_date: '2019-05-08' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Splunk Stream - - Bro +name: Baseline of SMB Traffic - MLTK +id: df98763b-0b08-4281-8ef9-08db7ac572a9 +version: '1.0' +date: '2019-05-08' description: This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. -eli5: Create a machine-learning (ML) model to characterize the number of SMB connections - observed in your environment. This may help identify spikes in SMB traffic that - may be indicative of attackers scanning or attempting to propagate to other systems - in your environment. By default, this model is built over 30 days of data and profiles - the number of SMB connections in your environment by the hour of day/day of week - that the connections occur. how_to_implement: You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, @@ -43,18 +21,20 @@ how_to_implement: You must be ingesting network traffic and populating the Netwo which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -id: df98763b-0b08-4281-8ef9-08db7ac572a9 -known_false_positives: '' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2019-05-08' -name: Baseline of SMB Traffic - MLTK -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic + where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb + by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval + DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name("All_Traffic")` | fit DensityFunction + count by "HourOfDay,DayOfWeek" into smb_pdfmodel' +tags: + analytics_story: + - DHS Report TA18-074A + - Disabling Security Tools + - Emotet Malware (DHS Report TA18-201A) + - Hidden Cobra Malware + - Netsh Abuse + - Ransomware + detections: + - SMB Traffic Spike - MLTK + - Processes launching netsh diff --git a/baselines/baseline_s3_deletion_by_arn.yml b/baselines/baseline_s3_deletion_by_arn.yml deleted file mode 100644 index bf92bae087..0000000000 --- a/baselines/baseline_s3_deletion_by_arn.yml +++ /dev/null @@ -1,48 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=DeleteBucket | spath output=arn path=userIdentity.arn - | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) - as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, - stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, - avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count -creation_date: '2018-07-17' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search establishes, on a per-hour basis, the average and standard - deviation for the number of API calls related to deleting an S3 bucket by each user. - Also recorded is the number of data points for each user. This table is then outputted - to a lookup file to allow the detection search to operate quickly. -eli5: Use this search to create a baseline for API calls related to deleting an S3 - bucket, grouped by the users who initiated this activity. It returns all logged - API calls for S3 bucket-deletion activity and then pulls out the ARN that initiated - each call. Next, it calculates the number of API calls made per ARN per hour. For - each ARN, it calculates the average and standard deviation of this count on a per-hour - basis. It also includes the number of data points for each ARN. This table is stored - in a lookup file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail - inputs. -id: fc0edd96-ff2b-48b0-9f1f-63eq3783fd63 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-07-17' -name: Baseline of S3 Bucket deletion activity by ARN -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/baseline_security_group_activity_by_arn.yml b/baselines/baseline_security_group_activity_by_arn.yml deleted file mode 100644 index aca2ef9bb2..0000000000 --- a/baselines/baseline_security_group_activity_by_arn.yml +++ /dev/null @@ -1,49 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail `security_group_api_calls` | spath output=arn path=userIdentity.arn - | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) - as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, - stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, - avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | - stats count -creation_date: '2018-04-17' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search establishes, on a per-hour basis, the average and the standard - deviation for the number of API calls related to security groups made by each user. - Also recorded is the number of data points for each user. This table is then outputted - to a lookup file to allow the detection search to operate quickly. -eli5: Use this search to create a baseline for API calls related to security groups - by the users who initiated this activity. It returns all logged API calls for all - security-group-related activity, pulls out the ARN that initiated each call, and - collects the `eventNames` in one-hour groupings. Next, it calculates the number - of API calls made per ARN per hour. For each ARN, it calculates the average and - standard deviation of this count on a per-hour basis. It also includes the number - of data points for each ARN. This table is stored in a lookup file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail - inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -id: fc0edd96-ff2b-48b0-9f1f-63da3783fd63 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-04-17' -name: Baseline of Security Group Activity by ARN -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/brand_abuse_dnstwist_domains.yml b/baselines/brand_abuse_dnstwist_domains.yml deleted file mode 100644 index 1f1d235a65..0000000000 --- a/baselines/brand_abuse_dnstwist_domains.yml +++ /dev/null @@ -1,43 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse="true" - | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count' -creation_date: '2017-06-01' -data_metadata: - data_source: - - Splunk Enterprise Security Content Update - providing_technologies: - - Splunk Enterprise -description: This search creates permutations of your existing domains, removes the - valid domain names and stores them in a specified lookup file so they can be checked - for in the associated detection searches. -eli5: This search starts with the dnstwist command consuming domains from a file called - domains.csv in the DA-ESS-SOC/lookups directory. This search then adds a domain\_abuse=true - term to each permutation, removes all the valid domain names and stores all that - information into a lookup file that is used in the associated detection search. - Alternatively domain dnstwist permutations can be calculated from domains in the - `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` lookups located - in **Splunk\_SA\_CIM** using argument `populate_from_cim=true`. Also an individual - domain can be passed using argument `domain=` -how_to_implement: To successfully implement this search you need to update the file - called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` - and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. -id: 19f7d2ec-6028-4d01-bcdb-bda9a034c17f -known_false_positives: '' -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -modification_date: '2018-10-08' -name: DNSTwist Domain Names -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/baselines/count_of_assets_by_category.yml b/baselines/count_of_assets_by_category.yml new file mode 100644 index 0000000000..99411b1b50 --- /dev/null +++ b/baselines/count_of_assets_by_category.yml @@ -0,0 +1,19 @@ +name: Count of assets by category +id: dcfd6b40-42f9-469d-a433-2e53f7489ff9 +version: '1.0' +date: '2017-09-13' +description: This search shows you every asset category you have and the assets that + belong to those categories. +how_to_implement: To successfully implement this search you must first leverage the + Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv + file which should then be mapped to the Identity_Management data model. The Identity_Management + data model will contain a list of known authorized company assets. Ensure that all + inventoried systems are constantly vetted and updated. +author: Bhavin Patel, Splunk +search: '| from datamodel Identity_Management.All_Assets | stats count values(nt_host) + by category | sort -count' +tags: + analytics_story: + - Asset Tracking + detections: + - Detect Unauthorized Assets by MAC address diff --git a/baselines/count_of_unique_ips_connecting_to_ports.yml b/baselines/count_of_unique_ips_connecting_to_ports.yml new file mode 100644 index 0000000000..7610cb45be --- /dev/null +++ b/baselines/count_of_unique_ips_connecting_to_ports.yml @@ -0,0 +1,13 @@ +name: Count of Unique IPs Connecting to Ports +id: 9f3bae5a-9fe3-49df-8c84-5edc51d84b7f +version: '1.0' +date: '2017-09-13' +description: The search counts the number of times a connection was observed to each + destination port, and the number of unique source IPs connecting to them. +how_to_implement: To successfully implement this search, you must be ingesting network + traffic, and populating the Network_Traffic data model. +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts + from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` + | sort - count' +tags: {} diff --git a/baselines/create_a_list_of_approved_aws_service_accounts.yml b/baselines/create_a_list_of_approved_aws_service_accounts.yml new file mode 100644 index 0000000000..e20ec70f9a --- /dev/null +++ b/baselines/create_a_list_of_approved_aws_service_accounts.yml @@ -0,0 +1,21 @@ +name: Create a list of approved AWS service accounts +id: fc0edc95-ff2b-48b1-5f6f-63ga3789fd43 +version: '2.0' +date: '2018-12-03' +description: This search looks for successful API activity in CloudTrail within the + last 30 days, filters out known users from the identity table, and outputs values + of users into `aws_service_accounts.csv` lookup file. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Please validate the service account entires in `aws_service_accounts.csv`, + which is a lookup file created as a result of running this support search. Please + remove the entries of service accounts that are not legitimate. +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail errorCode=success | rename userName as identity + | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count + by identity | table identity | outputlookup aws_service_accounts | stats count +tags: + analytics_story: + - AWS User Monitoring + detections: + - Detect AWS API Activities From Unapproved Accounts diff --git a/baselines/discover_dns_records.yml b/baselines/discover_dns_records.yml index 449dc34241..2a4315ee8b 100644 --- a/baselines/discover_dns_records.yml +++ b/baselines/discover_dns_records.yml @@ -1,52 +1,26 @@ -baseline: - splunk: - schedule: - cron_schedule: 0 0 1 * * - earliest_time: -30d@d - latest_time: -10m@m - search: '| inputlookup cim_corporate_email_domains.csv | inputlookup append=T - cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | - eval domain = trim(replace(domain, "\*", "")) | join domain [|tstats `security_content_summariesonly` - count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution - where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query - | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] - | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,domain,type,query,answer - | outputlookup createinapp=true discovered_dns_records.csv' -creation_date: '2019-02-14' -data_metadata: - data_models: - - Network_Resolution - data_source: - - Network Communication - providing_technologies: - - Splunk Stream - - Bro +name: Discover DNS records +id: c096f721-8842-42ce-bfc7-74bd8c72b7c3 +version: '1.0' +date: '2019-02-14' description: The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup -eli5: Discover the DNS records and their answers for domains owned by the company - using network traffic events. The discovered events are exported as a lookup named - `discovered_dns_records.csv` -entities: - - query - - answer how_to_implement: To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation -id: c096f721-8842-42ce-bfc7-74bd8c72b7c3 -known_false_positives: 'Please vet the lookup created by this baseline search ' -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -modification_date: '2019-02-14' -name: Discover DNS records -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -spec_version: 2 -type: splunk -version: '1.0' +author: Jose Hernandez, Splunk +search: '| inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv + | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, + "\*", "")) | join domain [|tstats `security_content_summariesonly` count values(DNS.record_type) + as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE + DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | + where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv + delim=" " answer | makemv delim=" " type | sort -count | table count,domain,type,query,answer + | outputlookup createinapp=true discovered_dns_records.csv' +tags: + analytics_story: + - DNS Hijacking + detections: + - DNS record changed diff --git a/baselines/dnstwist_domain_names.yml b/baselines/dnstwist_domain_names.yml new file mode 100644 index 0000000000..54f2a308ae --- /dev/null +++ b/baselines/dnstwist_domain_names.yml @@ -0,0 +1,21 @@ +name: DNSTwist Domain Names +id: 19f7d2ec-6028-4d01-bcdb-bda9a034c17f +version: '2.0' +date: '2018-10-08' +description: This search creates permutations of your existing domains, removes the + valid domain names and stores them in a specified lookup file so they can be checked + for in the associated detection searches. +how_to_implement: To successfully implement this search you need to update the file + called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` + and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. +author: David Dorsey, Splunk +search: '| dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse="true" + | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count' +tags: + analytics_story: + - Brand Monitoring + - Suspicious Emails + detections: + - Monitor Email For Brand Abuse + - Monitor DNS For Brand Abuse + - Monitor Web Traffic For Brand Abuse diff --git a/baselines/identify_ports_on_network.yml b/baselines/identify_ports_on_network.yml deleted file mode 100644 index fd19d7fe50..0000000000 --- a/baselines/identify_ports_on_network.yml +++ /dev/null @@ -1,39 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts - from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` - | sort - count' -creation_date: '2017-06-24' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communication - providing_technologies: - - Splunk Stream - - Bro -description: The search counts the number of times a connection was observed to each - destination port, and the number of unique source IPs connecting to them. -eli5: For each port being accessed on the network, this search gives the total number - of connections observed, and the number of unique IP addresses making those connections. -how_to_implement: To successfully implement this search, you must be ingesting network - traffic, and populating the Network_Traffic data model. -id: 9f3bae5a-9fe3-49df-8c84-5edc51d84b7f -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-13' -name: Count of Unique IPs Connecting to Ports -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/identify_systems_creating_rdp_traffic.yml b/baselines/identify_systems_creating_rdp_traffic.yml deleted file mode 100644 index 7a8029351b..0000000000 --- a/baselines/identify_systems_creating_rdp_traffic.yml +++ /dev/null @@ -1,38 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 - by All_Traffic.src | `drop_dm_object_name("All_Traffic")` | sort - count' -creation_date: '2017-04-24' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communication - providing_technologies: - - Splunk Stream - - Bro -description: This search counts the numbers of times the system has generated remote - desktop traffic. -eli5: This search counts the numbers of times the system has tried to connect to another - system on TCP/3389, the default port used for RDP traffic. -how_to_implement: To successfully implement this search, you must ingest network traffic - and populate the Network_Traffic data model. -id: 5cdda34f-4caf-4128-a713-0837fc48b67a -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-15' -name: Identify Systems Creating Remote Desktop Traffic -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/identify_systems_creating_remote_desktop_traffic.yml b/baselines/identify_systems_creating_remote_desktop_traffic.yml new file mode 100644 index 0000000000..fbe73f658d --- /dev/null +++ b/baselines/identify_systems_creating_remote_desktop_traffic.yml @@ -0,0 +1,13 @@ +name: Identify Systems Creating Remote Desktop Traffic +id: 5cdda34f-4caf-4128-a713-0837fc48b67a +version: '1.0' +date: '2017-09-15' +description: This search counts the numbers of times the system has generated remote + desktop traffic. +how_to_implement: To successfully implement this search, you must ingest network traffic + and populate the Network_Traffic data model. +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic + where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name("All_Traffic")` + | sort - count' +tags: {} diff --git a/baselines/identify_systems_receiving_rdp_traffic.yml b/baselines/identify_systems_receiving_rdp_traffic.yml deleted file mode 100644 index b838cf87be..0000000000 --- a/baselines/identify_systems_receiving_rdp_traffic.yml +++ /dev/null @@ -1,39 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 - by All_Traffic.dest | `drop_dm_object_name("All_Traffic")` | sort - count' -creation_date: '2017-04-24' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communication - providing_technologies: - - Splunk Stream - - Bro -description: This search counts the numbers of times the system has created remote - desktop traffic -eli5: This search counts the numbers of times the system has received a connection - to TCP/ 3389, the default port used for RDP traffic. -how_to_implement: To successfully implement this search you must ingest network traffic - and populate the Network_Traffic data model. If a system receives a lot of remote - desktop traffic, you can apply the category common_rdp_destination to it. -id: baaeea15-fe8a-4090-92c2-5b60943bb608 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-15' -name: Identify Systems Receiving Remote Desktop Traffic -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/identify_systems_receiving_remote_desktop_traffic.yml b/baselines/identify_systems_receiving_remote_desktop_traffic.yml new file mode 100644 index 0000000000..a0eadc74b3 --- /dev/null +++ b/baselines/identify_systems_receiving_remote_desktop_traffic.yml @@ -0,0 +1,14 @@ +name: Identify Systems Receiving Remote Desktop Traffic +id: baaeea15-fe8a-4090-92c2-5b60943bb608 +version: '1.0' +date: '2017-09-15' +description: This search counts the numbers of times the system has created remote + desktop traffic +how_to_implement: To successfully implement this search you must ingest network traffic + and populate the Network_Traffic data model. If a system receives a lot of remote + desktop traffic, you can apply the category common_rdp_destination to it. +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic + where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name("All_Traffic")` + | sort - count' +tags: {} diff --git a/baselines/identify_systems_using_remote_desktop.yml b/baselines/identify_systems_using_remote_desktop.yml index f58438864d..73e6f774ff 100644 --- a/baselines/identify_systems_using_remote_desktop.yml +++ b/baselines/identify_systems_using_remote_desktop.yml @@ -1,43 +1,13 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Endpoint.Processes where - Processes.process_name="*mstsc.exe*" by Processes.dest Processes.process_name - | `drop_dm_object_name(Processes)` | sort - count' -creation_date: '2017-04-18' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Identify Systems Using Remote Desktop +id: 063dfe9f-b1d7-4254-a16d-1e2e7eadd6a8 +version: '1.0' +date: '2019-04-01' description: This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. -eli5: This search counts the numbers of times the remote desktop process, mstsc.exe, - has run on each system. It does this by looking for the process name in the Endpoint - data model. how_to_implement: To successfully implement this search you must be ingesting endpoint data that records process activity. -id: 063dfe9f-b1d7-4254-a16d-1e2e7eadd6a8 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-04-01' -name: Identify Systems Using Remote Desktop -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Endpoint.Processes + where Processes.process_name="*mstsc.exe*" by Processes.dest Processes.process_name + | `drop_dm_object_name(Processes)` | sort - count' +tags: {} diff --git a/baselines/monitor_successful_backups.yml b/baselines/monitor_successful_backups.yml index 2609115c6f..4c9bc54ed4 100644 --- a/baselines/monitor_successful_backups.yml +++ b/baselines/monitor_successful_backups.yml @@ -1,39 +1,18 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype="netbackup_logs" "Disk/Partition backup completed successfully." - | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) - as dest by _time, MESSAGE -creation_date: '2017-08-24' -data_metadata: - data_source: - - Backup Logs - data_sourcetypes: - - netbackup_logs - providing_technologies: - - Netbackup +name: Monitor Successful Backups +id: b4d0dfb2-2195-4f6e-93a3-48468ed9734e +version: '1.0' +date: '2017-09-12' description: This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. -eli5: This search gives you the count and the hostname of all the systems that had - a successful backup each day. how_to_implement: To successfully implement this search you must be ingesting your backup logs. -id: b4d0dfb2-2195-4f6e-93a3-48468ed9734e -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-12' -name: Monitor Successful Backups -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: sourcetype="netbackup_logs" "Disk/Partition backup completed successfully." + | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as + dest by _time, MESSAGE +tags: + analytics_story: + - Monitor Backup Solution + detections: + - Unsuccessful Netbackup backups diff --git a/baselines/monitor_successful_windows_updates.yml b/baselines/monitor_successful_windows_updates.yml deleted file mode 100644 index 1c0b69c009..0000000000 --- a/baselines/monitor_successful_windows_updates.yml +++ /dev/null @@ -1,38 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates - where Updates.vendor_product="Microsoft Windows" AND Updates.status=installed - by _time span=1d' -creation_date: '2017-08-24' -data_metadata: - data_models: - - Updates - data_source: - - Windows Updates - providing_technologies: - - Microsoft Windows -description: This search is intended to give you a feel for how often successful Windows - updates are applied in your environments. Fluctuations in these numbers will allow - you to determine when you should be concerned. -eli5: This search gives you the count and name of all the systems that had a successful - update applied each day -how_to_implement: You must be ingesting your Windows Update Logs -id: 6a80535c-86a6-4b54-894c-4b446d0c701d -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-14' -name: Windows Updates Install Successes -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/monitor_unsuccessful_backups.yml b/baselines/monitor_unsuccessful_backups.yml index 9966a9426a..f14fa9aed0 100644 --- a/baselines/monitor_unsuccessful_backups.yml +++ b/baselines/monitor_unsuccessful_backups.yml @@ -1,39 +1,18 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype="netbackup_logs" "An error occurred, failed to backup." | bucket - _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest - by _time, MESSAGE -creation_date: '2017-08-24' -data_metadata: - data_source: - - Backup Logs - data_sourcetypes: - - netbackup_logs - providing_technologies: - - Netbackup +name: Monitor Unsuccessful Backups +id: b2178fed-592f-492b-b851-74161678aa56 +version: '1.0' +date: '2017-09-12' description: This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. -eli5: This search gives you the count and hostname of all the systems that had a backup - failure each day how_to_implement: To successfully implement this search you must be ingesting your backup logs. -id: b2178fed-592f-492b-b851-74161678aa56 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-12' -name: Monitor Unsuccessful Backups -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: sourcetype="netbackup_logs" "An error occurred, failed to backup." | bucket + _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by + _time, MESSAGE +tags: + analytics_story: + - Monitor Backup Solution + detections: + - Unsuccessful Netbackup backups diff --git a/baselines/monitor_unsuccessful_windows_updates.yml b/baselines/monitor_unsuccessful_windows_updates.yml deleted file mode 100644 index a1b734bf0e..0000000000 --- a/baselines/monitor_unsuccessful_windows_updates.yml +++ /dev/null @@ -1,38 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates - where Updates.vendor_product="Microsoft Windows" AND Updates.status=failure - by _time span=1d' -creation_date: '2017-08-24' -data_metadata: - data_models: - - Updates - data_source: - - Windows Updates - providing_technologies: - - Microsoft Windows -description: This search is intended to give you a feel for how often Windows updates - fail to install in your environment. Fluctuations in these numbers will allow you - to determine when you should be concerned. -eli5: This search gives you the count of the number of systems that attempted and - failed to install a Windows update each day. -how_to_implement: You must be ingesting your Windows Update Logs -id: 6a4dbd1b-4502-4a11-943a-82b5ae7a42d7 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-14' -name: Windows Updates Install Failures -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml b/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml new file mode 100644 index 0000000000..41a7e93df7 --- /dev/null +++ b/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml @@ -0,0 +1,22 @@ +name: Previously seen API call per user roles in CloudTrail +id: fc0edc95-fq2c-48b0-9f6f-63da3289fd03 +version: '1.0' +date: '2018-04-16' +description: This search looks for successful API calls made by different user roles, + then creates a baseline of the earliest and latest times we have encountered this + user role. It also returns the name of the API call in our dataset--grouped by user + role and name of the API call--that occurred within the last 30 days. In this support + search, we are only looking for events where the user identity is Assumed Role. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, + which is a lookup file created as a result of running this support search. +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole + | stats earliest(_time) as earliest latest(_time) as latest by userName eventName + | outputlookup previously_seen_api_calls_from_user_roles | stats count +tags: + analytics_story: + - AWS User Monitoring + detections: + - Detect new API calls from user roles diff --git a/baselines/previously_seen_aws_cross_account_activity.yml b/baselines/previously_seen_aws_cross_account_activity.yml index 07db734f93..39e0c81ae3 100644 --- a/baselines/previously_seen_aws_cross_account_activity.yml +++ b/baselines/previously_seen_aws_cross_account_activity.yml @@ -1,45 +1,23 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId - path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId - | search requestingAccountId=* | where requestingAccountId!=requestedAccountId - | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, - requestedAccountId | outputlookup previously_seen_aws_cross_account_activity - | stats count -creation_date: '2018-06-04' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: Previously Seen AWS Cross Account Activity +id: 1cc22b09-c867-416e-a511-cb36ac44aee2 +version: '1.0' +date: '2018-06-04' description: This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. -eli5: In this support search, we look for **AssumeRole** events where the requesting - account is different from the requested account. The first and last times these - events are seen are written to a lookup file. how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -id: 1cc22b09-c867-416e-a511-cb36ac44aee2 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-06-04' -name: Previously Seen AWS Cross Account Activity -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId + path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId + | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | + stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, + requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats + count +tags: + analytics_story: + - AWS Cross Account Activity + detections: + - AWS Cross Account Activity From Previously Unseen Account diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml new file mode 100644 index 0000000000..c4c5cde8bf --- /dev/null +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -0,0 +1,23 @@ +name: Previously Seen AWS Provisioning Activity Sources +id: ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee +version: '1.0' +date: '2018-03-16' +description: This search builds a table of the first and last times seen for every + IP address (along with its physical location) previously associated with cloud-provisioning + activity. This is broadly defined as any event that runs or creates something. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime + by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv + | stats count +tags: + analytics_story: + - AWS Suspicious Provisioning Activities + detections: + - AWS Cloud Provisioning From Previously Unseen City + - AWS Cloud Provisioning From Previously Unseen Region + - AWS Cloud Provisioning From Previously Unseen Country + - AWS Cloud Provisioning From Previously Unseen IP Address diff --git a/baselines/previously_seen_aws_regions.yml b/baselines/previously_seen_aws_regions.yml new file mode 100644 index 0000000000..22a73df2d0 --- /dev/null +++ b/baselines/previously_seen_aws_regions.yml @@ -0,0 +1,21 @@ +name: Previously Seen AWS Regions +id: fc0edc95-ff2b-48b0-9f6f-63da3789fd63 +version: '1.0' +date: '2018-01-08' +description: This search looks for CloudTrail events where an AWS instance is started + and creates a baseline of most recent time (latest) and the first time (earliest) + we've seen this region in our dataset grouped by the value awsRegion for the last + 30 days +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail + inputs. +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest + latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv + | stats count +tags: + analytics_story: + - AWS Cryptomining + - Suspicious AWS EC2 Activities + detections: + - EC2 Instance Started In Previously Unseen Region diff --git a/baselines/previously_seen_aws_users.yml b/baselines/previously_seen_aws_users.yml deleted file mode 100644 index 06734edecd..0000000000 --- a/baselines/previously_seen_aws_users.yml +++ /dev/null @@ -1,56 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: 0 0 1 * * - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn - as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region - LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime - by user src City Region Country | outputlookup previously_seen_users_console_logins.csv - | stats count -creation_date: '2018-02-23' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where a user logs into the console, - then creates a baseline of the latest and earliest times, City, Region, and Country - we have encountered this user in our dataset, grouped by ARN, within the last 30 - days. -eli5: In this support search, we look for console login events by a particular user - and create an initial baseline cache for the previous 30 days, including the earliest - and latest times, City, Region, and Country a particular user ARN is seen in our - dataset, grouped by the ARN value. In cases where City and Region cannot be determined, - the source IP address is substituted for these values. -entities: - - user - - src -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, - which is a lookup file created as a result of running this support search. -id: fc0edc95-ff2b-48b0-9f6f-63da3789fd03 -known_false_positives: n/a -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -modification_date: '2018-04-30' -name: Previously seen users in CloudTrail -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -spec_version: 2 -type: splunk -version: '1.1' diff --git a/baselines/previously_seen_cloud_compute_creations_by_user.yml b/baselines/previously_seen_cloud_compute_creations_by_user.yml index 819fb144a1..9d492620b3 100644 --- a/baselines/previously_seen_cloud_compute_creations_by_user.yml +++ b/baselines/previously_seen_cloud_compute_creations_by_user.yml @@ -1,45 +1,18 @@ -baseline: - splunk: - lookups: - - previously_seen_cloud_compute_creations_by_user - macros: - - previously_seen_cloud_compute_creations_by_user_input_filter - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from - datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_creations_by_user_input_filter` - by Compute.src_user | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_creations_by_user - | stats count' -creation_date: '2019-10-03' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP +name: Previously Seen Cloud Compute Creations By User +id: 9fa1c205-4e08-4681-bb1b-d0943e734b85 +version: '1.0' +date: '2018-03-15' description: This search builds a table of previously seen users that have launched a cloud compute instance. -eli5: In this support search, we create a table of the earliest and latest time for - each user that has created a cloud compute instance. how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -id: 9fa1c205-4e08-4681-bb1b-d0943e734b85 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-15' -name: Previously Seen Cloud Compute Creations By User -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute + where Compute.action=run `previously_seen_cloud_compute_creations_by_user_input_filter` + by Compute.src_user | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_creations_by_user + | stats count' +tags: + analytics_story: + - Cloud Cryptomining + detections: + - Cloud Compute Instance Created By Previously Unseen User diff --git a/baselines/previously_seen_cloud_compute_images.yml b/baselines/previously_seen_cloud_compute_images.yml index 85323c89f9..c871274b48 100644 --- a/baselines/previously_seen_cloud_compute_images.yml +++ b/baselines/previously_seen_cloud_compute_images.yml @@ -1,45 +1,18 @@ -baseline: - splunk: - lookups: - - previously_seen_cloud_compute_images - macros: - - previously_seen_cloud_compute_image_input_filter - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from - datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` - by Compute.image_id | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_images - | stats count' -creation_date: '2019-10-03' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP +name: Previously Seen Cloud Compute Images +id: 3782ad10-5ce2-46e2-b9c4-1de9ecd3aecc +version: '1.0' +date: '2018-03-12' description: This search builds a table of previously seen images used to launch cloud compute instances -eli5: In this support search, we create a table of the earliest and latest time for - each image id that has been seen. This table is then outputted to a csv file. how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -id: 3782ad10-5ce2-46e2-b9c4-1de9ecd3aecc -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-12' -name: Previously Seen Cloud Compute Images -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute + where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id + | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_images + | stats count' +tags: + analytics_story: + - Cloud Cryptomining + detections: + - Cloud Compute Instance Created With Previously Unseen Image diff --git a/baselines/previously_seen_cloud_compute_instance_types.yml b/baselines/previously_seen_cloud_compute_instance_types.yml index 5d971aafcf..4d11210d4d 100644 --- a/baselines/previously_seen_cloud_compute_instance_types.yml +++ b/baselines/previously_seen_cloud_compute_instance_types.yml @@ -1,48 +1,18 @@ -baseline: - splunk: - lookups: - - previously_seen_cloud_compute_instance_types - macros: - - previously_seen_cloud_compute_instance_types_input_filter - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from - datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_instance_types_input_filter` - by Compute.instance_type | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_instance_types - | stats count' -creation_date: '2019-10-03' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP +name: Previously Seen Cloud Compute Instance Types +id: 0ef13d46-164e-4cf5-816e-b3c0df170d00 +version: '1.0' +date: '2019-10-03' description: This search builds a table of previously seen cloud compute instance types -eli5: In this support search, we create a table of the first time `firstTime` and - most recent time `lastTime` that the compute type has been seen in our dataset. - We only look for those events where an instance has been created. All of these entries - will be added to the `previously_seen_cloud_compute_instance_types` lookup file, - which will act as a baseline for detections. how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -id: 0ef13d46-164e-4cf5-816e-b3c0df170d00 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-10-03' -name: Previously Seen Cloud Compute Instance Types -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute + where Compute.action=run `previously_seen_cloud_compute_instance_types_input_filter` + by Compute.instance_type | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_instance_types + | stats count' +tags: + analytics_story: + - Cloud Cryptomining + detections: + - Cloud Compute Instance Created With Previously Unseen Instance Type diff --git a/baselines/previously_seen_cloud_regions.yml b/baselines/previously_seen_cloud_regions.yml new file mode 100644 index 0000000000..fad9c0bbfe --- /dev/null +++ b/baselines/previously_seen_cloud_regions.yml @@ -0,0 +1,20 @@ +name: Previously Seen Cloud Regions +id: b5e232db-dec6-4db8-aaa1-dd5474521e40 +version: '1.0' +date: '2019-10-02' +description: This search looks for cloud compute events where a compute instance is + started and creates a baseline of most recent time, `lastTime` and the first time + `firstTime` we've seen this region in our dataset grouped by the region for the + last 30 days +how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs + and have the Security Research cloud data model installed. +author: David Dorsey, Splunk +search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute + where Compute.action=start `previously_seen_cloud_regions_input_filter` by Compute.region + | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_regions + | stats count' +tags: + analytics_story: + - Cloud Cryptomining + detections: + - Cloud Compute Instance Started In Previously Unused Region diff --git a/baselines/previously_seen_cmd_arguments.yml b/baselines/previously_seen_cmd_arguments.yml deleted file mode 100644 index cf73b2ad66..0000000000 --- a/baselines/previously_seen_cmd_arguments.yml +++ /dev/null @@ -1,48 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime - from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe AND Processes.process="* - /c *" by Processes.process | `drop_dm_object_name(Processes)`' -creation_date: '2018-04-09' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for command-line arguments where `cmd.exe /c` is used - to execute a program, then creates a baseline of the earliest and latest times we - have encountered this command-line argument in our dataset within the last 30 days. -eli5: In this support search, we look for command-line arguments using the parameter - `/c` to execute processes and create an initial baseline cache for the previous - 30 days. This will include the earliest and latest times a particular command-line - argument is seen in our dataset, grouped by the command-line value. -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must be ingesting - logs with both the process name and command line from your endpoints. The complete - process name with command-line arguments are mapped to the "process" field in the - Endpoint data model. -id: fc0edc95-ff2b-48b0-9f6f-63da3789fd23 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-03-01' -name: Previously seen command line arguments -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/baselines/previously_seen_command_line_arguments.yml b/baselines/previously_seen_command_line_arguments.yml new file mode 100644 index 0000000000..30e00acb41 --- /dev/null +++ b/baselines/previously_seen_command_line_arguments.yml @@ -0,0 +1,30 @@ +name: Previously seen command line arguments +id: fc0edc95-ff2b-48b0-9f6f-63da3789fd23 +version: '2.0' +date: '2019-03-01' +description: This search looks for command-line arguments where `cmd.exe /c` is used + to execute a program, then creates a baseline of the earliest and latest times we + have encountered this command-line argument in our dataset within the last 30 days. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must be ingesting + logs with both the process name and command line from your endpoints. The complete + process name with command-line arguments are mapped to the "process" field in the + Endpoint data model. +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe + AND Processes.process="* /c *" by Processes.process | `drop_dm_object_name(Processes)`' +tags: + analytics_story: + - DHS Report TA18-074A + - Disabling Security Tools + - Hidden Cobra Malware + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Suspicious Command-Line Executions + - Suspicious MSHTA Activity + detections: + - First time seen command line argument + - Processes launching netsh + - Detect Prohibited Applications Spawning cmd.exe diff --git a/baselines/previously_seen_ec2_amis.yml b/baselines/previously_seen_ec2_amis.yml index db54ee9d52..e178d032e4 100644 --- a/baselines/previously_seen_ec2_amis.yml +++ b/baselines/previously_seen_ec2_amis.yml @@ -1,40 +1,19 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename - requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) - as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv - | stats count -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: Previously Seen EC2 AMIs +id: bb1bd99d-1e93-45f1-9571-cfed42d372b9 +version: '1.0' +date: '2018-03-12' description: This search builds a table of previously seen AMIs used to launch EC2 instances -eli5: In this support search, we create a table of the earliest and latest time that - a specific AMI ID has been seen. This table is then outputted to a csv file. how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -id: bb1bd99d-1e93-45f1-9571-cfed42d372b9 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-12' -name: Previously Seen EC2 AMIs -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename + requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) + as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv + | stats count +tags: + analytics_story: + - AWS Cryptomining + detections: + - EC2 Instance Started With Previously Unseen AMI diff --git a/baselines/previously_seen_ec2_instance_types.yml b/baselines/previously_seen_ec2_instance_types.yml index 3f958f4f8c..232ef47c5f 100644 --- a/baselines/previously_seen_ec2_instance_types.yml +++ b/baselines/previously_seen_ec2_instance_types.yml @@ -1,41 +1,18 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename - requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType - | stats earliest(_time) as earliest latest(_time) as latest by instanceType - | outputlookup previously_seen_ec2_instance_types.csv | stats count -creation_date: '2018-03-08' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: Previously Seen EC2 Instance Types +id: b8f029f2-65a6-4d76-be98-dad1c9d59c45 +version: '1.0' +date: '2018-03-08' description: This search builds a table of previously seen EC2 instance types -eli5: In this support search, we create a table of the earliest and latest time that - a specific EC2 instance type has been seen. The instanceType request field is not - required and defaults to m1.small, so any time this field is null, the search defaults - the field to m1.small. This table is then outputted to a csv file. how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -id: b8f029f2-65a6-4d76-be98-dad1c9d59c45 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-08' -name: Previously Seen EC2 Instance Types -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename + requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType + | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup + previously_seen_ec2_instance_types.csv | stats count +tags: + analytics_story: + - AWS Cryptomining + detections: + - EC2 Instance Started With Previously Unseen Instance Type diff --git a/baselines/previously_seen_ec2_launches_by_user.yml b/baselines/previously_seen_ec2_launches_by_user.yml index d419d4e79d..86e275b619 100644 --- a/baselines/previously_seen_ec2_launches_by_user.yml +++ b/baselines/previously_seen_ec2_launches_by_user.yml @@ -1,40 +1,19 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename - userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as - lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats - count -creation_date: '2018-03-15' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: Previously Seen EC2 Launches By User +id: 6c767ac0-0906-4355-9a83-927f5ee7bdad +version: '1.0' +date: '2018-03-15' description: This search builds a table of previously seen ARNs that have launched a EC2 instance. -eli5: In this support search, we create a table of the earliest and latest times that - an ARN has launched a EC2 instance. This table is then outputted to a csv file. how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -id: 6c767ac0-0906-4355-9a83-927f5ee7bdad -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-15' -name: Previously Seen EC2 Launches By User -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename + userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime + by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count +tags: + analytics_story: + - AWS Cryptomining + - Suspicious AWS EC2 Activities + detections: + - EC2 Instance Started With Previously Unseen User diff --git a/baselines/previously_seen_ec2_modifications.yml b/baselines/previously_seen_ec2_modifications.yml deleted file mode 100644 index 0933421192..0000000000 --- a/baselines/previously_seen_ec2_modifications.yml +++ /dev/null @@ -1,42 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail `ec2_modification_api_calls` errorCode=success | spath - output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) - as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user - | stats count -creation_date: '2018-04-05' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search builds a table of previously seen ARNs that have launched - a EC2 instance. -eli5: In this support search, we create a table of the earliest and latest times that - an ARN has modified a EC2 instance. The list of APIs that modify an EC2 are defined - in the `ec2_modification_api_calls` macro for ease of use. This table is then outputted - to a file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail - inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -id: 4d69091b-d975-4267-85df-888bd41034eb -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-04-05' -name: Previously Seen EC2 Modifications By User -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/previously_seen_ec2_modifications_by_user.yml b/baselines/previously_seen_ec2_modifications_by_user.yml new file mode 100644 index 0000000000..d7b00395c2 --- /dev/null +++ b/baselines/previously_seen_ec2_modifications_by_user.yml @@ -0,0 +1,19 @@ +name: Previously Seen EC2 Modifications By User +id: 4d69091b-d975-4267-85df-888bd41034eb +version: '1.0' +date: '2018-04-05' +description: This search builds a table of previously seen ARNs that have launched + a EC2 instance. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail + inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail `ec2_modification_api_calls` errorCode=success | + spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) + as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats + count +tags: + analytics_story: + - Unusual AWS EC2 Modifications + detections: + - EC2 Instance Modified With Previously Unseen User diff --git a/baselines/previously_seen_provisioning_activity_src.yml b/baselines/previously_seen_provisioning_activity_src.yml deleted file mode 100644 index 8e1159a426..0000000000 --- a/baselines/previously_seen_provisioning_activity_src.yml +++ /dev/null @@ -1,43 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -90d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime - by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv - | stats count -creation_date: '2018-03-16' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search builds a table of the first and last times seen for every - IP address (along with its physical location) previously associated with cloud-provisioning - activity. This is broadly defined as any event that runs or creates something. -eli5: This search includes any event name that begins with "run" or "create," and - then determines the first and last time these events were seen for each IP address - that initiated the action. The search then consults a **GeoIP** database to determine - the physical location of this IP address. This table outputs to a file. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-16' -name: Previously Seen AWS Provisioning Activity Sources -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/previously_seen_running_windows_services.yml b/baselines/previously_seen_running_windows_services.yml new file mode 100644 index 0000000000..5f4daab731 --- /dev/null +++ b/baselines/previously_seen_running_windows_services.yml @@ -0,0 +1,20 @@ +name: Previously Seen Running Windows Services +id: 64ce0ade-cb01-4678-bddd-d31c0b175394 +version: '2.0' +date: '2020-01-13' +description: This collects the services that have been started across your entire + enterprise. +how_to_implement: While this search does not require you to adhere to Splunk CIM, + you must be ingesting your Windows security-event logs for it to execute successfully. + Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. +author: David Dorsey, Splunk +search: eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name + | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, + latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services + | stats count +tags: + analytics_story: + - Orangeworm Attack Group + - Windows Service Abuse + detections: + - First Time Seen Running Windows Service diff --git a/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml b/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml new file mode 100644 index 0000000000..49b72e8913 --- /dev/null +++ b/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml @@ -0,0 +1,21 @@ +name: Previously seen S3 bucket access by remote IP +id: fc0edc15-fq2c-48b0-9f6f-63qa1281fd03 +version: '1.0' +date: '2018-06-28' +description: This search looks for successful access to S3 buckets from remote IP + addresses, then creates a baseline of the earliest and latest times we have encountered + this remote IP within the last 30 days. In this support search, we are only looking + for S3 access events where the HTTP response code from AWS is "200" +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs + inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, + which is a lookup file created as a result of running this support search. +author: Bhavin Patel, Splunk +search: sourcetype=aws:s3:accesslogs http_status=200 | stats earliest(_time) as + earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip + | stats count +tags: + analytics_story: + - Suspicious AWS S3 Activities + detections: + - Detect S3 access from a new IP diff --git a/baselines/previously_seen_s3_remote_ip.yml b/baselines/previously_seen_s3_remote_ip.yml deleted file mode 100644 index a2df669af3..0000000000 --- a/baselines/previously_seen_s3_remote_ip.yml +++ /dev/null @@ -1,45 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:s3:accesslogs http_status=200 | stats earliest(_time) - as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup - previously_seen_S3_access_from_remote_ip | stats count -creation_date: '2018-06-28' -data_metadata: - data_source: - - AWS S3 Access logs - data_sourcetypes: - - aws:s3:accesslogs - providing_technologies: - - AWS -description: This search looks for successful access to S3 buckets from remote IP - addresses, then creates a baseline of the earliest and latest times we have encountered - this remote IP within the last 30 days. In this support search, we are only looking - for S3 access events where the HTTP response code from AWS is "200" -eli5: In this support search, we are looking for successful S3 bucket-access attempts - made from remote IPs. The intent is to create an initial baseline cache of remote - IP addresses per bucket name for the previous 30 days--including the earliest and - latest times seen in our dataset--grouped by the value of remote IP and the name - of the S3 bucket. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs - inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, - which is a lookup file created as a result of running this support search. -id: fc0edc15-fq2c-48b0-9f6f-63qa1281fd03 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-06-28' -name: Previously seen S3 bucket access by remote IP -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/previously_seen_user_roles.yml b/baselines/previously_seen_user_roles.yml deleted file mode 100644 index 35b0498244..0000000000 --- a/baselines/previously_seen_user_roles.yml +++ /dev/null @@ -1,47 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole - | stats earliest(_time) as earliest latest(_time) as latest by userName eventName - | outputlookup previously_seen_api_calls_from_user_roles | stats count -creation_date: '2018-04-01' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for successful API calls made by different user roles, - then creates a baseline of the earliest and latest times we have encountered this - user role. It also returns the name of the API call in our dataset--grouped by user - role and name of the API call--that occurred within the last 30 days. In this support - search, we are only looking for events where the user identity is Assumed Role. -eli5: In this support search, we are looking for successful API calls made by user - roles within your AWS infrastructure. The intent is to create an initial baseline - cache of names of the API calls per security role for the previous 30 days--including - the earliest and latest times seen in our dataset--grouped by the value of user - role and the name of the API call. It is also worth noting that the role of a particular - user is parsed as "userName" in the CloudTrail logs. -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, - which is a lookup file created as a result of running this support search. -id: fc0edc95-fq2c-48b0-9f6f-63da3289fd03 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-04-16' -name: Previously seen API call per user roles in CloudTrail -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml new file mode 100644 index 0000000000..eafe11ec93 --- /dev/null +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -0,0 +1,26 @@ +name: Previously seen users in CloudTrail +id: fc0edc95-ff2b-48b0-9f6f-63da3789fd03 +version: '1.1' +date: '2018-04-30' +description: This search looks for CloudTrail events where a user logs into the console, + then creates a baseline of the latest and earliest times, City, Region, and Country + we have encountered this user in our dataset, grouped by ARN, within the last 30 + days. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, + which is a lookup file created as a result of running this support search. +author: Jason Brewer, Splunk +search: sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn + as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region + LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime + by user src City Region Country | outputlookup previously_seen_users_console_logins.csv + | stats count +tags: + analytics_story: + - Suspicious AWS Login Activities + detections: + - Detect AWS Console Login by User from New Region + - Detect AWS Console Login by User from New Country + - Detect new user AWS Console Login + - Detect AWS Console Login by User from New City diff --git a/baselines/previously_seen_windows_service_starts.yml b/baselines/previously_seen_windows_service_starts.yml deleted file mode 100644 index e3d9b75d56..0000000000 --- a/baselines/previously_seen_windows_service_starts.yml +++ /dev/null @@ -1,37 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -30d@d - latest_time: -10m@m - search: eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services | stats count -creation_date: '2018-07-20' -data_metadata: - data_eventtypes: - - wineventlog_system - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This collects the services that have been started across your entire - enterprise. -eli5: In this support search, we look for Windows system-event code that indicates - a status change of a Windows service. In this specific log event, the `param1` field represents the - "service_name" and the `param2` represents the action/status of the service. This search will create a table of the first and last time as particular Windows service was seen to be in the `running` status. -how_to_implement: While this search does not require you to adhere to Splunk CIM, - you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -id: 64ce0ade-cb01-4678-bddd-d31c0b175394 -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2020-01-13' -name: Previously Seen Running Windows Services -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/baselines/systems_ready_for_spectre_meltdown_patch.yml b/baselines/systems_ready_for_spectre_meltdown_patch.yml deleted file mode 100644 index 71d85e9df2..0000000000 --- a/baselines/systems_ready_for_spectre_meltdown_patch.yml +++ /dev/null @@ -1,47 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: '' - earliest_time: -1d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry - AND (All_Changes.object_path="HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat*") - by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, - All_Changes.object_path | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")`' -creation_date: '2018-01-08' -data_metadata: - data_models: - - Change_Analysis - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: Some AV applications can cause the Spectre/Meltdown patch for Windows - not to install successfully. This registry key is supposed to be created by the - AV engine when it has been patched to be able to handle the Windows patch. If this - key has been written, the system can then be patched for Spectre and Meltdown. -eli5: This search looks to see if a registry key was created at `HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat`. - It will tell you when it was created and, if possible, what process created it. -how_to_implement: You need to be ingesting logs with both the process name and command-line - from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 - of the Sysmon TA. -id: fc0edc95-ff2b-48b0-9f6f-63da3789fd61 -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-01-08' -name: Systems Ready for Spectre-Meltdown Windows Patch -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/systems_ready_for_spectre_meltdown_windows_patch.yml b/baselines/systems_ready_for_spectre_meltdown_windows_patch.yml new file mode 100644 index 0000000000..55eb0d8d00 --- /dev/null +++ b/baselines/systems_ready_for_spectre_meltdown_windows_patch.yml @@ -0,0 +1,23 @@ +name: Systems Ready for Spectre-Meltdown Windows Patch +id: fc0edc95-ff2b-48b0-9f6f-63da3789fd61 +version: '1.0' +date: '2018-01-08' +description: Some AV applications can cause the Spectre/Meltdown patch for Windows + not to install successfully. This registry key is supposed to be created by the + AV engine when it has been patched to be able to handle the Windows patch. If this + key has been written, the system can then be patched for Spectre and Meltdown. +how_to_implement: You need to be ingesting logs with both the process name and command-line + from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 + of the Sysmon TA. +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry + AND (All_Changes.object_path="HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat*") + by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, + All_Changes.object_path | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + | `drop_dm_object_name("All_Changes")`' +tags: + analytics_story: + - Spectre And Meltdown Vulnerabilities + detections: + - Spectre and Meltdown Vulnerable Systems diff --git a/baselines/train_ec2_excessive_runinstances.yml b/baselines/train_ec2_excessive_runinstances.yml deleted file mode 100644 index 3ecfc9b732..0000000000 --- a/baselines/train_ec2_excessive_runinstances.yml +++ /dev/null @@ -1,60 +0,0 @@ -baseline: - splunk: - macros: - - ec2_excessive_runinstances_mltk_input_filter - schedule: - cron_schedule: '' - earliest_time: -91d@d - latest_time: -1d@d - search: >- - sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` - | bucket span=10m _time - | stats count as instances_launched by _time src_user - | fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 -creation_date: '2019-11-14' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search is used to build a Machine Learning Toolkit (MLTK) model - for how many RunInstances users do in the environment. By default, the search - uses the last 90 days of data to build the model. The model created by this search - is then used in the corresponding detection search, which identifies subsequent - outliers in the number of RunInstances performed by a user in a small time window. -eli5: Create a machine-learning (ML) model to establish a baseline for how many - RunInstances users do in the environment. This can help you identify excessive - numbers of RunInstances which may warrant further investigation to determine if there - is misuse or abuse. -how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs.\ - - In addition, you must have the Machine Learning Toolkit (MLTK) version - >= 4.2 installed, along with any required dependencies. Depending on the number - of users in your environment, you may also need to adjust the value for max_inputs - in the MLTK settings for the DensityFunction algorithm, then ensure that the search - completes in a reasonable timeframe. By default, the search builds the model using - the past 30 days of data. You can modify the search window to build the model over - a longer period of time, which may give you better results. You may also want to - periodically re-run this search to rebuild the model with the latest data.\ - - More information on the algorithm used in the search can be found at - `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.' -id: fa5634df-fb05-4b4b-aba0-6115138bb1ba -known_false_positives: '' -maintainers: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -modification_date: '2019-11-14' -name: Baseline of Excessive AWS Instances Launched by User - MLTK -original_authors: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/train_ec2_excessive_terminateinstances.yml b/baselines/train_ec2_excessive_terminateinstances.yml deleted file mode 100644 index d84c119e4d..0000000000 --- a/baselines/train_ec2_excessive_terminateinstances.yml +++ /dev/null @@ -1,60 +0,0 @@ -baseline: - splunk: - macros: - - ec2_excessive_terminateinstances_mltk_input_filter - schedule: - cron_schedule: '' - earliest_time: -91d@d - latest_time: -1d@d - search: >- - sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` - | bucket span=10m _time - | stats count as instances_terminated by _time src_user - | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 -creation_date: '2019-11-14' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search is used to build a Machine Learning Toolkit (MLTK) model - for how many TerminateInstances users do in the environment. By default, the search - uses the last 90 days of data to build the model. The model created by this search - is then used in the corresponding detection search, which identifies subsequent - outliers in the number of TerminateInstances performed by a user in a small time window. -eli5: Create a machine-learning (ML) model to establish a baseline for how many - TerminateInstances users do in the environment. This can help you identify excessive - numbers of TerminateInstances which may warrant further investigation to determine if there - is misuse or abuse. -how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs.\ - - In addition, you must have the Machine Learning Toolkit (MLTK) version - >= 4.2 installed, along with any required dependencies. Depending on the number - of users in your environment, you may also need to adjust the value for max_inputs - in the MLTK settings for the DensityFunction algorithm, then ensure that the search - completes in a reasonable timeframe. By default, the search builds the model using - the past 30 days of data. You can modify the search window to build the model over - a longer period of time, which may give you better results. You may also want to - periodically re-run this search to rebuild the model with the latest data.\ - - More information on the algorithm used in the search can be found at - `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.' -id: b28ed6de-e4ba-40f7-ae0a-93a088c774ab -known_false_positives: '' -maintainers: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -modification_date: '2019-11-14' -name: Baseline of Excessive AWS Instances Terminated by User - MLTK -original_authors: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/update_previously_seen_aws_users.yml b/baselines/update_previously_seen_aws_users.yml deleted file mode 100644 index 527d79bbef..0000000000 --- a/baselines/update_previously_seen_aws_users.yml +++ /dev/null @@ -1,50 +0,0 @@ -baseline: - splunk: - schedule: - cron_schedule: 0 0 1 * * - earliest_time: -60m@m - latest_time: m@m - search: sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn - as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region - LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime - by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region - Country | outputlookup previously_seen_users_console_logins.csv -creation_date: '2019-04-25' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where a user logs into the console, - then updates the baseline of the latest and earliest times, City, Region, and Country - we have encountered this user in our dataset, grouped by ARN, within the last hour. -eli5: In this support search, we look for console login events by a particular user - to update the baseline cache of users/arns making the accesses, including the earliest - and latest times, City, Region, and Country a particular user ARN is seen in our - dataset, grouped by the ARN value. In cases where City and Region cannot be determined, - the source IP address is substituted for these values. -entities: - - user - - src -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, - which is a lookup file created as a result of running this support search. -id: 06c036e6-d6d7-4daa-bd76-411c3d356031 -known_false_positives: n/a -maintainers: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -modification_date: '2018-04-30' -name: Update previously seen users in CloudTrail -original_authors: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -spec_version: 2 -type: splunk -version: '1.0' diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml new file mode 100644 index 0000000000..8b07ed7dd0 --- /dev/null +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -0,0 +1,26 @@ +name: Update previously seen users in CloudTrail +id: 06c036e6-d6d7-4daa-bd76-411c3d356031 +version: '1.0' +date: '2018-04-30' +description: This search looks for CloudTrail events where a user logs into the console, + then updates the baseline of the latest and earliest times, City, Region, and Country + we have encountered this user in our dataset, grouped by ARN, within the last hour. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, + which is a lookup file created as a result of running this support search. +author: Jason Brewer, Splunk +search: sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn + as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region + LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime + by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv + | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region + Country | outputlookup previously_seen_users_console_logins.csv +tags: + analytics_story: + - Suspicious AWS Login Activities + detections: + - Detect AWS Console Login by User from New Region + - Detect AWS Console Login by User from New Country + - Detect new user AWS Console Login + - Detect AWS Console Login by User from New City diff --git a/baselines/windows_updates_install_failures.yml b/baselines/windows_updates_install_failures.yml new file mode 100644 index 0000000000..5c9d02a37d --- /dev/null +++ b/baselines/windows_updates_install_failures.yml @@ -0,0 +1,13 @@ +name: Windows Updates Install Failures +id: 6a4dbd1b-4502-4a11-943a-82b5ae7a42d7 +version: '1.0' +date: '2017-09-14' +description: This search is intended to give you a feel for how often Windows updates + fail to install in your environment. Fluctuations in these numbers will allow you + to determine when you should be concerned. +how_to_implement: You must be ingesting your Windows Update Logs +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` dc(Updates.dest) as count FROM + datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=failure + by _time span=1d' +tags: {} diff --git a/baselines/windows_updates_install_successes.yml b/baselines/windows_updates_install_successes.yml new file mode 100644 index 0000000000..a4c084f794 --- /dev/null +++ b/baselines/windows_updates_install_successes.yml @@ -0,0 +1,13 @@ +name: Windows Updates Install Successes +id: 6a80535c-86a6-4b54-894c-4b446d0c701d +version: '1.0' +date: '2017-09-14' +description: This search is intended to give you a feel for how often successful Windows + updates are applied in your environments. Fluctuations in these numbers will allow + you to determine when you should be concerned. +how_to_implement: You must be ingesting your Windows Update Logs +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` dc(Updates.dest) as count FROM + datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=installed + by _time span=1d' +tags: {} diff --git a/dashboards/.gitkeep b/dashboards/.gitkeep new file mode 100644 index 0000000000..e69de29bb2 diff --git a/deployment/deployment.yml b/deployment/deployment.yml new file mode 100644 index 0000000000..202e7d13f3 --- /dev/null +++ b/deployment/deployment.yml @@ -0,0 +1,17 @@ +name: Enterprise Security deployment configuration +id: bc91a8cd-35e7-4bb2-6140-e756cc46f212 +date: '2020-04-27' +description: This configuration file applies to all correlation searches that are used for detection +author: Bhavin Patel +scheduling: + cron_schedule: '*/10 * * * *' + earliest_time: -10m + latest_time: now + schedule_window: auto +alert_action: + notable: + rule_description: '%description%' + rule_title: '%name%' +tags: + analytics_story: + - all diff --git a/detections/abnormally_high_aws_instances_launched_by_user.yml b/detections/abnormally_high_aws_instances_launched_by_user.yml new file mode 100644 index 0000000000..4ae5dbc3f3 --- /dev/null +++ b/detections/abnormally_high_aws_instances_launched_by_user.yml @@ -0,0 +1,35 @@ +name: Abnormally High AWS Instances Launched by User +id: 2a9b80d3-6340-4345-b5ad-290bf5d0dac4 +version: '1.0' +date: '2018-02-26' +description: This search looks for CloudTrail events where a user successfully launches + an abnormally high number of instances. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. The threshold value should be tuned to your environment. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | bucket + span=10m _time | stats count AS instances_launched by _time userName | eventstats + avg(instances_launched) as total_launched_avg, stdev(instances_launched) as total_launched_stdev + | eval threshold_value = 4 | eval isOutlier=if(instances_launched > total_launched_avg+(total_launched_stdev + * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), + "-10m@m") | eval num_standard_deviations_away = round(abs(instances_launched - total_launched_avg) + / total_launched_stdev, 2) | table _time, userName, instances_launched, num_standard_deviations_away, + total_launched_avg, total_launched_stdev +known_false_positives: Many service accounts configured within an AWS infrastructure + are known to exhibit this behavior. Please adjust the threshold values and filter + out service accounts from the output. Always verify if this search alerted on a + human user. +tags: + analytics_story: + - AWS Cryptomining + - Suspicious AWS EC2 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 13 + nist: + - DE.DP + - DE.AE diff --git a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml new file mode 100644 index 0000000000..fb7ff60e42 --- /dev/null +++ b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml @@ -0,0 +1,31 @@ +name: Abnormally High AWS Instances Launched by User - MLTK +id: dec41ad5-d579-42cb-b4c6-f5dbb778bbe5 +version: '1.0' +date: '2019-11-14' +description: This search looks for CloudTrail events where a user successfully launches + an abnormally high number of instances. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. The threshold value should be tuned to your environment. +type: ESCU +references: [] +author: Jason Brewer, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` + | bucket span=10m _time | stats count as instances_launched by _time src_user | + apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as + isOutlier | where isOutlier=1 +known_false_positives: Many service accounts configured within an AWS infrastructure + are known to exhibit this behavior. Please adjust the threshold values and filter + out service accounts from the output. Always verify if this search alerted on a + human user. +tags: + analytics_story: + - Cloud Cryptomining + - Suspicious AWS EC2 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 13 + nist: + - DE.DP + - DE.AE diff --git a/detections/abnormally_high_aws_instances_terminated_by_user.yml b/detections/abnormally_high_aws_instances_terminated_by_user.yml new file mode 100644 index 0000000000..3fa579b83f --- /dev/null +++ b/detections/abnormally_high_aws_instances_terminated_by_user.yml @@ -0,0 +1,35 @@ +name: Abnormally High AWS Instances Terminated by User +id: ada0f478-84a8-4641-s3f3-d82362dffd75 +version: '1.0' +date: '2018-02-26' +description: This search looks for CloudTrail events where an abnormally high number + of instances were successfully terminated by a user in a 10-minute window +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success | + bucket span=10m _time | stats count AS instances_terminated by _time userName | + eventstats avg(instances_terminated) as total_terminations_avg, stdev(instances_terminated) + as total_terminations_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_terminated + > total_terminations_avg+(total_terminations_stdev * threshold_value), 1, 0) | search + isOutlier=1 AND _time >= relative_time(now(), "-10m@m")| eval num_standard_deviations_away + = round(abs(instances_terminated - total_terminations_avg) / total_terminations_stdev, + 2) |table _time, userName, instances_terminated, num_standard_deviations_away, total_terminations_avg, + total_terminations_stdev +known_false_positives: Many service accounts configured with your AWS infrastructure + are known to exhibit this behavior. Please adjust the threshold values and filter + out service accounts from the output. Always verify whether this search alerted + on a human user. +tags: + analytics_story: + - Suspicious AWS EC2 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 13 + nist: + - DE.DP + - DE.AE diff --git a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml new file mode 100644 index 0000000000..edc3f6cea2 --- /dev/null +++ b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml @@ -0,0 +1,30 @@ +name: Abnormally High AWS Instances Terminated by User - MLTK +id: 1c02b86a-cd85-473e-a50b-014a9ac8fe3e +version: '1.0' +date: '2019-11-14' +description: This search looks for CloudTrail events where a user successfully terminates + an abnormally high number of instances. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. The threshold value should be tuned to your environment. +type: ESCU +references: [] +author: Jason Brewer, Splunk +search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` + | bucket span=10m _time | stats count as instances_terminated by _time src_user | + apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" + as isOutlier | where isOutlier=1 +known_false_positives: Many service accounts configured within an AWS infrastructure + are known to exhibit this behavior. Please adjust the threshold values and filter + out service accounts from the output. Always verify if this search alerted on a + human user. +tags: + analytics_story: + - Suspicious AWS EC2 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 13 + nist: + - DE.DP + - DE.AE diff --git a/detections/abnormally_high_ec2_instances_launched.yml b/detections/abnormally_high_ec2_instances_launched.yml deleted file mode 100644 index ae6a597344..0000000000 --- a/detections/abnormally_high_ec2_instances_launched.yml +++ /dev/null @@ -1,108 +0,0 @@ -asset_type: AWS Instance -confidence: medium -creation_date: '2018-02-26' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where a user successfully launches - an abnormally high number of instances. -detect: - splunk: - correlation_rule: - notable: - nes_fields: userName - rule_description: An abnormally high number of instances were launched by - a user within in a 10-minute window - rule_title: High Number of instances launched by $userName$ - risk: - risk_object: userName - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: '*/10 * * * *' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | - bucket span=10m _time | stats count AS instances_launched by _time userName - | eventstats avg(instances_launched) as total_launched_avg, stdev(instances_launched) - as total_launched_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_launched - > total_launched_avg+(total_launched_stdev * threshold_value), 1, 0) | search - isOutlier=1 AND _time >= relative_time(now(), "-10m@m") | eval num_standard_deviations_away - = round(abs(instances_launched - total_launched_avg) / total_launched_stdev, - 2) | table _time, userName, instances_launched, num_standard_deviations_away, - total_launched_avg, total_launched_stdev - suppress: - suppress_fields: userName - suppress_period: 3600s -eli5: In this search, we query CloudTrail logs to look for events where an instance - is successfully launched by a particular user. Since we want to detect a high number - of instances launched within a short period, we create event buckets for 10-minute - windows. We then calculate the total number of instances launched by a particular - user, as well as the average and standard deviation values. Assign a `threshold_value` - in the search. Start with 3 (but it will likely need to be tweaked for your environment). - The `eval` function will set the outlier 1 if the number of instances is greater - than the average number of instances terminated, added to the multiplied value of - threshold and standard deviation. For your reference, we then keep only the outliers - and calculate the number of standard deviations away the value is from the average. -entities: - - userName -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. The threshold value should be tuned to your environment. -id: 2a9b80d3-6340-4345-b5ad-290bf5d0dac4 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 - name: Get EC2 Launch Details - type: splunk - - id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 - name: Get EC2 Instance Details by instanceId - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: Many service accounts configured within an AWS infrastructure - are known to exhibit this behavior. Please adjust the threshold values and filter - out service accounts from the output. Always verify if this search alerted on a - human user. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - DE.DP - - DE.AE -modification_date: '2018-02-26' -name: Abnormally High AWS Instances Launched by User -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/abnormally_high_instance_termination.yml b/detections/abnormally_high_instance_termination.yml deleted file mode 100644 index f06f0ca3fd..0000000000 --- a/detections/abnormally_high_instance_termination.yml +++ /dev/null @@ -1,106 +0,0 @@ -asset_type: AWS Instance -confidence: medium -creation_date: '2018-02-26' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where an abnormally high number - of instances were successfully terminated by a user in a 10-minute window -detect: - splunk: - correlation_rule: - notable: - nes_fields: userName - rule_description: An abnormally high number of instances were terminated by - a user in a 10-minute window - rule_title: High number of instances terminated by $userName$ - risk: - risk_object: userName - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: '*/10 * * * *' - earliest_time: -30d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success - | bucket span=10m _time | stats count AS instances_terminated by _time userName - | eventstats avg(instances_terminated) as total_terminations_avg, stdev(instances_terminated) - as total_terminations_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_terminated - > total_terminations_avg+(total_terminations_stdev * threshold_value), 1, - 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m")| eval - num_standard_deviations_away = round(abs(instances_terminated - total_terminations_avg) - / total_terminations_stdev, 2) |table _time, userName, instances_terminated, - num_standard_deviations_away, total_terminations_avg, total_terminations_stdev - suppress: - suppress_fields: userName - suppress_period: 3600s -eli5: In this search, we query CloudTrail logs to look for events where an instance - is successfully terminated by a particular user. Since we want to detect a high - number of instances terminated within a short period, we create event buckets for - 10-minute windows. We then calculate the total number of instances terminated by - a particular user, as well as the average- and standard-deviation values. Assign - a `threshold_value` in the search. Try starting with 3 (but it will likely need - to be tweaked for your environment). The `eval` function will set the outlier to - 1 if the number of instances is greater than the average number of instances terminated, - added to the multiplied value of threshold and standard deviation. We then filter - out outliers with a value of 1 and show only those instance-termination events that - happened within the previous 10 minutes. -entities: - - userName -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: ada0f478-84a8-4641-s3f3-d82362dffd75 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 - name: Get EC2 Instance Details by instanceId - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: Many service accounts configured with your AWS infrastructure - are known to exhibit this behavior. Please adjust the threshold values and filter - out service accounts from the output. Always verify whether this search alerted - on a human user. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - DE.DP - - DE.AE -modification_date: '2018-02-26' -name: Abnormally High AWS Instances Terminated by User -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/access_lsass_memory_for_dump_creation.yml b/detections/access_lsass_memory_for_dump_creation.yml index 17fad65794..b215fed710 100644 --- a/detections/access_lsass_memory_for_dump_creation.yml +++ b/detections/access_lsass_memory_for_dump_creation.yml @@ -1,88 +1,33 @@ -asset_type: Windows -confidence: high -creation_date: '2019-12-06' -data_metadata: - data_eventtypes: - - wineventlog_sysmon - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: Detect memory dumping of the LSASS process. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: Possible attempt at credential dumping was detected on $dest$. - rule_title: LSASS memory dump detected on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - macros: - - sysmon - - access_lsass_memory_for_dump_creation_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* - | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId - | rename Computer as dest - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `access_lsass_memory_for_dump_creation_filter` ' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. - This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process - can be created with tools such as Windows Task Manager or procdump. -entities: - - dest -how_to_implement: This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -id: fb4c31b0-13e8-4155-8aa5-24de4b8d6717 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 6 - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 - nist: - - DE.CM -modification_date: '2019-12-06' name: Access LSASS Memory for Dump Creation -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss +id: fb4c31b0-13e8-4155-8aa5-24de4b8d6717 +version: '2' +date: '2019-12-06' +description: Detect memory dumping of the LSASS process. +how_to_implement: This search requires Sysmon Logs and a Sysmon configuration, which + includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. + We strongly recommend that you specify your environment-specific configurations + (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition + with configurations for your Splunk environment. The search also uses a post-filter + macro designed to filter out known false positives. +type: ESCU references: - - https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf -security_domain: endpoint -spec_version: 2 -type: splunk -version: "2" +- https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf +author: Patrick Bareiss, Splunk +search: '`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* + | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, + TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter` ' +known_false_positives: Administrators can create memory dumps for debugging purposes, + but memory dumps of the LSASS process would be unusual. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 6 + - CIS 8 + nist: + - DE.CM diff --git a/detections/account_harvesting.yml b/detections/account_harvesting.yml deleted file mode 100644 index e2b52a00dc..0000000000 --- a/detections/account_harvesting.yml +++ /dev/null @@ -1,105 +0,0 @@ -asset_type: Account -confidence: medium -creation_date: '2018-07-12' -data_metadata: - data_source: - - Network Communications - data_sourcetypes: - - stream:http - providing_technologies: - - Splunk Stream -description: This search is used to identify the creation of multiple user accounts - using the same email domain name. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_user - rule_description: This search is used to identify multiple created accounts - tied to a specific email domain. Such activity is often indicative of account - harvesting. A list of $src_user$ accounts were created. - rule_title: 'Web Fraud Detection: Possible Account Harvesting' - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 40 - schedule: - cron_schedule: 0 1 * * * - earliest_time: -1445m@m - latest_time: -10m@m - search: sourcetype=stream:http http_content_type=text* uri="/magento2/customer/account/loginPost/" - | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" - | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) - as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> - 25 - suppress: - suppress_fields: user - suppress_period: 3600s -eli5: When a fraudster is setting the stage for a campaign, they will often create - many user accounts on the website. This is a simple example of how to detect a many-account - creation hosted on a Magento2 e-commerce platform, where the fraudster is using - email addresses from a single email domain. -entities: - - src_user -how_to_implement: We start with a dataset that provides visibility into the email - address used for the account creation. In this example, we are narrowing our search - down to the single web page that hosts the Magento2 e-commerce platform (via URI) - used for account creation, the single http content-type to grab only the user's - clicks, and the http field that provides the username (form_data), for performance - reasons. After we have the username and email domain, we look for numerous account - creations per email domain. Common data sources used for this detection are customized - Apache logs or Splunk Stream. -id: 31337aaa-941d-4ada-81ac-q2a17be5bf0d -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-1120-e756cc06fd89 - name: Get Web Session Information via session_id - type: splunk - - id: 5df39b3f-447d-4869-b673-8f45ad4616fe - name: Get Emails From Specific Sender - type: splunk -known_false_positives: As is common with many fraud-related searches, we are usually - looking to attribute risk or synthesize relevant context with loosely written detections - that simply detect anamolous behavior. This search will need to be customized to - fit your environment—improving its fidelity by counting based on something - much more specific, such as a device ID that may be present in your dataset. Consideration - for whether the large number of registrations are occuring from a first-time seen - domain may also be important. Extending the search window to look further back - in time, or even calculating the average per hour/day for each email domain to look - for an anomalous spikes, will improve this search. You can also use Shannon entropy - or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness - or similarity of the email name or email domain, as the names are often machine-generated. -maintainers: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Create Account - nist: - - DE.CM - - DE.DP -modification_date: '2018-10-08' -name: Web Fraud - Account Harvesting -original_authors: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger -references: - - https://splunkbase.splunk.com/app/2734/ - - https://splunkbase.splunk.com/app/1809/ -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/acl_with_open_ports.yml b/detections/acl_with_open_ports.yml deleted file mode 100644 index 1cadc3ca57..0000000000 --- a/detections/acl_with_open_ports.yml +++ /dev/null @@ -1,95 +0,0 @@ -asset_type: AWS Instance -confidence: medium -creation_date: '2017-01-08' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: The search looks for CloudTrail events to detect if any network ACLs - were created with all the ports open to a specified CIDR. -detect: - splunk: - correlation_rule: - notable: - nes_fields: aws_account_id, src, arn - rule_description: $src_user$ created a network access control list with all - ports open. - rule_title: Network ACL created with all ports open by $src_user$ - risk: - risk_object: arn - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -1d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=CreateNetworkAclEntry | mvexpand - requestParameters | mvexpand responseElements | search requestParameters.portRange.from=1024 - requestParameters.portRange.to=65535 requestParameters.ruleAction=allow | - rename userIdentity.arn as arn | rename requestParameters.networkAclId as - networkAclId | table _time aws_account_id src userName arn networkAclId requestParameters.* - responseElements.* - suppress: - suppress_fields: arn - suppress_period: 14400s -eli5: A network access control list (ACL) is a layer of security for your VPC that - acts as a firewall for controlling traffic in and out of one or more subnets. Network - ACLs with all open ports have a larger attack surface. This search looks for events - within your CloudTrail logs to check if there were any Network ACLs created with - ports ranging from 1024 to 65525. This search will create a table comprised of AWS - account id, src, user and all parameters of the request made by the user and the - server response. -entities: - - src_user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail - inputs. -id: ada0f478-84a8-4641-a3f1-d82362d6bd75 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7ah9534c242 - name: AWS Network ACL Details from ID - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It's possible that an admin has created this ACL with all ports - open for some legitimate purpose however, this should be scoped and not allowed - in production environment. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 11 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - nist: - - DE.DP - - DE.AE -modification_date: '2017-01-10' -name: AWS Network Access Control List Created with All Open Ports -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/activity_related_to_pass_the_hash.yml b/detections/activity_related_to_pass_the_hash.yml deleted file mode 100644 index 5169d8b2df..0000000000 --- a/detections/activity_related_to_pass_the_hash.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2016-09-13' -data_metadata: - data_eventtypes: - - wineventlog_security - data_source: - - Authentication - providing_technologies: - - Microsoft Windows -description: This search looks for specific authentication events from the Windows - Security Event logs to detect potential attempts at using the Pass-the-Hash technique. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, dest, user - rule_description: This search looks for Authentication log events from the - Windows Security Audit logs to detect potential attempts for Passing the - Hash - rule_title: Detect Activity Related to Pass the Hash - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 10 - macros: - - wineventlog_security - - detect_activity_related_to_pass_the_hash_attacks_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '`wineventlog_security` EventCode=4624 (Logon_Type=3 LogonProcessName=NtLmSsp WorkstationName=WORKSTATION NOT AccountName="ANONYMOUS LOGON") OR - (EventCode=4624 Logon_Type=9 LogonProcessName=seclogo) - | stats count min(_time) as firstTime max(_time) as lastTime by EventCode, Logon_Type, WorkstationName, user, dest - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `detect_activity_related_to_pass_the_hash_attacks_filter` ' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: To detect pass the hash activity, we look at all events with event code 4624 - that specify a logon type 3 (network logons) for remote pass the hash attacks and - logon type 9 for local pass the hash attacks. The search also filters out - events with an account name of 'Anonymous' to help reduce false positives. -entities: - - dest -how_to_implement: To successfully implement this search, you must ingest your Windows - Security Event logs and leverage the latest TA for Windows. -id: f5939373-8054-40ad-8c64-cec478a22a4b -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Legitimate logon activity by authorized NTLM systems may be - detected by this search. Please investigate as appropriate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Lateral Movement - - Pass the Hash - mitre_technique_id: - - T1075 - nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2020-01-09' -name: Detect Activity Related to Pass the Hash Attacks -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: access -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/add_to_untrust_cert_store.yml b/detections/add_to_untrust_cert_store.yml deleted file mode 100644 index df0f0b47c8..0000000000 --- a/detections/add_to_untrust_cert_store.yml +++ /dev/null @@ -1,115 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-04-09' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: Attempt to add a certificate to the untrusted certificate store -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: Attempt to add a certificate to the untrusted certificate - store - rule_title: Attempt To Add Certificate to Untrusted Store - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) - as process max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* - ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' - suppress: - suppress_fields: process, dest - suppress_period: 86400s -eli5: Attackers will often attempt to disable security tools in order to evade detection. - It is also possible for end users to attempt to disable anti-virus or other security - tools to circumvent restrictions they encounter while trying to execute other programs. - One way malware may accomplish this is by adding the legitimate certificate used - to sign the security software to the untrusted certificate store. This will cause - the system to no longer trust the software signed with this certificate and disallow - it from executing. This search simply looks for the execution of **certutil.exe** - with the parameters `-addcert` and `disallowed`, which add a certification to the - "untrusted" certificate store. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: 6bc5243e-ef36-45dc-9b12-f4a6be131159 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: There may be legitimate reasons for administrators to add a - certificate to the untrusted certificate store. In such cases, this will typically - be done on a large number of systems. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 8 - kill_chain_phases: - - Installation - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Disabling Security Tools - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2018-11-15' -name: Attempt To Add Certificate To Untrusted Store -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '4.0' diff --git a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml new file mode 100644 index 0000000000..97cd63b3da --- /dev/null +++ b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml @@ -0,0 +1,25 @@ +name: Amazon EKS Kubernetes cluster scan detection +id: 294c4686-63dd-4fe6-93a2-ca807626704a +version: '1.0' +date: '2020-04-15' +description: This search provides information of unauthenticated requests via user + agent, and authentication data against Kubernetes cluster in AWS +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch + EKS Logs inputs. +type: ESCU +references: [] +author: Rod Soto, Splunk +search: sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" userAgent!="AWS + Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime + max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name + values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) + by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + |`kubernetes_aws_scan_fingerprint_detection` +known_false_positives: Not all unauthenticated requests are malicious, but frequency, + UA and source IPs will provide context. +tags: + analytics_story: + - Kubernetes Scanning Activity + kill_chain_phases: + - Reconnaissance diff --git a/detections/amazon_eks_kubernetes_pod_scan_detection.yml b/detections/amazon_eks_kubernetes_pod_scan_detection.yml new file mode 100644 index 0000000000..b43f24a547 --- /dev/null +++ b/detections/amazon_eks_kubernetes_pod_scan_detection.yml @@ -0,0 +1,26 @@ +name: Amazon EKS Kubernetes Pod scan detection +id: dbfca1dd-b8e5-4ba4-be0e-e565e5d62002 +version: '1.0' +date: '2020-04-15' +description: This search provides detection information on unauthenticated requests + against Kubernetes' Pods API +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch + EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` + macro to filter out the false positives. +type: ESCU +references: [] +author: Rod Soto, Splunk +search: sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" verb=list + objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name + sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime + values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) + values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_detection` +known_false_positives: Not all unauthenticated requests are malicious, but frequency, + UA and source IPs and direct request to API provide context. +tags: + analytics_story: + - Kubernetes Scanning Activity + kill_chain_phases: + - Reconnaissance diff --git a/detections/anomalous_webclick.yml b/detections/anomalous_webclick.yml deleted file mode 100644 index e093a80b6e..0000000000 --- a/detections/anomalous_webclick.yml +++ /dev/null @@ -1,101 +0,0 @@ -asset_type: account -confidence: medium -creation_date: '2018-07-12' -data_metadata: - data_source: - - Network Communications - data_sourcetypes: - - stream:http - providing_technologies: - - Splunk Stream -description: This search is used to examine web sessions to identify those where the - clicks are occurring too quickly for a human or are occurring with a near-perfect - cadence (high periodicity or low standard deviation), resembling a script driven - session. -detect: - splunk: - correlation_rule: - notable: - nes_fields: session_id - rule_description: This search is used to examine web sessions in order to - identify unnaturally rapid clicks with near-perfect cadence (high periodicity - or low standard deviation), which resemble a script-driven session. - rule_title: 'Web Fraud Detection: Anomalous User Clickspeed' - risk: - risk_object: session_id - risk_object_type: - - other - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=stream:http http_content_type=text* | rex field=cookie "form_key=(?\w+)" - | streamstats window=2 current=1 range(_time) as TimeDelta by session_id | - where TimeDelta>0 |stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) - as ClickSpeedAvg by session_id | where count>5 AND (ClickSpeedStdDev<.5 OR - ClickSpeedAvg<.5) - suppress: - suppress_fields: session_id - suppress_period: 3600s -eli5: It's suspicious when someone or something is moving throughout your website - too quickly or with a perfect click cadence. Fortunately, it's easy to detect by - calculating the time between clicks for each session and highlighting the anomalous - behavior. -entities: - - session_id -how_to_implement: Start with a dataset that allows you to see clickstream data for - each user click on the website. That data must have a time stamp and must contain - a reference to the session identifier being used by the website. This ties the clicks - together into clickstreams. This value is usually found in the http cookie. With - a bit of tuning, a version of this search could be used in high-volume scenarios, - such as scraping, crawling, application DDOS, credit-card testing, account takeover, - etc. Common data sources used for this detection are customized Apache logs, customized - IIS, and Splunk Stream. -id: 31337bbb-bc22-4752-b599-ef192df2dc7a -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-1120-e756cc06fd89 - name: Get Web Session Information via session_id - type: splunk - - id: 5df39b3f-447d-4869-b673-8f45ad4616fe - name: Get Emails From Specific Sender - type: splunk -known_false_positives: As is common with many fraud-related searches, we are usually - looking to attribute risk or synthesize relevant context with loosly written detections - that simply detect anamoluous behavior. -maintainers: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger -mappings: - cis20: - - CIS 6 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Initial Access - - Valid Accounts - nist: - - DE.AE - - DE.CM -modification_date: '2018-10-08' -name: Web Fraud - Anomalous User Clickspeed -original_authors: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger -references: - - https://en.wikipedia.org/wiki/Session_ID - - https://en.wikipedia.org/wiki/Session_(computer_science) - - https://en.wikipedia.org/wiki/HTTP_cookie - - https://splunkbase.splunk.com/app/1809/ -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/api_acitivity_from_previously_unseen_user_role.yml b/detections/api_acitivity_from_previously_unseen_user_role.yml deleted file mode 100644 index e356065607..0000000000 --- a/detections/api_acitivity_from_previously_unseen_user_role.yml +++ /dev/null @@ -1,97 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc95-fq2c-48b0-9f6f-63da3289fd03 - name: Previously seen API call per user roles in CloudTrail - type: splunk -confidence: medium -creation_date: '2018-04-01' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search detects new API calls that have either never been seen before - or that have not been seen in the previous hour, where the identity type is `AssumedRole`. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A new API call made by $user$ has been detected. This API - activity has either never been seen before or has not been seen within the - last hour. - rule_title: New API call by $user$ detected - risk: - risk_object: user - risk_object_type: - - user - risk_score: 10 - schedule: - cron_schedule: 30 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole - [search sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole - | stats earliest(_time) as earliest latest(_time) as latest by userName eventName - | inputlookup append=t previously_seen_api_calls_from_user_roles | stats - min(earliest) as earliest, max(latest) as latest by userName eventName | outputlookup - previously_seen_api_calls_from_user_roles| eval newApiCallfromUserRole=if(earliest>=relative_time(now(), - "-70m@m"), 1, 0) | where newApiCallfromUserRole=1 | `security_content_ctime(earliest)` | `security_content_ctime(latest)` - | table eventName userName] |rename userName as user| stats values(eventName) - earliest(_time) as earliest latest(_time) as latest by user | `security_content_ctime(earliest)` - | `security_content_ctime(latest)` - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: The subsearch will execute first and return the user roles and names of the - API calls completed within the last hour, where the type of user identity is `AssumedRole`. - It then appends the historical data to those results in the lookup file. Next, it - recalculates the `earliest` and `latest` fields for each user role, as well as the - name of the API call, and returns only those roles and API calls that have first - been seen in the past hour. This is combined with the main search to return the - values of API calls, name of the user role, and the earliest and latest time of - this activity. It is worth noting that the name of the role of a particular user - is parsed as "userName" in the CloudTrail logs. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. This search works best when you run the "Previously seen API call per user - roles in CloudTrail" support search once to create a history of previously seen - user roles. -id: 22773e84-bac0-4595-b086-20d3f335b4f1 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 - name: Investigate AWS User Activities by user field - type: splunk -known_false_positives: It is possible that there are legitimate user roles making - new or infrequently used API calls in your infrastructure, causing the search to - trigger. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 1 - nist: - - ID.AM -modification_date: '2018-04-16' -name: Detect new API calls from user roles -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/attackers_scanning_for_vulnerable_jboss_servers.yml deleted file mode 100644 index 3b780a10e2..0000000000 --- a/detections/attackers_scanning_for_vulnerable_jboss_servers.yml +++ /dev/null @@ -1,89 +0,0 @@ -asset_type: Web Server -confidence: medium -creation_date: '2016-10-04' -data_metadata: - data_models: - - Web - data_source: - - Network Communications - - Web Server - providing_technologies: - - Splunk Stream - - Palo Alto Firewall - - Apache - - Bro -description: This search looks for specific GET or HEAD requests to web servers that - are indicative of reconnaissance attempts to identify vulnerable JBoss servers. - JexBoss is described as the exploit tool of choice for this malicious activity. -detect: - splunk: - correlation_rule: - notable: - nes_fields: '' - rule_description: This search looks for specific GET/HEAD requests to web - servers that are indicative of reconnaissance attempts to identify vulnerable - JBoss servers. - rule_title: Detect attackers scanning for vulnerable JBoss servers - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") - AND (Web.url="*/web-console/ServerInfo.jsp*" OR Web.url="*web-console*" OR - Web.url="*jmx-console*" OR Web.url = "*invoker*") by Web.http_method, Web.url, - Web.src, Web.dest | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest,url - suppress_period: 86400s -eli5: This search returns the number of times a URL associated with this type of JexBoss - probe is observed. -entities: - - dest -how_to_implement: You must be ingesting data from the web server or network traffic - that contains web specific information, and populating the Web data model. -id: 104658f4-afdc-499e-9719-17243f982681 -investigations: - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: It's possible for legitimate HTTP requests to be made to URLs - containing the suspicious paths. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - kill_chain_phases: - - Reconnaissance - mitre_attack: - - Discovery - - System Information Discovery -modification_date: '2017-09-23' -name: Detect attackers scanning for vulnerable JBoss servers -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/attempt_to_add_certificate_to_untrusted_store.yml b/detections/attempt_to_add_certificate_to_untrusted_store.yml new file mode 100644 index 0000000000..c68b140756 --- /dev/null +++ b/detections/attempt_to_add_certificate_to_untrusted_store.yml @@ -0,0 +1,36 @@ +name: Attempt To Add Certificate To Untrusted Store +id: 6bc5243e-ef36-45dc-9b12-f4a6be131159 +version: '4.0' +date: '2018-11-15' +description: Attempt to add a certificate to the untrusted certificate store +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) + as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe + (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process + Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' +known_false_positives: There may be legitimate reasons for administrators to add a + certificate to the untrusted certificate store. In such cases, this will typically + be done on a large number of systems. +tags: + analytics_story: + - Disabling Security Tools + mitre_attack_id: + - T1089 + kill_chain_phases: + - Installation + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml index 0a8403bed8..c8bc5255db 100644 --- a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml +++ b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml @@ -1,95 +1,39 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-08-28' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, registry_path, registry_key_name, registry_value_name - rule_description: An attempt to modify the default PowerShell execution policy - in the registry to "Unrestricted" or "Bypass" was detected on $dest$. - rule_title: Attempt To Set PowerShell Execution Policy To "Unrestricted" or "Bypass" On - $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - macros: - - attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry - where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* - Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) - by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest - | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` ' - suppress: - suppress_fields: process_name, dest - suppress_period: 86400s -eli5: This search looks for changes of the ExecutionPolicy in the registry. The ExecutionPolicy - is a safety feature that controls the conditions under which PowerShell loads configuration - files and runs scripts. Usually, the ExecutionPolicy is "Restricted" for Windows clients and - "RemoteSigned" for Windows Servers, allowing only certain scripts to run. This search detects - when an attacker sets the ExecutionPolicy to "Unrestricted" or "Bypass." -entities: - - dest +name: Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass +id: c2590137-0b08-4985-9ec5-6ae23d92f63d +version: '4.0' +date: '2019-12-02' +description: Monitor for changes of the ExecutionPolicy in the registry to the values + "unrestricted" or "bypass," which allows the execution of malicious scripts. how_to_implement: You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be - ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. -id: c2590137-0b08-4985-9ec5-6ae23d92f63d -known_false_positives: Administrators may attempt to change the default execution - policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" - as this search is designed to identify, would be unusual. Hits should be reviewed - and investigated as appropriate. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 3 - - CIS 8 - kill_chain_phases: - - Installation - - Actions on Objectives - mitre_technique_id: - - T1086 - - T1064 - mitre_attack: - - Execution - - PowerShell - - Scripting - nist: - - DE.CM -modification_date: '2019-12-02' -name: Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss + ingesting logs with the fields registry_path, registry_key_name, and registry_value_name + from your endpoints. +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '4.0' +author: Patrick Bareiss, Splunk +search: "| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time)\ + \ as lastTime from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\\ + \\Microsoft\\\\Powershell\\\\1\\\\ShellIds\\\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy\ + \ (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass)\ + \ by Registry.registry_path Registry.registry_key_name Registry.registry_value_name\ + \ Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`|\ + \ `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter`\_" +known_false_positives: Administrators may attempt to change the default execution + policy on a system for a variety of reasons. However, setting the policy to "unrestricted" + or "bypass" as this search is designed to identify, would be unusual. Hits should + be reviewed and investigated as appropriate. +tags: + analytics_story: + - Malicious PowerShell + - Credential Dumping + mitre_attack_id: + - T1086 + - T1064 + kill_chain_phases: + - Installation + - Actions on Objectives + cis20: + - CIS 3 + - CIS 8 + nist: + - DE.CM diff --git a/detections/attempt_to_stop_security_service.yml b/detections/attempt_to_stop_security_service.yml new file mode 100644 index 0000000000..9cc383f3f4 --- /dev/null +++ b/detections/attempt_to_stop_security_service.yml @@ -0,0 +1,44 @@ +name: Attempt To Stop Security Service +id: c8e349c6-b97c-486e-8949-bd7bcd1f3910 +version: '2.0' +date: '2017-09-15' +description: This search looks for attempts to stop security-related services on the + endpoint. +how_to_implement: You must be ingesting data that records the file-system activity + from your hosts to populate the Endpoint file-system data-model node. If you are + using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which + you want to collect data. The search is shipped with a lookup file, `security_services.csv`, + that can be edited to update the list of services to monitor. This lookup file can + be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, + or via the Splunk console. You should add the names of services an attacker might + use on the command line and surround with asterisks (*****), so that they work properly + when searching the command line. The file should be updated with the names of any + services you would like to monitor for attempts to stop the service., +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where (Processes.process_name = net.exe OR Processes.process_name = sc.exe) Processes.process="* + stop *" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + |lookup security_services_lookup service as process OUTPUTNEW category, description + | search category=security' +known_false_positives: None identified. Attempts to disable security-related services + should be identified and understood. +tags: + analytics_story: + - Disabling Security Tools + mitre_attack_id: + - T1089 + kill_chain_phases: + - Installation + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/attempted_credential_dump_from_registry_via_reg.yml b/detections/attempted_credential_dump_from_registry_via_reg.yml deleted file mode 100644 index 4a42aa101a..0000000000 --- a/detections/attempted_credential_dump_from_registry_via_reg.yml +++ /dev/null @@ -1,103 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-08-28' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Sysmon -description: Monitor for execution of reg.exe with parameters specifying - an export of keys that contain hashed credentials that attackers may try to crack - offline. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, process_name, process - rule_description: An attempt to save registry keys holding credentials was - identified by $user$. - rule_title: Attempted Credential Dump From Registry from $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 80 - macros: - - attempted_credential_dump_from_registry_via_reg_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime - from datamodel=Endpoint.Processes where (Processes.process_name=reg.exe OR Processes.process_name=cmd.exe) Processes.process=*save* - (Processes.process=*HKEY_LOCAL_MACHINE\\Security* OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR - Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR - Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) - by Processes.user Processes.process_name Processes.process Processes.dest - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `attempted_credential_dump_from_registry_via_reg_filter`' - suppress: - suppress_fields: process_name, dest - suppress_period: 86400s -eli5: This search looks for the process reg.exe with the "save" parameter, which specifies - a binary export from the registry. In addition, it looks for the keys that contain - the hashed credentials, which attackers may retrieve and use for brute-force attacks - in order to harvest legitimate credentials. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints, to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: 14038953-e5f2-4daf-acff-5452062baf03 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: None identified. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_technique_id: - - T1003 - mitre_attack: - - Credential Access - - Credential Dumping - nist: - - DE.CM -modification_date: '2019-12-02' -name: Attempted Credential Dump From Registry via Reg.exe -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '4.0' diff --git a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml new file mode 100644 index 0000000000..bf63df1c35 --- /dev/null +++ b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml @@ -0,0 +1,34 @@ +name: Attempted Credential Dump From Registry via Reg.exe +id: 14038953-e5f2-4daf-acff-5452062baf03 +version: '4.0' +date: '2019-12-02' +description: Monitor for execution of reg.exe with parameters specifying an export + of keys that contain hashed credentials that attackers may try to crack offline. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints, to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: [] +author: Patrick Bareiss, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=reg.exe + OR Processes.process_name=cmd.exe) Processes.process=*save* (Processes.process=*HKEY_LOCAL_MACHINE\\Security* + OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* + OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) + by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_filter`' +known_false_positives: None identified. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 16 + nist: + - DE.CM diff --git a/detections/attrib_to_hide_files.yml b/detections/attrib_to_hide_files.yml deleted file mode 100644 index 099387ec43..0000000000 --- a/detections/attrib_to_hide_files.yml +++ /dev/null @@ -1,108 +0,0 @@ -asset_type: '' -confidence: medium -creation_date: '2017-10-23' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: Attackers leverage an existing Windows binary, attrib.exe, to mark specific - as hidden by using specific flags so that the victim does not see the file. The - search looks for specific command-line arguments to detect the use of attrib.exe - to hide files. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: Attrib.exe is often used by attackers to hide malware files - and directories in windows environments. This rule detects command-line - arguments used to hide a file/directory - rule_title: 'Suspicious usage of attrib.exe on $dest$ ' - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - attrib_to_hide_files_filter - schedule: - cron_schedule: 30 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) values(Processes.process) - as process max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process - Processes.process_name Processes.user | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `attrib_to_hide_files_filter`' - suppress: - suppress_fields: dest, process - suppress_period: 86400s -eli5: This search is looking to detect command-line execution with of attrib.exe binary - with the +h flag set. The +h flag is used to hide a file. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: c77162d3-f93c-45cc-80c8-22f6b5264g9f -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: 'Some applications and users may legitimately use attrib.exe - to interact with the files. ' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Persistence - nist: - - DE.CM -modification_date: '2020-03-16' -name: Hiding Files And Directories With Attrib.exe -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/aws_activity_from_non_approved_accounts.yml b/detections/aws_activity_from_non_approved_accounts.yml deleted file mode 100644 index 94ffc92da8..0000000000 --- a/detections/aws_activity_from_non_approved_accounts.yml +++ /dev/null @@ -1,118 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc95-ff2b-48b1-5f6f-63ga3789fd43 - name: Create a list of approved AWS service accounts - type: splunk -confidence: medium -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for successful CloudTrail activity by user accounts - that are not listed in the identity table or `aws_service_accounts.csv`. It returns - event names and count, as well as the first and last time a specific user or service - is detected, grouped by users. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A successful API activity was invoked by $user$, an unapproved/unknown - account. - rule_title: 'Successful API activity by a non-approved account: $user$' - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail errorCode=success | rename userName as identity - | search NOT [| inputlookup identity_lookup_expanded | fields identity] | - search NOT [| inputlookup aws_service_accounts | fields identity] | rename - identity as user | stats count min(_time) as firstTime max(_time) as lastTime - values(eventName) as eventName by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - suppress: - suppress_fields: user - suppress_period: 14400s -eli5: In this search, we are looking for successful API calls via CloudTrail. We filter - out events triggered by known users listed in the `identity_lookup_expanded` lookup - file and the service accounts. Once filtered out, we output a table with the event - names and count, as well as the first and last time a specific user or service is - detected. -entities: - - user -how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. You must also populate the `identity_lookup_expanded` lookup shipped with - the Asset and Identity framework to be able to look up users in your identity table - in Enterprise Security (ES). Leverage the support search called "Create a list of - approved AWS service accounts": run it once every 30 days to create and validate - a list of service accounts.\ - - This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet - supported by ES Incident Review and therefore cannot be viewed when a notable event - is raised. These fields contribute additional context to the notable. To see the - additional metadata, add the following fields, if not already present, to Incident - Review - Event Attributes (Configure > Incident Management > Incident Review Settings - > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ - - 1. \ - - 1. **Label:** First Time, **Field:** firstTime\ - - 1. \ - - 1. **Label:** Last Time, **Field:** lastTime\ - - Detailed documentation on how to create a new field within Incident Review may be - found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: ada0f478-84a8-4641-a3f1-d82362d4bd55 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 - name: Investigate AWS User Activities by user field - type: splunk -known_false_positives: It's likely that you'll find activity detected by users/service - accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` - file. If the user is a legitimate service account, update the `aws_service_accounts.csv` - table with that entry. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Execution - nist: - - DE.DP - - DE.CM - - PR.AC - - ID.AM -modification_date: '2018-03-13' -name: Detect AWS API Activities From Unapproved Accounts -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: access -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/aws_activity_in_new_region.yml b/detections/aws_activity_in_new_region.yml deleted file mode 100644 index 0285237a0a..0000000000 --- a/detections/aws_activity_in_new_region.yml +++ /dev/null @@ -1,110 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd63 - name: Previously Seen AWS Regions - type: splunk -confidence: medium -creation_date: '2018-02-01' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where an instance is started - in a particular region in the last one hour and then compares it to a lookup file - of previously seen regions where an instance was started -detect: - splunk: - correlation_rule: - notable: - nes_fields: awsRegion - rule_description: An AWS instance is started in a new, previously unseen, - region - rule_title: AWS instance is started in a new region - risk: - risk_object: awsRegion - risk_object_type: - - other - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail earliest=-1h StartInstances - | stats earliest(_time) as earliest latest(_time) as latest by awsRegion - | inputlookup append=t previously_seen_aws_regions.csv - | stats min(earliest) as earliest max(latest) as latest by awsRegion - | outputlookup previously_seen_aws_regions.csv - | eval regionStatus=if(earliest >= relative_time(now(),"-1d@d"), "Instance Started in a New Region","Previously Seen Region") - | `security_content_ctime(earliest)` - | `security_content_ctime(latest)` - | where regionStatus="Instance Started in a New Region" - suppress: - suppress_fields: awsRegion - suppress_period: 14400s -eli5: In this search, we query CloudTrail logs to look for events that indicate that - an instance was started in a particular region. Using the `previously_seen_aws_regions.csv` - lookup file created using the support search, we compare the region where this instance - was started to all previously observed regions. The `eval` and `if` functions determine - that the earliest times seen for this region and instance were within the last day. - If a new region is detected, it will alert you with "Instance Started in a New Region". - However, this region will be added to the list of `previously_seen_aws_regions.csv`. - Please maintain `previously_seen_aws_regions.csv` -entities: - - awsRegion -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Run the "Previously seen AWS Regions" support search only once to create - of baseline of previously seen regions. -id: ada0f478-84a8-4641-a3f3-d82362d6fd75 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 - name: Get EC2 Launch Details - type: splunk - - id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 - name: Get EC2 Instance Details by instanceId - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: It's possible that a user has unknowingly started an instance - in a new region. Please verify that this activity is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 12 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - nist: - - DE.DP - - DE.AE -modification_date: '2018-02-23' -name: EC2 Instance Started In Previously Unseen Region -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml index 5a41797557..871e7f27da 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml @@ -1,75 +1,29 @@ -asset_type: AWS Instance -baselines: - - id: ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee - name: Previously Seen AWS Provisioning Activity Sources - type: splunk -confidence: medium -creation_date: '2018-03-16' -data_metadata: - data_source: - - AWS CloudTrail - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: AWS Cloud Provisioning From Previously Unseen City +id: 344a1778-0b25-490c-adb1-de8beddf59cd +version: '1.0' +date: '2018-03-16' description: 'This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." ' -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, city - rule_description: Your AWS infrastructure was provisioned from a city, $city$, - which has never before been seen provisioning your infrastructure. - rule_title: AWS Provision Activity From $city$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search City=* [search sourcetype=aws:cloudtrail (eventName=Run* - OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats - earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, - City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, - City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval - newCity=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCity=1 - | table City] | spath output=user userIdentity.arn | rename sourceIPAddress - as src_ip | table _time, user, src_ip, City, eventName, errorCode - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: The subsearch returns all events with event names that start with "Run" or "Create," - and then does a `GeoIP` lookup on the IP address that initiated the action within - the last hour. It appends the historical data to those results in the lookup file. - Next, it recalculates the `firstTime` and `lastTime` field for each country, region, - city, and IP address and outputs this data to the lookup file to update the local - cache. It then calculates the `firstTime` and `lastTime` for each city. It returns - only those events from cities that have first been seen in the past hour. This is - combined with the main search to return the time, user, IP address, city, event - name, and error code from the action. -entities: - - dest how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -id: 344a1778-0b25-490c-adb1-de8beddf59cd -investigations: - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk - - id: 0abeeb40-1255-4b68-91d1-7a7eb410c4b8 - name: Get All AWS Activity From City - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search City=* [search sourcetype=aws:cloudtrail (eventName=Run* + OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) + as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country + | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country + | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), + "-70m@m"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn + | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, + errorCode known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching within, plus what is\ @@ -81,23 +35,10 @@ known_false_positives: "This is a strictly behavioral search, so we define \"fal \ free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution\ \ (particularly small countries in less economically powerful regions), this may\ \ be much less valuable to you." -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: +tags: + analytics_story: + - AWS Suspicious Provisioning Activities cis20: - - CIS 1 + - CIS 1 nist: - - ID.AM -modification_date: '2018-03-16' -name: AWS Cloud Provisioning From Previously Unseen City -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' + - ID.AM diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml index 6ce3c7218c..071f97513b 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml @@ -1,76 +1,29 @@ -asset_type: AWS Instance -baselines: - - id: ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee - name: Previously Seen AWS Provisioning Activity Sources - type: splunk -confidence: medium -creation_date: '2018-03-16' -data_metadata: - data_source: - - AWS CloudTrail - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: AWS Cloud Provisioning From Previously Unseen Country +id: ceb8d3d8-06cb-49eb-beaf-829526e33ff0 +version: '1.0' +date: '2018-03-16' description: 'This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." ' -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, country - rule_description: Your AWS infrastructure was provisioned from a country, - $country$, which has never before been seen provisioning your infrastructure. - rule_title: AWS Provision Activity From $country$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* - OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats - earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, - City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, - City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by Country | - eval newCountry=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where - newCountry=1 | table Country] | spath output=user userIdentity.arn | rename - sourceIPAddress as src_ip | table _time, user, src_ip, Country, eventName, - errorCode - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: The subsearch returns all events with event names that start with "Run" or "Create," - and then does a `GeoIP` lookup on the IP address that initiated the action within - the last hour. It appends the historical data to those results in the lookup file. - Next, it recalculates the `firstTime` and `lastTime` field for each country, region, - city, and IP address and outputs this data to the lookup file to update the local - cache. It then calculates the `firstTime` and `lastTime` for each country. It returns - only those events from countries that have first been seen in the past hour. This - is combined with the main search to return the time, user, IP address, city, event - name, and error code from the action. -entities: - - dest how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -id: ceb8d3d8-06cb-49eb-beaf-829526e33ff0 -investigations: - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk - - id: e763cdb9-00da-41e0-9bda-444debc9501a - name: Get All AWS Activity From Country - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* + OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) + as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country + | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country + | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime + >= relative_time(now(), "-70m@m"), 1, 0) | where newCountry=1 | table Country] | + spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, + user, src_ip, Country, eventName, errorCode known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching over plus what is stored\ @@ -82,23 +35,10 @@ known_false_positives: "This is a strictly behavioral search, so we define \"fal \ version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution\ \ (particularly small countries in less economically powerful regions), this may\ \ be much less valuable to you." -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: +tags: + analytics_story: + - AWS Suspicious Provisioning Activities cis20: - - CIS 1 + - CIS 1 nist: - - ID.AM -modification_date: '2018-03-16' -name: AWS Cloud Provisioning From Previously Unseen Country -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' + - ID.AM diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_ip.yml b/detections/aws_cloud_provisioning_from_previously_unseen_ip.yml deleted file mode 100644 index 6235964325..0000000000 --- a/detections/aws_cloud_provisioning_from_previously_unseen_ip.yml +++ /dev/null @@ -1,100 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee - name: Previously Seen AWS Provisioning Activity Sources - type: splunk -confidence: medium -creation_date: '2018-03-16' -data_metadata: - data_source: - - AWS CloudTrail - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: 'This search looks for AWS provisioning activities from previously unseen - IP addresses. Provisioning activities are defined broadly as any event that begins - with "Run" or "Create." ' -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip - rule_description: Your AWS infrastructure was provisioned from an IP, $src_ip$, - which has never before been seen provisioning your infrastructure. - rule_title: AWS Provision Activity From $src_ip$ - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* - OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats - earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, - City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, - City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress - | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where - newIP=1 | table sourceIPAddress] | spath output=user userIdentity.arn | rename - sourceIPAddress as src_ip | table _time, user, src_ip, eventName, errorCode - suppress: - suppress_fields: src_ip - suppress_period: 14400s -eli5: The subsearch returns all events with event names that start with "Run" or "Create," - and then does a `GeoIP` lookup on the IP address that initiated the action within - the last hour. It appends the historical data to those results in the lookup file. - Next, it recalculates the `firstTime` and `lastTime` field for each country, region, - city, and IP address and outputs this data to the lookup file to update the local - cache. It then calculates the `firstTime` and `lastTime` for each city. It returns - only those events from IP addresses that have first been seen in the past hour. - This is combined with the main search to return the time, user, IP address, city, - event name, and error code from the action. -entities: - - src_ip -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. This search works best when you run the "Previously Seen AWS Provisioning - Activity Sources" support search once to create a history of previously seen locations - that have provisioned AWS resources. -id: 42e15012-ac14-4801-94f4-f1acbe64880b -investigations: - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk -known_false_positives: "This is a strictly behavioral search, so we define \"false\ - \ positive\" slightly differently. Every time this fires, it will accurately reflect\ - \ the first occurrence in the time period you're searching within, plus what is\ - \ stored in the cache feature. But while there are really no \"false positives\"\ - \ in a traditional sense, there is definitely lots of noise.\\\n This search will\ - \ fire any time a new IP address is seen in the **GeoIP** database for any kind\ - \ of provisioning activity. If you typically do all provisioning from tools inside\ - \ of your country, there should be few false positives. If you are located in countries\ - \ where the free version of **MaxMind GeoIP** that ships by default with Splunk\ - \ has weak resolution (particularly small countries in less economically powerful\ - \ regions), this may be much less valuable to you." -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 1 - nist: - - ID.AM -modification_date: '2018-03-16' -name: AWS Cloud Provisioning From Previously Unseen IP Address -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml new file mode 100644 index 0000000000..28784215f1 --- /dev/null +++ b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml @@ -0,0 +1,44 @@ +name: AWS Cloud Provisioning From Previously Unseen IP Address +id: 42e15012-ac14-4801-94f4-f1acbe64880b +version: '1.0' +date: '2018-03-16' +description: 'This search looks for AWS provisioning activities from previously unseen + IP addresses. Provisioning activities are defined broadly as any event that begins + with "Run" or "Create." ' +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. This search works best when you run the "Previously Seen AWS Provisioning + Activity Sources" support search once to create a history of previously seen locations + that have provisioned AWS resources. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* + OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) + as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country + | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country + | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by sourceIPAddress | eval newIP=if(firstTime + >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | table sourceIPAddress] + | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table + _time, user, src_ip, eventName, errorCode +known_false_positives: "This is a strictly behavioral search, so we define \"false\ + \ positive\" slightly differently. Every time this fires, it will accurately reflect\ + \ the first occurrence in the time period you're searching within, plus what is\ + \ stored in the cache feature. But while there are really no \"false positives\"\ + \ in a traditional sense, there is definitely lots of noise.\\\n This search will\ + \ fire any time a new IP address is seen in the **GeoIP** database for any kind\ + \ of provisioning activity. If you typically do all provisioning from tools inside\ + \ of your country, there should be few false positives. If you are located in countries\ + \ where the free version of **MaxMind GeoIP** that ships by default with Splunk\ + \ has weak resolution (particularly small countries in less economically powerful\ + \ regions), this may be much less valuable to you." +tags: + analytics_story: + - AWS Suspicious Provisioning Activities + cis20: + - CIS 1 + nist: + - ID.AM diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml index 484ff855cb..7bd5963a0f 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml @@ -1,76 +1,29 @@ -asset_type: AWS Instance -baselines: - - id: ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee - name: Previously Seen AWS Provisioning Activity Sources - type: splunk -confidence: medium -creation_date: '2018-03-16' -data_metadata: - data_source: - - AWS CloudTrail - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: AWS Cloud Provisioning From Previously Unseen Region +id: 7971d3df-da82-4648-a6e5-b5637bea5253 +version: '1.0' +date: '2018-03-16' description: This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, Region - rule_description: Your AWS infrastructure was provisioned from a region, $Region$, - which has never before been seen provisioning your infrastructure. - rule_title: AWS Provision Activity From $region$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Region=* [search sourcetype=aws:cloudtrail (eventName=Run* - OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats - earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, - City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, - City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by Region | - eval newRegion=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where - newRegion=1 | table Region] | spath output=user userIdentity.arn | rename - sourceIPAddress as src_ip | table _time, user, src_ip, Region, eventName, - errorCode - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: The subsearch returns all events with event names that start with "Run" or "Create," - and then does a `GeoIP` lookup on the IP address that initiated the action within - the last hour. It appends the historical data to those results in the lookup file. - Next, it recalculates the `firstTime` and `lastTime` field for each country, region, - city, and IP address and outputs this data to the lookup file to update the local - cache. It then calculates the `firstTime` and `lastTime` for each city. It returns - only those events from regions that have first been seen in the past hour. This - is combined with the main search to return the time, user, IP address, city, event - name, and error code from the action. -entities: - - dest how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -id: 7971d3df-da82-4648-a6e5-b5637bea5253 -investigations: - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk - - id: 5b794bef-1743-4f6f-804a-43915a2702ff - name: Get All AWS Activity From Region - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search Region=* [search sourcetype=aws:cloudtrail (eventName=Run* + OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) + as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country + | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country + | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= + relative_time(now(), "-70m@m"), 1, 0) | where newRegion=1 | table Region] | spath + output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, + src_ip, Region, eventName, errorCode known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching within, plus what is\ @@ -82,23 +35,10 @@ known_false_positives: "This is a strictly behavioral search, so we define \"fal \ version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution\ \ (particularly small countries in less economically powerful regions), this may\ \ be much less valuable to you." -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: +tags: + analytics_story: + - AWS Suspicious Provisioning Activities cis20: - - CIS 1 + - CIS 1 nist: - - ID.AM -modification_date: '2018-03-16' -name: AWS Cloud Provisioning From Previously Unseen Region -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' + - ID.AM diff --git a/detections/aws_cross_account_activity_from_new_account.yml b/detections/aws_cross_account_activity_from_new_account.yml deleted file mode 100644 index ce1f8f645f..0000000000 --- a/detections/aws_cross_account_activity_from_new_account.yml +++ /dev/null @@ -1,128 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: 1cc22b09-c867-416e-a511-cb36ac44aee2 - name: Previously Seen AWS Cross Account Activity - type: splunk -confidence: medium -creation_date: '2018-02-01' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for AssumeRole events where an IAM role in a different - account is requested for the first time. -detect: - splunk: - correlation_rule: - notable: - nes_fields: requestingAccountId, requestedAccountId, src_user, dest_user - rule_description: Access to $dest_user$ was requested for the first time by - $src_user$ - rule_title: AWS Account $dest_user$ access by $src_user$ - risk: - risk_object: dest_user - risk_object_type: - - user - risk_score: 20 - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId - path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId - | search requestingAccountId=* | where requestingAccountId != requestedAccountId - | inputlookup append=t previously_seen_aws_cross_account_activity | multireport - [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) - as firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) - as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity - | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d - %H:%M:%S")))) as firstTime, max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), - lastTime))) as lastTime by requestingAccountId, requestedAccountId | where - firstTime >= relative_time(now(), "-70m@m") AND isnotnull(_time) | spath output=accessKeyId - path=responseElements.credentials.accessKeyId | spath output=requestingARN - path=resources{}.ARN | stats values(awsRegion) as awsRegion values(firstTime) - as firstTime values(lastTime) as lastTime values(sharedEventID) as sharedEventID, - values(requestingARN) as src_user, values(responseElements.assumedRoleUser.arn) - as dest_user by _time, requestingAccountId, requestedAccountId, accessKeyId] - | table _time, firstTime, lastTime, src_user, requestingAccountId, dest_user, - requestedAccountId, awsRegion, accessKeyId, sharedEventID - suppress: - suppress_fields: requestingAccountId, requestedAccountId - suppress_period: 14400s -eli5: 'This search\ - - 1. Retrieves the **AssumeRole** event\ - - 1. Verifies that the log entry contains a value for the account ID of the requesting - account\ - - 1. Ensures that the requesting account ID does not match the account ID of the requested - account\ - - 1. Pulls in the previously seen requesting and requested account IDs\ - - 1. Splits up and executes multiple search paths at the same.\ - - 1. The first path determines the **firstTime** and **lastTime** entries for the - cache file\ - - 1. Outputs the data to the cache file.\ - - 1. Creates a conditional statement that is always false (both because we don''t - want these values to exit the search pipeline and because we think we''re clever).The - second pipeline adds the **firstTime** and **lastTime** entries to search results. - Next, it filters out any account pairs that haven''t been seen for the first time - within the last hour. The `isnotnull(_time)` will remove the entries from the cache - file.\ - - The search finishes by gathering the data that it will display to the user.' -entities: - - dest_user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Run the `Previously Seen AWS Cross Account Activity` support search only - once to create the baseline of previously seen cross account activity. Thanks to - Pablo Vega at Recurly for suggesting improvements to the search. -id: 64fbbddf-fabf-4edf-80b3-0cc36ef37727 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: 703b65a4-a0ae-4171-965d-45507506c64f - name: AWS Investigate User Activities By AccessKeyId - type: splunk - - id: b0d2e6a8-75fa-4b1b-9486-3d32acadf891 - name: AWS Investigate User Activities By Source User - type: splunk -known_false_positives: Using multiple AWS accounts and roles is perfectly valid behavior. - It's suspicious when an account requests privileges of an account it hasn't before. - You should validate with the account owner that this is a legitimate request. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - nist: - - PR.AC - - PR.DS - - DE.AE -modification_date: '2018-11-02' -name: AWS Cross Account Activity From Previously Unseen Account -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/aws_cross_account_activity_from_previously_unseen_account.yml b/detections/aws_cross_account_activity_from_previously_unseen_account.yml new file mode 100644 index 0000000000..10a2bf0c6c --- /dev/null +++ b/detections/aws_cross_account_activity_from_previously_unseen_account.yml @@ -0,0 +1,45 @@ +name: AWS Cross Account Activity From Previously Unseen Account +id: 64fbbddf-fabf-4edf-80b3-0cc36ef37727 +version: '2.0' +date: '2018-11-02' +description: This search looks for AssumeRole events where an IAM role in a different + account is requested for the first time. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Run the `Previously Seen AWS Cross Account Activity` support search only + once to create the baseline of previously seen cross account activity. Thanks to + Pablo Vega at Recurly for suggesting improvements to the search. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId + path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId + | search requestingAccountId=* | where requestingAccountId != requestedAccountId + | inputlookup append=t previously_seen_aws_cross_account_activity | multireport + [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as + firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as + lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity + | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d + %H:%M:%S")))) as firstTime, max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), + lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime + >= relative_time(now(), "-70m@m") AND isnotnull(_time) | spath output=accessKeyId + path=responseElements.credentials.accessKeyId | spath output=requestingARN path=resources{}.ARN + | stats values(awsRegion) as awsRegion values(firstTime) as firstTime values(lastTime) + as lastTime values(sharedEventID) as sharedEventID, values(requestingARN) as src_user, + values(responseElements.assumedRoleUser.arn) as dest_user by _time, requestingAccountId, + requestedAccountId, accessKeyId] | table _time, firstTime, lastTime, src_user, requestingAccountId, + dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID +known_false_positives: Using multiple AWS accounts and roles is perfectly valid behavior. + It's suspicious when an account requests privileges of an account it hasn't before. + You should validate with the account owner that this is a legitimate request. +tags: + analytics_story: + - AWS Cross Account Activity + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - PR.AC + - PR.DS + - DE.AE diff --git a/detections/aws_network_access_control_list_created_with_all_open_ports.yml b/detections/aws_network_access_control_list_created_with_all_open_ports.yml new file mode 100644 index 0000000000..34631bb25c --- /dev/null +++ b/detections/aws_network_access_control_list_created_with_all_open_ports.yml @@ -0,0 +1,30 @@ +name: AWS Network Access Control List Created with All Open Ports +id: ada0f478-84a8-4641-a3f1-d82362d6bd75 +version: '1.0' +date: '2017-01-10' +description: The search looks for CloudTrail events to detect if any network ACLs + were created with all the ports open to a specified CIDR. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail + inputs. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventName=CreateNetworkAclEntry | mvexpand requestParameters + | mvexpand responseElements | search requestParameters.portRange.from=1024 requestParameters.portRange.to=65535 + requestParameters.ruleAction=allow | rename userIdentity.arn as arn | rename requestParameters.networkAclId + as networkAclId | table _time aws_account_id src userName arn networkAclId requestParameters.* + responseElements.* +known_false_positives: It's possible that an admin has created this ACL with all ports + open for some legitimate purpose however, this should be scoped and not allowed + in production environment. +tags: + analytics_story: + - AWS Network ACL Activity + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 11 + nist: + - DE.DP + - DE.AE diff --git a/detections/aws_network_access_control_list_deleted.yml b/detections/aws_network_access_control_list_deleted.yml new file mode 100644 index 0000000000..9589defa5c --- /dev/null +++ b/detections/aws_network_access_control_list_deleted.yml @@ -0,0 +1,31 @@ +name: AWS Network Access Control List Deleted +id: ada0f478-84a8-4641-a3f1-d82362d6fd75 +version: '1.0' +date: '2017-01-10' +description: Enforcing network-access controls is one of the defensive mechanisms + used by cloud administrators to restrict access to a cloud instance. After the attacker + has gained control of the AWS console by compromising an admin account, they can + delete a network ACL and gain access to the instance from anywhere. This search + will query the CloudTrail logs to detect users deleting network ACLs. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventName=DeleteNetworkAcl|rename userIdentity.arn + as arn | stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) + values(errorCode) values(userAgent) values(userIdentity.*) by src userName arn eventName + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` +known_false_positives: It's possible that a user has legitimately deleted a network + ACL. +tags: + analytics_story: + - AWS Network ACL Activity + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 11 + nist: + - DE.DP + - DE.AE diff --git a/detections/aws_spike_acl_activity.yml b/detections/aws_spike_acl_activity.yml deleted file mode 100644 index 00446a4958..0000000000 --- a/detections/aws_spike_acl_activity.yml +++ /dev/null @@ -1,151 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edd96-ff2b-4810-9f1f-63da3783fd63 - name: Baseline of Network ACL Activity by ARN - type: splunk -confidence: medium -creation_date: '2018-05-17' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search will detect users creating spikes in API activity related - to network access-control lists (ACLs)in your AWS environment. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A spike in the number of AWS API calls related to network - ACLs by $user$ was detected. - rule_title: Spike in AWS Network ACL activity detected by $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 10 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail `network_acl_events` [search sourcetype=aws:cloudtrail - `network_acl_events` | spath output=arn path=userIdentity.arn | stats count - as apiCalls by arn | inputlookup network_acl_activity_baseline append=t | - fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount - | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, - 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval - avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, - stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) - | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup - network_acl_activity_baseline | eval dataPointThreshold = 15, deviationThreshold - = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) - AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn - as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn - | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) - as uniqueApisCalled by user - suppress: - suppress_fields: user - suppress_period: 14400s -eli5: 'This search and its corresponding subsearch run through the following series - of steps: \ - - 1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls - specifically for creating/modifying/replacing network Access Control Lists (ACLs).\ - - 1. Kick off a subsearch that retrieves the same data and pulls out the ARN into - a more friendly format.\ - - 1. Count the number of API calls per Amazon Resource Name (ARN).\ - - 1. Load the cache file that contains the number of data points, the count from the - latest hour, the API call average, and the standard deviation for each ARN.\ - - 1. Drop the count from the latest hour, since it is not necessary, and merge the - rest of the data with the results of the stats command. \ - - 1. Rename `apiCalls` as `latestCount`.\ - - 1. Calculate the new average value for each ARN with the latest count, weighting - the past much more heavily than the current hour. They do the same for the standard - deviation--weighting the past more heavily than the current.\ - - 1. Update the cache file with the latest results.\ - - 1. Set the minimum threshold for the number of data points and set the number of - standard deviations away from the mean it must be to be considered a spike.\ - - 1. Make a determination regarding whether or not the current count is a spike by - checking to see if the minimum data-point threshold has been met and the count is - a sufficient number of standard deviations away from the average.\ - - 1. Filter out anything that it determines is not a spike and return the list of - ARNs to the main search. The main search subsequently gets the names of all the - API calls, the number of unique API calls, and the total number of API calls for - each of these ARNs. Finally, it looks up the average and standard deviation and - returns both the average and the number of standard deviations the spike is from - the average.' -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit - your environment. The `dataPointThreshold` variable is the minimum number of data - points required to have a statistically significant amount of data to determine. - The `deviationThreshold` variable is the number of standard deviations away from - the mean that the value must be to be considered a spike. This search works best - when you run the "Baseline of Network ACL Activity by ARN" support search once to - create a lookup file of previously seen Network ACL Activity. To add or remove API - event names related to network ACLs, edit the macro `network_acl_events`. -id: ada0f478-84a8-4641-a1f1-e32372d4bd53 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: f3fb4d1c-5f33-4b01-b541-c3ah9534c241 - name: AWS Network Interface details via resourceId - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7ah9534c242 - name: AWS Network ACL Details from ID - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: The false-positive rate may vary based on the values of`dataPointThreshold` - and `deviationThreshold`. Please modify this according the your environment. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 12 - - CIS 11 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Exfiltration - nist: - - DE.DP - - DE.CM - - PR.AC -modification_date: '2018-05-21' -name: Detect Spike in Network ACL Activity -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/badrabbit_schtasks.yml b/detections/badrabbit_schtasks.yml deleted file mode 100644 index 84fa769397..0000000000 --- a/detections/badrabbit_schtasks.yml +++ /dev/null @@ -1,111 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-11-03' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for flags passed to schtasks.exe on the command-line - that indicate that task names related to the execution of Bad Rabbit ransomware - were created or deleted. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: This search looks for flags passed to schtasks.exe on the - command-line that indicate that task names specific to Bad Rabbit ransomware - has been created or deleted - rule_title: Scheduled tasks used in BadRabbit ransomware detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Processes.process) as process from datamodel=Endpoint.Processes - where Processes.process_name=schtasks.exe (Processes.process= "*create*" OR - Processes.process= "*delete*") by Processes.parent_process Processes.process_name - Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` - | search (process=*rhaegal* OR process=*drogon* OR *viserion_*)' - suppress: - suppress_fields: dest, process_name - suppress_period: 28800s -eli5: The search looks for execution of schtasks.exe with parameters that indicate - that specific task names related to the Bad Rabbit ransomware were created or deleted. - The specific task name used are rhaegal, drogon and viserion_. Schtasks.exe is a - native windows program that is used to schedule tasks on local or remote systems. - Attackers often leverage this capability to schedule the execution of commands or - establish persistence. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: 1297fb80-f42a-4b4a-9c8b-78c066437cf6 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: No known false positives -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Lateral Movement - - Execution - - Scheduled Task - nist: - - PR.IP -modification_date: '2019-02-28' -name: Scheduled tasks used in BadRabbit ransomware -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/batch_file_write_system32.yml b/detections/batch_file_write_system32.yml deleted file mode 100644 index 0c26711c0e..0000000000 --- a/detections/batch_file_write_system32.yml +++ /dev/null @@ -1,105 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-12-14' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: The search looks for a batch file (.bat) written to the Windows system - directory tree. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A batch file was written to the system directory on $dest$. - rule_title: Batch file write to system32 detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name - values(Filesystem.user) as user from datamodel=Endpoint.Filesystem by Filesystem.file_path - | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| - rex field=file_name "(?\.[^\.]+)$" | search file_path=*system32* - AND file_extension=.bat' - suppress: - suppress_fields: dest,file_name - suppress_period: 14400s -eli5: This search looks at file modifications across your hosts, as well as for evidence - of batch files being written to paths that include "system32." This activity is - consistent with some SamSam attacks and is, in general, suspicious. -entities: - - dest -how_to_implement: You must be ingesting data that records the file-system activity - from your hosts to populate the Endpoint file-system data-model node. If you are - using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which - you want to collect data. -id: 503d17cb-9eab-4cf8-a20e-01d5c6987ae3 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc - name: Investigate Successful Remote Desktop Authentications - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk -known_false_positives: It is possible for this search to generate a notable event - for a batch file write to a path that includes the string "system32", but is not - the actual Windows system directory. As such, you should confirm the path of the - batch file identified by the search. In addition, a false positive may be generated - by an administrator copying a legitimate batch file in this directory tree. You - should confirm that the activity is legitimate and modify the search to add exclusions, - as necessary. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Delivery - mitre_attack: [] - nist: - - PR.PT - - DE.CM -modification_date: '2018-12-14' -name: Batch File Write to System32 -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/batch_file_write_to_system32.yml b/detections/batch_file_write_to_system32.yml new file mode 100644 index 0000000000..cc0a678697 --- /dev/null +++ b/detections/batch_file_write_to_system32.yml @@ -0,0 +1,36 @@ +name: Batch File Write to System32 +id: 503d17cb-9eab-4cf8-a20e-01d5c6987ae3 +version: '1.0' +date: '2018-12-14' +description: The search looks for a batch file (.bat) written to the Windows system + directory tree. +how_to_implement: You must be ingesting data that records the file-system activity + from your hosts to populate the Endpoint file-system data-model node. If you are + using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which + you want to collect data. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name + values(Filesystem.user) as user from datamodel=Endpoint.Filesystem by Filesystem.file_path + | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| + rex field=file_name "(?\.[^\.]+)$" | search file_path=*system32* + AND file_extension=.bat' +known_false_positives: It is possible for this search to generate a notable event + for a batch file write to a path that includes the string "system32", but is not + the actual Windows system directory. As such, you should confirm the path of the + batch file identified by the search. In addition, a false positive may be generated + by an administrator copying a legitimate batch file in this directory tree. You + should confirm that the activity is legitimate and modify the search to add exclusions, + as necessary. +tags: + analytics_story: + - SamSam Ransomware + kill_chain_phases: + - Delivery + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/brand_abuse_dns.yml b/detections/brand_abuse_dns.yml deleted file mode 100644 index 5fdebb30ba..0000000000 --- a/detections/brand_abuse_dns.yml +++ /dev/null @@ -1,98 +0,0 @@ -asset_type: Endpoint -baselines: - - id: 19f7d2ec-6028-4d01-bcdb-bda9a034c17f - name: DNSTwist Domain Names - type: splunk -confidence: high -creation_date: '2017-06-01' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: This search looks for DNS requests for faux domains similar to the domains - that you want to have monitored for abuse. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, query - rule_description: The host $src$ issued a DNS request for a domain to that - which you are monitoring for brand abuse. - rule_title: DNS Query Brand Abuse from $src$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(DNS.answer) as IPs min(_time) as firstTime - from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` - | `security_content_ctime(firstTime)`| `brand_abuse_dns`' - suppress: - suppress_fields: src,query - suppress_period: 14400s -eli5: This search gathers all the answers to each system's DNS query, then filters - out all queries that do not appear on the list of faux "look-a-like" domains that - have been generated from the brand abuse domains you are monitoring. -entities: - - src -how_to_implement: You need to ingest data from your DNS logs. Specifically you must - ingest the domain that is being queried and the IP of the host originating the request. - Ideally, you should also be ingesting the answer to the query and the query type. - This approach allows you to also create your own localized passive DNS capability - which can aid you in future investigations. You also need to have run the search - "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that - will be checked for. -id: 24dd17b1-e2fb-4c31-878c-d4f746595bfa -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: None at this time -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - kill_chain_phases: - - Delivery - - Actions on Objectives -modification_date: '2017-09-23' -name: Monitor DNS For Brand Abuse -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/brand_abuse_email.yml b/detections/brand_abuse_email.yml deleted file mode 100644 index 2471d880ac..0000000000 --- a/detections/brand_abuse_email.yml +++ /dev/null @@ -1,106 +0,0 @@ -asset_type: Endpoint -baselines: - - id: 19f7d2ec-6028-4d01-bcdb-bda9a034c17f - name: DNSTwist Domain Names - type: splunk -confidence: high -creation_date: '2017-06-01' -data_metadata: - data_models: - - Email - data_source: - - Email - providing_technologies: - - Microsoft Exchange - - Bro - - Splunk Stream -description: This search looks for emails claiming to be sent from a domain similar - to one that you want to have monitored for abuse. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_user, message_id - rule_description: The sender $src_user$ has sent an email from a similar domain - to that which you are monitoring for brand abuse. - rule_title: Possible Brand Abuse from $src_user$ - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(All_Email.recipient) as recipients, - min(_time) as firstTime, max(_time) as lastTime from datamodel=Email by All_Email.src_user, - All_Email.message_id | `drop_dm_object_name("All_Email")` | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | eval temp=split(src_user, "@") | eval email_domain=mvindex(temp, - 1) | lookup update=true brandMonitoring_lookup domain as email_domain OUTPUT - domain_abuse | search domain_abuse=true | table message_id, src_user, email_domain, - recipients, firstTime, lastTime' - suppress: - suppress_fields: message_id, src_user - suppress_period: 86400s -eli5: This search looks at the sender address in email headers, and identifies those - with a sender address using a domain name that matches the list of permutations - generated for the domain you want to monitor. -entities: - - src_user -how_to_implement: You need to ingest email header data. Specifically the sender's - address (src_user) must be populated. You also need to have run the search "ESCU - - DNSTwist Domain Names", which creates the permutations of the domain that will - be checked for. -id: b2ea1f38-3a3e-4b8a-9cf1-82760d86a6b8 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd75 - name: Get Email Info - type: splunk - - id: 5df39b3f-447d-4869-b673-8f45ad4616fe - name: Get Emails From Specific Sender - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: None at this time -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 7 - kill_chain_phases: - - Delivery - nist: - - PR.IP -modification_date: '2018-01-05' -name: Monitor Email For Brand Abuse -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/brand_abuse_web.yml b/detections/brand_abuse_web.yml deleted file mode 100644 index cdc5a02cd2..0000000000 --- a/detections/brand_abuse_web.yml +++ /dev/null @@ -1,97 +0,0 @@ -asset_type: Endpoint -baselines: - - id: 19f7d2ec-6028-4d01-bcdb-bda9a034c17f - name: DNSTwist Domain Names - type: splunk -confidence: high -creation_date: '2017-06-01' -data_metadata: - data_models: - - Web - data_source: - - Web Traffic - providing_technologies: - - Splunk Stream - - Bro - - Bluecoat - - Palo Alto Firewall -description: This search looks for Web requests to faux domains similar to the one - that you want to have monitored for abuse. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, url - rule_description: The host $src$ connected to a web site with a domain similar - to that which you are monitoring for brand abuse. - rule_title: Web URL Brand Abuse from $src$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Web.url) as urls min(_time) as firstTime - from datamodel=Web by Web.src | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` - | `brand_abuse_web`' - suppress: - suppress_fields: src - suppress_period: 86400s -eli5: This search looks at all the URLs an endpoint is connecting to and then checks - the URL against a list of faux domains that could be indicative of brand abuse. -entities: - - src -how_to_implement: You need to ingest data from your web traffic. This can be accomplished - by indexing data from a web proxy, or using a network traffic analysis tool, such - as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain - Names", which creates the permutations of the domain that will be checked for. -id: 134da869-e264-4a8f-8d7e-fcd0ec88f301 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: None at this time -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 7 - kill_chain_phases: - - Delivery - mitre_attack: [] - nist: - - PR.IP -modification_date: '2017-09-23' -name: Monitor Web Traffic For Brand Abuse -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/change_file_association.yml b/detections/change_file_association.yml deleted file mode 100644 index 79c4e289d8..0000000000 --- a/detections/change_file_association.yml +++ /dev/null @@ -1,121 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-01-26' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for changes to registry values that control Windows - file associations, executed by a process that is not typical for legitimate, routine - changes to this area. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name, process - rule_description: The system $dest$ had an unusual change to a file association - rule_title: Suspicious File Association Change on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - macros: - - change_file_association_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) - as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name!=Explorer.exe - AND Processes.process_name!=OpenWith.exe by Processes.process_id Processes.dest - | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path - count FROM datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* - by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | - table process_id dest registry_path]| `change_file_association_filter`' - suppress: - suppress_fields: dest,user - suppress_period: 28800s -eli5: This search looks for changes made to the registry that control Windows file - associations. It is typical for users to change the file association to open certain - types of files with specific applications. However, when these changes are legitimately - performed, they are typically done via the processes explorer.exe or openwith.exe. - The search first executes the subsearch that looks at the Registry node, which specifies - setting a value in the registry and creates a table of process_id and dest. It then - uses those arguments to find out what process and parent process were responsible - for making those registry changes. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting information - on registry changes that include the name of the process responsible for the changes - from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` - nodes. -id: 1b989a0e-0129-4446-a695-f193a5b746fc -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: There may be other processes in your environment that users - may legitimately use to modify file associations. If this is the case and you are - finding false positives, you can modify the search to add those processes as exceptions. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Change Default File Association - nist: - - DE.CM - - PR.PT - - PR.IP -modification_date: '2020-03-16' -name: Suspicious Changes to File Associations -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/child_processes_of_spoolsv_exe.yml b/detections/child_processes_of_spoolsv_exe.yml new file mode 100644 index 0000000000..eb6e971288 --- /dev/null +++ b/detections/child_processes_of_spoolsv_exe.yml @@ -0,0 +1,39 @@ +name: Child Processes of Spoolsv.exe +id: aa0c4aeb-5b18-41c4-8c07-f1442d7599df +version: '3.0' +date: '2020-03-16' +description: This search looks for child processes of spoolsv.exe. This activity is + associated with a POC privilege-escalation exploit associated with CVE-2018-8440. + Spoolsv.exe is the process associated with the Print Spooler service in Windows + and typically runs as SYSTEM. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro + to filter out legitimate child processes spawned by spoolsv.exe. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process_name) + as process_name values(Processes.process) as process min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe + AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process + Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `children_of_spoolsv_filter`' +known_false_positives: Some legitimate printer-related processes may show up as children + of spoolsv.exe. You should confirm that any activity as legitimate and may be added + as exclusions in the search. +tags: + analytics_story: + - Windows Privilege Escalation + mitre_attack_id: + - T1068 + kill_chain_phases: + - Exploitation + cis20: + - CIS 5 + - CIS 8 + nist: + - PR.AC + - PR.PT + - DE.CM diff --git a/detections/children_of_spoolsv.yml b/detections/children_of_spoolsv.yml deleted file mode 100644 index 71eaef8c88..0000000000 --- a/detections/children_of_spoolsv.yml +++ /dev/null @@ -1,112 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-11-26' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for child processes of spoolsv.exe. This activity is - associated with a POC privilege-escalation exploit associated with CVE-2018-8440. - Spoolsv.exe is the process associated with the Print Spooler service in Windows - and typically runs as SYSTEM. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process_name, parent_process_name - rule_description: A child process of spoolsv.exe was detected on $dest$. - rule_title: Spoolsv.exe spawned a child process on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - macros: - - children_of_spoolsv_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process_name) as process_name - values(Processes.process) as process min(_time) as firstTime max(_time) as - lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe - AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process - Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `children_of_spoolsv_filter`' - suppress: - suppress_fields: dest, parent_process_name - suppress_period: 86400s -eli5: This search looks for child processes of spoolsv.exe, which is associated with - the Print Spooler service on Windows. Children of this process typically run under - the SYSTEM context. This search should address the POC developed for the Windows - local-privilege-escalation exploit announced in September of 2018. The associated - vulnerability was assigned CVE-2018-8440. More information is available at https://doublepulsar.com/task-scheduler-alpc-exploit-high-level-analysis-ff08cda6ad4f. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. -id: aa0c4aeb-5b18-41c4-8c07-f1442d7599df -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Some legitimate printer-related processes may show up as children - of spoolsv.exe. You should confirm that any activity as legitimate and may be added - as exclusions in the search. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 5 - - CIS 8 - kill_chain_phases: - - Exploitation - mitre_attack: - - Privilege Escalation - - Exploitation for Privilege Escalation - nist: - - PR.AC - - PR.PT - - DE.CM -modification_date: '2020-03-16' -name: Child Processes of Spoolsv.exe -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/clients_connecting_to_multiple_dns_servers.yml b/detections/clients_connecting_to_multiple_dns_servers.yml index bdcaaf78af..d22499bfee 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.yml +++ b/detections/clients_connecting_to_multiple_dns_servers.yml @@ -1,51 +1,9 @@ -asset_type: Endpoint -baselines: [] -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro +name: Clients Connecting to Multiple DNS Servers +id: 74ec6f18-604b-4202-a567-86b2066be3ce +version: '2.0' +date: '2020-01-16' description: This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. -detect: - splunk: - correlation_rule: - macros: - - clients_connecting_to_multiple_dns_servers_output_filter - notable: - nes_fields: src, dest - rule_description: This search allows you to identify the endpoints that have - connected to more than five DNS servers over the time frame specified in - the search. - rule_title: Client $src$ Connecting to Multiple DNS Servers - risk: - risk_object: src - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) - as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY - by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count - > 5 | `clients_connecting_to_multiple_dns_servers_output_filter`' - suppress: - suppress_fields: src - suppress_period: 86400s -eli5: DNS Queries with multiple DNS servers from a single client is unusual and may - be indicative of malicious activity. This search works by performing a count by - the source of the distinct destinations for the DNS traffic. The search uses the - `Network_Resolution` data model. -entities: - - dest - - src how_to_implement: 'This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ @@ -59,40 +17,29 @@ how_to_implement: 'This search requires that DNS data is being ingested and popu Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: 74ec6f18-604b-4202-a567-86b2066be3ce -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk +type: ESCU +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count, values(DNS.dest) AS dest + dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY + by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count > 5 | + `clients_connecting_to_multiple_dns_servers_output_filter`' known_false_positives: It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: - cis20: - - CIS 9 - - CIS 12 - - CIS 13 +tags: + analytics_story: + - Host Redirection + - Suspicious DNS Traffic + - Command and Control + - DNS Hijacking + mitre_attack_id: + - T1048 kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Exfiltration - - Exfiltration Over Alternative Protocol + - Command and Control + cis20: + - CIS 9 + - CIS 12 + - CIS 13 nist: - - PR.PT - - DE.AE - - PR.DS -modification_date: '2020-01-16' -name: Clients Connecting to Multiple DNS Servers -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' + - PR.PT + - DE.AE + - PR.DS diff --git a/detections/cloud_compute_activity_in_new_region.yml b/detections/cloud_compute_activity_in_new_region.yml deleted file mode 100644 index 39fc24bfa2..0000000000 --- a/detections/cloud_compute_activity_in_new_region.yml +++ /dev/null @@ -1,107 +0,0 @@ -asset_type: Cloud Compute Instance -baselines: - - id: b5e232db-dec6-4db8-aaa1-dd5474521e40 - name: Previously Seen Cloud Regions - type: splunk -confidence: medium -creation_date: '2019-10-02' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: This search looks at cloud-infrastructure events where an instance is - created in any region within the last hour and then compares it to a lookup file - of previously seen regions where instances have been created. -detect: - splunk: - correlation_rule: - lookups: - - previously_seen_cloud_regions - macros: - - previously_seen_cloud_regions_input_filter - - previously_seen_cloud_regions_search_window_begin_offset - notable: - drilldown_name: See all activity in $region$ - drilldown_search: '| from datamodel:Cloud_Infrastructure.Compute | search region="$region$"' - nes_fields: dest,region - rule_description: A cloud compute instance, $dest$, is started in a new, previously - unseen, region $region$ - rule_title: Cloud instance $dest$ started in a new region $region$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) - as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances - `previously_seen_cloud_regions_input_filter` by Compute.region, Compute.src_user - | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions - | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) - as dest by region, src_user | multireport [| table region, firstTime, lastTime - | outputlookup previously_seen_cloud_regions | where fact=fiction][| eval - new_region=if(firstTime >= relative_time(now(), `previously_seen_cloud_regions_search_window_begin_offset`), 1, 0) - | where new_region=1 - | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table region, dest, src_user, - firstTime, lastTime' - suppress: - suppress_fields: dest,region - suppress_period: 14400s -eli5: In this search, we query cloud infrastructure compute logs to look for events - that indicate that an instance was started in a particular region. Using the \"previously_seen_cloud_regions\" - lookup file created using the support search, we compare the region where this instance - was started to all previously observed regions. The \"eval\" and \"if\" functions determine - that the earliest times seen for this region and instance were within the last day. - If a new region is detected, it will alert you with \"Instance Started in a New Region.\" - However, this region will be added to the list in \"previously_seen_cloud_regions.\" -entities: - - dest - - region - - src_user -how_to_implement: You must be ingesting the appropriate cloud-infrastructure logs - and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) - installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously - seen regions. -id: fa4089e2-50e3-40f7-8469-d2cc1564ca59 -investigations: - - id: 3dc3a8e7-394b-44ae-8262-4ef8e90b723d - name: Investigate User Activities In Single Cloud Region - type: splunk - - id: 33a95cf2-900c-4636-8fca-5c5f71474720 - name: Investigate Cloud Compute Instance Activities - type: splunk -known_false_positives: It's possible that a user has unknowingly started an instance - in a new region. Please verify that this activity is legitimate. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 12 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - nist: - - DE.DP - - DE.AE -modification_date: '2019-10-02' -name: Cloud Compute Instance Started In Previously Unused Region -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml index 4b6d0a0ffb..d41510dc16 100644 --- a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml +++ b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml @@ -1,97 +1,32 @@ -asset_type: Cloud Compute Instance -baselines: - - id: 9fa1c205-4e08-4681-bb1b-d0943e734b85 - name: Previously Seen Cloud Compute Creations By User - type: splunk -confidence: medium -creation_date: '2019-10-03' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: This search looks for cloud compute instances created by users - who have not created them before. -detect: - splunk: - correlation_rule: - lookups: - - previously_seen_cloud_compute_creations_by_user - macros: - - previously_seen_cloud_compute_creations_by_user_input_filter - - previously_seen_cloud_compute_creations_by_user_search_window_begin_offset - notable: - drilldown_name: Show all instances created by $src_user$ - drilldown_search: '| from datamodel:Cloud_Infrastructure.Compute | action=run src_user=$src_user$' - nes_fields: src_user, dest - rule_description: The compute instance $dest$ was created by $src_user$. This - is the first time $src_user$ has created a compute instance. - rule_title: Cloud Compute Instance Created By Previously Unseen User $src_user$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) - as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run by - Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t - previously_seen_cloud_compute_creations_by_user | stats min(firstTime) as - firstTime max(lastTime) as lastTime, values(dest) as dest by src_user | multireport - [| table src_user, firstTime, lastTime | outputlookup previously_seen_cloud_compute_creations_by_user - | where fact=fiction][| eval new_user=if(firstTime >= relative_time(now(), - `previously_seen_cloud_compute_creations_by_user_search_window_begin_offset`), 1, 0) - | where new_user=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] - | table src_user, dest, firstTime, lastTime' - suppress: - suppress_fields: src_user, dest - suppress_period: 14400s -eli5: For each user, the search returns the first time seen, last time seen, and the systems. It then appends the historical data and merges it into the data. The - search then splits and outputs the updated times for each user back to the lookup - file and then clears out any output. The other part of the search limits the results - to when the user was seen for the first time within the previous 70 minutes. - It then displays the new user, the instances created by that user, and the associated times. -entities: - - dest - - src_user +name: Cloud Compute Instance Created By Previously Unseen User +id: 76988f6a-3935-48f6-a9e5-6fca8b3ed843 +version: '1.0' +date: '2018-03-12' +description: This search looks for cloud compute instances created by users who have + not created them before. how_to_implement: You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) - installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of - baseline of previously seen users. -id: 76988f6a-3935-48f6-a9e5-6fca8b3ed843 -investigations: - - id: 2ef6310f-8e79-42af-b20b-b4eeaba9608a - name: Investigate User Activities In All Cloud Regions - type: splunk - - id: 33a95cf2-900c-4636-8fca-5c5f71474720 - name: Investigate Cloud Compute Instance Activities - type: splunk -known_false_positives: It's possible that a user will start to create compute instances - for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 1 - nist: - - ID.AM -modification_date: '2018-03-12' -name: Cloud Compute Instance Created By Previously Unseen User -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey + installed. Run the "Previously Seen Cloud Compute Creations By User" support search + to create of baseline of previously seen users. +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` earliest(_time) as firstTime, latest(_time) + as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute + where Compute.action=run by Compute.src_user | `drop_dm_object_name("Compute")` + | inputlookup append=t previously_seen_cloud_compute_creations_by_user | stats + min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by src_user + | multireport [| table src_user, firstTime, lastTime | outputlookup previously_seen_cloud_compute_creations_by_user + | where fact=fiction][| eval new_user=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_creations_by_user_search_window_begin_offset`), + 1, 0) | where new_user=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] + | table src_user, dest, firstTime, lastTime' +known_false_positives: It's possible that a user will start to create compute instances + for the first time, for any number of reasons. Verify with the user launching instances + that this is the intended behavior. +tags: + analytics_story: + - Cloud Cryptomining + cis20: + - CIS 1 + nist: + - ID.AM diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml new file mode 100644 index 0000000000..301b5865e2 --- /dev/null +++ b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml @@ -0,0 +1,32 @@ +name: Cloud Compute Instance Created With Previously Unseen Image +id: bc24922d-987c-4645-b288-f8c73ec194c4 +version: '1.0' +date: '2018-10-12' +description: This search looks for cloud compute instances being created with previously + unseen image IDs. +how_to_implement: You must be ingesting the appropriate cloud-infrastructure logs + and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) + installed. Run the "Previously Seen Cloud Compute Images" support search to create + a baseline of previously seen images. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) + as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` + by Compute.image_id, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup + append=t previously_seen_cloud_compute_images | stats min(firstTime) as firstTime + max(lastTime) as lastTime, values(dest) as dest by image_id, src_user | multireport + [| table image_id, firstTime, lastTime | outputlookup previously_seen_cloud_compute_images + | where fact=fiction][| eval new_image=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_image_search_window_begin_offset`), + 1, 0) | where new_image=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] + | table image_id, dest, src_user, firstTime, lastTime' +known_false_positives: After a new image is created, the first systems created with + that image will cause this alert to fire. Verify that the image being used was + created by a legitimate user. +tags: + analytics_story: + - Cloud Cryptomining + cis20: + - CIS 1 + nist: + - ID.AM diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_image_id.yml b/detections/cloud_compute_instance_created_with_previously_unseen_image_id.yml deleted file mode 100644 index c6741eaaff..0000000000 --- a/detections/cloud_compute_instance_created_with_previously_unseen_image_id.yml +++ /dev/null @@ -1,96 +0,0 @@ -asset_type: Cloud Compute Instance -baselines: - - id: 3782ad10-5ce2-46e2-b9c4-1de9ecd3aecc - name: Previously Seen Cloud Compute Images - type: splunk -confidence: medium -creation_date: '2019-10-03' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: This search looks for cloud compute instances being created with previously - unseen image IDs. -detect: - splunk: - correlation_rule: - lookups: - - previously_seen_cloud_compute_images - macros: - - previously_seen_cloud_compute_image_input_filter - - previously_seen_cloud_compute_image_search_window_begin_offset - notable: - drilldown_name: Show all instances created with image $image_id$ - drilldown_search: '| from datamodel:Cloud_Infrastructure.Compute | image_id=$image_id$' - nes_fields: dest - rule_description: The cloud compute instance $dest$ was created with previously - unused image $image_id$. - rule_title: Cloud Compute Instances Created With New Image - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) - as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` - by Compute.image_id, Compute.src_user | `drop_dm_object_name("Compute")` | - inputlookup append=t previously_seen_cloud_compute_images | stats min(firstTime) - as firstTime max(lastTime) as lastTime, values(dest) as dest by image_id, - src_user | multireport [| table image_id, firstTime, lastTime | outputlookup - previously_seen_cloud_compute_images | where fact=fiction][| eval new_image=if(firstTime - >= relative_time(now(), `previously_seen_cloud_compute_image_search_window_begin_offset`), 1, 0) | where new_image=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table image_id, dest, src_user, firstTime, lastTime' - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: For each image ID and user, the search returns the first time seen, last time seen, and the systems. It then appends the historical data and merges it into the - data. The search then splits and outputs the updated times for each image back to - the lookup file and clears out any output. The other part of the search limits - the results to when the image was seen for the first time within the previous 70 minutes. It then displays the new image, the instances created using it, the - user who created it, and the associated times. -entities: - - dest - - src_user -how_to_implement: You must be ingesting the appropriate cloud-infrastructure logs - and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) - installed. Run the "Previously Seen Cloud Compute Images" support search to create - a baseline of previously seen images. -id: bc24922d-987c-4645-b288-f8c73ec194c4 -investigations: - - id: 2ef6310f-8e79-42af-b20b-b4eeaba9608a - name: Investigate User Activities In All Cloud Regions - type: splunk - - id: 33a95cf2-900c-4636-8fca-5c5f71474720 - name: Investigate Cloud Compute Instance Activities - type: splunk -known_false_positives: After a new image is created, the first systems created with - that image will cause this alert to fire. Verify that the image being used was - created by a legitimate user. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 1 - nist: - - ID.AM -modification_date: '2018-10-12' -name: Cloud Compute Instance Created With Previously Unseen Image -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml index 2685bfc54b..b18f021d14 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml @@ -1,100 +1,32 @@ -asset_type: Cloud Compute Instance -baselines: - - id: 0ef13d46-164e-4cf5-816e-b3c0df170d00 - name: Previously Seen Cloud Compute Instance Types - type: splunk -confidence: medium -creation_date: '2019-10-03' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: Find EC2 instances being created with previously unseen - instance types. -detect: - splunk: - correlation_rule: - lookups: - - previously_seen_cloud_compute_instance_types - macros: - - previously_seen_cloud_compute_instance_types_input_filter - - previously_seen_cloud_compute_instance_types_search_window_begin_offset - notable: - drilldown_name: Find all compute instances of type $instance_type$ - drilldown_search: '| from datamodel:Cloud_Infrastructure.Compute | instance_type=$instance_type$' - nes_fields: instance_type - rule_description: The instance type $instance_type$ was used for the first - time to create $dest$. - rule_title: New Cloud Compute Instance Type $instance_type$ detected - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) - as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances - `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type, - Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t - previously_seen_cloud_compute_instance_types | stats min(firstTime) as firstTime - max(lastTime) as lastTime, values(dest) as dest by instance_type, src_user - | multireport [| table instance_type, firstTime, lastTime | outputlookup previously_seen_cloud_compute_instance_types - | where fact=fiction][| eval new_type=if(firstTime >= relative_time(now(), - `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), 1, 0) - | where new_type=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] - | table instance_type, dest, src_user, firstTime, lastTime' - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: For each instance type and user, the search returns the first time seen, last time seen, and the system. It then appends the historical data and merges it into - the data. The search then splits and outputs the updated times for each instance - type back to the lookup file and clears out any output. The other part of the - search limits the results to when the instance type was seen for the first time - within the previous 70 minutes. It then displays the new instance type, the - instances created using it, the user who created them, and the times associated. -entities: - - dest - - src_user +name: Cloud Compute Instance Created With Previously Unseen Instance Type +id: c6ddbf53-9715-49f3-bb4c-fb2e8a309cda +version: '1.0' +date: '2018-03-12' +description: Find EC2 instances being created with previously unseen instance types. how_to_implement: You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. -id: c6ddbf53-9715-49f3-bb4c-fb2e8a309cda -investigations: - - id: 2ef6310f-8e79-42af-b20b-b4eeaba9608a - name: Investigate User Activities In All Cloud Regions - type: splunk - - id: 33a95cf2-900c-4636-8fca-5c5f71474720 - name: Investigate Cloud Compute Instance Activities - type: splunk -known_false_positives: It is possible that an admin will create a new system using - a new instance type that has never been used before. Verify with the creator that they intended - to create the system with the new instance type. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 1 - nist: - - ID.AM -modification_date: '2018-03-12' -name: Cloud Compute Instance Created With Previously Unseen Instance Type -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) + as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances + `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type, + Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_instance_types + | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest + by instance_type, src_user | multireport [| table instance_type, firstTime, lastTime + | outputlookup previously_seen_cloud_compute_instance_types | where fact=fiction][| + eval new_type=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), + 1, 0) | where new_type=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] + | table instance_type, dest, src_user, firstTime, lastTime' +known_false_positives: It is possible that an admin will create a new system using + a new instance type that has never been used before. Verify with the creator that + they intended to create the system with the new instance type. +tags: + analytics_story: + - Cloud Cryptomining + cis20: + - CIS 1 + nist: + - ID.AM diff --git a/detections/cloud_compute_instance_started_in_previously_unused_region.yml b/detections/cloud_compute_instance_started_in_previously_unused_region.yml new file mode 100644 index 0000000000..d281a81ce9 --- /dev/null +++ b/detections/cloud_compute_instance_started_in_previously_unused_region.yml @@ -0,0 +1,36 @@ +name: Cloud Compute Instance Started In Previously Unused Region +id: fa4089e2-50e3-40f7-8469-d2cc1564ca59 +version: '1.0' +date: '2019-10-02' +description: This search looks at cloud-infrastructure events where an instance is + created in any region within the last hour and then compares it to a lookup file + of previously seen regions where instances have been created. +how_to_implement: You must be ingesting the appropriate cloud-infrastructure logs + and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) + installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search + to create a baseline of previously seen regions. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) + as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances + `previously_seen_cloud_regions_input_filter` by Compute.region, Compute.src_user + | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions + | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest + by region, src_user | multireport [| table region, firstTime, lastTime | outputlookup + previously_seen_cloud_regions | where fact=fiction][| eval new_region=if(firstTime + >= relative_time(now(), `previously_seen_cloud_regions_search_window_begin_offset`), + 1, 0) | where new_region=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] + | table region, dest, src_user, firstTime, lastTime' +known_false_positives: It's possible that a user has unknowingly started an instance + in a new region. Please verify that this activity is legitimate. +tags: + analytics_story: + - Cloud Cryptomining + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 12 + nist: + - DE.DP + - DE.AE diff --git a/detections/common_ransomware_extensions.yml b/detections/common_ransomware_extensions.yml index f276171835..5076023967 100644 --- a/detections/common_ransomware_extensions.yml +++ b/detections/common_ransomware_extensions.yml @@ -1,49 +1,9 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-08-21' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon +name: Common Ransomware Extensions +id: a9e5c5db-db11-43ca-86a8-c852d1b2c0ec +version: '3.0' +date: '2020-03-16' description: The search looks for file modifications with extensions commonly used by Ransomware -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A file modification was detected on $dest$ with an extension - commonly used by ransomware. - rule_title: Ransomware Extension detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - macros: - - common_ransomware_extensions_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) - as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | - `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| - rex field=file_name "(?\.[^\.]+)$" | `ransomware_extensions` | `common_ransomware_extensions_filter`' - suppress: - suppress_fields: dest,file_name - suppress_period: 14400s -eli5: This search looks at file modifications across your hosts and identifies files - with extensions that are commonly associated with the encrypted files generated - by ransomware. -entities: - - dest how_to_implement: 'You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which @@ -62,62 +22,25 @@ how_to_implement: 'You must be ingesting data that records the filesystem activi Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: a9e5c5db-db11-43ca-86a8-c852d1b2c0ec -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: d98675ed-da43-4a7e-96a7-eeca3232ba8e - name: Get Update Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d44 - name: Get Backup Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) + as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex + field=file_name "(?\.[^\.]+)$" | `ransomware_extensions` | `common_ransomware_extensions_filter`' known_false_positives: It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 +tags: + analytics_story: + - SamSam Ransomware + - Ransomware kill_chain_phases: - - Actions on Objectives - mitre_attack: [] + - Actions on Objectives + cis20: + - CIS 8 nist: - - PR.PT - - DE.CM -modification_date: '2020-03-16' -name: Common Ransomware Extensions -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' + - PR.PT + - DE.CM diff --git a/detections/common_ransomware_notes.yml b/detections/common_ransomware_notes.yml index 6f21591ee3..1c6c412e1b 100644 --- a/detections/common_ransomware_notes.yml +++ b/detections/common_ransomware_notes.yml @@ -1,111 +1,32 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-08-21' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon +name: Common Ransomware Notes +id: ada0f478-84a8-4641-a3f1-d82362d6bd71 +version: '3.0' +date: '2020-03-16' description: The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A file modification associated with a ransomware victim - notification file detected on $dest$ - rule_title: Ransomware Note File detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - macros: - - common_ransomware_notes_filter - - ransomware_notes - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) - as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | - `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`|`ransomware_notes`| `common_ransomware_notes_filter`' - suppress: - suppress_fields: dest,file_name - suppress_period: 14400s -eli5: This search looks at file modifications in the Change Analysis data model. It - checks modified file names against an included lookup file, which contains the names - of note files left behind by ransomware (to inform the victim how they can pay the - ransom and retrieve their files). The search returns a list of files with matching - names. -entities: - - dest how_to_implement: You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -id: ada0f478-84a8-4641-a3f1-d82362d6bd71 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: d98675ed-da43-4a7e-96a7-eeca3232ba8e - name: Get Update Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d44 - name: Get Backup Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) + as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`|`ransomware_notes`| + `common_ransomware_notes_filter`' known_false_positives: It's possible that a legitimate file could be created with the same name used by ransomware note files. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 +tags: + analytics_story: + - SamSam Ransomware + - Ransomware kill_chain_phases: - - Actions on Objectives - mitre_attack: [] + - Actions on Objectives + cis20: + - CIS 8 nist: - - PR.PT - - DE.CM -modification_date: '2020-03-16' -name: Common Ransomware Notes -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' + - PR.PT + - DE.CM diff --git a/detections/container_implant_aws_detection.yml b/detections/container_implant_aws_detection.yml deleted file mode 100644 index d40a30cd62..0000000000 --- a/detections/container_implant_aws_detection.yml +++ /dev/null @@ -1,65 +0,0 @@ -asset_type: AWS ECR container -confidence: medium -creation_date: '2020-02-20' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - AWS Cloud Trail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This searches show information on uploaded containers including source user, image id, source IP - user type, http user agent, region, first time, last time of operation (PutImage). These searches - are based on Cloud Infrastructure Data Model. -detect: - splunk: - correlation_rule: - notable: - nes_fields: image_id, src_user, region, user_type - rule_description: A new container with image id $image_id$ uploaded to AWS ECR by user $src_user$ - rule_title: New container uploaded to AWS ECR - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 30 - macros: - - container_implant_aws_detection_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.http_user_agent="AWS Internal" AND Compute.event_name="PutImage" by Compute.image_id Compute.src_user Compute.src Compute.region Compute.msg Compute.user_type | `drop_dm_object_name("Compute")` | `container_implant_aws_detection_filter`' -eli5: In this search we can detect if a new container has been uploaded to Amazon Elastic Container Registry, operator can monitor users uploading containers, image ids of new uploaded containers. -entities: - - src_user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for - AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. -id: f0f70b40-f7ad-489d-9905-23d149da8099 -known_false_positives: Uploading container is a normal behavior from developers or users with access to container registry. -investigations: - - id: 6027623f-7d10-4847-af3b-8d7e87970451 - name: Investigate AWS ECR container listing activity - type: splunk -maintainers: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -mappings: - mitre_attack: - - Persistence - mitre_technique_id: - - T1525 -modification_date: '2020-02-20' -name: New container uploaded to AWS ECR -original_authors: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/container_implant_gcp_detection.yml b/detections/container_implant_gcp_detection.yml deleted file mode 100644 index 3e2a472cc8..0000000000 --- a/detections/container_implant_gcp_detection.yml +++ /dev/null @@ -1,57 +0,0 @@ -asset_type: GCP GCR Container -confidence: medium -creation_date: '2020-02-20' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - google:gcp:pubsub:messages - providing_technologies: - - GCP -description: This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_user, account, bucket_name, event_name - rule_description: An GCP GCR container uploaded by $src_user$ - rule_title: GCP GCR container uploaded - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 30 - macros: - - container_implant_gcp_detection_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '|tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Storage where Storage.event_name=storage.objects.create by Storage.src_user Storage.account Storage.action Storage.bucket_name Storage.event_name Storage.http_user_agent Storage.msg Storage.object_path | `drop_dm_object_name("Storage")` | `container_implant_gcp_detection_filter`' -eli5: In this search we can detect if a new container has been uploaded to Google Container Registry, - operator can monitor users uploading containers, object paths of new uploaded containers. -entities: - - src_user -how_to_implement: You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. -id: 4f00ca88-e766-4605-ac65-ae51c9fd185b -known_false_positives: Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. -maintainers: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -mappings: - mitre_attack: - - Persistence - mitre_technique_id: - - T1525 -modification_date: '2020-02-20' -name: GCP GCR container uploaded -original_authors: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/create_local_admin_accounts_using_net_exe.yml b/detections/create_local_admin_accounts_using_net_exe.yml new file mode 100644 index 0000000000..c3e38355d4 --- /dev/null +++ b/detections/create_local_admin_accounts_using_net_exe.yml @@ -0,0 +1,34 @@ +name: Create local admin accounts using net.exe +id: b89919ed-fe5f-492c-b139-151bb162040e +version: '3.0' +date: '2020-03-16' +description: This search looks for the creation of local administrator accounts using + net.exe. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.user) as + user values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe + OR Processes.process_name=net1.exe) by Processes.process Processes.process_name + Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* + OR process=*user*) |`create_local_admin_via_net_filter`' +known_false_positives: Administrators often leverage net.exe to create admin accounts. +tags: + analytics_story: + - DHS Report TA18-074A + mitre_attack_id: + - T1059 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/create_local_admin_via_net.yml b/detections/create_local_admin_via_net.yml deleted file mode 100644 index 6cc228236c..0000000000 --- a/detections/create_local_admin_via_net.yml +++ /dev/null @@ -1,111 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-03-28' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for the creation of local administrator accounts using - net.exe. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: Net.exe was used to create local administrator accounts - on $dest$. - rule_title: Local administrator account created on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - create_local_admin_via_net_filter - schedule: - cron_schedule: 0 8 * * * - earliest_time: -1440m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) - as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by - Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*localgroup* OR - process=*/add* OR process=*user*) |`create_local_admin_via_net_filter`' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: Net.exe is a built-in Windows command-line tool that can be used to add, display, - or modify user accounts. While Microsoft administrators use this tool to manage - user groups, threat actors often leverage it to create local admin accounts to maintain - persistence. In this search, we are looking for the execution of process net.exe - with command-line parameters such as `localgroup`, `add`, or `user` that may correspond - to the creation of local admin accounts or setting user/group properties. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: b89919ed-fe5f-492c-b139-151bb162040e -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Administrators often leverage net.exe to create admin accounts. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Command-Line Interface - - Persistence - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-16' -name: Create local admin accounts using net.exe -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/create_or_delete_network_shares.yml b/detections/create_or_delete_network_shares.yml deleted file mode 100644 index 9b80147b91..0000000000 --- a/detections/create_or_delete_network_shares.yml +++ /dev/null @@ -1,120 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-06-14' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for the creation or deletion of hidden shares using - net.exe. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest,process_name - rule_description: Net.exe was used to create or delete hidden network shares - by $user$ on $dest$ - rule_title: Hidden File shares created/deleted on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - create_or_delete_windows_shares_filter - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) - as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by - Processes.process Processes.process_name Processes.dest - | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) - | `create_or_delete_windows_shares_filter`' - suppress: - suppress_fields: dest,process_name - suppress_period: 86400s -eli5: In this search, we are looking for the command-line execution of net.exe with - command-line parameters such as `net`, `share`, or `delete` that may correspond to - the creation/deletion of windows drive shares. Net.exe is a built-in command-line tool - on Windows that can be used to create, delete, and manage shared resources on the computer, - both locally and remotely. Though this tool is used by Microsoft administrators to manage the network shares, - attackers also leverage it to create and delete (hidden) file shares by appending - "$" after the name of the share. Since the creation/deletion of hidden shares is a - special case of detecting share creation/deletion we have commented out - the regex that adds that additional matching criteria. If only hidden share detection is desired - add `| regex process="\S+[$]"` before the last pipe in the search. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: qw9919ed-fe5f-492c-b139-151bb162140e -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Administrators often leverage net.exe to create or delete network - shares. You should verify that the activity was intentional and is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Lateral Movement - mitre_technique_id: - - T1077 - - T1126 - nist: - - PR.PT - - DE.CM -modification_date: '2020-01-20' -name: Create or delete windows shares using net.exe -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: - - https://attack.mitre.org/techniques/T1077/ - - https://attack.mitre.org/techniques/T1126/ -security_domain: endpoint -spec_version: 2 -type: splunk -version: '4.0' diff --git a/detections/create_or_delete_windows_shares_using_net_exe.yml b/detections/create_or_delete_windows_shares_using_net_exe.yml new file mode 100644 index 0000000000..4b91efc020 --- /dev/null +++ b/detections/create_or_delete_windows_shares_using_net_exe.yml @@ -0,0 +1,35 @@ +name: Create or delete windows shares using net.exe +id: qw9919ed-fe5f-492c-b139-151bb162140e +version: '4.0' +date: '2020-01-20' +description: This search looks for the creation or deletion of hidden shares using + net.exe. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: +- https://attack.mitre.org/techniques/T1077/ +- https://attack.mitre.org/techniques/T1126/ +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.user) as + user values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe + OR Processes.process_name=net1.exe) by Processes.process Processes.process_name + Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) + | `create_or_delete_windows_shares_filter`' +known_false_positives: Administrators often leverage net.exe to create or delete network + shares. You should verify that the activity was intentional and is legitimate. +tags: + analytics_story: + - Hidden Cobra Malware + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/create_remote_thread_into_lsass.yml b/detections/create_remote_thread_into_lsass.yml index 91afff13fc..8ab642d9dc 100644 --- a/detections/create_remote_thread_into_lsass.yml +++ b/detections/create_remote_thread_into_lsass.yml @@ -1,86 +1,33 @@ -asset_type: Windows -confidence: high -creation_date: '2019-12-06' -data_metadata: - data_eventtypes: - - wineventlog_sysmon - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: Detect remote thread creation into LSASS consistent with credential dumping. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: Possible attempt at credential dumping was detected on $dest$. - rule_title: remote thread creation into LSASS on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - macros: - - sysmon - - create_remote_thread_into_lsass_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '`sysmon` EventID=8 TargetImage=*lsass.exe - | stats count min(_time) as firstTime max(_time) as lastTime by Computer, EventCode, TargetImage, TargetProcessId - | rename Computer as dest - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`create_remote_thread_into_lsass_filter`' - suppress: - suppress_fields: dest, TargetProcessId - suppress_period: 86400s -eli5: This search detects the creation of a remote thread into LSASS (Local Security Authority Subsystem Service). - This technique can be used by attackers to inject code into LSASS and dump the memory in order to obtain credentials. -entities: - - dest -how_to_implement: 'This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives.' -id: 67d4dbef-9564-4699-8da8-03a151529edc -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 8 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_technique_id: - - T1003 - mitre_attack: - - Credential Access - - Credential Dumping - nist: - - DE.CM -modification_date: '2019-12-06' name: Create Remote Thread into LSASS -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss +id: 67d4dbef-9564-4699-8da8-03a151529edc +version: '1' +date: '2019-12-06' +description: Detect remote thread creation into LSASS consistent with credential dumping. +how_to_implement: This search needs Sysmon Logs with a Sysmon configuration, which + includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. + We strongly recommend that you specify your environment-specific configurations + (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition + with configurations for your Splunk environment. The search also uses a post-filter + macro designed to filter out known false positives. +type: ESCU references: - - https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf -security_domain: endpoint -spec_version: 2 -type: splunk -version: "1" +- https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf +author: Patrick Bareiss, Splunk +search: '`sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as firstTime + max(_time) as lastTime by Computer, EventCode, TargetImage, TargetProcessId | rename + Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + |`create_remote_thread_into_lsass_filter`' +known_false_positives: Other tools can access LSASS for legitimate reasons and generate + an event. In these cases, tweaking the search may help eliminate noise. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + - CIS 16 + nist: + - DE.CM diff --git a/detections/creation_of_shadow_copy.yml b/detections/creation_of_shadow_copy.yml index f151457714..d0c082b6dc 100644 --- a/detections/creation_of_shadow_copy.yml +++ b/detections/creation_of_shadow_copy.yml @@ -1,91 +1,36 @@ -asset_type: Endpoint -confidence: high -creation_date: '2019-12-10' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Sysmon -description: Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest, process_name, process - rule_description: An attempt to create a shadow copy with Ntdsutil, Vssadmin, or Wmic was detected on $dest$. - rule_title: Attempted Credential Dump of ntds.dit from $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 60 - macros: - - creation_of_shadow_copy_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where (Processes.process_name=ntdsutil.exe Processes.process=*ntds* Processes.process=*create*) OR (Processes.process_name=vssadmin.exe Processes.process=*create* Processes.process=*shadow*) - OR (Processes.process_name=wmic.exe Processes.process=*shadowcopy* Processes.process=*create*) - by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `creation_of_shadow_copy_filter`' - suppress: - suppress_fields: process_name, dest - suppress_period: 86400s -eli5: The ntds.dit file contains the Active Directory (AD) database. This file can't be copied directly. - That's why attackers will first create a shadow copy before exfiltrating the file. This search detects the creation - of a shadow copy using Ntdsutil, Vssadmin, or Wmic. -entities: - - dest +name: Creation of Shadow Copy +id: eb120f5f-b879-4a63-97c1-93352b5df844 +version: '1.0' +date: '2019-12-10' +description: Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create + a shadow copy. how_to_implement: You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -id: eb120f5f-b879-4a63-97c1-93352b5df844 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 8 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 - nist: - - DE.CM -modification_date: '2019-12-10' -name: Creation of Shadow Copy -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss +type: ESCU references: - - https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' +- https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf +author: Patrick Bareiss, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=ntdsutil.exe + Processes.process=*ntds* Processes.process=*create*) OR (Processes.process_name=vssadmin.exe + Processes.process=*create* Processes.process=*shadow*) OR (Processes.process_name=wmic.exe + Processes.process=*shadowcopy* Processes.process=*create*) by Processes.dest Processes.user + Processes.process_name Processes.process Processes.parent_process Processes.process_id + Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | `creation_of_shadow_copy_filter`' +known_false_positives: Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic + will create false positives. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + - CIS 16 + nist: + - DE.CM diff --git a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml index 0608ed6938..f399159f3a 100644 --- a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml +++ b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml @@ -1,87 +1,33 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2019-12-10' -data_metadata: - data_eventtypes: - - powershell scriptblock logging - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search detects the use of wmic and Powershell to create a shadow copy. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest - rule_description: An attempt to create a shadow copy with wmic and Powershell was detected on $dest$. - rule_title: Attempted Credential Dump of ntds.dit on $dest$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - macros: - - sysmon - - creation_of_shadow_copy_with_wmic_and_powershell_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '`sysmon` Message=*win32_shadowcopy* Message=*Create* - | stats count min(_time) as firstTime max(_time) as lastTime by dvc User EventCode Message - | rename User as user, dvc as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `creation_of_shadow_copy_with_wmic_and_powershell_filter` ' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: The ntds.dit file contains the Active Directory (AD) database. This file can't be copied directly. - That's why attackers create a shadow copy before exfiltrating the file. This search detects the creation - of a shadow copy using wmic, which is executed by Powershell. -entities: - - dest -how_to_implement: You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -id: 2ed8b538-d284-449a-be1d-82ad1dbd186b -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: Legtimate administrator usage of wmic to create a shadow copy. -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 8 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 - nist: - - DE.CM -modification_date: '2019-12-10' name: Creation of Shadow Copy with wmic and powershell -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -references: - - https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf -security_domain: endpoint -spec_version: 2 -type: splunk +id: 2ed8b538-d284-449a-be1d-82ad1dbd186b version: '1.0' +date: '2019-12-10' +description: This search detects the use of wmic and Powershell to create a shadow + copy. +how_to_implement: You must enable Powershell scriptblock logging in order to detect + this attack.This search uses an input macro named `sysmon`. We strongly recommend + that you specify your environment-specific configurations (index, source, sourcetype, + etc.) for Windows Sysmon logs. Replace the macro definition with configurations + for your Splunk environment. The search also uses a post-filter macro designed to + filter out known false positives. +type: ESCU +references: +- https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf +author: Patrick Bareiss, Splunk +search: '`sysmon` Message=*win32_shadowcopy* Message=*Create* | stats count min(_time) + as firstTime max(_time) as lastTime by dvc User EventCode Message | rename User + as user, dvc as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `creation_of_shadow_copy_with_wmic_and_powershell_filter` ' +known_false_positives: Legtimate administrator usage of wmic to create a shadow copy. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + - CIS 16 + nist: + - DE.CM diff --git a/detections/cred_dump_via_copy_from_shadowcopy.yml b/detections/cred_dump_via_copy_from_shadowcopy.yml deleted file mode 100644 index a7250a1a46..0000000000 --- a/detections/cred_dump_via_copy_from_shadowcopy.yml +++ /dev/null @@ -1,90 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2019-12-10' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Sysmon -description: This search detects credential dumping using copy command from a shadow copy. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest, process_name, process - rule_description: credential dumping using copy command was detected on $dest$. - rule_title: Attempted Credential Dump using copy command from $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 40 - macros: - - cred_dump_via_copy_from_shadowcopy_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where Processes.process_name=cmd.exe (Processes.process=*\\system32\\config\\sam* OR Processes.process=*\\system32\\config\\security* OR Processes.process=*\\system32\\config\\system* OR Processes.process=*\\windows\\ntds\\ntds.dit*) - by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `cred_dump_via_copy_from_shadowcopy_filter`' - suppress: - suppress_fields: user, dest, process - suppress_period: 86400s -eli5: The file system, security, sam and ntds.dit containing sensitive credentials. Normally, the files can't be easily copied. - But it is possible by creating first a shadow copy and then copy it from the shadow copy. This search will detect this attack of - credential dumping. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: d8c406fe-23d2-45f3-a983-1abe7b83ff3b -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: unknown -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 8 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 - nist: - - DE.CM -modification_date: '2019-12-10' -name: Credential Dumping via Copy Command from Shadow Copy -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -references: - - https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/cred_dump_via_symlink_shadowcopy.yml b/detections/cred_dump_via_symlink_shadowcopy.yml deleted file mode 100644 index 3a0c6977a5..0000000000 --- a/detections/cred_dump_via_symlink_shadowcopy.yml +++ /dev/null @@ -1,89 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2019-12-10' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Sysmon -description: This search detects the creation of a symlink to a shadow copy. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest, process_name, process - rule_description: credential dumping using symlink on $dest$. - rule_title: Attempted Credential Dump using symlink from $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 40 - macros: - - cred_dump_via_symlink_shadowcopy_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where Processes.process_name=cmd.exe Processes.process=*mklink* Processes.process=*HarddiskVolumeShadowCopy* - by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `cred_dump_via_symlink_shadowcopy_filter` ' - suppress: - suppress_fields: user, dest, process - suppress_period: 86400s -eli5: The file system, security, sam, and ntds.dit containing sensitive credentials. Normally, the files can't be easily copied, but it can be done by creating shadow copy and then create a symlink to the shadow copy. This search will detect this attack of - credential dumping. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: c5eac648-fae0-4263-91a6-773df1f4c903 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: unknown -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 8 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 - nist: - - DE.CM -modification_date: '2019-12-10' -name: Credential Dumping via Symlink to Shadow Copy -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -references: - - https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml new file mode 100644 index 0000000000..2f70642e10 --- /dev/null +++ b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml @@ -0,0 +1,34 @@ +name: Credential Dumping via Copy Command from Shadow Copy +id: d8c406fe-23d2-45f3-a983-1abe7b83ff3b +version: '1.0' +date: '2019-12-10' +description: This search detects credential dumping using copy command from a shadow + copy. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: +- https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf +author: Patrick Bareiss, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe + (Processes.process=*\\system32\\config\\sam* OR Processes.process=*\\system32\\config\\security* + OR Processes.process=*\\system32\\config\\system* OR Processes.process=*\\windows\\ntds\\ntds.dit*) + by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process + Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_copy_from_shadowcopy_filter`' +known_false_positives: unknown +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + - CIS 16 + nist: + - DE.CM diff --git a/detections/credential_dumping_via_symlink_to_shadow_copy.yml b/detections/credential_dumping_via_symlink_to_shadow_copy.yml new file mode 100644 index 0000000000..d352b71f72 --- /dev/null +++ b/detections/credential_dumping_via_symlink_to_shadow_copy.yml @@ -0,0 +1,32 @@ +name: Credential Dumping via Symlink to Shadow Copy +id: c5eac648-fae0-4263-91a6-773df1f4c903 +version: '1.0' +date: '2019-12-10' +description: This search detects the creation of a symlink to a shadow copy. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: +- https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf +author: Patrick Bareiss, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe + Processes.process=*mklink* Processes.process=*HarddiskVolumeShadowCopy* by Processes.dest + Processes.user Processes.process_name Processes.process Processes.parent_process + Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_symlink_shadowcopy_filter` ' +known_false_positives: unknown +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + - CIS 16 + nist: + - DE.CM diff --git a/detections/cscript_via_cmd.yml b/detections/cscript_via_cmd.yml deleted file mode 100644 index 3981c1527b..0000000000 --- a/detections/cscript_via_cmd.yml +++ /dev/null @@ -1,114 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-10-09' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for the execution of the cscript.exe or wscript.exe - processes, with a parent of cmd.exe. The search will return the count, the first - and last time this execution was seen on a machine, the user, and the destination - of the machine -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process_name, parent_process - rule_description: Potentially malicious script execution detected. - rule_title: 'Command prompt is executing scripts on $dest$ using $process_name$ ' - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.parent_process_name="cmd.exe" (Processes.process_name=cscript.exe OR - Processes.process_name =wscript.exe) by Processes.parent_process Processes.process_name - Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process_name - suppress_period: 86400s -eli5: Attackers often leverage various scripting languages to execute their attacks. - In a Windows environment, the Windows Script Host is the tool that interprets the - scripts and is included in all modern versions of Windows. The Windows Script Host - is available as a command-line tool called "cscript.exe" or "wscript.exe." To detect - this behavior, the search looks for process-creation events for cscript.exe or wscript.exe - with a parent process of cmd.exe. The search will return the count, the first and - last times this behavior was seen on a destination machine, and user and process - information. -entities: - - dest - - process_name - - user -how_to_implement: To successfully implement this search, you must be ingesting data - that records process activity from your hosts to populate the endpoint data model - in the processes node. If you are using Sysmon, you must have at least version 6.0.4 - of the Sysmon TA. -id: b89919ed-fe5f-492c-b139-95dbb162039e -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Some legitimate applications may exhibit this behavior. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Exploitation - mitre_attack: - - Execution - - Command-Line Interface - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-02' -name: Detect Use of cmd.exe to Launch Script Interpreters -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/delete_shadow_copies.yml b/detections/delete_shadow_copies.yml deleted file mode 100644 index 481e6b06b6..0000000000 --- a/detections/delete_shadow_copies.yml +++ /dev/null @@ -1,115 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-02-17' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: The vssadmin.exe utility is used to interact with the Volume Shadow Copy - Service. Wmic is an interface to the Windows Management Instrumentation. This - search looks for either of these tools being used to delete shadow copies. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: Using $process_name$ to delete shadow copies is common behavior - by ransomware. This activity was observed on $dest$ - rule_title: Deleting Shadow Copies on $dest$ with $process_name$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 75 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=vssadmin.exe - OR Processes.process_name=wmic.exe) by Processes.user Processes.process_name - Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*delete* AND process=*shadow*' - suppress: - suppress_fields: dest, user - suppress_period: 14400s -eli5: This search looks for execution of vssadmin or wmic with both the "delete" and - "shadows" parameters passed on the command-line. The two arguments are searched - for separately because we can't predict the number of spaces between the words on - the command-line. The search will return the number of times this activity was observed, - and the times of the first and last event. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: b89919ed-ee5f-492c-b139-95dbb162039e -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: vssadmin.exe and wmic.exe are standard applications shipped - with modern versions of windows. They may be used by administrators to legitimately - delete old backup copies, although this is typically rare. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - - CIS 10 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Impact - mitre_technique_id: - - T1490 - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2020-04-17' -name: Deleting Shadow Copies -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.1' diff --git a/detections/deleting_shadow_copies.yml b/detections/deleting_shadow_copies.yml new file mode 100644 index 0000000000..5e271880fb --- /dev/null +++ b/detections/deleting_shadow_copies.yml @@ -0,0 +1,37 @@ +name: Deleting Shadow Copies +id: b89919ed-ee5f-492c-b139-95dbb162039e +version: '2.1' +date: '2020-04-17' +description: The vssadmin.exe utility is used to interact with the Volume Shadow Copy + Service. Wmic is an interface to the Windows Management Instrumentation. This + search looks for either of these tools being used to delete shadow copies. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=vssadmin.exe + OR Processes.process_name=wmic.exe) by Processes.user Processes.process_name Processes.parent_process_name + Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | search process=*delete* AND process=*shadow*' +known_false_positives: vssadmin.exe and wmic.exe are standard applications shipped + with modern versions of windows. They may be used by administrators to legitimately + delete old backup copies, although this is typically rare. +tags: + analytics_story: + - SamSam Ransomware + - Ransomware + - Windows Log Manipulation + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + - CIS 10 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/deletion_network_acl.yml b/detections/deletion_network_acl.yml deleted file mode 100644 index a87195b53c..0000000000 --- a/detections/deletion_network_acl.yml +++ /dev/null @@ -1,88 +0,0 @@ -asset_type: AWS Instance -confidence: medium -creation_date: '2017-01-08' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: Enforcing network-access controls is one of the defensive mechanisms - used by cloud administrators to restrict access to a cloud instance. After the attacker - has gained control of the AWS console by compromising an admin account, they can - delete a network ACL and gain access to the instance from anywhere. This search - will query the CloudTrail logs to detect users deleting network ACLs. -detect: - splunk: - correlation_rule: - notable: - nes_fields: arn, eventName - rule_description: AWS network ACL has been deleted by $arn$. - rule_title: AWS Network ACL deleted by $arn$ - risk: - risk_object: arn - risk_object_type: - - user - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -1d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=DeleteNetworkAcl|rename userIdentity.arn - as arn | stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) - values(errorCode) values(userAgent) values(userIdentity.*) by src userName - arn eventName | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - suppress: - suppress_fields: arn - suppress_period: 14400s -eli5: The search looks for CloudTrail events to detect whether any network ACLs have - been deleted and gives you values of error messages and error codes (if any), user - details, user source IP, the user who initiated this request, and the name of the - event. -entities: - - arn -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: ada0f478-84a8-4641-a3f1-d82362d6fd75 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It's possible that a user has legitimately deleted a network - ACL. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 11 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - nist: - - DE.DP - - DE.AE -modification_date: '2017-01-10' -name: AWS Network Access Control List Deleted -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/detect_activity_related_to_pass_the_hash_attacks.yml b/detections/detect_activity_related_to_pass_the_hash_attacks.yml new file mode 100644 index 0000000000..4c72180678 --- /dev/null +++ b/detections/detect_activity_related_to_pass_the_hash_attacks.yml @@ -0,0 +1,34 @@ +name: Detect Activity Related to Pass the Hash Attacks +id: f5939373-8054-40ad-8c64-cec478a22a4b +version: '3.0' +date: '2020-01-09' +description: This search looks for specific authentication events from the Windows + Security Event logs to detect potential attempts at using the Pass-the-Hash technique. +how_to_implement: To successfully implement this search, you must ingest your Windows + Security Event logs and leverage the latest TA for Windows. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '`wineventlog_security` EventCode=4624 (Logon_Type=3 LogonProcessName=NtLmSsp + WorkstationName=WORKSTATION NOT AccountName="ANONYMOUS LOGON") OR (EventCode=4624 + Logon_Type=9 LogonProcessName=seclogo) | stats count min(_time) as firstTime max(_time) + as lastTime by EventCode, Logon_Type, WorkstationName, user, dest | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | `detect_activity_related_to_pass_the_hash_attacks_filter` ' +known_false_positives: Legitimate logon activity by authorized NTLM systems may be + detected by this search. Please investigate as appropriate. +tags: + analytics_story: + - Lateral Movement + mitre_attack_id: + - T1075 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 16 + nist: + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/detections/detect_api_activity_from_users_without_mfa.yml b/detections/detect_api_activity_from_users_without_mfa.yml new file mode 100644 index 0000000000..55b8a9e60a --- /dev/null +++ b/detections/detect_api_activity_from_users_without_mfa.yml @@ -0,0 +1,54 @@ +name: Detect API activity from users without MFA +id: 2a9b80d3-6340-4345-w5ad-212bf5d1dac4 +version: '1.0' +date: '2018-05-17' +description: This search looks for CloudTrail events where a user logged into the + AWS account, is making API calls and has not enabled Multi Factor authentication. + Multi factor authentication adds a layer of security by forcing the users to type + a unique authentication code from an approved authentication device when they access + AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged + IAM users. +how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Leverage the support search `Create a list of approved AWS service accounts`: + run it once every 30 days to create a list of service accounts and validate them.\ + + This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) + that are not yet supported by ES Incident Review and therefore cannot be viewed + when a notable event is raised. These fields contribute additional context to the + notable. To see the additional metadata, add the following fields, if not already + present, to Incident Review - Event Attributes (Configure > Incident Management + > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** + eventName\ + + 1. \ + + 1. **Label:** AWS User ARN, **Field:** userIdentity.arn\ + + 1. \ + + 1. **Label:** AWS User Type, **Field:** userIdentity.type\ + + Detailed documentation on how to create a new field within Incident Review may be + found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail userIdentity.sessionContext.attributes.mfaAuthenticated=false + | search NOT [| inputlookup aws_service_accounts | fields identity | rename identity + as user]| stats count min(_time) as firstTime max(_time) as lastTime values(eventName) + as eventName by userIdentity.arn userIdentity.type user | `security_content_ctime(firstTime)` | + `security_content_ctime(lastTime)` +known_false_positives: Many service accounts configured within an AWS infrastructure + do not have multi factor authentication enabled. Please ignore the service accounts, + if triggered and instead add them to the aws_service_accounts.csv file to fine tune + the detection. It is also possible that the search detects users in your environment + using Single Sign-On systems, since the MFA is not handled by AWS. +tags: + analytics_story: + - AWS User Monitoring + cis20: + - CIS 16 + nist: + - DE.DP + - PR.AC diff --git a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml new file mode 100644 index 0000000000..5d1b4efcc1 --- /dev/null +++ b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml @@ -0,0 +1,27 @@ +name: Detect attackers scanning for vulnerable JBoss servers +id: 104658f4-afdc-499e-9719-17243f982681 +version: '1.0' +date: '2017-09-23' +description: This search looks for specific GET or HEAD requests to web servers that + are indicative of reconnaissance attempts to identify vulnerable JBoss servers. + JexBoss is described as the exploit tool of choice for this malicious activity. +how_to_implement: You must be ingesting data from the web server or network traffic + that contains web specific information, and populating the Web data model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") + AND (Web.url="*/web-console/ServerInfo.jsp*" OR Web.url="*web-console*" OR Web.url="*jmx-console*" + OR Web.url = "*invoker*") by Web.http_method, Web.url, Web.src, Web.dest | `drop_dm_object_name("Web")` + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +known_false_positives: It's possible for legitimate HTTP requests to be made to URLs + containing the suspicious paths. +tags: + analytics_story: + - SamSam Ransomware + - JBoss Vulnerability + mitre_attack_id: + - T1082 + kill_chain_phases: + - Reconnaissance diff --git a/detections/detect_aws_api_activities_from_unapproved_accounts.yml b/detections/detect_aws_api_activities_from_unapproved_accounts.yml new file mode 100644 index 0000000000..1656ef50ae --- /dev/null +++ b/detections/detect_aws_api_activities_from_unapproved_accounts.yml @@ -0,0 +1,57 @@ +name: Detect AWS API Activities From Unapproved Accounts +id: ada0f478-84a8-4641-a3f1-d82362d4bd55 +version: '1.0' +date: '2018-03-13' +description: This search looks for successful CloudTrail activity by user accounts + that are not listed in the identity table or `aws_service_accounts.csv`. It returns + event names and count, as well as the first and last time a specific user or service + is detected, grouped by users. +how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. You must also populate the `identity_lookup_expanded` lookup shipped with + the Asset and Identity framework to be able to look up users in your identity table + in Enterprise Security (ES). Leverage the support search called "Create a list of + approved AWS service accounts": run it once every 30 days to create and validate + a list of service accounts.\ + + This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet + supported by ES Incident Review and therefore cannot be viewed when a notable event + is raised. These fields contribute additional context to the notable. To see the + additional metadata, add the following fields, if not already present, to Incident + Review - Event Attributes (Configure > Incident Management > Incident Review Settings + > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ + + 1. \ + + 1. **Label:** First Time, **Field:** firstTime\ + + 1. \ + + 1. **Label:** Last Time, **Field:** lastTime\ + + Detailed documentation on how to create a new field within Incident Review may be + found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail errorCode=success | rename userName as identity + | search NOT [| inputlookup identity_lookup_expanded | fields identity] | search + NOT [| inputlookup aws_service_accounts | fields identity] | rename identity as + user | stats count min(_time) as firstTime max(_time) as lastTime values(eventName) + as eventName by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +known_false_positives: It's likely that you'll find activity detected by users/service + accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` + file. If the user is a legitimate service account, update the `aws_service_accounts.csv` + table with that entry. +tags: + analytics_story: + - AWS User Monitoring + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.DP + - DE.CM + - PR.AC + - ID.AM diff --git a/detections/detect_aws_console_login_by_user_from_new_city.yml b/detections/detect_aws_console_login_by_user_from_new_city.yml new file mode 100644 index 0000000000..c10475eb6c --- /dev/null +++ b/detections/detect_aws_console_login_by_user_from_new_city.yml @@ -0,0 +1,39 @@ +name: Detect AWS Console Login by User from New City +id: 121b0b11-f8ac-4ed6-a132-3800ca4fc07a +version: '1.0' +date: '2018-04-30' +description: This search looks for CloudTrail events wherein a console login event + by a user was recorded within the last hour, then compares the event to a lookup + file of previously seen users (by ARN values) who have logged into the console. + The alert is fired if the user has logged into the console for the first time within + the last hour +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Run the "Previously seen users in CloudTrail" support search only once to + create a baseline of previously seen IAM users within the last 30 days. Run "Update + previously seen users in CloudTrail" hourly (or more frequently depending on how + often you run the detection searches) to refresh the baselines. +type: ESCU +author: Jason Brewer, Splunk +search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by user City | join user type=outer [| inputlookup + previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen + by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), + "@d"), "New City","Previously Seen City") | eval UserData=if(earliestseen >= relative_time(now(), + "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New City" + AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| + `security_content_ctime(earliestseen)` | table user City userStatus firstTime lastTime + earliestseen' +known_false_positives: When a legitimate new user logins for the first time, this + activity will be detected. Check how old the account is and verify that the user + activity is legitimate. +tags: + analytics_story: + - Suspicious AWS Login Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.DP + - DE.AE diff --git a/detections/detect_aws_console_login_by_user_from_new_country.yml b/detections/detect_aws_console_login_by_user_from_new_country.yml new file mode 100644 index 0000000000..50baf1944b --- /dev/null +++ b/detections/detect_aws_console_login_by_user_from_new_country.yml @@ -0,0 +1,39 @@ +name: Detect AWS Console Login by User from New Country +id: 67bd3def-c41c-4bf6-837b-ae196b4257c6 +version: '1.0' +date: '2018-04-30' +description: This search looks for CloudTrail events wherein a console login event + by a user was recorded within the last hour, then compares the event to a lookup + file of previously seen users (by ARN values) who have logged into the console. + The alert is fired if the user has logged into the console for the first time within + the last hour +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Run the "Previously seen users in CloudTrail" support search only once to + create a baseline of previously seen IAM users within the last 30 days. Run "Update + previously seen users in CloudTrail" hourly (or more frequently depending on how + often you run the detection searches) to refresh the baselines. +type: ESCU +author: Jason Brewer, Splunk +search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by user Country | join user type=outer [| + inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen + by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), + "@d"), "New Country","Previously Seen Country") | eval UserData=if(earliestseen + >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | + where userStatus="New Country" AND UserData="Old User" | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)`|`security_content_ctime(earliestseen)` | table + user Country userStatus firstTime lastTime earliestseen' +known_false_positives: When a legitimate new user logins for the first time, this + activity will be detected. Check how old the account is and verify that the user + activity is legitimate. +tags: + analytics_story: + - Suspicious AWS Login Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.DP + - DE.AE diff --git a/detections/detect_aws_console_login_by_user_from_new_region.yml b/detections/detect_aws_console_login_by_user_from_new_region.yml new file mode 100644 index 0000000000..a0c39dabc3 --- /dev/null +++ b/detections/detect_aws_console_login_by_user_from_new_region.yml @@ -0,0 +1,39 @@ +name: Detect AWS Console Login by User from New Region +id: 9f31aa8e-e37c-46bc-bce1-8b3be646d026 +version: '1.0' +date: '2018-04-30' +description: This search looks for CloudTrail events wherein a console login event + by a user was recorded within the last hour, then compares the event to a lookup + file of previously seen users (by ARN values) who have logged into the console. + The alert is fired if the user has logged into the console for the first time within + the last hour +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Run the "Previously seen users in CloudTrail" support search only once to + create a baseline of previously seen IAM users within the last 30 days. Run "Update + previously seen users in CloudTrail" hourly (or more frequently depending on how + often you run the detection searches) to refresh the baselines. +type: ESCU +author: Jason Brewer, Splunk +search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by user Region | join user type=outer [| + inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen + by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), + "@d"), "New Region","Previously Seen Region") | eval UserData=if(earliestseen >= + relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where + userStatus="New Region" AND UserData="Old User" | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | `security_content_ctime(earliestseen)` | table + user Region userStatus firstTime lastTime earliestseen' +known_false_positives: When a legitimate new user logins for the first time, this + activity will be detected. Check how old the account is and verify that the user + activity is legitimate. +tags: + analytics_story: + - Suspicious AWS Login Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.DP + - DE.AE diff --git a/detections/detect_credential_dumping_through_LSASS_access.yml b/detections/detect_credential_dumping_through_LSASS_access.yml index f3dc4d36c7..87bfb3782e 100644 --- a/detections/detect_credential_dumping_through_LSASS_access.yml +++ b/detections/detect_credential_dumping_through_LSASS_access.yml @@ -1,99 +1,39 @@ -asset_type: Windows -confidence: medium -creation_date: '2018-08-28' -data_metadata: - data_eventtypes: - - wineventlog_sysmon - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search looks for reading lsass memory consistent with credential dumping. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest - rule_description: Possible attempt at credential dumping was detected on $dest$. - rule_title: Detect reading lsass memory on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - macros: - - sysmon - - detect_credential_dumping_through_LSASS_access_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '`sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) - | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess - | rename Computer as dest - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `detect_credential_dumping_through_LSASS_access_filter`' - suppress: - suppress_fields: user, dest, ProcessName - suppress_period: 86400s -eli5: This search looks for LSASS access using Credential Dumping tools by detecting Process access with - Sysmon logs (EventCode 10), TargetImage lsass.exe and GrantedAccess 0x1410 or 0x1010. - This will for example detect the use of sekurlsa::logonpasswords in Mimikatz. -entities: - - dest -how_to_implement: 'This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives.' -id: 2c365e57-4414-4540-8dc0-73ab10729996 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: The activity may be legitimate. Other tools can access lsass - for legitimate reasons, and it's possible this event could be generated - in those cases. In these cases, false positives should be fairly obvious and you - may need to tweak the search to eliminate noise. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 - nist: - - PR.IP - - PR.AC - - DE.CM -modification_date: '2019-12-03' name: Detect Credential Dumping through LSASS access -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss +id: 2c365e57-4414-4540-8dc0-73ab10729996 +version: '3' +date: '2019-12-03' +description: This search looks for reading lsass memory consistent with credential + dumping. +how_to_implement: This search needs Sysmon Logs and a sysmon configuration, which + includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. + We strongly recommend that you specify your environment-specific configurations + (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition + with configurations for your Splunk environment. The search also uses a post-filter + macro designed to filter out known false positives. +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: "3" +author: Patrick Bareiss, Splunk +search: '`sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) + | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, + SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename + Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `detect_credential_dumping_through_LSASS_access_filter`' +known_false_positives: The activity may be legitimate. Other tools can access lsass + for legitimate reasons, and it's possible this event could be generated in those + cases. In these cases, false positives should be fairly obvious and you may need + to tweak the search to eliminate noise. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 16 + nist: + - PR.IP + - PR.AC + - DE.CM diff --git a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml new file mode 100644 index 0000000000..67d171a40e --- /dev/null +++ b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml @@ -0,0 +1,52 @@ +name: Detect DNS requests to Phishing Sites leveraging EvilGinx2 +id: 24dd17b1-e2fb-4c31-878c-d4f226595bfa +version: '1.0' +date: '2019-04-29' +description: This search looks for DNS requests for phishing domains that are leveraging + EvilGinx tools to mimic websites. +how_to_implement: "You need to ingest data from your DNS logs in the Network_Resolution\ + \ datamodel. Specifically you must ingest the domain that is being queried and the\ + \ IP of the host originating the request. Ideally, you should also be ingesting\ + \ the answer to the query and the query type. This approach allows you to also create\ + \ your own localized passive DNS capability which can aid you in future investigations.\ + \ You will have to add legitimate domain names to the `legit_domains.csv` file shipped\ + \ with the app. \\\n **Splunk>Phantom Playbook Integration**\\\nIf Splunk>Phantom\ + \ is also configured in your environment, a Playbook called `Lets Encrypt Domain\ + \ Investigate` can be configured to run when any results are found by this detection\ + \ search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`,\ + \ add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response\ + \ Actions when configuring this detection search, and set the corresponding Playbook\ + \ to active. \\\n(Playbook link:`https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/`).\\\ + \n" +type: ESCU +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(DNS.answer) as answer from datamodel=Network_Resolution.DNS by + DNS.dest DNS.src DNS.query host | `drop_dm_object_name(DNS)`| rex field=query ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" + | stats count values(query) as query by domain dest src answer| search `evilginx_phishlets_amazon` + OR `evilginx_phishlets_facebook` OR `evilginx_phishlets_github` OR `evilginx_phishlets_0365` + OR `evilginx_phishlets_outlook` OR `evilginx_phishlets_aws` OR `evilginx_phishlets_google` + | search NOT [ inputlookup legit_domains.csv | fields domain]| join domain type=outer + [| tstats count `security_content_summariesonly` values(Web.url) as url from datamodel=Web.Web + by Web.dest Web.site | rename "Web.*" as * | rex field=site ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" + | table dest domain url] | table count src dest query answer domain url' +known_false_positives: If a known good domain is not listed in the legit_domains.csv + file, then the search could give you false postives. Please update that lookup file + to filter out DNS requests to legitimate domains. +tags: + analytics_story: + - Common Phishing Frameworks + mitre_attack_id: + - T1192 + kill_chain_phases: + - Delivery + - Command and Control + cis20: + - CIS 8 + - CIS 7 + nist: + - ID.AM + - PR.DS + - PR.IP + - DE.AE + - DE.CM diff --git a/detections/detect_excessive_account_lockouts_from_endpoint.yml b/detections/detect_excessive_account_lockouts_from_endpoint.yml new file mode 100644 index 0000000000..7206159e8a --- /dev/null +++ b/detections/detect_excessive_account_lockouts_from_endpoint.yml @@ -0,0 +1,38 @@ +name: Detect Excessive Account Lockouts From Endpoint +id: c026e3dd-7e18-4abb-8f41-929e836efe74 +version: '3.0' +date: '2019-04-18' +description: This search identifies endpoints that have caused a relatively high number + of account lockouts in a short period. +how_to_implement: "You must ingest your Windows security event logs in the `Change`\ + \ datamodel under the nodename is `Account_Management`, for this search to execute\ + \ successfully. Please consider updating the cron schedule and the count of lockouts\ + \ you want to monitor, according to your environment. \\\n **Splunk>Phantom Playbook\ + \ Integration**\\\nIf Splunk>Phantom is also configured in your environment, a Playbook\ + \ called \"Excessive Account Lockouts Enrichment and Response\" can be configured\ + \ to run when any results are found by this detection search. The Playbook executes\ + \ the Contextual and Investigative searches in this Story, conducts additional information\ + \ gathering on Windows endpoints, and takes a response action to shut down the affected\ + \ endpoint. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`,\ + \ add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response\ + \ Actions when configuring this detection search, and set the corresponding Playbook\ + \ to active. \\\n(Playbook Link:`https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\\\ + \n" +type: ESCU +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management + All_Changes.result="lockout" by All_Changes.dest All_Changes.result |`drop_dm_object_name("All_Changes")` + |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | search count > 5' +known_false_positives: It's possible that a widely used system, such as a kiosk, could + cause a large number of account lockouts. +tags: + analytics_story: + - Account Monitoring and Controls + mitre_attack_id: + - T1078 + cis20: + - CIS 16 + nist: + - PR.IP diff --git a/detections/detect_excessive_user_account_lockouts.yml b/detections/detect_excessive_user_account_lockouts.yml new file mode 100644 index 0000000000..e612236bc8 --- /dev/null +++ b/detections/detect_excessive_user_account_lockouts.yml @@ -0,0 +1,29 @@ +name: Detect Excessive User Account Lockouts +id: 95a7f9a5-6096-437e-a19e-86f42ac609bd +version: '2.0' +date: '2019-03-01' +description: This search detects user accounts that have been locked out a relatively + high number of times in a short period. +how_to_implement: ou must ingest your Windows security event logs in the `Change` + datamodel under the nodename is `Account_Management`, for this search to execute + successfully. Please consider updating the cron schedule and the count of lockouts + you want to monitor, according to your environment. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management + All_Changes.result="lockout" by All_Changes.user All_Changes.result |`drop_dm_object_name("All_Changes")` + |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | search count > 5' +known_false_positives: It is possible that a legitimate user is experiencing an issue + causing multiple account login failures leading to lockouts. +tags: + analytics_story: + - Account Monitoring and Controls + mitre_attack_id: + - T1078 + cis20: + - CIS 16 + nist: + - PR.IP diff --git a/detections/dyn_dns_queries.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml similarity index 53% rename from detections/dyn_dns_queries.yml rename to detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index f72977089c..ecc59ccd70 100644 --- a/detections/dyn_dns_queries.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -1,50 +1,13 @@ -asset_type: Endpoint -baselines: [] -confidence: medium -creation_date: '2017-11-17' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro +name: Detect hosts connecting to dynamic domain providers +id: c77162d3-f93c-45cc-80c8-22f6v5464g9f +version: '2.0' +date: '2020-01-16' description: Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. -detect: - splunk: - correlation_rule: - notable: - nes_fields: answer, src, query - rule_description: The search has detected a host making outbound queries to - Dynamic DNS providers - rule_title: Host $src$ detected to make a query to a Dynamic DNS provider - risk: - risk_object: src - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(DNS.answer) as answer min(_time) - as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` - | `security_content_ctime(firstTime)` | `dynamic_dns_providers`' - suppress: - suppress_fields: src, query - suppress_period: 86400s -eli5: The search leverages an accelerated `Network_Resolution` data model to count - and list the values of resolved domains for each DNS query. It checks the results - against the list of Dynamic DNS providers in the lookup `dynamic_dns_providers` - by each host (DNS.src). -entities: - - src how_to_implement: 'First, you''ll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is @@ -70,42 +33,31 @@ how_to_implement: 'First, you''ll need to ingest data from your DNS operations. Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: c77162d3-f93c-45cc-80c8-22f6v5464g9f -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk +type: ESCU +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(DNS.answer) as answer + min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query + | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)` | `dynamic_dns_providers`' known_false_positives: Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: - cis20: - - CIS 8 - - CIS 12 - - CIS 13 +tags: + analytics_story: + - Data Protection + - DNS Hijacking + - Prohibited Traffic Allowed or Protocol Mismatch + - Command and Control + - Dynamic DNS + - Suspicious DNS Traffic kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Exfiltration - - Defense Evasion + - Command and Control + - Actions on Objectives + cis20: + - CIS 8 + - CIS 12 + - CIS 13 nist: - - PR.DS - - PR.PT - - DE.AE - - DE.CM -modification_date: '2020-01-16' -name: Detect hosts connecting to dynamic domain providers -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' + - PR.DS + - PR.PT + - DE.AE + - DE.CM diff --git a/detections/detect_large_outbound_icmp_packets.yml b/detections/detect_large_outbound_icmp_packets.yml new file mode 100644 index 0000000000..62ccd7703a --- /dev/null +++ b/detections/detect_large_outbound_icmp_packets.yml @@ -0,0 +1,46 @@ +name: Detect Large Outbound ICMP Packets +id: e9c102de-4d43-42a7-b1c8-8062ea297419 +version: '2.0' +date: '2018-06-01' +description: This search looks for outbound ICMP packets with a packet size larger + than 1,000 bytes. Various threat actors have been known to use ICMP as a command + and control channel for their attack infrastructure. Large ICMP packets from an + endpoint to a remote host may be indicative of this activity. +how_to_implement: 'In order to run this search effectively, we highly recommend that + you leverage the Assets and Identity framework. It is important that you have a + good understanding of how your network segments are designed and that you are able + to distinguish internal from external address space. Add a category named `internal` + to the CIDRs that host the company''s assets in the `assets_by_cidr.csv` lookup + file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. + More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. + This search also requires you to be ingesting your network traffic and populating + the Network_Traffic data model' +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count earliest(_time) as firstTime + latest(_time) as lastTime values(All_Traffic.action) values(All_Traffic.bytes) from + datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category + !=internal (All_Traffic.protocol=icmp OR All_Traffic.transport=icmp) All_Traffic.bytes + > 1000 by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` + | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) + | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' +known_false_positives: ICMP packets are used in a variety of ways to help troubleshoot + networking issues and ensure the proper flow of traffic. As such, it is possible + that a large ICMP packet could be perfectly legitimate. If large ICMP packets are + associated with command and control traffic, there will typically be a large number + of these packets observed over time. If the search is providing a large number of + false positives, you can modify the search to adjust the byte threshold or whitelist + specific IP addresses, as necessary. +tags: + analytics_story: + - Command and Control + mitre_attack_id: + - T1095 + kill_chain_phases: + - Command and Control + cis20: + - CIS 9 + - CIS 12 + nist: + - DE.AE diff --git a/detections/detect_long_dns_txt_record_response.yml b/detections/detect_long_dns_txt_record_response.yml new file mode 100644 index 0000000000..b2f8f7667d --- /dev/null +++ b/detections/detect_long_dns_txt_record_response.yml @@ -0,0 +1,45 @@ +name: Detect Long DNS TXT Record Response +id: 05437c07-62f5-452e-afdc-04dd44815bb9 +version: '1.0' +date: '2017-09-18' +description: This search is used to detect attempts to use DNS tunneling, by calculating + the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission + for data exfiltration, command and control, or evasion of security controls can + often be detected by noting unusually large volumes of DNS traffic. +how_to_implement: To successfully implement this search you need to ingest data from + your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, + this query requires that the DNS data model is populated with information regarding + the DNS record type that is being returned as well as the data in the answer section + of the protocol. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Resolution where DNS.message_type=response AND + DNS.record_type=TXT by DNS.src DNS.dest DNS.answer DNS.record_type | `drop_dm_object_name("DNS")` + | eval anslen=len(answer) | search anslen>100 | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | rename src as "Source IP", dest as "Destination + IP", answer as "DNS Answer" anslen as "Answer Length" record_type as "DNS Record + Type" firstTime as "First Time" lastTime as "Last Time" count as Count | table "Source + IP" "Destination IP" "DNS Answer" "DNS Record Type" "Answer Length" Count "First + Time" "Last Time"' +known_false_positives: It's possible that legitimate TXT record responses can be long + enough to trigger this search. You can modify the packet threshold for this search + to help mitigate false positives. +tags: + analytics_story: + - Suspicious DNS Traffic + - Command and Control + mitre_attack_id: + - T1043 + kill_chain_phases: + - Command and Control + cis20: + - CIS 8 + - CIS 12 + - CIS 13 + nist: + - PR.DS + - PR.PT + - DE.AE + - DE.CM diff --git a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml new file mode 100644 index 0000000000..1589b6e486 --- /dev/null +++ b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml @@ -0,0 +1,37 @@ +name: Detect malicious requests to exploit JBoss servers +id: c8bff7a4-11ea-4416-a27d-c5bca472913d +version: '1.0' +date: '2017-09-23' +description: This search is used to detect malicious HTTP requests crafted to exploit + jmx-console in JBoss servers. The malicious requests have a long URL length, as + the payload is embedded in the URL. +how_to_implement: You must ingest data from the web server or capture network data + that contains web specific information with solutions such as Bro or Splunk Stream, + and populating the Web data model +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") + by Web.http_method, Web.url,Web.url_length Web.src, Web.dest | search Web.url="*jmx-console/HtmlAdaptor?action=invokeOpByName&name=jboss.admin*import*" + AND Web.url_length > 200 | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | table src, dest_ip, http_method, url, firstTime, + lastTime' +known_false_positives: No known false positives for this detection. +tags: + analytics_story: + - SamSam Ransomware + - JBoss Vulnerability + kill_chain_phases: + - Delivery + cis20: + - CIS 12 + - CIS 4 + - CIS 18 + nist: + - ID.RA + - PR.PT + - PR.IP + - DE.AE + - PR.MA + - DE.CM diff --git a/detections/detect_mimikatz_using_loaded_images.yml b/detections/detect_mimikatz_using_loaded_images.yml index 156f87899b..a6e22c923c 100644 --- a/detections/detect_mimikatz_using_loaded_images.yml +++ b/detections/detect_mimikatz_using_loaded_images.yml @@ -1,87 +1,36 @@ -asset_type: Windows -confidence: high -creation_date: '2019-12-03' -data_metadata: - data_eventtypes: - - wineventlog_sysmon - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search looks for reading loaded Images unique to credential dumping with Mimikatz. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: Possible attempt at credential dumping was detected on $dest$. - rule_title: Detect Mimikatz using loaded images on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - macros: - - sysmon - - detect_mimikatz_using_loaded_images_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '`sysmon` EventCode=7 | stats values(ImageLoaded) as ImageLoaded values(ProcessId) as ProcessId by Computer, Image - | search ImageLoaded=*WinSCard.dll ImageLoaded=*cryptdll.dll ImageLoaded=*hid.dll ImageLoaded=*samlib.dll ImageLoaded=*vaultcli.dll - | rename Computer as dest - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_mimikatz_using_loaded_images_filter`' - suppress: - suppress_fields: dest, Image - suppress_period: 86400s -eli5: This search looks for loaded images (dll) unique for Mimikatz using Sysmon EventCode 7 logs. -entities: - - dest -how_to_implement: 'This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives.' -id: 29e307ba-40af-4ab2-91b2-3c6b392bbba0 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: Other tools can import the same DLLs. These tools should be - part of a whtelist. -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 6 - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 - nist: - - DE.AE - - DE.CM -modification_date: '2019-12-03' name: Detect Mimikatz Using Loaded Images -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss +id: 29e307ba-40af-4ab2-91b2-3c6b392bbba0 +version: '1' +date: '2019-12-03' +description: This search looks for reading loaded Images unique to credential dumping + with Mimikatz. +how_to_implement: This search needs Sysmon Logs and a sysmon configuration, which + includes EventCode 7 with powershell.exe. This search uses an input macro named + `sysmon`. We strongly recommend that you specify your environment-specific configurations + (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition + with configurations for your Splunk environment. The search also uses a post-filter + macro designed to filter out known false positives. +type: ESCU references: - - https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html -security_domain: endpoint -spec_version: 2 -type: splunk -version: "1" +- https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html +author: Patrick Bareiss, Splunk +search: '`sysmon` EventCode=7 | stats values(ImageLoaded) as ImageLoaded values(ProcessId) + as ProcessId by Computer, Image | search ImageLoaded=*WinSCard.dll ImageLoaded=*cryptdll.dll + ImageLoaded=*hid.dll ImageLoaded=*samlib.dll ImageLoaded=*vaultcli.dll | rename + Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `detect_mimikatz_using_loaded_images_filter`' +known_false_positives: Other tools can import the same DLLs. These tools should be + part of a whtelist. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 6 + - CIS 8 + nist: + - DE.AE + - DE.CM diff --git a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml new file mode 100644 index 0000000000..3d3afded3e --- /dev/null +++ b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml @@ -0,0 +1,39 @@ +name: Detect Mimikatz Via PowerShell And EventCode 4703 +id: 98917be2-bfc8-475a-8618-a9bb06575188 +version: '2.0' +date: '2019-02-27' +description: This search looks for PowerShell requesting privileges consistent with + credential dumping. +how_to_implement: 'You must be ingesting Windows Security logs. You must also enable + the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. + Additionally, this search requires you to enable your Group Management Audit Logs + in your Local Windows Security Policy and to be ingesting those logs. More information + on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. + Finally, please make sure that the local administrator group name is "Administrators" + to be able to look for the right group membership changes.' +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: eventtype=wineventlog_security signature_id=4703 Process_Name=*powershell.exe + | rex field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" + | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) + as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs as + "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` +known_false_positives: The activity may be legitimate. PowerShell is often used by + administrators to perform various tasks, and it's possible this event could be generated + in those cases. In these cases, false positives should be fairly obvious and you + may need to tweak the search to eliminate noise. +tags: + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 16 + nist: + - PR.IP + - PR.AC + - DE.CM diff --git a/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml new file mode 100644 index 0000000000..4fb9e2c4c3 --- /dev/null +++ b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml @@ -0,0 +1,35 @@ +name: Detect mshta.exe running scripts in command-line arguments +id: b89919ed-fe5f-492c-b139-95dqb161039e +version: '2.0' +date: '2018-12-03' +description: This search looks for the execution of "mshta.exe" with command-line + arguments that launch a script. The search will return the first time and last time + these command-line arguments were used for these executions, as well as the target + system, the user, process "mshta.exe" and its parent process. +how_to_implement: To successfully implement this search, you need to be ingesting + logs with the process name, parent process, and command-line executions from your + endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the + Sysmon TA. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=mshta.exe + by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| + search (process=*vbscript* OR process=*javascript*)' +known_false_positives: Although unlikely, some legitimate applications may exhibit + this behavior, triggering a false positive. +tags: + analytics_story: + - Suspicious MSHTA Activity + mitre_attack_id: + - T1059 + kill_chain_phases: + - Exploitation + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/detect_new_api_calls_from_user_roles.yml b/detections/detect_new_api_calls_from_user_roles.yml new file mode 100644 index 0000000000..931ba516ee --- /dev/null +++ b/detections/detect_new_api_calls_from_user_roles.yml @@ -0,0 +1,34 @@ +name: Detect new API calls from user roles +id: 22773e84-bac0-4595-b086-20d3f335b4f1 +version: '1.0' +date: '2018-04-16' +description: This search detects new API calls that have either never been seen before + or that have not been seen in the previous hour, where the identity type is `AssumedRole`. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. This search works best when you run the "Previously seen API call per user + roles in CloudTrail" support search once to create a history of previously seen + user roles. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole + [search sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole + | stats earliest(_time) as earliest latest(_time) as latest by userName eventName + | inputlookup append=t previously_seen_api_calls_from_user_roles | stats min(earliest) + as earliest, max(latest) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles| + eval newApiCallfromUserRole=if(earliest>=relative_time(now(), "-70m@m"), 1, 0) | + where newApiCallfromUserRole=1 | `security_content_ctime(earliest)` | `security_content_ctime(latest)` + | table eventName userName] |rename userName as user| stats values(eventName) earliest(_time) + as earliest latest(_time) as latest by user | `security_content_ctime(earliest)` + | `security_content_ctime(latest)` +known_false_positives: It is possible that there are legitimate user roles making + new or infrequently used API calls in your infrastructure, causing the search to + trigger. +tags: + analytics_story: + - AWS User Monitoring + cis20: + - CIS 1 + nist: + - ID.AM diff --git a/detections/detect_new_local_admin_account.yml b/detections/detect_new_local_admin_account.yml new file mode 100644 index 0000000000..58d8779525 --- /dev/null +++ b/detections/detect_new_local_admin_account.yml @@ -0,0 +1,55 @@ +name: Detect New Local Admin account +id: b25f6f62-0712-43c1-b203-083231ffd97d +version: '1.0' +date: '2019-02-28' +description: This search looks for newly created accounts that have been elevated + to local administrators. +how_to_implement: 'You must be ingesting Windows Security logs. You must also enable + the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. + Additionally, this search requires you to enable your Group Management Audit Logs + in your Local Windows Security Policy and to be ingesting those logs. More information + on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. + Finally, please make sure that the local administrator group name is "Administrators" + to be able to look for the right group membership changes.\ + + This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not + yet supported by ES Incident Review and therefore cannot be viewed when a notable + event is raised. These fields contribute additional context to the notable. To see + the additional metadata, add the following fields, if not already present, to Incident + Review - Event Attributes (Configure > Incident Management > Incident Review Settings + > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ + + 1. \ + + 1. **Label:** Group Name, **Field:** Group_Name\ + + 1. \ + + 1. **Label:** Message, **Field:** Message\ + + Detailed documentation on how to create a new field within Incident Review may be + found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' +type: ESCU +references: [] +author: David Dorsey, Splunk +search: eventtype = wineventlog_security signature_id=4720 OR (signature_id=4732 Group_Name= + Administrators) | transaction Security_ID connected=false maxspan=180m | search + signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID + Group_Name src_user Message +known_false_positives: The activity may be legitimate. For this reason, it's best + to verify the account with an administrator and ask whether there was a valid service + request for the account creation. If your local administrator group name is not + "Administrators", this search may generate an excessive number of false positives +tags: + analytics_story: + - DHS Report TA18-074A + mitre_attack_id: + - T1078 + kill_chain_phases: + - Actions on Objectives + - Command and Control + cis20: + - CIS 16 + nist: + - PR.AC + - DE.CM diff --git a/detections/detect_new_login_attempts_to_routers.yml b/detections/detect_new_login_attempts_to_routers.yml new file mode 100644 index 0000000000..3f1cc7f6d6 --- /dev/null +++ b/detections/detect_new_login_attempts_to_routers.yml @@ -0,0 +1,31 @@ +name: Detect New Login Attempts to Routers +id: 104658f4-afdc-499e-9719-17243rr826f1 +version: '1.0' +date: '2017-09-12' +description: The search queries the authentication logs for assets that are categorized + as routers in the ES Assets and Identity Framework, to identify connections that + have not been seen before in the last 30 days. +how_to_implement: To successfully implement this search, you must ensure the network + router devices are categorized as "router" in the Assets and identity table. You + must also populate the Authentication data model with logs related to users authenticating + to routing infrastructure. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count earliest(_time) as earliest + latest(_time) as latest from datamodel=Authentication where Authentication.dest_category=router + by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= relative_time(now(), + "-30d@d"), 1, 0) | where isOutlier=1| `security_content_ctime(earliest)`| `security_content_ctime(latest)` + | `drop_dm_object_name("Authentication")`' +known_false_positives: Legitimate router connections may appear as new connections +tags: + analytics_story: + - Router & Infrastructure Security + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 11 + nist: + - PR.PT + - PR.AC + - PR.IP diff --git a/detections/detect_new_open_s3_buckets.yml b/detections/detect_new_open_s3_buckets.yml new file mode 100644 index 0000000000..839a9bd2ae --- /dev/null +++ b/detections/detect_new_open_s3_buckets.yml @@ -0,0 +1,33 @@ +name: Detect New Open S3 buckets +id: 2a9b80d3-6340-4345-b5ad-290bf3d0dac4 +version: '1.0' +date: '2018-07-25' +description: This search looks for CloudTrail events where a user has created an open/public + S3 bucket. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail + inputs. The threshold value should be tuned to your environment. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail AllUsers eventName=PutBucketAcl | spath output=userIdentityArn + path=userIdentity.arn | spath output=bucketName path=requestParameters.bucketName + | spath output=aclControlList path=requestParameters.AccessControlPolicy.AccessControlList + | spath input=aclControlList output=grantee path=Grant{} | mvexpand grantee | spath + input=grantee | search Grantee.URI=*AllUsers | rename userIdentityArn as user| table + _time, src,awsRegion Permission, Grantee.URI, bucketName, user +known_false_positives: While this search has no known false positives, it is possible + that an AWS admin has legitimately created a public bucket for a specific purpose. + That said, AWS strongly advises against granting full control to the "All Users" + group. +tags: + analytics_story: + - Suspicious AWS S3 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 13 + nist: + - PR.DS + - PR.AC + - DE.CM diff --git a/detections/detect_new_user_aws_console_login.yml b/detections/detect_new_user_aws_console_login.yml new file mode 100644 index 0000000000..3c98c23f58 --- /dev/null +++ b/detections/detect_new_user_aws_console_login.yml @@ -0,0 +1,37 @@ +name: Detect new user AWS Console Login +id: ada0f478-84a8-4641-a3f3-d82362dffd75 +version: '1.0' +date: '2018-04-30' +description: This search looks for CloudTrail events wherein a console login event + by a user was recorded within the last hour, then compares the event to a lookup + file of previously seen users (by ARN values) who have logged into the console. + The alert is fired if the user has logged into the console for the first time within + the last hour +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Run the "Previously seen users in CloudTrail" support search only once to + create a baseline of previously seen IAM users within the last 30 days. Run "Update + previously seen users in CloudTrail" hourly (or more frequently depending on how + often you run the detection searches) to refresh the baselines. +type: ESCU +author: Bhavin Patel, Splunk +search: 'sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn + as user | stats earliest(_time) as firstTime latest(_time) as lastTime by user | + inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by user | eval userStatus=if(firstTime >= + relative_time(now(), "-70m@m"), "First Time Logging into AWS Console","Previously + Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| + where userStatus ="First Time Logging into AWS Console" ' +known_false_positives: When a legitimate new user logins for the first time, this + activity will be detected. Check how old the account is and verify that the user + activity is legitimate. +tags: + analytics_story: + - Suspicious AWS Login Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.DP + - DE.AE diff --git a/detections/detect_oulook_exe_writing_a__zip_file.yml b/detections/detect_oulook_exe_writing_a__zip_file.yml new file mode 100644 index 0000000000..0a5920394d --- /dev/null +++ b/detections/detect_oulook_exe_writing_a__zip_file.yml @@ -0,0 +1,44 @@ +name: Detect Oulook.exe writing a .zip file +id: a51bfe1a-94f0-4822-b1e4-16ae10145893 +version: '2.0' +date: '2020-03-16' +description: This search looks for execution of process `outlook.exe` where the process + is writing a `.zip` file to the disk. +how_to_implement: You must be ingesting data that records filesystem and process activity + from your hosts to populate the Endpoint data model. This is typically populated + via endpoint detection-and-response products, such as Carbon Black, or endpoint + data sources, such as Sysmon. +type: ESCU +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name=outlook.exe + OR Processes.process_name=explorer.exe by _time span=5m Processes.parent_process_id + Processes.process_id Processes.dest Processes.process_name Processes.parent_process_name + Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | rename process_id as malicious_id| rename + parent_process_id as outlook_id| join malicious_id type=inner[| tstats `security_content_summariesonly` + count values(Filesystem.file_path) as file_path values(Filesystem.file_name) as + file_name FROM datamodel=Endpoint.Filesystem where (Filesystem.file_path=*zip* OR + Filesystem.file_name=*.lnk ) AND (Filesystem.file_path=C:\\Users* OR Filesystem.file_path=*Local\\Temp*) + by _time span=5m Filesystem.process_id Filesystem.file_hash Filesystem.dest | + `drop_dm_object_name(Filesystem)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | rename process_id as malicious_id| fields malicious_id outlook_id dest file_path + file_name file_hash count file_id] | table firstTime lastTime user malicious_id + outlook_id process_name parent_process_name file_name file_path | where file_name + != "" | `outlook_writing_zip_filter`' +known_false_positives: It is not uncommon for outlook to write legitimate zip files + to the disk. +tags: + analytics_story: + - Phishing Payloads + mitre_attack_id: + - T1193 + kill_chain_phases: + - Installation + - Actions on Objectives + cis20: + - CIS 7 + - CIS 8 + nist: + - ID.AM + - PR.DS diff --git a/detections/detect_outbound_smb_traffic.yml b/detections/detect_outbound_smb_traffic.yml new file mode 100644 index 0000000000..eca2d96d78 --- /dev/null +++ b/detections/detect_outbound_smb_traffic.yml @@ -0,0 +1,48 @@ +name: Detect Outbound SMB Traffic +id: 7f5fb3e1-4209-414-90db-0ec21b936378 +version: '2.0' +date: '2020-01-22' +description: This search looks for outbound SMB connections made by hosts within your + network to the Internet. SMB traffic is used for Windows file-sharing activity. + One of the techniques often used by attackers involves retrieving the credential + hash using an SMB request made to a compromised server controlled by the threat + actor. +how_to_implement: 'In order to run this search effectively, we highly recommend that + you leverage the Assets and Identity framework. It is important that you have good + understanding of how your network segments are designed, and be able to distinguish + internal from external address space. Add a category named `internal` to the CIDRs + that host the company''s assets in `assets_by_cidr.csv` lookup file, which is located + in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating + this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. + This search also requires you to be ingesting your network traffic and populating + the Network_Traffic data model' +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count earliest(_time) as earliest + latest(_time) as latest values(All_Traffic.action) from datamodel=Network_Traffic + where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 + OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip + | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 + AND dest_ip!=192.168.0.0/16) | `security_content_ctime(earliest)`| `security_content_ctime(latest)` + | `outbound_smb_connections_filter` ' +known_false_positives: It is likely that the outbound Server Message Block (SMB) traffic + is legitimate, if the company's internal networks are not well-defined in the Assets + and Identity Framework. Categorize the internal CIDR blocks as `internal` in the + lookup file to avoid creating notable events for traffic destined to those CIDR + blocks. Any other network connection that is going out to the Internet should be + investigated and blocked. Best practices suggest preventing external communications + of all SMB versions and related protocols at the network boundary. +tags: + analytics_story: + - Hidden Cobra Malware + - DHS Report TA18-074A + mitre_attack_id: + - T1043 + kill_chain_phases: + - Actions on Objectives + - Command and Control + cis20: + - CIS 12 + nist: + - DE.CM diff --git a/detections/detect_path_interception_by_creation_of_program_exe.yml b/detections/detect_path_interception_by_creation_of_program_exe.yml new file mode 100644 index 0000000000..2fda445b41 --- /dev/null +++ b/detections/detect_path_interception_by_creation_of_program_exe.yml @@ -0,0 +1,32 @@ +name: Detect Path Interception By Creation Of program.exe +id: c77162d3-f93c-45cc-80c8-22f6v5264g9f +version: '2.0' +date: '2018-11-15' +description: 'The search is looking for the creation of program.exe in the C: drive. The + creation of this file in that location may be driven by a motive to perform path + interception.' +how_to_implement: You must be ingesting data that records the file-system activity + from your hosts to populate the Endpoint file-system data model node. This is typically + populated via endpoint detection-and-response products, such as Carbon Black, or + other endpoint data sources, such as Sysmon. The data used for this search is typically + generated via logs that report file system reads and writes. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) + as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem + where Filesystem.file_path="C:\\program.exe" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`' +known_false_positives: 'It is unlikely that a normal user may create and place this + file in the C: drive. Confirm with the user.' +tags: + analytics_story: + - Windows Persistence Techniques + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/detect_processes_used_for_system_network_configuration_discovery.yml b/detections/detect_processes_used_for_system_network_configuration_discovery.yml new file mode 100644 index 0000000000..c0139f808f --- /dev/null +++ b/detections/detect_processes_used_for_system_network_configuration_discovery.yml @@ -0,0 +1,37 @@ +name: Detect processes used for System Network Configuration Discovery +id: a51bfe1a-94f0-48cc-b1e4-16ae10145893 +version: '1.0' +date: '2018-11-20' +description: This search looks for fast execution of processes used for system network + configuration discovery on the endpoint. +how_to_implement: You must be ingesting data that records registry activity from your + hosts to populate the Endpoint data model in the processes node. This is typically + populated via endpoint detection-and-response products, such as Carbon Black, or + endpoint data sources, such as Sysmon. The data used for this search is usually + generated via logs that report reads and writes to the registry or that are populated + via Windows event logs, after enabling process tracking in your Windows audit settings. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.process_name + Processes.user _time | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` + | transaction dest connected=false maxpause=5m |where eventcount>=5 | table firstTime + lastTime dest user process_name process parent_process eventcount' +known_false_positives: It is uncommon for normal users to execute a series of commands + used for network discovery. System administrators often use scripts to execute these + commands. These can generate false positives. +tags: + analytics_story: + - Unusual Processes + kill_chain_phases: + - Installation + - Command and Control + - Actions on Objectives + cis20: + - CIS 2 + nist: + - ID.AM + - PR.DS diff --git a/detections/detect_prohibited_applications_spawning_cmd_exe.yml b/detections/detect_prohibited_applications_spawning_cmd_exe.yml new file mode 100644 index 0000000000..ba65349c48 --- /dev/null +++ b/detections/detect_prohibited_applications_spawning_cmd_exe.yml @@ -0,0 +1,35 @@ +name: Detect Prohibited Applications Spawning cmd.exe +id: dcfd6b40-42f9-469d-a433-2e53f7486664 +version: '3.0' +date: '2020-02-03' +description: This search looks for executions of cmd.exe spawned by a process that + is often abused by attackers and that does not typically launch cmd.exe. +how_to_implement: You must be ingesting data that records process activity from your + hosts and populates the Endpoint data model with the resultant dataset. This search + includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list + of processes that should not be spawning cmd.exe. You can modify this lookup to + better suit your environment. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name + Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`]' +known_false_positives: There are circumstances where an application may legitimately + execute and interact with the Windows command-line interface. Investigate and modify + the lookup file, as appropriate. +tags: + analytics_story: + - Suspicious MSHTA Activity + - Suspicious Command-Line Executions + mitre_attack_id: + - T1059 + kill_chain_phases: + - Exploitation + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/detect_psexec_with_accepteula_flag.yml b/detections/detect_psexec_with_accepteula_flag.yml new file mode 100644 index 0000000000..03182f21a1 --- /dev/null +++ b/detections/detect_psexec_with_accepteula_flag.yml @@ -0,0 +1,42 @@ +name: Detect PsExec With accepteula Flag +id: b89919ed-fe5f-492c-b139-151xb162040e +version: '2.0' +date: '2019-02-26' +description: This search looks for events where `PsExec.exe` is run with the `accepteula` + flag in the command line. PsExec is a built-in Windows utility that enables you + to execute processes on other systems. It is fully interactive for console applications. + This tool is widely used for launching interactive command prompts on remote systems. + Threat actors leverage this extensively for executing code on compromised systems. + If an attacker is running PsExec for the first time, they will be prompted to accept + the end-user license agreement (EULA), which can be passed as the argument `accepteula` + within the command line. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = PsExec.exe Processes.process = "*accepteula*" by + Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| + `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' +known_false_positives: Administrators can leverage PsExec for accessing remote systems + and might pass `accepteula` as an argument if they are running this tool for the + first time. However, it is not likely that you'd see multiple occurrences of this + event on a machine +tags: + analytics_story: + - SamSam Ransomware + - DHS Report TA18-074A + mitre_attack_id: + - T1059 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/detect_rare_executables.yml b/detections/detect_rare_executables.yml new file mode 100644 index 0000000000..727a831b34 --- /dev/null +++ b/detections/detect_rare_executables.yml @@ -0,0 +1,44 @@ +name: Detect Rare Executables +id: 44fddcb2-8d3b-454c-874e-7c6de5a4f7ac +version: '5.0' +date: '2020-03-16' +description: This search will return a table of rare processes, the names of the systems + running them, and the users who initiated each process. +how_to_implement: To successfully implement this search, you must be ingesting data + that records process activity from your hosts and populating the endpoint data model + with the resultant dataset. The macro `filter_rare_process_whitelist` searches two + lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` + and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, + add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from + the default lookup file, you will have to modify the macro itself to set the whitelist + value for that process to false. You can modify the limit parameter and search scheduling + to better suit your environment. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.dest) as + dest values(Processes.user) as user min(_time) as firstTime max(_time) as lastTime + from datamodel=Endpoint.Processes by Processes.process_name | rename Processes.process_name + as process | rex field=user "(?.*)\\\\(?.*)" | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes + by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name + as process| `filter_rare_process_whitelist`| table process ] | `rare_executables_on_endpoint_filter`' +known_false_positives: Some legitimate processes may be only rarely executed in your + environment. As these are identified, update `rare_process_whitelist_local.csv` + to filter them out of your search results. +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - Unusual Processes + kill_chain_phases: + - Installation + - Command and Control + - Actions on Objectives + cis20: + - CIS 2 + - CIS 8 + nist: + - ID.AM + - PR.PT + - PR.DS + - DE.CM diff --git a/detections/detect_s3_access_from_a_new_ip.yml b/detections/detect_s3_access_from_a_new_ip.yml new file mode 100644 index 0000000000..c0915c0160 --- /dev/null +++ b/detections/detect_s3_access_from_a_new_ip.yml @@ -0,0 +1,38 @@ +name: Detect S3 access from a new IP +id: 2a9b80d3-6340-4345-b5ad-291bq3d0daq4 +version: '1.0' +date: '2018-06-28' +description: This search looks at S3 bucket-access logs and detects new or previously + unseen remote IP addresses that have successfully accessed an S3 bucket. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access + logs' inputs. This search works best when you run the "Previously Seen S3 Bucket + Access by Remote IP" support search once to create a history of previously seen + remote IPs and bucket names. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:s3:accesslogs http_status=200 [search sourcetype=aws:s3:accesslogs + http_status=200 | stats earliest(_time) as firstTime latest(_time) as lastTime by + bucket_name remote_ip | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv + | stats min(firstTime) as firstTime, max(lastTime) as lastTime by bucket_name remote_ip + | outputlookup previously_seen_S3_access_from_remote_ip.csv | eval newIP=if(firstTime + >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` | table bucket_name remote_ip]| iplocation remote_ip + |rename remote_ip as src_ip | table _time bucket_name src_ip City Country operation + request_uri +known_false_positives: S3 buckets can be accessed from any IP, as long as it can make + a successful connection. This will be a false postive, since the search is looking + for a new IP within the past hour +tags: + analytics_story: + - Suspicious AWS S3 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 13 + - CIS 14 + nist: + - PR.DS + - PR.AC + - DE.CM diff --git a/detections/detect_spike_in_aws_api_activity.yml b/detections/detect_spike_in_aws_api_activity.yml new file mode 100644 index 0000000000..6d0c2fc590 --- /dev/null +++ b/detections/detect_spike_in_aws_api_activity.yml @@ -0,0 +1,62 @@ +name: Detect Spike in AWS API Activity +id: ada0f478-84a8-4641-a3f1-d32362d4bd55 +version: '1.0' +date: '2018-04-09' +description: This search will detect users creating spikes of API activity in your + AWS environment. It will also update the cache file that factors in the latest + data. +how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit + your environment. The `dataPointThreshold` variable is the minimum number of data + points required to have a statistically significant amount of data to determine. + The `deviationThreshold` variable is the number of standard deviations away from + the mean that the value must be to be considered a spike.\ + + This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) + that are not yet supported by ES Incident Review and therefore cannot be viewed + when a notable event is raised. These fields contribute additional context to the + notable. To see the additional metadata, add the following fields, if not already + present, to Incident Review - Event Attributes (Configure > Incident Management + > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** + eventName\ + + 1. \ + + 1. **Label:** Number of API Calls, **Field:** numberOfApiCalls\ + + 1. \ + + 1. **Label:** Unique API Calls, **Field:** uniqueApisCalled\ + + Detailed documentation on how to create a new field within Incident Review may be + found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventType=AwsApiCall [search sourcetype=aws:cloudtrail + eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls + by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | + stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, + 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, + avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), + numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, + stdevApiCalls | outputlookup api_call_by_user_baseline | eval dataPointThreshold + = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) + AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as + userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn + | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) + as uniqueApisCalled by user +known_false_positives: '' +tags: + analytics_story: + - AWS User Monitoring + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.DP + - DE.CM + - PR.AC diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml new file mode 100644 index 0000000000..a7fd705ef8 --- /dev/null +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -0,0 +1,55 @@ +name: Detect Spike in blocked Outbound Traffic from your AWS +id: ada0f278-84a8-46w1-a3f1-w32372d4bd53 +version: '1.0' +date: '2018-05-07' +description: This search will detect spike in blocked outbound network connections + originating from within your AWS environment. It will also update the cache file + that factors in the latest data. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow + logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit + your environment. The `dataPointThreshold` variable is the number of data points + required to meet the definition of "spike." The `deviationThreshold` variable is + the number of standard deviations away from the mean that the value must be to be + considered a spike. This search works best when you run the "Baseline of Blocked + Outbound Connection" support search once to create a history of previously seen + blocked outbound connections. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR + src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 + AND dest_ip!=192.168.0.0/16) [search sourcetype=aws:cloudwatchlogs:vpcflow action=blocked + (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 + AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | stats count as numberOfBlockedConnections + by src_ip | inputlookup baseline_blocked_outbound_connections append=t | fields + - latestCount | stats values(*) as * by src_ip | rename numberOfBlockedConnections + as latestCount | eval newAvgBlockedConnections=avgBlockedConnections + (latestCount-avgBlockedConnections)/720 + | eval newStdevBlockedConnections=sqrt(((pow(stdevBlockedConnections, 2)*719 + (latestCount-newAvgBlockedConnections)*(latestCount-avgBlockedConnections))/720)) + | eval avgBlockedConnections=coalesce(newAvgBlockedConnections, avgBlockedConnections), + stdevBlockedConnections=coalesce(newStdevBlockedConnections, stdevBlockedConnections), + numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table src_ip, + latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup + baseline_blocked_outbound_connections | eval dataPointThreshold = 5, deviationThreshold + = 3 | eval isSpike=if((latestCount > avgBlockedConnections+deviationThreshold*stdevBlockedConnections) + AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | table src_ip] + | stats values(dest_ip) as "Blocked Destination IPs", values(interface_id) as "resourceId" + count as numberOfBlockedConnections, dc(dest_ip) as uniqueDestConnections by src_ip +known_false_positives: The false-positive rate may vary based on the values of`dataPointThreshold` + and `deviationThreshold`. Additionally, false positives may result when AWS administrators + roll out policies enforcing network blocks, causing sudden increases in the number + of blocked outbound connections. +tags: + analytics_story: + - Command and Control + - Suspicious AWS Traffic + - AWS Network ACL Activity + kill_chain_phases: + - Actions on Objectives + - Command and Control + cis20: + - CIS 11 + nist: + - DE.AE + - DE.CM + - PR.AC diff --git a/detections/detect_spike_in_network_acl_activity.yml b/detections/detect_spike_in_network_acl_activity.yml new file mode 100644 index 0000000000..36059a85bc --- /dev/null +++ b/detections/detect_spike_in_network_acl_activity.yml @@ -0,0 +1,47 @@ +name: Detect Spike in Network ACL Activity +id: ada0f478-84a8-4641-a1f1-e32372d4bd53 +version: '1.0' +date: '2018-05-21' +description: This search will detect users creating spikes in API activity related + to network access-control lists (ACLs)in your AWS environment. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit + your environment. The `dataPointThreshold` variable is the minimum number of data + points required to have a statistically significant amount of data to determine. + The `deviationThreshold` variable is the number of standard deviations away from + the mean that the value must be to be considered a spike. This search works best + when you run the "Baseline of Network ACL Activity by ARN" support search once to + create a lookup file of previously seen Network ACL Activity. To add or remove API + event names related to network ACLs, edit the macro `network_acl_events`. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail `network_acl_events` [search sourcetype=aws:cloudtrail + `network_acl_events` | spath output=arn path=userIdentity.arn | stats count as apiCalls + by arn | inputlookup network_acl_activity_baseline append=t | fields - latestCount + | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, + 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, + avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), + numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, + stdevApiCalls | outputlookup network_acl_activity_baseline | eval dataPointThreshold + = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) + AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as + userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn + | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) + as uniqueApisCalled by user +known_false_positives: The false-positive rate may vary based on the values of`dataPointThreshold` + and `deviationThreshold`. Please modify this according the your environment. +tags: + analytics_story: + - AWS Network ACL Activity + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 12 + - CIS 11 + nist: + - DE.DP + - DE.CM + - PR.AC diff --git a/detections/detect_spike_in_s3_bucket_deletion.yml b/detections/detect_spike_in_s3_bucket_deletion.yml new file mode 100644 index 0000000000..bde12a46fc --- /dev/null +++ b/detections/detect_spike_in_s3_bucket_deletion.yml @@ -0,0 +1,46 @@ +name: Detect Spike in S3 Bucket deletion +id: ad12w478-84a8-4641-a3w1-e32372q4bd53 +version: '1.0' +date: '2018-11-27' +description: This search detects users creating spikes in API activity related to + deletion of S3 buckets in your AWS environment. It will also update the cache file + that factors in the latest data. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit + your environment. The `dataPointThreshold` variable is the minimum number of data + points required to have a statistically significant amount of data to determine. + The `deviationThreshold` variable is the number of standard deviations away from + the mean that the value must be to be considered a spike. This search works best + when you run the "Baseline of S3 Bucket deletion activity by ARN" support search + once to create a baseline of previously seen S3 bucket-deletion activity. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail eventName=DeleteBucket [search sourcetype=aws:cloudtrail + eventName=DeleteBucket | spath output=arn path=userIdentity.arn | stats count as + apiCalls by arn | inputlookup s3_deletion_baseline append=t | fields - latestCount + | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, + 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, + avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), + numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, + stdevApiCalls | outputlookup s3_deletion_baseline | eval dataPointThreshold = 15, + deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) + AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as + userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn + | spath output=bucketName path=requestParameters.bucketName | stats values(bucketName) + as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user +known_false_positives: Based on the values of`dataPointThreshold` and `deviationThreshold`, + the false positive rate may vary. Please modify this according the your environment. +tags: + analytics_story: + - Suspicious AWS S3 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 13 + nist: + - DE.DP + - DE.CM + - PR.AC diff --git a/detections/detect_spike_in_security_group_activity.yml b/detections/detect_spike_in_security_group_activity.yml new file mode 100644 index 0000000000..9216bc5c49 --- /dev/null +++ b/detections/detect_spike_in_security_group_activity.yml @@ -0,0 +1,47 @@ +name: Detect Spike in Security Group Activity +id: ada0f478-84a8-4641-a3f1-e32372d4bd53 +version: '1.0' +date: '2018-04-18' +description: This search will detect users creating spikes in API activity related + to security groups in your AWS environment. It will also update the cache file + that factors in the latest data. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit + your environment. The `dataPointThreshold` variable is the minimum number of data + points required to have a statistically significant amount of data to determine. + The `deviationThreshold` variable is the number of standard deviations away from + the mean that the value must be to be considered a spike.This search works best + when you run the "Baseline of Security Group Activity by ARN" support search once + to create a history of previously seen Security Group Activity. To add or remove + API event names for security groups, edit the macro `security_group_api_calls`. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail `security_group_api_calls` [search sourcetype=aws:cloudtrail + `security_group_api_calls` | spath output=arn path=userIdentity.arn | stats count + as apiCalls by arn | inputlookup security_group_activity_baseline append=t | fields + - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval + newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, + 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, + avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), + numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, + stdevApiCalls | outputlookup security_group_activity_baseline | eval dataPointThreshold + = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) + AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as + userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn + | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) + as uniqueApisCalled by user +known_false_positives: Based on the values of`dataPointThreshold` and `deviationThreshold`, + the false positive rate may vary. Please modify this according the your environment. +tags: + analytics_story: + - AWS User Monitoring + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.DP + - DE.CM + - PR.AC diff --git a/detections/detect_unauthorized_assets_by_mac_address.yml b/detections/detect_unauthorized_assets_by_mac_address.yml new file mode 100644 index 0000000000..865d4ee51a --- /dev/null +++ b/detections/detect_unauthorized_assets_by_mac_address.yml @@ -0,0 +1,40 @@ +name: Detect Unauthorized Assets by MAC address +id: dcfd6b40-42f9-469d-a433-2e53f7489ff4 +version: '1.0' +date: '2017-09-13' +description: By populating the organization's assets within the assets_by_str.csv, + we will be able to detect unauthorized devices that are trying to connect with the + organization's network by inspecting DHCP request packets, which are issued by devices + when they attempt to obtain an IP address from the DHCP server. The MAC address + associated with the source of the DHCP request is checked against the list of known + devices, and reports on those that are not found. +how_to_implement: This search uses the Network_Sessions data model shipped with Enterprise + Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv + file located in SA-IdentityManagement, which will contain a list of known authorized + organizational assets including their MAC addresses. Ensure that all inventoried + systems have their MAC address populated. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Sessions + where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST by All_Sessions.src_ip + All_Sessions.src_mac | dedup All_Sessions.src_mac| `drop_dm_object_name("Network_Sessions")`|`drop_dm_object_name("All_Sessions")` + | search NOT [| inputlookup asset_lookup_by_str |rename mac as src_mac | fields + + src_mac]' +known_false_positives: This search might be prone to high false positives. Please + consider this when conducting analysis or investigations. Authorized devices may + be detected as unauthorized. If this is the case, verify the MAC address of the + system responsible for the false positive and add it to the Assets and Identity + framework with the proper information. +tags: + analytics_story: + - Asset Tracking + kill_chain_phases: + - Reconnaissance + - Delivery + - Actions on Objectives + cis20: + - CIS 1 + nist: + - ID.AM + - PR.DS diff --git a/detections/detect_usb_device_insertion.yml b/detections/detect_usb_device_insertion.yml new file mode 100644 index 0000000000..931147fc76 --- /dev/null +++ b/detections/detect_usb_device_insertion.yml @@ -0,0 +1,37 @@ +name: Detect USB device insertion +id: 104658f4-afdc-499f-9719-17a43f9826f5 +version: '1.0' +date: '2017-11-27' +description: The search is used to detect hosts that generate Windows Event ID 4663 + for successful attempts to write to or read from a removable storage and Event ID + 4656 for failures, which occurs when a USB drive is plugged in. In this scenario + we are querying the Change_Analysis data model to look for Windows Event ID 4656 + or 4663 where the priority of the affected host is marked as high in the ES Assets + and Identity Framework. +how_to_implement: To successfully implement this search, you must ingest Windows Security + Event logs and track event code 4663 and 4656. Ensure that the field from the event + logs is being mapped to the result_id field in the Change_Analysis data model. To + minimize the alert volume, this search leverages the Assets and Identity framework + to filter out events from those assets not marked high priority in the Enterprise + Security Assets and Identity Framework. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count earliest(_time) AS earliest + latest(_time) AS latest from datamodel=Change_Analysis where (nodename = All_Changes) + All_Changes.result="Removable Storage device" (All_Changes.result_id=4663 OR All_Changes.result_id=4656) + (All_Changes.src_priority=high) by All_Changes.dest | `drop_dm_object_name("All_Changes")`| + `security_content_ctime(earliest)`| `security_content_ctime(latest)` ' +known_false_positives: Legitimate USB activity will also be detected. Please verify + and investigate as appropriate. +tags: + analytics_story: + - Data Protection + kill_chain_phases: + - Installation + - Actions on Objectives + cis20: + - CIS 13 + nist: + - PR.PT + - PR.DS diff --git a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml new file mode 100644 index 0000000000..f48160d13a --- /dev/null +++ b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml @@ -0,0 +1,34 @@ +name: Detect Use of cmd.exe to Launch Script Interpreters +id: b89919ed-fe5f-492c-b139-95dbb162039e +version: '3.0' +date: '2020-03-02' +description: This search looks for the execution of the cscript.exe or wscript.exe + processes, with a parent of cmd.exe. The search will return the count, the first + and last time this execution was seen on a machine, the user, and the destination + of the machine +how_to_implement: To successfully implement this search, you must be ingesting data + that records process activity from your hosts to populate the endpoint data model + in the processes node. If you are using Sysmon, you must have at least version 6.0.4 + of the Sysmon TA. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.parent_process_name="cmd.exe" (Processes.process_name=cscript.exe + OR Processes.process_name =wscript.exe) by Processes.parent_process Processes.process_name + Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' +known_false_positives: Some legitimate applications may exhibit this behavior. +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - Suspicious Command-Line Executions + mitre_attack_id: + - T1059 + kill_chain_phases: + - Exploitation + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/detect_web_traffic_to_dynamic_domain_providers.yml b/detections/detect_web_traffic_to_dynamic_domain_providers.yml new file mode 100644 index 0000000000..c06b246800 --- /dev/null +++ b/detections/detect_web_traffic_to_dynamic_domain_providers.yml @@ -0,0 +1,45 @@ +name: Detect web traffic to dynamic domain providers +id: 134da869-e264-4a8f-8d7e-fcd01c18f301 +version: '1.0' +date: '2018-09-06' +description: This search looks for web connections to dynamic DNS providers. +how_to_implement: 'This search requires you to be ingesting web-traffic logs. You + can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis + tool, such as Bro or Splunk Stream. The web data model must contain the URL being + requested, the IP address of the host initiating the request, and the destination + IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, + which contains a non-exhaustive list of dynamic DNS providers. Consider periodically + updating this local lookup file with new domains.\ + + This search produces fields (`isDynDNS`) that are not yet supported by ES Incident + Review and therefore cannot be viewed when a notable event is raised. These fields + contribute additional context to the notable. To see the additional metadata, add + the following fields, if not already present, to Incident Review - Event Attributes + (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. + **Label:** IsDynamicDNS, **Field:** isDynDNS\ + + Detailed documentation on how to create a new field within Incident Review may be + found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Web.url) as url min(_time) + as firstTime from datamodel=Web where Web.status=200 by Web.src Web.dest Web.status + | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `dynamic_dns_web_traffic`' +known_false_positives: It is possible that list of dynamic DNS providers is outdated + and/or that the URL being requested is legitimate. +tags: + analytics_story: + - Dynamic DNS + mitre_attack_id: + - T1102 + - T1041 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 7 + - CIS 8 + nist: + - PR.IP + - DE.DP diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml new file mode 100644 index 0000000000..99ef09ed65 --- /dev/null +++ b/detections/detection_of_dns_tunnels.yml @@ -0,0 +1,54 @@ +name: Detection of DNS Tunnels +id: 104658f4-afdc-499f-9719-17a43f9826f4 +version: '1.0' +date: '2017-09-18' +description: This search is used to detect DNS tunneling, by calculating the sum of + the length of DNS queries and DNS answers. The search also filters out potential + false positives by filtering out queries made to internal systems and the queries + originating from internal DNS, Web, and Email servers. Endpoints using DNS as a + method of transmission for data exfiltration, command and control, or evasion of + security controls can often be detected by noting an unusually large volume of DNS + traffic. +how_to_implement: To successfully implement this search, we must ensure that DNS data + is being ingested and mapped to the appropriate fields in the Network_Resolution + data model. Fields like src_category are automatically provided by the Assets and + Identity Framework shipped with Splunk Enterprise Security. You will need to ensure + you are using the Assets and Identity Framework and populating the src_category + field. You will also need to enable the `cim_corporate_web_domain_search()` macro + which will essentially filter out the DNS queries made to the corporate web domains + to reduce alert fatigue. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` dc("DNS.query") as count from + datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" NOT + (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" + NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" + OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.query" | rename "DNS.src" + as src "DNS.query" as message | eval length=len(message) | stats sum(length) as + length by src | append [ tstats `security_content_summariesonly` dc("DNS.answer") + as count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" + NOT (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" + NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" + OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.answer" | rename + "DNS.src" as src "DNS.answer" as message | eval message=if(message=="unknown","", + message) | eval length=len(message) | stats sum(length) as length by src ] | stats + sum(length) as length by src | where length > 10000' +known_false_positives: It's possible that normal DNS traffic will exhibit this behavior. + If an alert is generated, please investigate and validate as appropriate. The threshold + can also be modified to better suit your environment. +tags: + analytics_story: + - Suspicious DNS Traffic + - Data Protection + - Command and Control + mitre_attack_id: + - T1043 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 13 + nist: + - PR.PT + - PR.DS diff --git a/detections/detection_of_tools_built_by_nirsoft.yml b/detections/detection_of_tools_built_by_nirsoft.yml new file mode 100644 index 0000000000..c14600d46d --- /dev/null +++ b/detections/detection_of_tools_built_by_nirsoft.yml @@ -0,0 +1,34 @@ +name: Detection of tools built by NirSoft +id: 1297fb80-f42a-4q4a-9c8b-78c061417cf6 +version: '2.0' +date: '2018-12-03' +description: This search looks for specific command-line arguments that may indicate + the execution of tools made by Nirsoft, which are legitimate, but may be abused + by attackers. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) values(Processes.process) + as process max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process="* + /stext *" OR Processes.process="* /scomma *" ) by Processes.parent_process Processes.process_name + Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` + |`security_content_ctime(lastTime)`' +known_false_positives: While legitimate, these NirSoft tools are prone to abuse. You + should verfiy that the tool was used for a legitimate purpose. +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + mitre_attack_id: + - T1072 + - T1087 + kill_chain_phases: + - Installation + - Actions on Objectives + cis20: + - CIS 3 + nist: + - PR.IP diff --git a/detections/disable_remote_uac.yml b/detections/disable_remote_uac.yml deleted file mode 100644 index 0395ab920e..0000000000 --- a/detections/disable_remote_uac.yml +++ /dev/null @@ -1,106 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-10-12' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: The search looks for modifications to registry keys that control the - enforcement of Windows User Account Control (UAC). -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, registry_path - rule_description: The registry key SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\LocalAccountTokenFilterPolicy - was modified. This registry key is associated with disabling remote UAC - on Windows. - rule_title: Registry Key Associated With Disabling Remote UAC Modified on - $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="*Windows\\CurrentVersion\\Policies\\System\\LocalAccountTokenFilterPolicy" - by Registry.dest, Registry.registry_key_name Registry.user - Registry.registry_path Registry.action | `drop_dm_object_name(Registry)`' - suppress: - suppress_fields: dest, user, registry_path - suppress_period: 14400s -eli5: This search checks to see if the registry key SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\LocalAccountTokenFilterPolicy - was modified. This registry key can be used to disable remote User Account Control. The - search returns the count, the first time activity was seen, last time activity was - seen, the registry path that was modified, the host where the modification took - place and the user that performed the modification. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records registry activity from your hosts to populate the endpoint data model - in the registry node. This is typically populated via endpoint detection-and-response - products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. - The data used for this search is typically generated via logs that report registry - modifications. -id: bbc644bc-37df-4e1a-9c88-ec9a53e2038c -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: This registry key may be modified via administrators to implement - a change in system policy. This type of change should be a very rare occurrence. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Modify Registry - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-02' -name: Disabling Remote User Account Control -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml new file mode 100644 index 0000000000..b3bbbbe3e4 --- /dev/null +++ b/detections/disabling_remote_user_account_control.yml @@ -0,0 +1,34 @@ +name: Disabling Remote User Account Control +id: bbc644bc-37df-4e1a-9c88-ec9a53e2038c +version: '3.0' +date: '2020-03-02' +description: The search looks for modifications to registry keys that control the + enforcement of Windows User Account Control (UAC). +how_to_implement: To successfully implement this search, you must be ingesting data + that records registry activity from your hosts to populate the endpoint data model + in the registry node. This is typically populated via endpoint detection-and-response + products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. + The data used for this search is typically generated via logs that report registry + modifications. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="*Windows\\CurrentVersion\\Policies\\System\\LocalAccountTokenFilterPolicy" + by Registry.dest, Registry.registry_key_name Registry.user Registry.registry_path + Registry.action | `drop_dm_object_name(Registry)`' +known_false_positives: This registry key may be modified via administrators to implement + a change in system policy. This type of change should be a very rare occurrence. +tags: + analytics_story: + - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics + mitre_attack_id: + - T1112 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/dns_amplification_any_query.yml b/detections/dns_amplification_any_query.yml deleted file mode 100644 index 0f1d9d1698..0000000000 --- a/detections/dns_amplification_any_query.yml +++ /dev/null @@ -1,87 +0,0 @@ -asset_type: DNS Servers -confidence: high -creation_date: '2016-08-24' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: The search is used to identify attempts to use your DNS Infrastructure - for DDoS purposes via a DNS amplification attack leveraging ANY queries. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: The search is used to identify attempts to use your DNS - Infrastructure for DDoS purposes via a DNS amplification attack leveraging - ANY queries. - rule_title: Large Volume of DNS ANY Queries - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - schedule: - cron_schedule: '*/5 * * * *' - earliest_time: -15m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution where - nodename=DNS "DNS.message_type"="QUERY" "DNS.record_type"="ANY" by "DNS.dest" - | `drop_dm_object_name("DNS")` | where count>200' - suppress: - suppress_fields: dest - suppress_period: 7200s -eli5: This search counts the number of DNS ANY queries received in 5 minutes, and - generates a Notable Event if the count exceeds a predefined threshold. The search - returns the count, the first time, and the last time a DNS packet was observed with - the ANY flag set. -entities: - - dest -how_to_implement: To successfully implement this search you must ensure that DNS data - is populating the Network_Resolution data model. -id: 8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk -known_false_positives: Legitimate ANY requests may trigger this search, however it - is unusual to see a large volume of them under typical circumstances. You may modify - the threshold in the search to better suit your environment. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 11 - - CIS 12 - kill_chain_phases: - - Actions on Objectives - nist: - - PR.PT - - DE.AE - - PR.IP -modification_date: '2017-09-20' -name: Large Volume of DNS ANY Queries -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/dns_evilginx_subdomains.yml b/detections/dns_evilginx_subdomains.yml deleted file mode 100644 index 45f4a674b4..0000000000 --- a/detections/dns_evilginx_subdomains.yml +++ /dev/null @@ -1,108 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2019-04-29' -data_metadata: - data_models: - - Network_Resolution - - Web - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: This search looks for DNS requests for phishing domains that are leveraging - EvilGinx tools to mimic websites. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, query - rule_description: The host $src$ issued a DNS request for a domain that could - be a phishing site leverating EvilGinx toolkit. - rule_title: DNS request for EvilGinx subdomain detected on $src$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) - as firstTime max(_time) as lastTime values(DNS.answer) as answer from datamodel=Network_Resolution.DNS - by DNS.dest DNS.src DNS.query host | `drop_dm_object_name(DNS)`| rex field=query - ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | stats count values(query) - as query by domain dest src answer| search `evilginx_phishlets_amazon` OR - `evilginx_phishlets_facebook` OR `evilginx_phishlets_github` OR `evilginx_phishlets_0365` - OR `evilginx_phishlets_outlook` OR `evilginx_phishlets_aws` OR `evilginx_phishlets_google` - | search NOT [ inputlookup legit_domains.csv | fields domain]| join domain - type=outer [| tstats count `security_content_summariesonly` values(Web.url) - as url from datamodel=Web.Web by Web.dest Web.site | rename "Web.*" as * | - rex field=site ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | table - dest domain url] | table count src dest query answer domain url' - suppress: - suppress_fields: src, query - suppress_period: 14400s -eli5: This search gathers all the answers to each system's DNS query, then filters - for queries that have subdomains extracted from the EvilGinx toolkit. It will then - run a regex to extract `legit_domains` from the query and remove that from the detection - if it is listed in the `legit_domains.csv` -entities: - - src -how_to_implement: "You need to ingest data from your DNS logs in the Network_Resolution\ - \ datamodel. Specifically you must ingest the domain that is being queried and the\ - \ IP of the host originating the request. Ideally, you should also be ingesting\ - \ the answer to the query and the query type. This approach allows you to also create\ - \ your own localized passive DNS capability which can aid you in future investigations.\ - \ You will have to add legitimate domain names to the `legit_domains.csv` file shipped\ - \ with the app. \\\n **Splunk>Phantom Playbook Integration**\\\nIf Splunk>Phantom\ - \ is also configured in your environment, a Playbook called `Lets Encrypt Domain\ - \ Investigate` can be configured to run when any results are found by this detection\ - \ search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`,\ - \ add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response\ - \ Actions when configuring this detection search, and set the corresponding Playbook\ - \ to active. \\\n(Playbook link:`https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/`).\\\ - \n" -id: 24dd17b1-e2fb-4c31-878c-d4f226595bfa -investigations: - - id: bc91a8cf-35e7-4bb2-2240-e756cc06fd73 - name: Get Certificate logs for a domain - type: splunk - - id: c096f721-8842-42ce-2fc7-742d8272b712 - name: Domain Certificate Investigation - type: phantom -known_false_positives: If a known good domain is not listed in the legit_domains.csv - file, then the search could give you false postives. Please update that lookup file - to filter out DNS requests to legitimate domains. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - - CIS 7 - kill_chain_phases: - - Delivery - - Command and Control - mitre_attack: - - Spearphishing Link - - Command and Control - nist: - - ID.AM - - PR.DS - - PR.IP - - DE.AE - - DE.CM -modification_date: '2019-04-29' -name: Detect DNS requests to Phishing Sites leveraging EvilGinx2 -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/dns_query_length_mltk.yml b/detections/dns_query_length_mltk.yml deleted file mode 100644 index 84914faa68..0000000000 --- a/detections/dns_query_length_mltk.yml +++ /dev/null @@ -1,151 +0,0 @@ -asset_type: Endpoint -baselines: - - id: c914844c-0ff5-4efc-8d44-c063443129ba - name: Baseline of DNS Query Length - MLTK - type: splunk -confidence: medium -creation_date: '2019-05-08' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: This search allows you to identify DNS requests that are unusually large - for the record type being requested in your environment. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src - rule_description: Identify DNS traffic with unusual query lengths by record - type - rule_title: DNS query length outliers - risk: - risk_object: src - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as start_time max(_time) - as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution - by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval query_length = len(query) - | apply dns_query_pdfmodel threshold=0.01 | rename "IsOutlier(query_length)" - as isOutlier | search isOutlier > 0 | sort -query_length | table start_time - end_time query record_type count src dest query_length | `dns_query_length_mltk_filter` ' - suppress: - suppress_fields: query - suppress_period: 43200s -eli5: Attackers often use random, long domain names for components of their attack - infrastructure. This search leverages the probability distribution function algorithm - provided by the Machine Learning Toolkit (MLTK) to identify outliers in the length - of the DNS query for each record type observed. The companion search "Baseline of - DNS Query Length - MLTK" creates a machine-learning (ML) model built over the historical - data used by this search. The determination of what is considered an outlier may - be adjusted via the threshold parameter in the search. More information on the algorithm - used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -entities: - - src -how_to_implement: 'To successfully implement this search, you will need to ensure - that DNS data is populating the Network_Resolution data model. In addition, the - Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your - search heads, along with any required dependencies. Finally, the support search - "Baseline of DNS Query Length - MLTK" must be executed before this detection search, - because it builds a machine-learning (ML) model over the historical data used by - this search. It is important that this search is run in the same app context as - the associated support search, so that the model created by the support search is - available for use. You should periodically re-run the support search to rebuild - the model with the latest data available in your environment.\ - - This search produces fields (`query`,`query_length`,`count`) that are not yet supported - by ES Incident Review and therefore cannot be viewed when a notable event is raised. - These fields contribute additional context to the notable. To see the additional - metadata, add the following fields, if not already present, to Incident Review - - Event Attributes (Configure > Incident Management > Incident Review Settings > Add - New Entry):\\n1. **Label:** DNS Query, **Field:** query\ - - 1. \ - - 1. **Label:** DNS Query Length, **Field:** query_length\ - - 1. \ - - 1. **Label:** Number of events, **Field:** count\ - - Detailed documentation on how to create a new field within Incident Review may be - found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: 85fbcfe8-9718-4911-adf6-7000d077a3a9 -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 - name: Get DNS traffic ratio - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: If you are seeing more results than desired, you may consider - reducing the value for threshold in the search. You should also periodically re-run - the support search to re-build the ML model on the latest data. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - - CIS 12 - kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Exfiltration - - Commonly Used Port - mitre_technique_id: - - T1071 - nist: - - PR.PT - - DE.AE - - DE.CM -modification_date: '2020-01-22' -name: DNS Query Length Outliers - MLTK -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/dns_query_length_outliers___mltk.yml b/detections/dns_query_length_outliers___mltk.yml new file mode 100644 index 0000000000..a3082433b8 --- /dev/null +++ b/detections/dns_query_length_outliers___mltk.yml @@ -0,0 +1,63 @@ +name: DNS Query Length Outliers - MLTK +id: 85fbcfe8-9718-4911-adf6-7000d077a3a9 +version: '2.0' +date: '2020-01-22' +description: This search allows you to identify DNS requests that are unusually large + for the record type being requested in your environment. +how_to_implement: 'To successfully implement this search, you will need to ensure + that DNS data is populating the Network_Resolution data model. In addition, the + Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your + search heads, along with any required dependencies. Finally, the support search + "Baseline of DNS Query Length - MLTK" must be executed before this detection search, + because it builds a machine-learning (ML) model over the historical data used by + this search. It is important that this search is run in the same app context as + the associated support search, so that the model created by the support search is + available for use. You should periodically re-run the support search to rebuild + the model with the latest data available in your environment.\ + + This search produces fields (`query`,`query_length`,`count`) that are not yet supported + by ES Incident Review and therefore cannot be viewed when a notable event is raised. + These fields contribute additional context to the notable. To see the additional + metadata, add the following fields, if not already present, to Incident Review - + Event Attributes (Configure > Incident Management > Incident Review Settings > Add + New Entry):\\n1. **Label:** DNS Query, **Field:** query\ + + 1. \ + + 1. **Label:** DNS Query Length, **Field:** query_length\ + + 1. \ + + 1. **Label:** Number of events, **Field:** count\ + + Detailed documentation on how to create a new field within Incident Review may be + found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as start_time + max(_time) as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution + by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval + query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename "IsOutlier(query_length)" + as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time + query record_type count src dest query_length | `dns_query_length_mltk_filter` ' +known_false_positives: If you are seeing more results than desired, you may consider + reducing the value for threshold in the search. You should also periodically re-run + the support search to re-build the ML model on the latest data. +tags: + analytics_story: + - Hidden Cobra Malware + - Suspicious DNS Traffic + - Command and Control + mitre_attack_id: + - T1043 + kill_chain_phases: + - Command and Control + cis20: + - CIS 8 + - CIS 12 + nist: + - PR.PT + - DE.AE + - DE.CM diff --git a/detections/dns_query_length_with_high_standard_deviation.yml b/detections/dns_query_length_with_high_standard_deviation.yml index 551e5c046b..3c76c72037 100644 --- a/detections/dns_query_length_with_high_standard_deviation.yml +++ b/detections/dns_query_length_with_high_standard_deviation.yml @@ -1,114 +1,34 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro +name: DNS Query Length With High Standard Deviation +id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f5 +version: '1.0' +date: '2020-01-22' description: This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src - rule_description: Filter DNS requests and compute the standard deviation then - filter on 2 times the standard deviation - rule_title: DNS query length with high standard deviation - risk: - risk_object: src - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution by - DNS.query DNS.record_type | `drop_dm_object_name("DNS")` | eval query_length - = len(query) | table query query_length record_type count | eventstats stdev(query_length) - AS stdev avg(query_length) AS avg p50(query_length) AS p50| where query_length>(avg+stdev*2) - | eval z_score=(query_length-avg)/stdev | `dns_query_length_with_high_standard_deviation_filter` ' - suppress: - suppress_fields: query - suppress_period: 43200s -eli5: Attackers often use random, long domain names for their attack infrastructure. - This search looks at all the queries observed over the search time frame, and identifies - any domains being resolved with names that are greater that 2 times the standard - deviation. -entities: - - src how_to_implement: To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. -id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f5 -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 - name: Get DNS traffic ratio - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It's possible there can be long domain names that are legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - - CIS 12 - kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Exfiltration - - Commonly Used Port - mitre_technique_id: - - T1071 - nist: - - PR.PT - - DE.AE - - DE.CM -modification_date: '2020-01-22' -name: DNS Query Length With High Standard Deviation -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +type: ESCU references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution + by DNS.query DNS.record_type | `drop_dm_object_name("DNS")` | eval query_length + = len(query) | table query query_length record_type count | eventstats stdev(query_length) + AS stdev avg(query_length) AS avg p50(query_length) AS p50| where query_length>(avg+stdev*2) + | eval z_score=(query_length-avg)/stdev | `dns_query_length_with_high_standard_deviation_filter` ' +known_false_positives: It's possible there can be long domain names that are legitimate. +tags: + analytics_story: + - Hidden Cobra Malware + - Suspicious DNS Traffic + - Command and Control + mitre_attack_id: + - T1043 + kill_chain_phases: + - Command and Control + cis20: + - CIS 8 + - CIS 12 + nist: + - PR.PT + - DE.AE + - DE.CM diff --git a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml new file mode 100644 index 0000000000..813739def1 --- /dev/null +++ b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml @@ -0,0 +1,37 @@ +name: DNS Query Requests Resolved by Unauthorized DNS Servers +id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f6 +version: '2.0' +date: '2020-01-17' +description: This search will detect DNS requests resolved by unauthorized DNS servers. + Legitimate DNS servers should be identified in the Enterprise Security Assets and + Identity Framework. +how_to_implement: To successfully implement this search you will need to ensure that + DNS data is populating the Network_Resolution data model. It also requires that + your DNS servers are identified correctly in the Assets and Identity table of Enterprise + Security. +type: ESCU +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution + where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src + DNS.dest | `drop_dm_object_name("DNS")` | `unauthorized_dns_servers_filter`' +known_false_positives: Legitimate DNS activity can be detected in this search. Investigate, + verify and update the list of authorized DNS servers as appropriate. +tags: + analytics_story: + - Host Redirection + - Suspicious DNS Traffic + - Command and Control + - DNS Hijacking + kill_chain_phases: + - Command and Control + cis20: + - CIS 1 + - CIS 3 + - CIS 8 + - CIS 12 + nist: + - ID.AM + - PR.DS + - PR.IP + - DE.AE + - DE.CM diff --git a/detections/dns_record_changed.yml b/detections/dns_record_changed.yml index fb54624042..0bdc39357c 100644 --- a/detections/dns_record_changed.yml +++ b/detections/dns_record_changed.yml @@ -1,59 +1,10 @@ -asset_type: Endpoint -baselines: - - id: c096f721-8842-42ce-bfc7-74bd8c72b7c3 - name: Discover DNS records - type: splunk -confidence: medium -creation_date: '2019-02-14' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro +name: DNS record changed +id: 44d3a43e-dcd5-49f7-8356-5209bb369065 +version: '2.0' +date: '2020-01-16' description: The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. -detect: - splunk: - correlation_rule: - lookups: - - discovered_dns_records - macros: - - dns_record_changed_filter - notable: - nes_fields: src - rule_description: The table represents a list of DNS records and their responses - for corporate domains that have recently changed - rule_title: DNS record changed - risk: - risk_object: src - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| inputlookup discovered_dns_records.csv | rename answer as discovered_answer - | join domain[|tstats `security_content_summariesonly` count values(DNS.record_type) as - type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution - where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query - | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] - | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer - | makemv current_answer | mvexpand current_answer | makemv discovered_answer - | eval n=mvfind(discovered_answer, current_answer) | where isnull(n) | `dns_record_changed_filter`' - suppress: - suppress_fields: src - suppress_period: 28800s -eli5: Using a lookup `discover_dns_records` generated by support search "Discover - DNS records" we check previous network traffic and make sure the responses have - not changed. -entities: - - src - - dest how_to_implement: "To successfully implement this search you will need to ensure that\ \ DNS data is populating the `Network_Resolution` data model. It also requires that\ \ the `discover_dns_record` lookup table be populated by the included support search\ @@ -67,47 +18,32 @@ how_to_implement: "To successfully implement this search you will need to ensure \ when configuring this detection search, and set the corresponding Playbook to\ \ active. \\\n(Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\\\ \n" -id: 44d3a43e-dcd5-49f7-8356-5209bb369065 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: c096f721-8842-42ce-bfc7-74bd9a72c712 - name: DNS Hijack Enrichment - type: phantom +type: ESCU +author: Jose Hernandez, Splunk +search: '| inputlookup discovered_dns_records.csv | rename answer as discovered_answer + | join domain[|tstats `security_content_summariesonly` count values(DNS.record_type) + as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution + where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query + | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] + | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer + | makemv current_answer | mvexpand current_answer | makemv discovered_answer | + eval n=mvfind(discovered_answer, current_answer) | where isnull(n) | `dns_record_changed_filter`' known_false_positives: Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: - cis20: - - CIS 1 - - CIS 3 - - CIS 8 - - CIS 12 +tags: + analytics_story: + - DNS Hijacking kill_chain_phases: - - Command and Control - mitre_attack: - - Exfiltration - - Command and Control - - Defense Evasion + - Command and Control + cis20: + - CIS 1 + - CIS 3 + - CIS 8 + - CIS 12 nist: - - ID.AM - - PR.DS - - PR.IP - - DE.AE - - DE.CM -modification_date: '2020-01-16' -name: DNS record changed -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' + - ID.AM + - PR.DS + - PR.IP + - DE.AE + - DE.CM diff --git a/detections/dns_tunnelling.yml b/detections/dns_tunnelling.yml deleted file mode 100644 index a492f3faba..0000000000 --- a/detections/dns_tunnelling.yml +++ /dev/null @@ -1,128 +0,0 @@ -asset_type: Endpoint -confidence: low -creation_date: '2017-07-19' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: This search is used to detect DNS tunneling, by calculating the sum of - the length of DNS queries and DNS answers. The search also filters out potential - false positives by filtering out queries made to internal systems and the queries - originating from internal DNS, Web, and Email servers. Endpoints using DNS as a - method of transmission for data exfiltration, command and control, or evasion of - security controls can often be detected by noting an unusually large volume of DNS - traffic. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src - rule_description: Potential DNS tunnel detected from $src$ which may be exfiltrating - large data - rule_title: DNS tunnel detected on $src$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` dc("DNS.query") as count from datamodel=Network_Resolution where - nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) - NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR - "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) - by "DNS.src","DNS.query" | rename "DNS.src" as src "DNS.query" as message - | eval length=len(message) | stats sum(length) as length by src | append [ - tstats `security_content_summariesonly` dc("DNS.answer") as count from datamodel=Network_Resolution where - nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) - NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR - "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) - by "DNS.src","DNS.answer" | rename "DNS.src" as src "DNS.answer" as message - | eval message=if(message=="unknown","", message) | eval length=len(message) - | stats sum(length) as length by src ] | stats sum(length) as length by src - | where length > 10000' - suppress: - suppress_fields: src, query - suppress_period: 43200s -eli5: The search will calculate the distinct count and sum of the length of DNS queries - made and DNS answers received by a particular host to alert the analyst if the combined - length is greater than 10000, which is not typical behavior. -entities: - - src -how_to_implement: To successfully implement this search, we must ensure that DNS data - is being ingested and mapped to the appropriate fields in the Network_Resolution - data model. Fields like src_category are automatically provided by the Assets and - Identity Framework shipped with Splunk Enterprise Security. You will need to ensure - you are using the Assets and Identity Framework and populating the src_category - field. You will also need to enable the `cim_corporate_web_domain_search()` macro - which will essentially filter out the DNS queries made to the corporate web domains - to reduce alert fatigue. -id: 104658f4-afdc-499f-9719-17a43f9826f4 -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 - name: Get DNS traffic ratio - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It's possible that normal DNS traffic will exhibit this behavior. - If an alert is generated, please investigate and validate as appropriate. The threshold - can also be modified to better suit your environment. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Command and Control - - Exfiltration - - Commonly Used Port - nist: - - PR.PT - - PR.DS -modification_date: '2017-09-18' -name: Detection of DNS Tunnels -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/dragonfly_schtasks.yml b/detections/dragonfly_schtasks.yml deleted file mode 100644 index fdff4b89a9..0000000000 --- a/detections/dragonfly_schtasks.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-03-19' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for flags passed to schtasks.exe on the command-line - that indicate a task name associated with the Dragonfly threat actor was created - or deleted. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: This search looks for flags passed to schtasks.exe on the - command line that indicate that a task--whose name is associated with the - Dragonfly threat actor--has been created or deleted - rule_title: Scheduled task used by Dragonfly threat actor detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - macros: - - dragonfly_schtasks_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe by - Processes.user Processes.process_name Processes.parent_process_name Processes.dest | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | - search (process=*delete* OR process=*create*) process=*reset* | `dragonfly_schtasks_filter`' - suppress: - suppress_fields: dest, process_name, process - suppress_period: 28800s -eli5: The search looks for execution of schtasks.exe with parameters that indicate - that a specific task "reset," whose name is associated with the Dragonfly threat - actor--has been created or deleted. Schtasks.exe is a native Windows program that - is used to schedule tasks on local or remote systems. Attackers often leverage this - capability to schedule the execution of commands or establish persistence. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: d5af132c-7c17-439c-9d31-13d55340f36c -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: No known false positives -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Scheduled Task - nist: - - PR.IP -modification_date: '2020-03-16' -name: Scheduled Task Name Used by Dragonfly Threat Actors -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/dump_lsass_via_comsvcs_dll.yml b/detections/dump_lsass_via_comsvcs_dll.yml index 77a2020584..46fde885b2 100644 --- a/detections/dump_lsass_via_comsvcs_dll.yml +++ b/detections/dump_lsass_via_comsvcs_dll.yml @@ -1,91 +1,33 @@ -asset_type: Endpoint -confidence: high -creation_date: '2020-02-21' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Sysmon +name: Dump LSASS via comsvcs DLL +id: 8943b567-f14d-4ee8-a0bb-2121d4ce3184 +version: '1.0' +date: '2020-02-21' description: Detect the usage of comsvcs.dll for dumping the lsass process. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, process_name, process - rule_description: An attempt to dump credentials of lsass by $user$ was detected. - rule_title: Dump LSASS via comsvcs DLL - risk: - risk_object: user - risk_object_type: - - user - risk_score: 80 - macros: - - dump_lsass_via_comsvcs_dll_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime - from datamodel=Endpoint.Processes where Processes.process_name=rundll32.exe Processes.process=*comsvcs.dll* - Processes.process=*MiniDump* by Processes.user Processes.process_name Processes.process Processes.dest - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | `dump_lsass_via_comsvcs_dll_filter`' - suppress: - suppress_fields: process_name, dest - suppress_period: 86400s -eli5: LSASS is the Local Security Authority Subsystem Service, which is responsible for storing the user credentials. - There are multiple ways to attack LSASS. This search detects the usage of comsvcs.dll for dumping the LSASS process. -entities: - - dest how_to_implement: You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -id: 8943b567-f14d-4ee8-a0bb-2121d4ce3184 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk -known_false_positives: None identified. -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_technique_id: - - T1003 - mitre_attack: - - Credential Access - - Credential Dumping - nist: - - DE.CM -modification_date: '2020-02-21' -name: Dump LSASS via comsvcs DLL -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss +type: ESCU references: - - https://modexp.wordpress.com/2019/08/30/minidumpwritedump-via-com-services-dll/ - - https://twitter.com/SBousseaden/status/1167417096374050817 -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' +- https://modexp.wordpress.com/2019/08/30/minidumpwritedump-via-com-services-dll/ +- https://twitter.com/SBousseaden/status/1167417096374050817 +author: Patrick Bareiss, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process_name=rundll32.exe + Processes.process=*comsvcs.dll* Processes.process=*MiniDump* by Processes.user Processes.process_name + Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `dump_lsass_via_comsvcs_dll_filter`' +known_false_positives: None identified. +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 16 + nist: + - DE.CM diff --git a/detections/dyn_dns_web_traffic.yml b/detections/dyn_dns_web_traffic.yml deleted file mode 100644 index dd6a95015f..0000000000 --- a/detections/dyn_dns_web_traffic.yml +++ /dev/null @@ -1,125 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-09-06' -data_metadata: - data_models: - - Web - data_source: - - Web Traffic - providing_technologies: - - Splunk Stream - - Bro - - Bluecoat - - Palo Alto Firewall -description: This search looks for web connections to dynamic DNS providers. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, url, dest - rule_description: The host $src$ has been detected making a web request to - $url$, which is a listed as a dynamic DNS provider. - rule_title: Dynamic DNS web traffic detected on $src$. - risk: - risk_object: src - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Web.url) - as url min(_time) as firstTime from datamodel=Web where Web.status=200 by - Web.src Web.dest Web.status | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` - | `dynamic_dns_web_traffic`' - suppress: - suppress_fields: src, url , dest - suppress_period: 86400s -eli5: This search looks for hosts in your environment that may be communicating with - a dynamic DNS provider. It checks each URL an endpoint is connecting to against - a list of dynamic DNS providers. It returns the source and destination IP address - of the web request, the URL requested, and the first time the event occurred. -entities: - - src -how_to_implement: 'This search requires you to be ingesting web-traffic logs. You - can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis - tool, such as Bro or Splunk Stream. The web data model must contain the URL being - requested, the IP address of the host initiating the request, and the destination - IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, - which contains a non-exhaustive list of dynamic DNS providers. Consider periodically - updating this local lookup file with new domains.\ - - This search produces fields (`isDynDNS`) that are not yet supported by ES Incident - Review and therefore cannot be viewed when a notable event is raised. These fields - contribute additional context to the notable. To see the additional metadata, add - the following fields, if not already present, to Incident Review - Event Attributes - (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. - **Label:** IsDynamicDNS, **Field:** isDynDNS\ - - Detailed documentation on how to create a new field within Incident Review may be - found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: 134da869-e264-4a8f-8d7e-fcd01c18f301 -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 - name: Get DNS traffic ratio - type: splunk - - id: 2f5b960b-71df-49c0-affc-74992ce60e45 - name: Investigate Web Activity From src_ip - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is possible that list of dynamic DNS providers is outdated - and/or that the URL being requested is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 7 - - CIS 8 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Command and Control - - Web Service - - Exfiltration Over Command and Control Channel - - Defense Evasion - nist: - - PR.IP - - DE.DP -modification_date: '2018-09-06' -name: Detect web traffic to dynamic domain providers -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/ec2_excessive_runinstances_mltk.yml b/detections/ec2_excessive_runinstances_mltk.yml deleted file mode 100644 index 7ca29a42c5..0000000000 --- a/detections/ec2_excessive_runinstances_mltk.yml +++ /dev/null @@ -1,107 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fa5634df-fb05-4b4b-aba0-6115138bb1ba - name: Baseline of Excessive AWS Instances Launched by User - MLTK - type: splunk -confidence: medium -creation_date: '2019-11-14' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where a user successfully launches - an abnormally high number of instances. -detect: - splunk: - correlation_rule: - macros: - - ec2_excessive_runinstances_mltk_input_filter - notable: - nes_fields: src_user - rule_description: An abnormally high number of instances were launched by - a user within in a 10-minute window - rule_title: High Number of instances launched by $src_user$ - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: '*/10 * * * *' - earliest_time: -70m@m - latest_time: -10m@m - search: >- - sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` - | bucket span=10m _time - | stats count as instances_launched by _time src_user - | apply ec2_excessive_runinstances_v1 - | rename "IsOutlier(instances_launched)" as isOutlier - | where isOutlier=1 - suppress: - suppress_fields: src_user - suppress_period: 3600s -eli5: In this search, we query CloudTrail logs to look for events where an instance - is successfully launched by a particular user. Since we want to detect a high number - of instances launched within a short period, we create event buckets for 10-minute - windows. We then compare the total number of instances launched by a particular - user against the saved baseline data in the model ec2_excessive_runinstances_v1. -entities: - - src_user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. The threshold value should be tuned to your environment. -id: dec41ad5-d579-42cb-b4c6-f5dbb778bbe5 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 - name: Get EC2 Launch Details - type: splunk - - id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 - name: Get EC2 Instance Details by instanceId - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: Many service accounts configured within an AWS infrastructure - are known to exhibit this behavior. Please adjust the threshold values and filter - out service accounts from the output. Always verify if this search alerted on a - human user. -maintainers: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - DE.DP - - DE.AE -modification_date: '2019-11-14' -name: Abnormally High AWS Instances Launched by User - MLTK -original_authors: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/ec2_excessive_terminateinstances_mltk.yml b/detections/ec2_excessive_terminateinstances_mltk.yml deleted file mode 100644 index d174f005eb..0000000000 --- a/detections/ec2_excessive_terminateinstances_mltk.yml +++ /dev/null @@ -1,107 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: b28ed6de-e4ba-40f7-ae0a-93a088c774ab - name: Baseline of Excessive AWS Instances Terminated by User - MLTK - type: splunk -confidence: medium -creation_date: '2019-11-14' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where a user successfully terminates - an abnormally high number of instances. -detect: - splunk: - correlation_rule: - macros: - - ec2_excessive_terminateinstances_mltk_input_filter - notable: - nes_fields: src_user - rule_description: An abnormally high number of instances were terminated by - a user within in a 10-minute window - rule_title: High Number of instances terminated by $src_user$ - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: '*/10 * * * *' - earliest_time: -70m@m - latest_time: -10m@m - search: >- - sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` - | bucket span=10m _time - | stats count as instances_terminated by _time src_user - | apply ec2_excessive_terminateinstances_v1 - | rename "IsOutlier(instances_terminated)" as isOutlier - | where isOutlier=1 - suppress: - suppress_fields: src_user - suppress_period: 3600s -eli5: In this search, we query CloudTrail logs to look for events where an instance - is successfully terminated by a particular user. Since we want to detect a high number - of instances terminated within a short period, we create event buckets for 10-minute - windows. We then compare the total number of instances terminated by a particular - user against the saved baseline data in the model ec2_excessive_terminateinstances_v1. -entities: - - src_user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. The threshold value should be tuned to your environment. -id: 1c02b86a-cd85-473e-a50b-014a9ac8fe3e -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 - name: Get EC2 Launch Details - type: splunk - - id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 - name: Get EC2 Instance Details by instanceId - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: Many service accounts configured within an AWS infrastructure - are known to exhibit this behavior. Please adjust the threshold values and filter - out service accounts from the output. Always verify if this search alerted on a - human user. -maintainers: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - DE.DP - - DE.AE -modification_date: '2019-11-14' -name: Abnormally High AWS Instances Terminated by User - MLTK -original_authors: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/ec2_instance_created_by_previously_unseen_user.yml b/detections/ec2_instance_created_by_previously_unseen_user.yml deleted file mode 100644 index 6d60fcf56a..0000000000 --- a/detections/ec2_instance_created_by_previously_unseen_user.yml +++ /dev/null @@ -1,103 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: 6c767ac0-0906-4355-9a83-927f5ee7bdad - name: Previously Seen EC2 Launches By User - type: splunk -confidence: medium -creation_date: '2018-03-15' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for EC2 instances being created by users who have not - created them before. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest - rule_description: The EC2 instance $dest$ was created by $user$. This user - has never created an EC2 instance before. - rule_title: EC2 Instance Created By Previously Unseen User $user$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail - eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime - latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as - arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv | stats - min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup - previously_seen_ec2_launches_by_user.csv | eval newUser=if(firstTime >= relative_time(now(), - "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType - as instanceType, responseElements.instancesSet.items{}.instanceId as dest, - userIdentity.arn as user | table _time, user, dest, instanceType - suppress: - suppress_fields: user, dest - suppress_period: 14400s -eli5: The subsearch returns the ARNs of all successful EC2 instance launches within - the last hour and then appends the historical data in the lookup file to those results. It - then recalculates the `firstTime` and `lastTime` field for each ARN and returns - only those ARNs that have first been seen in the past hour. This is combined with - the main search to return the time, user, and instance id of those systems. -entities: - - dest -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. This search works best when you run the "Previously Seen EC2 Launches By - User" support search once to create a history of previously seen ARNs. -id: 22773e84-bac0-4595-b086-20d3f735b4f1 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 - name: Get EC2 Launch Details - type: splunk - - id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 - name: Get EC2 Instance Details by instanceId - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: It's possible that a user will start to create EC2 instances - when they haven't before for any number of reasons. Verify with the user that is - launching instances that this is the intended behavior. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 1 - nist: - - ID.AM -modification_date: '2018-03-12' -name: EC2 Instance Started With Previously Unseen User -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/ec2_instance_modified_by_previously_unseen_user.yml b/detections/ec2_instance_modified_by_previously_unseen_user.yml deleted file mode 100644 index 7703d45119..0000000000 --- a/detections/ec2_instance_modified_by_previously_unseen_user.yml +++ /dev/null @@ -1,93 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: 4d69091b-d975-4267-85df-888bd41034eb - name: Previously Seen EC2 Modifications By User - type: splunk -confidence: medium -creation_date: '2018-04-09' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for EC2 instances being modified by users who have - not previously modified them. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest - rule_description: The EC2 instance $dest$ was modified by $user$. This user - has never modified an EC2 instance before. - rule_title: EC2 Instance Modified By Previously Unseen User $user$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail `ec2_modification_api_calls` [search sourcetype=aws:cloudtrail - `ec2_modification_api_calls` errorCode=success | stats earliest(_time) as firstTime - latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as - arn | inputlookup append=t previously_seen_ec2_modifications_by_user | stats - min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup - previously_seen_ec2_modifications_by_user | eval newUser=if(firstTime >= relative_time(now(), - "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest - responseElements.instancesSet.items{}.instanceId | spath output=user userIdentity.arn - | table _time, user, dest - suppress: - suppress_fields: user, dest - suppress_period: 14400s -eli5: The subsearch returns the ARNs of all successful EC2 instance modifications - within the last hour and then appends the historical data in the lookup file to - those results. EC2 modification APIs are defined by the macro `ec2_modification_api_calls`. - The search then recalculates the `firstTime` and `lastTime` field for each ARN and - returns only those ARNs that have first been seen in the past hour. This is combined - with the main search to return the time, user, and instance ID of those systems. -entities: - - dest -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. This search works best when you run the "Previously Seen EC2 Launches By - User" support search once to create a history of previously seen ARNs. To add or - remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -id: 56f91724-cf3f-4666-84e1-e3712fb41e76 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 - name: Get EC2 Instance Details by instanceId - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk -known_false_positives: It's possible that a new user will start to modify EC2 instances - when they haven't before for any number of reasons. Verify with the user that is - modifying instances that this is the intended behavior. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 1 - nist: - - ID.AM -modification_date: '2018-04-09' -name: EC2 Instance Modified With Previously Unseen User -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/ec2_instance_modified_with_previously_unseen_user.yml b/detections/ec2_instance_modified_with_previously_unseen_user.yml new file mode 100644 index 0000000000..e8537447c4 --- /dev/null +++ b/detections/ec2_instance_modified_with_previously_unseen_user.yml @@ -0,0 +1,33 @@ +name: EC2 Instance Modified With Previously Unseen User +id: 56f91724-cf3f-4666-84e1-e3712fb41e76 +version: '2.0' +date: '2018-04-09' +description: This search looks for EC2 instances being modified by users who have + not previously modified them. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. This search works best when you run the "Previously Seen EC2 Launches By + User" support search once to create a history of previously seen ARNs. To add or + remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail `ec2_modification_api_calls` [search sourcetype=aws:cloudtrail + `ec2_modification_api_calls` errorCode=success | stats earliest(_time) as firstTime + latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | + inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) + as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user + | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename + arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId + | spath output=user userIdentity.arn | table _time, user, dest +known_false_positives: It's possible that a new user will start to modify EC2 instances + when they haven't before for any number of reasons. Verify with the user that is + modifying instances that this is the intended behavior. +tags: + analytics_story: + - Unusual AWS EC2 Modifications + cis20: + - CIS 1 + nist: + - ID.AM diff --git a/detections/ec2_instance_started_in_previously_unseen_region.yml b/detections/ec2_instance_started_in_previously_unseen_region.yml new file mode 100644 index 0000000000..6054c44ec9 --- /dev/null +++ b/detections/ec2_instance_started_in_previously_unseen_region.yml @@ -0,0 +1,34 @@ +name: EC2 Instance Started In Previously Unseen Region +id: ada0f478-84a8-4641-a3f3-d82362d6fd75 +version: '1.0' +date: '2018-02-23' +description: This search looks for CloudTrail events where an instance is started + in a particular region in the last one hour and then compares it to a lookup file + of previously seen regions where an instance was started +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. Run the "Previously seen AWS Regions" support search only once to create + of baseline of previously seen regions. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=aws:cloudtrail earliest=-1h StartInstances | stats earliest(_time) + as earliest latest(_time) as latest by awsRegion | inputlookup append=t previously_seen_aws_regions.csv + | stats min(earliest) as earliest max(latest) as latest by awsRegion | outputlookup + previously_seen_aws_regions.csv | eval regionStatus=if(earliest >= relative_time(now(),"-1d@d"), + "Instance Started in a New Region","Previously Seen Region") | `security_content_ctime(earliest)` + | `security_content_ctime(latest)` | where regionStatus="Instance Started in a New + Region" +known_false_positives: It's possible that a user has unknowingly started an instance + in a new region. Please verify that this activity is legitimate. +tags: + analytics_story: + - AWS Cryptomining + - Suspicious AWS EC2 Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 12 + nist: + - DE.DP + - DE.AE diff --git a/detections/ec2_instance_started_with_previously_unseen_ami.yml b/detections/ec2_instance_started_with_previously_unseen_ami.yml index 3677473773..e0edccaca3 100644 --- a/detections/ec2_instance_started_with_previously_unseen_ami.yml +++ b/detections/ec2_instance_started_with_previously_unseen_ami.yml @@ -1,88 +1,34 @@ -asset_type: AWS Instance -baselines: - - id: bb1bd99d-1e93-45f1-9571-cfed42d372b9 - name: Previously Seen EC2 AMIs - type: splunk -confidence: medium -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: EC2 Instance Started With Previously Unseen AMI +id: 347ec301-601b-48b9-81aa-9ddf9c829dd3 +version: '1.0' +date: '2018-03-12' description: This search looks for EC2 instances being created with previously unseen AMIs. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: The EC2 instance $dest$ was created with previously unused - AMI $amiID$ - rule_title: EC2 Instance Type $dest$ Created With New AMI - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail - eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime - latest(_time) as lastTime by requestParameters.instancesSet.items{}.imageId - | rename requestParameters.instancesSet.items{}.imageId as amiID | inputlookup - append=t previously_seen_ec2_amis.csv | stats min(firstTime) as firstTime max(lastTime) - as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | eval newAMI=if(firstTime - >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` - | where newAMI=1 | rename amiID as requestParameters.instancesSet.items{}.imageId - | table requestParameters.instancesSet.items{}.imageId] | rename requestParameters.instanceType - as instanceType, responseElements.instancesSet.items{}.instanceId as dest, - userIdentity.arn as arn, requestParameters.instancesSet.items{}.imageId as - amiID | table firstTime, lastTime, arn, amiID, dest, instanceType - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: The subsearch returns the AMI image ID of all successful EC2 instance launches - within the last hour and then appends the historical data from the lookup file to - those results. It then recalculates the earliest and latest seen time field for - each AMI image ID and returns only those AMI image IDs that have first been seen - in the past hour. This is combined with the main search to return the time, user, - and instance id of those systems. -entities: - - dest how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. -id: 347ec301-601b-48b9-81aa-9ddf9c829dd3 -investigations: - - id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 - name: Get EC2 Launch Details - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail + eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) + as lastTime by requestParameters.instancesSet.items{}.imageId | rename requestParameters.instancesSet.items{}.imageId + as amiID | inputlookup append=t previously_seen_ec2_amis.csv | stats min(firstTime) + as firstTime max(lastTime) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv + | eval newAMI=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + | where newAMI=1 | rename amiID as requestParameters.instancesSet.items{}.imageId + | table requestParameters.instancesSet.items{}.imageId] | rename requestParameters.instanceType + as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn + as arn, requestParameters.instancesSet.items{}.imageId as amiID | table firstTime, + lastTime, arn, amiID, dest, instanceType known_false_positives: After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: +tags: + analytics_story: + - AWS Cryptomining cis20: - - CIS 1 + - CIS 1 nist: - - ID.AM -modification_date: '2018-03-12' -name: EC2 Instance Started With Previously Unseen AMI -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' + - ID.AM diff --git a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml index d4a2913c5f..a6bb0438df 100644 --- a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml +++ b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml @@ -1,93 +1,34 @@ -asset_type: AWS Instance -baselines: - - id: b8f029f2-65a6-4d76-be98-dad1c9d59c45 - name: Previously Seen EC2 Instance Types - type: splunk -confidence: medium -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS +name: EC2 Instance Started With Previously Unseen Instance Type +id: 65541c80-03c7-4e05-83c8-1dcd57a2e1ad +version: '2.0' +date: '2020-02-07' description: This search looks for EC2 instances being created with previously unseen instance types. -detect: - splunk: - correlation_rule: - notable: - nes_fields: instanceType - rule_description: The EC2 instance type $instanceType$ was used for the first - time to create $dest$. - rule_title: New EC2 Instance Type $instanceType$ detected - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=RunInstances - [search sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success - | fillnull value="m1.small" requestParameters.instanceType - | stats earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType - | rename requestParameters.instanceType as instanceType - | inputlookup append=t previously_seen_ec2_instance_types.csv - | stats min(earliest) as earliest max(latest) as latest by instanceType - | outputlookup previously_seen_ec2_instance_types.csv - | eval newType=if(earliest >= relative_time(now(), "-70m@m"), 1, 0) - | `security_content_ctime(earliest)` - | `security_content_ctime(latest)` - | where newType=1 - | rename instanceType as requestParameters.instanceType - | table requestParameters.instanceType] - | spath output=user userIdentity.arn - | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId - as dest | table _time, user, dest, instanceType - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: The subsearch returns the instance types of all successful EC2 instance launches - within the last hour and then appends the historical data in the lookup file to - those results. It then recalculates the earliest seen time field for each instance - type and returns only those instance types that has first been seen in the past - hour. This is combined with the main search to return the time, user, and instance - id of those systems. -entities: - - dest how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. -id: 65541c80-03c7-4e05-83c8-1dcd57a2e1ad -investigations: - - id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 - name: Get EC2 Launch Details - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail + eventName=RunInstances errorCode=success | fillnull value="m1.small" requestParameters.instanceType + | stats earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType + | rename requestParameters.instanceType as instanceType | inputlookup append=t previously_seen_ec2_instance_types.csv + | stats min(earliest) as earliest max(latest) as latest by instanceType | outputlookup + previously_seen_ec2_instance_types.csv | eval newType=if(earliest >= relative_time(now(), + "-70m@m"), 1, 0) | `security_content_ctime(earliest)` | `security_content_ctime(latest)` + | where newType=1 | rename instanceType as requestParameters.instanceType | table + requestParameters.instanceType] | spath output=user userIdentity.arn | rename requestParameters.instanceType + as instanceType, responseElements.instancesSet.items{}.instanceId as dest | table + _time, user, dest, instanceType known_false_positives: It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: +tags: + analytics_story: + - AWS Cryptomining cis20: - - CIS 1 + - CIS 1 nist: - - ID.AM -modification_date: '2020-02-07' -name: EC2 Instance Started With Previously Unseen Instance Type -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' + - ID.AM diff --git a/detections/ec2_instance_started_with_previously_unseen_user.yml b/detections/ec2_instance_started_with_previously_unseen_user.yml new file mode 100644 index 0000000000..0ce6335ab7 --- /dev/null +++ b/detections/ec2_instance_started_with_previously_unseen_user.yml @@ -0,0 +1,34 @@ +name: EC2 Instance Started With Previously Unseen User +id: 22773e84-bac0-4595-b086-20d3f735b4f1 +version: '1.0' +date: '2018-03-12' +description: This search looks for EC2 instances being created by users who have not + created them before. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. This search works best when you run the "Previously Seen EC2 Launches By + User" support search once to create a history of previously seen ARNs. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail + eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) + as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t + previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) + as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | eval + newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename + arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType + as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn + as user | table _time, user, dest, instanceType +known_false_positives: It's possible that a user will start to create EC2 instances + when they haven't before for any number of reasons. Verify with the user that is + launching instances that this is the intended behavior. +tags: + analytics_story: + - AWS Cryptomining + - Suspicious AWS EC2 Activities + cis20: + - CIS 1 + nist: + - ID.AM diff --git a/detections/email_attachments_with_lots_of_spaces.yml b/detections/email_attachments_with_lots_of_spaces.yml new file mode 100644 index 0000000000..4952803813 --- /dev/null +++ b/detections/email_attachments_with_lots_of_spaces.yml @@ -0,0 +1,39 @@ +name: Email Attachments With Lots Of Spaces +id: 56e877a6-1455-4479-ada6-0550dc1e22f8 +version: '2.0' +date: '2017-09-19' +description: Attackers often use spaces as a means to obfuscate an attachment's file + extension. This search looks for messages with email attachments that have many + spaces within the file names. +how_to_implement: "You need to ingest data from emails. Specifically, the sender's\ + \ address and the file names of any attachments must be mapped to the Email data\ + \ model. The threshold ratio is set to 10%, but this value can be configured to\ + \ suit each environment. \\\n **Splunk Phantom Playbook Integration**\\\nIf Splunk\ + \ Phantom is also configured in your environment, a playbook called \"Suspicious\ + \ Email Attachment Investigate and Delete\" can be configured to run when any results\ + \ are found by this detection search. To use this integration, install the Phantom\ + \ App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname\ + \ to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring\ + \ this detection search. The notable event will be sent to Phantom and the playbook\ + \ will gather further information about the file attachment and its network behaviors.\ + \ If Phantom finds malicious behavior and an analyst approves of the results, the\ + \ email will be deleted from the user's inbox." +type: ESCU +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(All_Email.recipient) + as recipient_address min(_time) as firstTime max(_time) as lastTime from datamodel=Email + where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` + | eval space_ratio = (mvcount(split(file_name," "))-1)/len(file_name) | search space_ratio + >= 0.1 | rex field=recipient_address "(?.*)@"' +known_false_positives: None at this time +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - Suspicious Emails + kill_chain_phases: + - Delivery + cis20: + - CIS 7 + nist: + - PR.IP diff --git a/detections/email_attachments_with_spaces.yml b/detections/email_attachments_with_spaces.yml deleted file mode 100644 index 59f0724a18..0000000000 --- a/detections/email_attachments_with_spaces.yml +++ /dev/null @@ -1,90 +0,0 @@ -asset_type: Endpoint -channel: ESCU -confidence: high -creation_date: '2017-04-21' -data_metadata: - data_models: - - Email - data_source: - - Email - providing_technologies: - - Microsoft Exchange -description: Attackers often use spaces as a means to obfuscate an attachment's file - extension. This search looks for messages with email attachments that have many - spaces within the file names. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_user, file_name - rule_description: 'The sender $src_user$ has sent an email with a suspicious - amount of spaces in the file name: $file_name$' - rule_title: Suspicious Email Attachment from $src_user$ - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 60 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(All_Email.recipient) as recipient_address - min(_time) as firstTime max(_time) as lastTime from datamodel=Email where - All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` - | eval space_ratio = (mvcount(split(file_name," "))-1)/len(file_name) | search - space_ratio >= 0.1 | rex field=recipient_address "(?.*)@"' - suppress: - suppress_fields: src_user - suppress_period: 86400s -eli5: This search looks at any emails with file attachment names that contain many - spaces, relative to the length of the file name. Specifically, it checks to see - whether spaces make up more than 10% of the number of characters in the file name. - This percentage can be tuned for each environment. The search will output the message - ID of the email, the count, the sender and recipient addresses, the first and last - time this event was seen, and the space ratio of the file attachment name. -entities: - - src - - message_id -how_to_implement: "You need to ingest data from emails. Specifically, the sender's\ - \ address and the file names of any attachments must be mapped to the Email data\ - \ model. The threshold ratio is set to 10%, but this value can be configured to\ - \ suit each environment. \\\n **Splunk Phantom Playbook Integration**\\\nIf Splunk\ - \ Phantom is also configured in your environment, a playbook called \"Suspicious\ - \ Email Attachment Investigate and Delete\" can be configured to run when any results\ - \ are found by this detection search. To use this integration, install the Phantom\ - \ App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname\ - \ to the \"Phantom Instance\" field in the Adaptive Response Actions when configuring\ - \ this detection search. The notable event will be sent to Phantom and the playbook\ - \ will gather further information about the file attachment and its network behaviors.\ - \ If Phantom finds malicious behavior and an analyst approves of the results, the\ - \ email will be deleted from the user's inbox." -id: 56e877a6-1455-4479-ada6-0550dc1e22f8 -investigations: - - id: 3096f721-8842-42ce-2fc7-742d8372b712 - name: Suspicious Email Attachment Investigate and Delete - type: phantom -known_false_positives: None at this time -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 7 - kill_chain_phases: - - Delivery - mitre_attack: [] - nist: - - PR.IP -modification_date: '2017-09-19' -name: Email Attachments With Lots Of Spaces -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/email_files_not_in_outlook_directory.yml b/detections/email_files_not_in_outlook_directory.yml deleted file mode 100644 index 53718f57ce..0000000000 --- a/detections/email_files_not_in_outlook_directory.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-12-13' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: The search looks at the change-analysis data model and detects email - files created outside the normal Outlook directory. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_path, action, file_name - rule_description: 'The system $dest$ has email files outside of the normal - Outlook directory ' - rule_title: Email files created or modified on $dest$ that are not in the - normal Outlook directory - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - email_files_not_in_outlook_directory_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path - min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem - where (Filesystem.file_name=*.pst OR Filesystem.file_name=*.ost) Filesystem.file_path - != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" by Filesystem.action Filesystem.process_id - Filesystem.file_name Filesystem.dest | `drop_dm_object_name("Filesystem")` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `email_files_not_in_outlook_directory_filter`' - suppress: - suppress_fields: dest, file_path - suppress_period: 86400s -eli5: In this search, we are looking for activities consistent with an adversary collecting - email data from local machines. The search will detect email files (files with .pst - or .ost extensions) created in directories other than the standard Outlook directory - (c:\users\username\My Documents\Outlook Files\. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records the file-system activity from your hosts to populate the Endpoint.Filesystem - data model node. This is typically populated via endpoint detection-and-response - products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. - The data used for this search is typically generated via logs that report file-system - reads and writes. -id: ee18ed37-0802-4268-9435-b3b91aaa18xx -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Administrators and users sometimes prefer backing up their - email data by moving the email files into a different folder. These attempts will - be detected by the search. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Collection - - Email Collection -modification_date: '2020-03-23' -name: Email files written outside of the Outlook directory -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/email_files_written_outside_of_the_outlook_directory.yml b/detections/email_files_written_outside_of_the_outlook_directory.yml new file mode 100644 index 0000000000..0ac0e64a37 --- /dev/null +++ b/detections/email_files_written_outside_of_the_outlook_directory.yml @@ -0,0 +1,34 @@ +name: Email files written outside of the Outlook directory +id: ee18ed37-0802-4268-9435-b3b91aaa18xx +version: '2.0' +date: '2020-03-23' +description: The search looks at the change-analysis data model and detects email + files created outside the normal Outlook directory. +how_to_implement: To successfully implement this search, you must be ingesting data + that records the file-system activity from your hosts to populate the Endpoint.Filesystem + data model node. This is typically populated via endpoint detection-and-response + products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. + The data used for this search is typically generated via logs that report file-system + reads and writes. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Filesystem.file_path) + as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem + where (Filesystem.file_name=*.pst OR Filesystem.file_name=*.ost) Filesystem.file_path + != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" + by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest + | `drop_dm_object_name("Filesystem")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| + `email_files_not_in_outlook_directory_filter`' +known_false_positives: Administrators and users sometimes prefer backing up their + email data by moving the email files into a different folder. These attempts will + be detected by the search. +tags: + analytics_story: + - Collection and Staging + mitre_attack_id: + - T1114 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 diff --git a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml new file mode 100644 index 0000000000..a3d2e7265e --- /dev/null +++ b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml @@ -0,0 +1,48 @@ +name: Email servers sending high volume traffic to hosts +id: 7f5fb3e1-4209-4914-90db-0ec21b556378 +version: '1.0' +date: '2017-12-20' +description: This search looks for an increase of data transfers from your email server + to your clients. This could be indicative of a malicious actor collecting data using + your email server. +how_to_implement: This search requires you to be ingesting your network traffic and + populating the Network_Traffic data model. Your email servers must be categorized + as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold + and minimum_data_samples values based on the network traffic in your environment. + The "deviation_threshold" field is a multiplying factor to control how much variation + you're willing to tolerate. The "minimum_data_samples" field is the minimum number + of connections of data samples required for the statistic to be valid. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as bytes_out + from datamodel=Network_Traffic where All_Traffic.src_category=email_server by All_Traffic.dest_ip + _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_out) + as avg_bytes_out stdev(bytes_out) as stdev_bytes_out | eventstats count as num_data_samples + avg(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_avg_bytes_out + stdev(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_stdev_bytes_out + by dest_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples + >= minimum_data_samples AND bytes_out > (avg_bytes_out + (deviation_threshold * + stdev_bytes_out)) AND bytes_out > (per_source_avg_bytes_out + (deviation_threshold + * per_source_stdev_bytes_out)) AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average + = round(abs(bytes_out - avg_bytes_out) / stdev_bytes_out, 2), num_standard_deviations_away_from_client_average + = round(abs(bytes_out - per_source_avg_bytes_out) / per_source_stdev_bytes_out, + 2) | table dest_ip, _time, bytes_out, avg_bytes_out, per_source_avg_bytes_out, num_standard_deviations_away_from_server_average, + num_standard_deviations_away_from_client_average' +known_false_positives: The false-positive rate will vary based on how you set the + deviation_threshold and data_samples values. Our recommendation is to adjust these + values based on your network traffic to and from your email servers. +tags: + analytics_story: + - Collection and Staging + mitre_attack_id: + - T1114 + - T1043 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 7 + nist: + - PR.PT + - DE.CM + - DE.AE diff --git a/detections/emailserver_high_volume_outbound_traffic_to_hosts.yml b/detections/emailserver_high_volume_outbound_traffic_to_hosts.yml deleted file mode 100644 index e662b8902a..0000000000 --- a/detections/emailserver_high_volume_outbound_traffic_to_hosts.yml +++ /dev/null @@ -1,120 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-12-20' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream -description: This search looks for an increase of data transfers from your email server - to your clients. This could be indicative of a malicious actor collecting data using - your email server. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest_ip - rule_description: High volume of traffic that originated from an email server - is being sent to $dest_ip$ - rule_title: High volume of traffic from an email server sent to $dest_ip$ - risk: - risk_object: dest_ip - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 0 * * * - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as bytes_out from - datamodel=Network_Traffic where All_Traffic.src_category=email_server by All_Traffic.dest_ip - _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_out) - as avg_bytes_out stdev(bytes_out) as stdev_bytes_out | eventstats count as - num_data_samples avg(eval(if(_time < relative_time(now(), "@d"), bytes_out, - null))) as per_source_avg_bytes_out stdev(eval(if(_time < relative_time(now(), - "@d"), bytes_out, null))) as per_source_stdev_bytes_out by dest_ip | eval - minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples - >= minimum_data_samples AND bytes_out > (avg_bytes_out + (deviation_threshold - * stdev_bytes_out)) AND bytes_out > (per_source_avg_bytes_out + (deviation_threshold - * per_source_stdev_bytes_out)) AND _time >= relative_time(now(), "@d") | eval - num_standard_deviations_away_from_server_average = round(abs(bytes_out - avg_bytes_out) - / stdev_bytes_out, 2), num_standard_deviations_away_from_client_average = - round(abs(bytes_out - per_source_avg_bytes_out) / per_source_stdev_bytes_out, - 2) | table dest_ip, _time, bytes_out, avg_bytes_out, per_source_avg_bytes_out, - num_standard_deviations_away_from_server_average, num_standard_deviations_away_from_client_average' - suppress: - suppress_fields: dest_ip - suppress_period: 86400s -eli5: This search may look complex, but it's a neat representation of how statistics - can help you understand your dataset to bubble up events that are not normal compared - to its behavior. The search consists of three parts. The first part of the SPL fetches - the data you want to work on. In this search, we calculate the sum of bytes sent - and bytes_out from systems categorized as email_server to each host. We then calculate - the average and standard deviation for the bytes sent to all the hosts combined - and on a per-host basis. Then we set threshold values to deviation_threshold and - minimum_data_samples using eval statements. The "deviation_threshold" field is a - multiplying factor to control how much variation you're willing to tolerate. The - "minimum_data_samples" field is the minimum number of connections of data samples - required for the statistic to be valid. We then check for byte transfers that are - statistically significantly higher than normal. The search then gives IP address - of the host, the time of the increased byte transfer, how much data was transferred, - and the average amount of data transfer the email server normally sends to all hosts - and to this specific host. Finally, it includes the number of standard deviations - away the byte count was from these averages. -entities: - - dest_ip -how_to_implement: This search requires you to be ingesting your network traffic and - populating the Network_Traffic data model. Your email servers must be categorized - as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold - and minimum_data_samples values based on the network traffic in your environment. - The "deviation_threshold" field is a multiplying factor to control how much variation - you're willing to tolerate. The "minimum_data_samples" field is the minimum number - of connections of data samples required for the statistic to be valid. -id: 7f5fb3e1-4209-4914-90db-0ec21b556378 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk -known_false_positives: The false-positive rate will vary based on how you set the - deviation_threshold and data_samples values. Our recommendation is to adjust these - values based on your network traffic to and from your email servers. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 7 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Collection - - Email Collection - - Commonly Used Port - nist: - - PR.PT - - DE.CM - - DE.AE -modification_date: '2017-12-20' -name: Email servers sending high volume traffic to hosts -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/excessive_dns_failures.yml b/detections/excessive_dns_failures.yml index b5c64c15c2..4e44ad8091 100644 --- a/detections/excessive_dns_failures.yml +++ b/detections/excessive_dns_failures.yml @@ -1,107 +1,38 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro +name: Excessive DNS Failures +id: 104658f4-afdc-499e-9719-17243f9826f1 +version: '1.0' +date: '2017-09-18' description: This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, query - rule_description: This search identifies DNS query failures by counting the - number of DNS responses that do not indicate success and triggers on more - than 50 occurrences. - rule_title: Excessive DNS Failures - risk: - risk_object: src - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values("DNS.query") as queries from - datamodel=Network_Resolution where nodename=DNS "DNS.reply_code"!="No Error" - "DNS.reply_code"!="NoError" DNS.reply_code!="unknown" NOT "DNS.query"="*.arpa" - "DNS.query"="*.*" by "DNS.src","DNS.query"| `drop_dm_object_name("DNS")`| - lookup cim_corporate_web_domain_lookup domain as query OUTPUT domain| where - isnull(domain)| lookup update=true alexa_lookup_by_str domain as query OUTPUT - rank| where isnull(rank)| stats sum(count) as count mode(queries) as queries - by src| `get_asset(src)`| where count>50' - suppress: - suppress_fields: src,query - suppress_period: 43200s -eli5: This search looks at DNS traffic with a reply code that is NOT indicative of - a successful response. Numerous unsuccessful replies may be indicative of DNS protocol - tampering or other malicious activity. If more than 50 of these unsuccessful responses - are observed over the time frame of the search, a notable event will be generated. -entities: - - src how_to_implement: To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -id: 104658f4-afdc-499e-9719-17243f9826f1 -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 - name: Get DNS traffic ratio - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values("DNS.query") as queries + from datamodel=Network_Resolution where nodename=DNS "DNS.reply_code"!="No Error" + "DNS.reply_code"!="NoError" DNS.reply_code!="unknown" NOT "DNS.query"="*.arpa" "DNS.query"="*.*" + by "DNS.src","DNS.query"| `drop_dm_object_name("DNS")`| lookup cim_corporate_web_domain_lookup + domain as query OUTPUT domain| where isnull(domain)| lookup update=true alexa_lookup_by_str + domain as query OUTPUT rank| where isnull(rank)| stats sum(count) as count mode(queries) + as queries by src| `get_asset(src)`| where count>50' known_false_positives: It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - - CIS 9 - - CIS 12 +tags: + analytics_story: + - Suspicious DNS Traffic + - Command and Control + mitre_attack_id: + - T1048 + - T1043 kill_chain_phases: - - Command and Control - mitre_attack: - - Exfiltration - - Exfiltration Over Alternative Protocol - - Command and Control - - Commonly Used Port + - Command and Control + cis20: + - CIS 8 + - CIS 9 + - CIS 12 nist: - - PR.PT - - DE.AE - - DE.CM -modification_date: '2017-09-18' -name: Excessive DNS Failures -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' + - PR.PT + - DE.AE + - DE.CM diff --git a/detections/excessive_lockouts_from_endpoint.yml b/detections/excessive_lockouts_from_endpoint.yml deleted file mode 100644 index 3535c89c72..0000000000 --- a/detections/excessive_lockouts_from_endpoint.yml +++ /dev/null @@ -1,91 +0,0 @@ -asset_type: Windows -confidence: low -creation_date: '2017-08-17' -data_metadata: - data_models: - - Change - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search identifies endpoints that have caused a relatively high number - of account lockouts in a short period. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: The system $dest$ has generated a high number of account - lockouts. - rule_title: $dest$ has generated a high number of account lockouts - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -4h@h - latest_time: -5m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management - All_Changes.result="lockout" by All_Changes.dest All_Changes.result |`drop_dm_object_name("All_Changes")` - |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | search count > 5' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: This search queries the `Change.All_Changes` datamodel under the nodename is - `Account_Management` , where the result is "lockout", which indicates that an account - has been locked out. It then counts the number of times an endpoint has caused an - account lockout within a four hour window and displays those hosts with a count - greater than or equal to five. -entities: - - dest -how_to_implement: "You must ingest your Windows security event logs in the `Change`\ - \ datamodel under the nodename is `Account_Management`, for this search to execute\ - \ successfully. Please consider updating the cron schedule and the count of lockouts\ - \ you want to monitor, according to your environment. \\\n **Splunk>Phantom Playbook\ - \ Integration**\\\nIf Splunk>Phantom is also configured in your environment, a Playbook\ - \ called \"Excessive Account Lockouts Enrichment and Response\" can be configured\ - \ to run when any results are found by this detection search. The Playbook executes\ - \ the Contextual and Investigative searches in this Story, conducts additional information\ - \ gathering on Windows endpoints, and takes a response action to shut down the affected\ - \ endpoint. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`,\ - \ add the correct hostname to the \"Phantom Instance\" field in the Adaptive Response\ - \ Actions when configuring this detection search, and set the corresponding Playbook\ - \ to active. \\\n(Playbook Link:`https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\\\ - \n" -id: c026e3dd-7e18-4abb-8f41-929e836efe74 -investigations: - - id: ab62b5c1-95d4-4e71-8fd7-53a55db33da4 - name: Excessive Account Lockouts Enrichment And Response - type: phantom -known_false_positives: It's possible that a widely used system, such as a kiosk, could - cause a large number of account lockouts. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: proyer@splunk.com - name: Philip Royer -mappings: - cis20: - - CIS 16 - mitre_attack: - - Initial Access - - Valid Accounts - nist: - - PR.IP -modification_date: '2019-04-18' -name: Detect Excessive Account Lockouts From Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -responses: [] -security_domain: access -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/excessive_user_account_lockouts.yml b/detections/excessive_user_account_lockouts.yml deleted file mode 100644 index 649484dc33..0000000000 --- a/detections/excessive_user_account_lockouts.yml +++ /dev/null @@ -1,99 +0,0 @@ -asset_type: Windows -confidence: medium -creation_date: '2017-08-17' -data_metadata: - data_models: - - Change - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search detects user accounts that have been locked out a relatively - high number of times in a short period. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: The account $user$ has been locked out an excessive number - of times - rule_title: $user$ locked account an excessive number of times - risk: - risk_object: user - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -4h@h - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management - All_Changes.result="lockout" by All_Changes.user All_Changes.result |`drop_dm_object_name("All_Changes")` - |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | search count > 5' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: This search queries the `Change.All_Changes` datamodel under the nodename is - `Account_Management` , where the result is "lockout", which indicates that an account - has been locked out. It then counts the number of times a user has caused an account - lockout within a four hour window and displays those users with a count greater - than or equal to five. -entities: - - user -how_to_implement: ou must ingest your Windows security event logs in the `Change` - datamodel under the nodename is `Account_Management`, for this search to execute - successfully. Please consider updating the cron schedule and the count of lockouts - you want to monitor, according to your environment. -id: 95a7f9a5-6096-437e-a19e-86f42ac609bd -investigations: - - id: 552bc86c-f72c-4d44-b3f2-06ede13af7bb - name: Get Logon Rights Modifications For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: 03bffe94-ec7a-4cbe-b677-6af40d1c4505 - name: Get Logon Rights Modifications For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is possible that a legitimate user is experiencing an issue - causing multiple account login failures leading to lockouts. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 16 - mitre_attack: - - Initial Access - - Valid Accounts - nist: - - PR.IP -modification_date: '2019-03-01' -name: Detect Excessive User Account Lockouts -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: access -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/execution_of_file_with_multiple_extensions.yml b/detections/execution_of_file_with_multiple_extensions.yml new file mode 100644 index 0000000000..7d443538bc --- /dev/null +++ b/detections/execution_of_file_with_multiple_extensions.yml @@ -0,0 +1,35 @@ +name: Execution of File with Multiple Extensions +id: b06a555e-dce0-417d-a2eb-28a5d8d66ef7 +version: '1.0' +date: '2018-11-02' +description: This search looks for processes launched from files that have double + extensions in the file name. This is typically done to obscure the "real" file extension + and make it appear as though the file being accessed is a data file, as opposed + to executable content. +how_to_implement: To successfully implement this search, you must be ingesting data + that records process activity from your hosts to populate the endpoint data model + in the processes node. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process = *.doc.exe + OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process + = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe by + Processes.dest Processes.user Processes.process Processes.parent_process | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)`' +known_false_positives: None identified. +tags: + analytics_story: + - Windows File Extension and Association Abuse + mitre_attack_id: + - T1042 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 8 + nist: + - DE.CM + - PR.PT + - PR.IP diff --git a/detections/execution_of_file_with_spaces_before_extension.yml b/detections/execution_of_file_with_spaces_before_extension.yml new file mode 100644 index 0000000000..709fd5dc42 --- /dev/null +++ b/detections/execution_of_file_with_spaces_before_extension.yml @@ -0,0 +1,34 @@ +name: Execution of File With Spaces Before Extension +id: ab0353e6-a956-420b-b724-a8b4846d5d5a +version: '1.0' +date: '2018-01-26' +description: This search looks for processes launched from files with at least five + spaces in the name before the extension. This is typically done to obfuscate the + file extension by pushing it outside of the default view. +how_to_implement: To successfully implement this search, you must be ingesting data + that records process activity from your hosts to populate the endpoint data model + in the processes node. If you are using Sysmon, you must have at least version 6.0.4 + of the Sysmon TA. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process_path) + as process_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process = "* .*" by Processes.dest Processes.user Processes.process + Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `drop_dm_object_name(Processes)`' +known_false_positives: None identified. +tags: + analytics_story: + - Windows File Extension and Association Abuse + mitre_attack_id: + - T1042 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 8 + nist: + - DE.CM + - PR.PT + - PR.IP diff --git a/detections/execution_of_nirsoft_tools.yml b/detections/execution_of_nirsoft_tools.yml deleted file mode 100644 index 3e1daf05cc..0000000000 --- a/detections/execution_of_nirsoft_tools.yml +++ /dev/null @@ -1,116 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-09-11' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for specific command-line arguments that may indicate - the execution of tools made by Nirsoft, which are legitimate, but may be abused - by attackers. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for specific arguments passed via the - command line and detects execution of tools built by NirSoft, which are - often abused by attackers. - rule_title: Potential abuse of NirSoft tools on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) values(Processes.process) - as process max(_time) as lastTime from datamodel=Endpoint.Processes where - (Processes.process="* /stext *" OR Processes.process="* /scomma *" ) by Processes.parent_process - Processes.process_name Processes.user | `drop_dm_object_name(Processes)` | - `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process - suppress_period: 28800s -eli5: The search looks for process-creation events accompanied by specific command-line - arguments ("scomma" and "stext"). These parameters may be leveraged by a set of - free, legitimate tools built by NirSoft. Attackers have been seen abusing the tools' - capabilities to steal passwords, set up key loggers, recover account information - from mail clients, and conduct other nefarious activities. The search will identify - the count, the first and last times a process is executed, the command-line arguments, - and the parent process. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: 1297fb80-f42a-4q4a-9c8b-78c061417cf6 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: While legitimate, these NirSoft tools are prone to abuse. You - should verfiy that the tool was used for a legitimate purpose. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - kill_chain_phases: - - Installation - - Actions on Objectives - mitre_attack: - - Discovery - - Execution - - Lateral Movement - - Third-party Software - - Account Discovery - nist: - - PR.IP -modification_date: '2018-12-03' -name: Detection of tools built by NirSoft -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/extended_period_without_successful_netbackup_backups.yml b/detections/extended_period_without_successful_netbackup_backups.yml new file mode 100644 index 0000000000..22cc222818 --- /dev/null +++ b/detections/extended_period_without_successful_netbackup_backups.yml @@ -0,0 +1,27 @@ +name: Extended Period Without Successful Netbackup Backups +id: a34aae96-ccf8-4aef-952c-3ea214444440 +version: '1.0' +date: '2017-09-12' +description: This search returns a list of hosts that have not successfully completed + a backup in over a week. +how_to_implement: To successfully implement this search you need to first obtain data + from your backup solution, either from the backup logs on your hosts, or from a + central server responsible for performing the backups. If you do not use Netbackup, + you can modify this search for your backup solution. Depending on how often you + backup your systems, you may want to modify how far in the past to look for a successful + backup, other than the default of seven days. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype="netbackup_logs" MESSAGE="Disk/Partition backup completed successfully." + | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` + | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), + "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest +known_false_positives: None identified +tags: + analytics_story: + - Monitor Backup Solution + cis20: + - CIS 10 + nist: + - PR.IP diff --git a/detections/file_with_samsam_extension.yml b/detections/file_with_samsam_extension.yml new file mode 100644 index 0000000000..3c26e311db --- /dev/null +++ b/detections/file_with_samsam_extension.yml @@ -0,0 +1,32 @@ +name: File with Samsam Extension +id: 02c6cfc2-ae66-4735-bfc7-6291da834cbf +version: '1.0' +date: '2018-12-14' +description: The search looks for file writes with extensions consistent with a SamSam + ransomware attack. +how_to_implement: You must be ingesting data that records file-system activity from + your hosts to populate the Endpoint file-system data-model node. If you are using + Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you + want to collect data. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) + as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex + field=file_name "(?\.[^\.]+)$" | search file_extension=.stubbin + OR file_extension=.berkshire OR file_extension=.satoshi OR file_extension=.sophos + OR file_extension=.keyxml' +known_false_positives: Because these extensions are not typically used in normal operations, + you should investigate all results. +tags: + analytics_story: + - SamSam Ransomware + kill_chain_phases: + - Installation + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/file_write_spikes.yml b/detections/file_write_spikes.yml deleted file mode 100644 index cdb8d28712..0000000000 --- a/detections/file_write_spikes.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: low -creation_date: '2017-08-20' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: The search looks for a sharp increase in the number of files written - to a particular host -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: A sharp increase in file writes was detected on $dest - rule_title: Spike in file writes on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - macros: - - file_write_spikes_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -7d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Filesystem where - Filesystem.action=created by _time span=1h, Filesystem.dest | `drop_dm_object_name(Filesystem)` - | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time - >= relative_time(maxtime, "-1d@d"), count, null))) as "count" avg(eval(if(_time upperBound) AND num_data_samples >=20, 1, 0) | search - isOutlier=1 | `file_write_spikes_filter`' - suppress: - suppress_fields: dest - suppress_period: 7200s -eli5: This search calculates counts the number of file modification events per hour - per host in your environment. It then takes the average and standard deviations - of those numbers and displays any hosts with more than 20 events that have over - four times the standard deviation more than the average number of file modifications. -entities: - - dest -how_to_implement: In order to implement this search, you must populate the Endpoint - file-system data model node. This is typically populated via endpoint detection - and response products, such as Carbon Black or endpoint data sources such as Sysmon. - The data used for this search is typically generated via logs that report reads - and writes to the file system. -id: fdb0f805-74e4-4539-8c00-618927333aae -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: It is important to understand that if you happen to install - any new applications on your hosts or are copying a large number of files, you can - expect to see a large increase of file modifications. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - DE.CM -modification_date: '2020-03-16' -name: Spike in File Writes -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/first_time_seen_cmd_line.yml b/detections/first_time_seen_cmd_line.yml deleted file mode 100644 index 058b722144..0000000000 --- a/detections/first_time_seen_cmd_line.yml +++ /dev/null @@ -1,141 +0,0 @@ -asset_type: Endpoint -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd23 - name: Previously seen command line arguments - type: splunk -confidence: medium -creation_date: '2018-04-09' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for command-line arguments that use a `/c` parameter - to execute a command that has not previously been seen. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: The system $dest$ executed a command-line argument, $process$, - that has not previously been seen. - rule_title: First-time seen command-line argument was detected on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - first_time_seen_cmd_line_filter - schedule: - cron_schedule: 30 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime - from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process - = "* /c *" by Processes.process Processes.process_name Processes.parent_process_name - Processes.dest| `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | search [| tstats `security_content_summariesonly` earliest(_time) as firstTime latest(_time) - as lastTime from datamodel=Endpoint.Processes where Processes.process_name - = cmd.exe Processes.process = "* /c *" by Processes.process | `drop_dm_object_name(Processes)` - | inputlookup append=t previously_seen_cmd_line_arguments | stats min(firstTime) - as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments - | eval newCmdLineArgument=if(firstTime >= relative_time(now(), "-70m@m"), - 1, 0) | where newCmdLineArgument=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | table process] | `first_time_seen_cmd_line_filter` ' - suppress: - suppress_fields: dest, process - suppress_period: 86400s -eli5: The subsearch returns all events where `cmd.exe` was used with a `/c` parameter - in the command-line arguments to execute other commands/programs. It appends the - historical data to those results in the lookup file. Next, it recalculates the `firstTime` - and `lastTime` field for command-line execution and outputs this data to the lookup - file to update the local cache. It returns only those events that have first been - seen in the past one hour. This is combined with the main search to return the time, - user, destination, process, parent process, and value of the command-line argument. -entities: - - dest - - process_name - - user -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must be ingesting - logs with both the process name and command line from your endpoints. The complete - process name with command-line arguments are mapped to the "process" field in the - Endpoint data model. Please make sure you run the support search "Previously seen - command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a - historical baseline of all command-line arguments. You must also validate this list. - For the search to do accurate calculation, ensure the search scheduling is the same - value as the `relative_time` evaluation function. -id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Legitimate programs can also use command-line arguments to - execute. Please verify the command-line arguments to check what command/program - is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - - CIS 8 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - - Scripting - - Persistence - - Command-Line Interface - mitre_technique_id: - - T1059 - - T1117 - - T1202 - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2020-03-02' -name: First time seen command line argument -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '4.1' diff --git a/detections/first_time_seen_command_line_argument.yml b/detections/first_time_seen_command_line_argument.yml new file mode 100644 index 0000000000..9437359955 --- /dev/null +++ b/detections/first_time_seen_command_line_argument.yml @@ -0,0 +1,54 @@ +name: First time seen command line argument +id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 +version: '4.1' +date: '2020-03-02' +description: This search looks for command-line arguments that use a `/c` parameter + to execute a command that has not previously been seen. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must be ingesting + logs with both the process name and command line from your endpoints. The complete + process name with command-line arguments are mapped to the "process" field in the + Endpoint data model. Please make sure you run the support search "Previously seen + command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a + historical baseline of all command-line arguments. You must also validate this list. + For the search to do accurate calculation, ensure the search scheduling is the same + value as the `relative_time` evaluation function. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe + Processes.process = "* /c *" by Processes.process Processes.process_name Processes.parent_process_name + Processes.dest| `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` + earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process + | `drop_dm_object_name(Processes)` | inputlookup append=t previously_seen_cmd_line_arguments + | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup + previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), + "-70m@m"), 1, 0) | where newCmdLineArgument=1 | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | table process] | `first_time_seen_cmd_line_filter` ' +known_false_positives: Legitimate programs can also use command-line arguments to + execute. Please verify the command-line arguments to check what command/program + is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` + macro to exclude legitimate parent_process_name +tags: + analytics_story: + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Suspicious Command-Line Executions + - Orangeworm Attack Group + - Hidden Cobra Malware + - DHS Report TA18-074A + mitre_attack_id: + - T1064 + - T1059 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 3 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/first_time_seen_running_windows_service.yml b/detections/first_time_seen_running_windows_service.yml index a6cb4849bb..72209927c0 100644 --- a/detections/first_time_seen_running_windows_service.yml +++ b/detections/first_time_seen_running_windows_service.yml @@ -1,103 +1,44 @@ -asset_type: Endpoint -baselines: - - id: 64ce0ade-cb01-4678-bddd-d31c0b175394 - name: Previously Seen Running Windows Services - type: splunk -confidence: medium -creation_date: '2018-07-22' -data_metadata: - data_eventtypes: - - wineventlog_system - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows +name: First Time Seen Running Windows Service +id: 823136f2-d755-4b6d-ae04-372b486a5808 +version: '2.0' +date: '2020-01-13' description: This search looks for the first time a Windows service is seen running in your environment. -detect: - splunk: - correlation_rule: - notable: - nes_fields: service_name - rule_description: The service $service_name$ is running on $dest$. This is - the first time this service has been run on any system. - rule_title: First Time Seen Windows Service $service_name$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 30 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" [ search eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | inputlookup append=t previously_seen_running_windows_services | stats min(firstTime) as firstTime max(lastTime) as lastTime by service_name | outputlookup previously_seen_running_windows_services| eval serviceStatus=if(firstTime >= relative_time(now(),"-60m@m"), "First time seen Windows service","Previously seen Windows service") | where serviceStatus="First time seen Windows service"| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table service_name]| table _time dest service_name - suppress: - suppress_fields: service_name, dest - suppress_period: 86400s -eli5: 'This search looks for a change in the status of a Windows service and extracts - the name of the service and the action taken by the service. Then the cache file - of previously seen Windows services is added to the search. At this point, the search - takes two different paths: the first updates the cache file with the latest information - and the second searches for services that have never before been seen. It returns - the time, the Windows host name, and the service name.' -entities: - - dest how_to_implement: While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, - should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -id: 823136f2-d755-4b6d-ae04-372b486a5808 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk + should be run before this search to create the baseline of known Windows services. + Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name + | rename param2 as action | search action="running" [ search eventtype=wineventlog_system + signature_id=7036 | rename param1 as service_name | rename param2 as action | search + action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime + by service_name | inputlookup append=t previously_seen_running_windows_services + | stats min(firstTime) as firstTime max(lastTime) as lastTime by service_name | + outputlookup previously_seen_running_windows_services| eval serviceStatus=if(firstTime + >= relative_time(now(),"-60m@m"), "First time seen Windows service","Previously + seen Windows service") | where serviceStatus="First time seen Windows service"| + `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table + service_name]| table _time dest service_name known_false_positives: A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 2 - - CIS 9 +tags: + analytics_story: + - Windows Service Abuse + - Orangeworm Attack Group + mitre_attack_id: + - T1050 kill_chain_phases: - - Installation - - Actions on Objectives - mitre_attack: - - Execution - - New Service - mitre_technique_id: - - T1050 + - Installation + - Actions on Objectives + cis20: + - CIS 2 + - CIS 9 nist: - - ID.AM - - PR.DS - - PR.AC - - DE.AE -modification_date: '2020-01-13' -name: First Time Seen Running Windows Service -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' + - ID.AM + - PR.DS + - PR.AC + - DE.AE diff --git a/detections/fsutil_deleting_journals.yml b/detections/fsutil_deleting_journals.yml deleted file mode 100644 index fb022b8a5e..0000000000 --- a/detections/fsutil_deleting_journals.yml +++ /dev/null @@ -1,116 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-06-27' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: The fsutil.exe application is a legitimate Windows utility used to perform - tasks related to the file allocation table (FAT) and NTFS file systems. The update - sequence number (USN) change journal provides a log of all changes made to the files - on the disk. This search looks for fsutil.exe deleting the USN journal. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: The system $dest$ deleted its NTFS journals. - rule_title: File System Journal Deleted on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fsutil.exe - by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | - search process="*deletejournal*" AND process="*usn*"' - suppress: - suppress_fields: dest,user,process_name - suppress_period: 14400s -eli5: This search looks for the execution of fsutil.exe with command-line arguments - to delete the USN journal. The search returns the count of the number of times it's - seen this process execution with these arguments, the first and last time it's seen - this behavior, the hosts it was executed on, and the user context under which it - was executed. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: b6e0ff70-b122-4227-9368-4cf322ab43c3 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 6 - - CIS 8 - - CIS 10 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Indicator Removal on Host - nist: - - DE.CM - - PR.PT - - DE.AE - - DE.DP - - PR.IP -modification_date: '2018-12-03' -name: USN Journal Deletion -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/gcp_gcr_container_uploaded.yml b/detections/gcp_gcr_container_uploaded.yml new file mode 100644 index 0000000000..710c0e2d67 --- /dev/null +++ b/detections/gcp_gcr_container_uploaded.yml @@ -0,0 +1,25 @@ +name: GCP GCR container uploaded +id: 4f00ca88-e766-4605-ac65-ae51c9fd185b +version: '1.0' +date: '2020-02-20' +description: This search show information on uploaded containers including source + user, account, action, bucket name event name, http user agent, message and destination + path. +how_to_implement: You must install the GCP App for Splunk (version 2.0.0 or later), + then configure stackdriver and set a subpub subscription to be imported to Splunk. + You must also install Cloud Infrastructure data model. Please also customize the + `container_implant_gcp_detection_filter` macro to filter out the false positives. +type: ESCU +references: [] +author: Rod Soto, Rico Valdez, Splunk +search: '|tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Storage + where Storage.event_name=storage.objects.create by Storage.src_user Storage.account + Storage.action Storage.bucket_name Storage.event_name Storage.http_user_agent Storage.msg + Storage.object_path | `drop_dm_object_name("Storage")` | `container_implant_gcp_detection_filter`' +known_false_positives: Uploading container is a normal behavior from developers or + users with access to container registry. GCP GCR registers container upload as a + Storage event, this search must be considered under the context of CONTAINER upload + creation which automatically generates a bucket entry for destination path. +tags: + analytics_story: + - Container Implantation Monitoring & Investigation diff --git a/detections/gcp_kubernetes_cluster_scan_detection.yml b/detections/gcp_kubernetes_cluster_scan_detection.yml new file mode 100644 index 0000000000..62c8b2df8a --- /dev/null +++ b/detections/gcp_kubernetes_cluster_scan_detection.yml @@ -0,0 +1,29 @@ +name: GCP Kubernetes cluster scan detection +id: db5957ec-0144-4c56-b512-9dccbe7a2d26 +version: '1.0' +date: '2020-04-15' +description: This search provides information of unauthenticated requests via user + agent, and authentication data against Kubernetes cluster +how_to_implement: You must install the GCP App for Splunk (version 2.0.0 or later), + then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. + You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection + to filter out FPs. +type: ESCU +references: [] +author: Rod Soto, Splunk +search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp!=127.0.0.1 + data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid + "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" + | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) + as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_name + values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) + as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name + as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | + `kubernetes_gcp_scan_fingerprint_detection` +known_false_positives: Not all unauthenticated requests are malicious, but frequency, + User Agent and source IPs will provide context. +tags: + analytics_story: + - Kubernetes Scanning Activity + kill_chain_phases: + - Reconnaissance diff --git a/detections/hiding_files_and_directories_with_attrib_exe.yml b/detections/hiding_files_and_directories_with_attrib_exe.yml new file mode 100644 index 0000000000..e3d30981d1 --- /dev/null +++ b/detections/hiding_files_and_directories_with_attrib_exe.yml @@ -0,0 +1,33 @@ +name: Hiding Files And Directories With Attrib.exe +id: c77162d3-f93c-45cc-80c8-22f6b5264g9f +version: '3.0' +date: '2020-03-16' +description: Attackers leverage an existing Windows binary, attrib.exe, to mark specific + as hidden by using specific flags so that the victim does not see the file. The + search looks for specific command-line arguments to detect the use of attrib.exe + to hide files. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) values(Processes.process) + as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe + (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user + | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| + `attrib_to_hide_files_filter`' +known_false_positives: 'Some applications and users may legitimately use attrib.exe + to interact with the files. ' +tags: + analytics_story: + - Windows Persistence Techniques + - Windows Defense Evasion Tactics + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/hosts_file_modification.yml b/detections/hosts_file_modification.yml deleted file mode 100644 index 81a4e357eb..0000000000 --- a/detections/hosts_file_modification.yml +++ /dev/null @@ -1,106 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-06-07' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: The search looks for modifications to the hosts file on all Windows endpoints - across your environment. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A file modification was noted for the hosts file on $dest$. - rule_title: Modification of hosts file detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.file_path - Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | search Filesystem.file_name=hosts - AND Filesystem.file_path=*Windows\\System32\\* | `drop_dm_object_name(Filesystem)`' - suppress: - suppress_fields: dest,user - suppress_period: 86400s -eli5: The hosts file is present on both Windows and Linux endpoints. The purpose of - the hosts file is to provide a mapping between hostnames and IP addresses, the same - way DNS is used to provide such a mapping. However, the information in the hosts - file takes precedence over information received via DNS and a DNS query will not - be issued if the hostname of interest is found in the hosts file. As such, attackers - have been observed adding entries to the host file to override any DNS resolution. - For this reason, it is useful to monitor for changes to this file, which typically - do not occur very often in legitimate cases. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records the file-system activity from your hosts to populate the Endpoint.Filesystem - data model node. This is typically populated via endpoint detection-and-response - products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. - The data used for this search is typically generated via logs that report file-system - reads and writes. -id: 06a6fc63-a72d-41dc-8736-7e3dd9612116 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: There may be legitimate reasons for system administrators to - add entries to this file. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - - CIS 8 - - CIS 12 - kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Exfiltration - nist: - - PR.IP - - PR.PT - - PR.AC - - DE.AE - - DE.CM -modification_date: '2018-11-02' -name: Windows hosts file modification -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/hosts_receiving_high_volume_network_traffic_from_email_servers.yml b/detections/hosts_receiving_high_volume_network_traffic_from_email_servers.yml deleted file mode 100644 index 45ee8c9f06..0000000000 --- a/detections/hosts_receiving_high_volume_network_traffic_from_email_servers.yml +++ /dev/null @@ -1,122 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-12-20' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream -description: This search looks for an increase of data transfers from your email server - to your clients. This could be indicative of a malicious actor collecting data using - your email server. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip - rule_description: $src_ip$ receiving high volume of traffic that originated - from an email server - rule_title: High volume traffic from email server received by $src_ip$ - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 0 * * * - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as bytes_in from - datamodel=Network_Traffic where All_Traffic.dest_category=email_server by - All_Traffic.src_ip _time span=1d | `drop_dm_object_name("All_Traffic")` | - eventstats avg(bytes_in) as avg_bytes_in stdev(bytes_in) as stdev_bytes_in - | eventstats count as num_data_samples avg(eval(if(_time < relative_time(now(), - "@d"), bytes_in, null))) as per_source_avg_bytes_in stdev(eval(if(_time < - relative_time(now(), "@d"), bytes_in, null))) as per_source_stdev_bytes_in - by src_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where - num_data_samples >= minimum_data_samples AND bytes_in > (avg_bytes_in + (deviation_threshold - * stdev_bytes_in)) AND bytes_in > (per_source_avg_bytes_in + (deviation_threshold - * per_source_stdev_bytes_in)) AND _time >= relative_time(now(), "@d") | eval - num_standard_deviations_away_from_server_average = round(abs(bytes_in - avg_bytes_in) - / stdev_bytes_in, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_in - - per_source_avg_bytes_in) / per_source_stdev_bytes_in, 2) | table src_ip, - _time, bytes_in, avg_bytes_in, per_source_avg_bytes_in, num_standard_deviations_away_from_server_average, - num_standard_deviations_away_from_client_average' - suppress: - suppress_fields: src_ip - suppress_period: 86400s -eli5: This search may look complex, but it's a neat representation of how statistics - can help you understand your dataset to bubble up events that are not normal compared - to its behavior. The search consists of three parts. The first part of the SPL fetches - the data you want to work on. In this search, we calculate the sum of bytes sent - and bytes_out from systems categorized as email_server to each host. We then calculate - the average and standard deviation for the bytes sent to all the hosts combined - and on a per-host basis. Then we set threshold values to deviation_threshold and - minimum_data_samples using eval statements. The "deviation_threshold" field is a - multiplying factor to control how much variation you're willing to tolerate. The - "minimum_data_samples" field is the minimum number of connections of data samples - required for the statistic to be valid. We then check for byte transfers that are - statistically significantly higher than normal. The search then gives IP address - of the host, the time of the increased byte transfer, how much data was transferred, - and the average amount of data transfer the email server normally sends to all hosts - and to this specific host. Finally, it includes the number of standard deviations - away the byte count was from these averages. -entities: - - src_ip -how_to_implement: This search requires you to be ingesting your network traffic and - populating the Network_Traffic data model. Your email servers must be categorized - as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold - and minimum_data_samples values based on the network traffic in your environment. - The "deviation_threshold" field is a multiplying factor to control how much variation - you're willing to tolerate. The "minimum_data_samples" field is the minimum number - of connections of data samples required for the statistic to be valid. -id: 7f5fb3e1-4209-4914-90db-0ec21b556368 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk -known_false_positives: The false-positive rate will vary based on how you set the - deviation_threshold and data_samples values. Our recommendation is to adjust these - values based on your network traffic to and from your email servers. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 7 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Collection - - Commonly Used Port - nist: - - PR.PT - - DE.CM - - DE.AE -modification_date: '2017-12-20' -name: Hosts receiving high volume of network traffic from email server -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml new file mode 100644 index 0000000000..194a8e223c --- /dev/null +++ b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml @@ -0,0 +1,47 @@ +name: Hosts receiving high volume of network traffic from email server +id: 7f5fb3e1-4209-4914-90db-0ec21b556368 +version: '1.0' +date: '2017-12-20' +description: This search looks for an increase of data transfers from your email server + to your clients. This could be indicative of a malicious actor collecting data using + your email server. +how_to_implement: This search requires you to be ingesting your network traffic and + populating the Network_Traffic data model. Your email servers must be categorized + as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold + and minimum_data_samples values based on the network traffic in your environment. + The "deviation_threshold" field is a multiplying factor to control how much variation + you're willing to tolerate. The "minimum_data_samples" field is the minimum number + of connections of data samples required for the statistic to be valid. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as bytes_in + from datamodel=Network_Traffic where All_Traffic.dest_category=email_server by All_Traffic.src_ip + _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_in) + as avg_bytes_in stdev(bytes_in) as stdev_bytes_in | eventstats count as num_data_samples + avg(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_avg_bytes_in + stdev(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_stdev_bytes_in + by src_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples + >= minimum_data_samples AND bytes_in > (avg_bytes_in + (deviation_threshold * stdev_bytes_in)) + AND bytes_in > (per_source_avg_bytes_in + (deviation_threshold * per_source_stdev_bytes_in)) + AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average + = round(abs(bytes_in - avg_bytes_in) / stdev_bytes_in, 2), num_standard_deviations_away_from_client_average + = round(abs(bytes_in - per_source_avg_bytes_in) / per_source_stdev_bytes_in, 2) + | table src_ip, _time, bytes_in, avg_bytes_in, per_source_avg_bytes_in, num_standard_deviations_away_from_server_average, + num_standard_deviations_away_from_client_average' +known_false_positives: The false-positive rate will vary based on how you set the + deviation_threshold and data_samples values. Our recommendation is to adjust these + values based on your network traffic to and from your email servers. +tags: + analytics_story: + - Collection and Staging + mitre_attack_id: + - T1043 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 7 + nist: + - PR.PT + - DE.CM + - DE.AE diff --git a/detections/identify_new_user_accounts.yml b/detections/identify_new_user_accounts.yml new file mode 100644 index 0000000000..cb851c0a46 --- /dev/null +++ b/detections/identify_new_user_accounts.yml @@ -0,0 +1,29 @@ +name: Identify New User Accounts +id: 475b9e27-17e4-46e2-b7e2-648221be3b89 +version: '1.0' +date: '2017-09-12' +description: This detection search will help profile user accounts in your environment + by identifying newly created accounts that have been added to your network in the + past week. +how_to_implement: To successfully implement this search, you need to be populating + the Enterprise Security Identity_Management data model in the assets and identity + framework. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| from datamodel Identity_Management.All_Identities | eval empStatus=case((now()-startDate)<604800, + "Accounts created in last week") | search empStatus="Accounts created in last week"| + `security_content_ctime(endDate)` | `security_content_ctime(startDate)`| table identity + empStatus endDate startDate' +known_false_positives: If the Identity_Management data model is not updated regularly, + this search could give you false positive alerts. Please consider this and investigate + appropriately. +tags: + analytics_story: + - Account Monitoring and Controls + mitre_attack_id: + - T1136 + cis20: + - CIS 16 + nist: + - PR.IP diff --git a/detections/kubernetes_aws_scan_fingerprint.yml b/detections/kubernetes_aws_scan_fingerprint.yml deleted file mode 100644 index 801fddcc9e..0000000000 --- a/detections/kubernetes_aws_scan_fingerprint.yml +++ /dev/null @@ -1,74 +0,0 @@ -asset_type: Amazon EKS Kubernetes cluster -confidence: high -creation_date: '2020-03-24' -data_metadata: - data_source: - - AWS CloudWatch EKS Logs - data_sourcetypes: - - aws:cloudwatchlogs:eks - providing_technologies: - - AWS -description: This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, cluster_name, http_user_agent - rule_description: This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS - rule_title: Amazon EKS Kubernetes cluster scan detection - risk: - risk_object: cluster_name - risk_object_type: - - other - risk_score: 70 - macros: - - kubernetes_aws_scan_fingerprint_detection - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: 'sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`kubernetes_aws_scan_fingerprint_detection`' -eli5: In this search we can detect unauthenticated web requests against an EKS cluster, by looking at k8s authentication data, user agent and source IPs. -entities: - - cluster_name - - src_ip -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs - inputs. -id: 294c4686-63dd-4fe6-93a2-ca807626704a -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: a636cca4-7434-4a15-a278-c70734938e39 - name: Amazon EKS Kubernetes activity by src_ip - type: splunk -known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. -maintainers: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -mappings: - mitre_attack: - - Discovery - kill_chain_phases: - - Reconnaissance - mitre_technique_id: - - T1190 -modification_date: '2020-04-15' -name: Amazon EKS Kubernetes cluster scan detection -original_authors: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/kubernetes_gcp_scan_fingerprint_attack.yml b/detections/kubernetes_gcp_scan_fingerprint_attack.yml deleted file mode 100644 index 06f58f180a..0000000000 --- a/detections/kubernetes_gcp_scan_fingerprint_attack.yml +++ /dev/null @@ -1,72 +0,0 @@ -asset_type: GCP Kubernetes cluster -confidence: high -creation_date: '2020-03-24' -data_metadata: - data_source: - - GCP Stackdriver logs - data_sourcetypes: - - google:gcp:pubsub:message - providing_technologies: - - GCP -description: This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, - rule_description: Detect scanning attempts against a GCP Kubernetes cluster - rule_title: GCP Kubernetes cluster scan detection - risk: - risk_object: cluster_name - risk_object_type: - - other - risk_score: 70 - macros: - - kubernetes_gcp_scan_fingerprint_detection - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_name values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_gcp_scan_fingerprint_detection` -eli5: In this search we can detect unauthenticated web requests and possible attack against a GCP cluster, by looking at k8s authentication data, user agent, source IPs and destionation -entities: - - cluster_name - - src_ip -how_to_implement: You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. -id: db5957ec-0144-4c56-b512-9dccbe7a2d26 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: c00e7626-92cc-4e06-9a51-b6db0a50bd1f - name: GCP Kubernetes activity by src_ip - type: splunk -known_false_positives: Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. -maintainers: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -mappings: - mitre_attack: - - Discovery - kill_chain_phases: - - Reconnaissance - mitre_technique_id: - - T1190 -modification_date: '2020-04-15' -name: GCP Kubernetes cluster scan detection -original_authors: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/kubernetes_pods_aws_scan_fingerprint.yml b/detections/kubernetes_pods_aws_scan_fingerprint.yml deleted file mode 100644 index b23731ebc6..0000000000 --- a/detections/kubernetes_pods_aws_scan_fingerprint.yml +++ /dev/null @@ -1,72 +0,0 @@ -asset_type: Amazon EKS Kubernetes cluster Pod -confidence: medium -creation_date: '2020-03-24' -data_metadata: - data_source: - - AWS CloudWatch EKS Logs - data_sourcetypes: - - aws:cloudwatchlogs:eks - providing_technologies: - - AWS -description: This search provides detection information on unauthenticated requests against Kubernetes' Pods API -detect: - splunk: - correlation_rule: - notable: - nes_fields: user.username, sourceIPs, verb, http_user_agent, group_name, requestURI - rule_description: This search provides detection information on unauthenticated requests against Kubernetes' Pods API - rule_title: Amazon EKS Kubernetes Pod scan detection - risk: - risk_object: cluster_name - risk_object_type: - - other - risk_score: 70 - macros: - - kubernetes_pods_aws_scan_fingerprint_detection - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" verb=list objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_detection` -eli5: In this search we can detect unauthenticated web requests against an EKS cluster Pod, by looking at k8s authentication data, user agent and source IPs and API direct request. -entities: - - cluster_name - - src_ip -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. -id: dbfca1dd-b8e5-4ba4-be0e-e565e5d62002 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: a636cca4-7434-4a15-a278-c70734938e39 - name: Amazon EKS Kubernetes activity by src_ip - type: splunk -known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. -maintainers: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -mappings: - mitre_attack: - - Discovery - kill_chain_phases: - - Reconnaissance - mitre_technique_id: - - T1190 -modification_date: '2020-04-15' -name: Amazon EKS Kubernetes Pod scan detection -original_authors: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/large_icmp_outbound.yml b/detections/large_icmp_outbound.yml deleted file mode 100644 index 4c17f11b73..0000000000 --- a/detections/large_icmp_outbound.yml +++ /dev/null @@ -1,112 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-06-01' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream - - Palo Alto Firewall -description: This search looks for outbound ICMP packets with a packet size larger - than 1,000 bytes. Various threat actors have been known to use ICMP as a command - and control channel for their attack infrastructure. Large ICMP packets from an - endpoint to a remote host may be indicative of this activity. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, dest_ip - rule_description: Large outbound ICMP packet detected. - rule_title: Large ICMP packet from $src_ip$ to $dest_ip$ detected - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count earliest(_time) as firstTime latest(_time) - as lastTime values(All_Traffic.action) values(All_Traffic.bytes) from datamodel=Network_Traffic - where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.protocol=icmp - OR All_Traffic.transport=icmp) All_Traffic.bytes > 1000 by All_Traffic.src_ip - All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 - AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' - suppress: - suppress_fields: src_ip - suppress_period: 28800s -eli5: This search works by looking at fields in the Network_Traffic data model, which - is populated by various firewalls and passive networking monitoring technologies. - Specifically, the search looks for ICMP packets larger than 1,000 bytes with a destination - that is external to your organization. -entities: - - src_ip -how_to_implement: 'In order to run this search effectively, we highly recommend that - you leverage the Assets and Identity framework. It is important that you have a - good understanding of how your network segments are designed and that you are able - to distinguish internal from external address space. Add a category named `internal` - to the CIDRs that host the company''s assets in the `assets_by_cidr.csv` lookup - file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. - More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. - This search also requires you to be ingesting your network traffic and populating - the Network_Traffic data model' -id: e9c102de-4d43-42a7-b1c8-8062ea297419 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: ICMP packets are used in a variety of ways to help troubleshoot - networking issues and ensure the proper flow of traffic. As such, it is possible - that a large ICMP packet could be perfectly legitimate. If large ICMP packets are - associated with command and control traffic, there will typically be a large number - of these packets observed over time. If the search is providing a large number of - false positives, you can modify the search to adjust the byte threshold or whitelist - specific IP addresses, as necessary. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 9 - - CIS 12 - kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Standard Non-Application Layer Protocol - nist: - - DE.AE -modification_date: '2018-06-01' -name: Detect Large Outbound ICMP Packets -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/large_volume_of_dns_any_queries.yml b/detections/large_volume_of_dns_any_queries.yml new file mode 100644 index 0000000000..4c1e28bbdb --- /dev/null +++ b/detections/large_volume_of_dns_any_queries.yml @@ -0,0 +1,29 @@ +name: Large Volume of DNS ANY Queries +id: 8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb +version: '1.0' +date: '2017-09-20' +description: The search is used to identify attempts to use your DNS Infrastructure + for DDoS purposes via a DNS amplification attack leveraging ANY queries. +how_to_implement: To successfully implement this search you must ensure that DNS data + is populating the Network_Resolution data model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution + where nodename=DNS "DNS.message_type"="QUERY" "DNS.record_type"="ANY" by "DNS.dest" + | `drop_dm_object_name("DNS")` | where count>200' +known_false_positives: Legitimate ANY requests may trigger this search, however it + is unusual to see a large volume of them under typical circumstances. You may modify + the threshold in the search to better suit your environment. +tags: + analytics_story: + - DNS Amplification Attacks + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 11 + - CIS 12 + nist: + - PR.PT + - DE.AE + - PR.IP diff --git a/detections/lnk_executing_a_process.yml b/detections/lnk_executing_a_process.yml deleted file mode 100644 index 5288ef531c..0000000000 --- a/detections/lnk_executing_a_process.yml +++ /dev/null @@ -1,94 +0,0 @@ -asset_type: Endpoint -baselines: [] -confidence: high -creation_date: '2019-04-29' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` - executing a process. This is common behavior used by various spear phishing tools. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process_name, file_name - rule_description: suspicious LNK file from $file_name$ is executing a process - $process_name$ on $dest$ - rule_title: LNK file $file_name$ is executing process $process_name$ on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - macros: - - lnk_executing_a_process_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_name="*.lnk" - AND (Filesystem.file_path="C:\\Users*" OR Filesystem.file_path="*Local\\Temp*") by - _time span=1h Filesystem.process_id Filesystem.file_name Filesystem.file_path - Filesystem.file_hash Filesystem.user | `drop_dm_object_name(Filesystem)` | - rename process_id as lnk_pid | join lnk_pid, _time [| tstats `security_content_summariesonly` - count FROM datamodel=Endpoint.Processes where Processes.process_name=* by - _time span=1h Processes.parent_process_id Processes.process_id Processes.process_name - Processes.dest Processes.process_path Processes.process | `drop_dm_object_name(Processes)` - | rename parent_process_id as lnk_pid | fields _time lnk_pid process_id dest - process_name process_path process] | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | table firstTime, lastTime, lnk_pid, process_id, user, dest, file_name, file_path, - process_name, process, process_path, file_hash | `lnk_executing_a_process_filter`' - suppress: - suppress_fields: dest,file_name - suppress_period: 86400s -eli5: In this search, we are essentially trying to detect if a LNK file created under - the C:\User* or *\Local\Temp\* directory structures is launching a process with - in 1 hour of its creation. LNK files or also known as Windows shortcut files are - commonly associated with phishing and are a [preferred method used for exploitation](https://www.fireeye.com/blog/threat-research/2017/04/fin7-phishing-lnk.html). -entities: - - dest -how_to_implement: You must be ingesting data that records filesystem and process activity - from your hosts to populate the Endpoint data model. This is typically populated - via endpoint detection-and-response products, such as Carbon Black, or endpoint - data sources, such as Sysmon. -id: 5d814af1-1041-47b5-a9ac-d754e82e9a26 -investigations: [] -known_false_positives: This detection should yield little or no false positive results. - It is uncommon for LNK files to execute process from temporary or user directories. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: - cis20: - - CIS 7 - - CIS 8 - kill_chain_phases: - - Installation - - Actions on Objectives - mitre_attack: - - Initial Access - - Spearphishing Attachment - nist: - - ID.AM - - PR.DS -modification_date: '2020-03-16' -name: Suspicious LNK file launching a process -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/local_admin_account_creation.yml b/detections/local_admin_account_creation.yml deleted file mode 100644 index 7823101d52..0000000000 --- a/detections/local_admin_account_creation.yml +++ /dev/null @@ -1,126 +0,0 @@ -asset_type: Windows -confidence: medium -creation_date: '2018-03-26' -data_metadata: - data_eventtypes: - - wineventlog_security - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search looks for newly created accounts that have been elevated - to local administrators. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user,src_user, dest - rule_description: The new user account $user$ was created on $dest$ by $src_user$. - rule_title: New local admin account $user$ created by $src_user$. - risk: - risk_object: user - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 9 * * * - earliest_time: -1440m@m - latest_time: -10m@m - search: eventtype = wineventlog_security signature_id=4720 OR (signature_id=4732 - Group_Name= Administrators) | transaction Security_ID connected=false maxspan=180m | search - signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID - Group_Name src_user Message - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: This search looks for Windows Event Code 4720 (account creation) and 4732 (account - added to a security-enabled local group), where the group name is "Administrators", - and determines whether they are generated for the same user's Security ID within - three hours of each other. It will return the user account that was added, the - Security ID, the group name to which the user was added, the account name of the - user who initiated the action, and the subsequent message returned. -entities: - - user -how_to_implement: 'You must be ingesting Windows Security logs. You must also enable - the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. - Additionally, this search requires you to enable your Group Management Audit Logs - in your Local Windows Security Policy and to be ingesting those logs. More information - on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. - Finally, please make sure that the local administrator group name is "Administrators" - to be able to look for the right group membership changes.\ - - This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not - yet supported by ES Incident Review and therefore cannot be viewed when a notable - event is raised. These fields contribute additional context to the notable. To see - the additional metadata, add the following fields, if not already present, to Incident - Review - Event Attributes (Configure > Incident Management > Incident Review Settings - > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ - - 1. \ - - 1. **Label:** Group Name, **Field:** Group_Name\ - - 1. \ - - 1. **Label:** Message, **Field:** Message\ - - Detailed documentation on how to create a new field within Incident Review may be - found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: b25f6f62-0712-43c1-b203-083231ffd97d -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: The activity may be legitimate. For this reason, it's best - to verify the account with an administrator and ask whether there was a valid service - request for the account creation. If your local administrator group name is not - "Administrators", this search may generate an excessive number of false positives -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - - Command and Control - mitre_attack: - - Valid Accounts - - Defense Evasion - - Persistence - nist: - - PR.AC - - DE.CM -modification_date: '2019-02-28' -name: Detect New Local Admin account -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: access -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/long_dns_text_response.yml b/detections/long_dns_text_response.yml deleted file mode 100644 index 6e61e544f1..0000000000 --- a/detections/long_dns_text_response.yml +++ /dev/null @@ -1,120 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-06-18' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: This search is used to detect attempts to use DNS tunneling, by calculating - the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission - for data exfiltration, command and control, or evasion of security controls can - often be detected by noting unusually large volumes of DNS traffic. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, query - rule_description: A DNS TXT record response of over 100 characters was detected. - rule_title: Long DNS TXT Record Response - risk: - risk_object: src - risk_object_type: - - system - risk_score: 70 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Network_Resolution where DNS.message_type=response - AND DNS.record_type=TXT by DNS.src DNS.dest DNS.answer DNS.record_type | `drop_dm_object_name("DNS")` - | eval anslen=len(answer) | search anslen>100 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | rename src as "Source IP", dest as "Destination IP", answer as "DNS Answer" - anslen as "Answer Length" record_type as "DNS Record Type" firstTime as "First - Time" lastTime as "Last Time" count as Count | table "Source IP" "Destination - IP" "DNS Answer" "DNS Record Type" "Answer Length" Count "First Time" "Last - Time"' - suppress: - suppress_fields: src - suppress_period: 86400s -eli5: This search uses the Network_Resolution data model and gathers all the answers - to DNS queries for TXT records. The query then looks at the answer section and calculates - the length of the answer. The search will then return information for those responses - that exceed 100 characters in length. -entities: - - src -how_to_implement: To successfully implement this search you need to ingest data from - your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, - this query requires that the DNS data model is populated with information regarding - the DNS record type that is being returned as well as the data in the answer section - of the protocol. -id: 05437c07-62f5-452e-afdc-04dd44815bb9 -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 - name: Get DNS traffic ratio - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It's possible that legitimate TXT record responses can be long - enough to trigger this search. You can modify the packet threshold for this search - to help mitigate false positives. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - - CIS 12 - - CIS 13 - kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Exfiltration - - Commonly Used Port - nist: - - PR.DS - - PR.PT - - DE.AE - - DE.CM -modification_date: '2017-09-18' -name: Detect Long DNS TXT Record Response -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/macos___re_opened_applications.yml b/detections/macos___re_opened_applications.yml new file mode 100644 index 0000000000..81839d0088 --- /dev/null +++ b/detections/macos___re_opened_applications.yml @@ -0,0 +1,34 @@ +name: MacOS - Re-opened Applications +id: 40bb64f9-f619-4e3d-8732-328d40377c4b +version: '1.0' +date: '2020-02-07' +description: This search looks for processes referencing the plist files that determine + which applications are re-opened when a user reboots their machine. +how_to_implement: In order to properly run this search, Splunk needs to ingest process + data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) + pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be + deployed across your indexers and universal forwarders in order to have the data + populate the Endpoint data model. +type: ESCU +references: [] +author: Jamie Windley, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process="*com.apple.loginwindow*" + by Processes.user Processes.process_name Processes.parent_process_name Processes.dest + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +known_false_positives: At this stage, there are no known false positives. During testing, + no process events refering the com.apple.loginwindow.plist files were observed during + normal operation of re-opening applications on reboot. Therefore, it can be asumed + that any occurences of this in the process events would be worth investigating. + In the event that the legitimate modification by the system of these files is in + fact logged to the process log, then the process_name of that process can be whitelisted. +tags: + kill_chain_phases: + - Installation + - Command and Control + cis20: + - CIS 8 + nist: + - DE.DP + - DE.CM diff --git a/detections/macos_re-opened_applications.yml b/detections/macos_re-opened_applications.yml deleted file mode 100644 index 55b5635484..0000000000 --- a/detections/macos_re-opened_applications.yml +++ /dev/null @@ -1,71 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2020-02-07' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint - providing_technologies: - - OSquery -description: This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. -detect: - splunk: - correlation_rule: - notable: - nes_fields: host - rule_description: Observed process referencing MacOS com.apple.loginwindow.plist files for Host $host$ - rule_title: Possible attempt to establish persistence on $host$ - risk: - risk_object: host - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process="*com.apple.loginwindow*" by Processes.user Processes.process_name Processes.parent_process_name Processes.dest - | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: host - suppress_period: 3600s -eli5: The search looks at the Endpoint data model to identify any MacOS process events referencing a property list file which determines which applications are "re-opened" during startup. This could indicate a malicious attempt to establish persistence on the system. -entities: - - host -how_to_implement: In order to properly run this search, Splunk needs to ingest process data - from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) - pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must - be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. -id: 40bb64f9-f619-4e3d-8732-328d40377c4b -known_false_positives: At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. -maintainers: - - company: Splunk - email: jwindley@splunk.com - name: Jamie Windley -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Installation - - Command and Control - mitre_attack: - - Persistence - mitre_technique_id: - - T1164 - nist: - - DE.DP - - DE.CM -modification_date: '2020-02-07' -name: MacOS - Re-opened Applications -original_authors: - - company: Splunk - email: jwindley@splunk.com - name: Jamie Windley -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/malicious_application_shimming_via_registry.yml b/detections/malicious_application_shimming_via_registry.yml deleted file mode 100644 index 8ea5335ec2..0000000000 --- a/detections/malicious_application_shimming_via_registry.yml +++ /dev/null @@ -1,113 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-08-27' -data_metadata: - data_models: - - Change_Analysis - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: This search looks for registry activity associated with application compatibility - shims, which can be leveraged by attackers for various nefarious purposes. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user - rule_description: A registry key that is used for persistence on Windows was - modified on $dest$ by $user$ - rule_title: Registry Key Associated With SHIM databases on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry - AND (All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\Custom*" OR - All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\InstalledSDB*") - by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, - All_Changes.object_path | `drop_dm_object_name("All_Changes")`' - suppress: - suppress_fields: dest,object_path - suppress_period: 86400s -eli5: In this search, we look for modifications to registry keys used for shim databases - on Microsoft platforms via the object_category and object_path field in the Change_Analysis - data model and give you the destination, command used to initiate the change, the - user who conducted this activity, the resource affected(object), and the whole path - of the object. An application compatibility shim is a small library that transparently - intercepts an API (via hooking), changes the parameters passed, handles the operation - itself, or redirects the operation elsewhere, such as additional code stored on - a system. This capability can be also leveraged by attackers to create and store - malicious files in a shim database as observed in CARBANAK backdoor. -entities: - - dest -how_to_implement: To successfully implement this search, you must populate the Change_Analysis - data model. This is typically populated via endpoint detection and response products, - such as Carbon Black or other endpoint data sources such as Sysmon. The data used - for this search is typically generated via logs that report reads and writes to - the registry. -id: f5f6af30-7aa7-4295-bfe9-07fe87c01bbb -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: There are many legitimate applications that leverage shim databases - for compatibility purposes for legacy applications -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Application Shimming - nist: - - PR.PT - - DE.CM -modification_date: '2017-09-15' -name: Registry Keys for Creating SHIM Databases -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml new file mode 100644 index 0000000000..a0fd706068 --- /dev/null +++ b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml @@ -0,0 +1,44 @@ +name: Malicious PowerShell Process - Connect To Internet With Hidden Window +id: ee18ed37-0802-4268-9435-b3b91aaa18db +version: '3.0' +date: '2018-12-03' +description: This search looks for PowerShell processes started with parameters to + modify the execution policy of the run, run in a hidden window, and connect to the + Internet. This combination of command-line options is suspicious because it's overriding + the default PowerShell execution policy, attempts to hide its activity from the + user, and connects to the Internet. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe + by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | search process="*-Exec*" process="*-WindowStyle*" process="*hidden*" process="*New-Object*" + process="*System.Net.WebClient*"' +known_false_positives: Legitimate process can have this combination of command-line + options, but it's not common. +tags: + analytics_story: + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Malicious PowerShell + mitre_attack_id: + - T1086 + - T1064 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 3 + - CIS 7 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/malicious_powershell_process___encoded_command.yml b/detections/malicious_powershell_process___encoded_command.yml new file mode 100644 index 0000000000..38923dd4ac --- /dev/null +++ b/detections/malicious_powershell_process___encoded_command.yml @@ -0,0 +1,39 @@ +name: Malicious PowerShell Process - Encoded Command +id: c4db14d9-7909-48b4-a054-aa14d89dbb19 +version: '3.0' +date: '2018-12-03' +description: This search looks for PowerShell processes that have encoded the script + within the command-line. Malware has been seen using this parameter, as it obfuscates + the code and makes it relatively easy to pass a script on the command-line. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe + by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | search process=*-EncodedCommand* OR process=*-enc*' +known_false_positives: System administrators may use this option, but it's not common. +tags: + analytics_story: + - Malicious PowerShell + mitre_attack_id: + - T1086 + - T1064 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 3 + - CIS 7 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/malicious_powershell_process___execution_policy_bypass.yml b/detections/malicious_powershell_process___execution_policy_bypass.yml new file mode 100644 index 0000000000..92a258438e --- /dev/null +++ b/detections/malicious_powershell_process___execution_policy_bypass.yml @@ -0,0 +1,42 @@ +name: Malicious PowerShell Process - Execution Policy Bypass +id: 9be56c82-b1cc-4318-87eb-d138afaaca39 +version: '3.0' +date: '2018-12-03' +description: This search looks for PowerShell processes started with parameters used + to bypass the local execution policy for scripts. These parameters are often observed + in attacks leveraging PowerShell scripts as they override the default PowerShell + execution policy. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process_id) as + process_id, values(Processes.parent_process_id) as parent_process_id values(Processes.process) + as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name=powershell.exe AND (Processes.process="* -ex*" OR Processes.process="* + bypass *") by Processes.process_id, Processes.user, Processes.dest | `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +known_false_positives: There may be legitimate reasons to bypass the PowerShell execution + policy. The PowerShell script being run with this parameter should be validated + to ensure that it is legitimate. +tags: + analytics_story: + - DHS Report TA18-074A + mitre_attack_id: + - T1086 + - T1064 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 3 + - CIS 7 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml new file mode 100644 index 0000000000..becbf54219 --- /dev/null +++ b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml @@ -0,0 +1,43 @@ +name: Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments +id: 2cdb91d2-542c-497f-b252-be495e71f38c +version: '3.0' +date: '2018-12-03' +description: This search looks for PowerShell processes started with a base64 encoded + command-line passed to it, with parameters to modify the execution policy for the + process, and those that prevent the display of an interactive prompt to the user. + This combination of command-line options is suspicious because it overrides the + default PowerShell execution policy, attempts to hide itself from the user, and + passes an encoded script to be run on the command-line. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe + by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| + search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI*' +known_false_positives: Legitimate process can have this combination of command-line + options, but it's not common. +tags: + analytics_story: + - Malicious PowerShell + mitre_attack_id: + - T1086 + - T1064 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 3 + - CIS 7 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/malicious_powershell_process_connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process_connect_to_internet_with_hidden_window.yml deleted file mode 100644 index 438dac1cd0..0000000000 --- a/detections/malicious_powershell_process_connect_to_internet_with_hidden_window.yml +++ /dev/null @@ -1,125 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-18' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for PowerShell processes started with parameters to - modify the execution policy of the run, run in a hidden window, and connect to the - Internet. This combination of command-line options is suspicious because it's overriding - the default PowerShell execution policy, attempts to hide its activity from the - user, and connects to the Internet. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: The system $dest$ executed a PowerShell process that connects - to the Internet with a hidden window. - rule_title: Malicious PowerShell Process detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 75 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe - by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | - search process="*-Exec*" process="*-WindowStyle*" process="*hidden*" process="*New-Object*" - process="*System.Net.WebClient*"' - suppress: - suppress_fields: process_name, dest - suppress_period: 86400s -eli5: This search looks for PowerShell processes running with specific command-line - arguments that indicate that the process will download a file from the Internet - without display anything to the user. The search for "*-Exec*" is to check and see - if the default execution policy for PowerShell is being overridden on the command-line. - The search for "*-WindowStyle*" and "*hidden*" are to see if the window that would - normally be displayed will be hidden from the user instead. Finally, the search - for "*New-Object*" and "*System.Net.WebClient*" are there to check to see if a PowerShell - object that can be used to download files will be created. This search will return - the host, the user the process ran under, the process and it's command-line arguments, - the number of times it's seen this process, and the first and last times it saw - this process. -entities: - - dest - - process_name - - user -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: ee18ed37-0802-4268-9435-b3b91aaa18db -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Legitimate process can have this combination of command-line - options, but it's not common. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 7 - - CIS 8 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - - PowerShell - - Scripting - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2018-12-03' -name: Malicious PowerShell Process - Connect To Internet With Hidden Window -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/malicious_powershell_process_encoded_command.yml b/detections/malicious_powershell_process_encoded_command.yml deleted file mode 100644 index 2723244b9e..0000000000 --- a/detections/malicious_powershell_process_encoded_command.yml +++ /dev/null @@ -1,113 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-18' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for PowerShell processes that have encoded the script - within the command-line. Malware has been seen using this parameter, as it obfuscates - the code and makes it relatively easy to pass a script on the command-line. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: The system $dest$ executed a PowerShell process that has - an encoded command on the command-line - rule_title: PowerShell process with an encoded command detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe - by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | - search process=*-EncodedCommand* OR process=*-enc*' - suppress: - suppress_fields: dest, user, process_name - suppress_period: 14400s -eli5: This search looks for PowerShell processes that are passing encoded commands - on the command-line. The flags "-EncodedCommand" and "-enc" are two different possible - flags that can be used to pass base64 encoded commands to PowerShell. This search - will return the host, the user the process ran under, the process and it's command-line - arguments, the number of times it's seen this process, and the first and last times - it saw this process. -entities: - - dest - - process_name - - user -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: c4db14d9-7909-48b4-a054-aa14d89dbb19 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: System administrators may use this option, but it's not common. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 7 - - CIS 8 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - - PowerShell - - Scripting - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2018-12-03' -name: Malicious PowerShell Process - Encoded Command -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/malicious_powershell_process_execpolicy.yml b/detections/malicious_powershell_process_execpolicy.yml deleted file mode 100644 index 8d5590b727..0000000000 --- a/detections/malicious_powershell_process_execpolicy.yml +++ /dev/null @@ -1,121 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-03-19' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for PowerShell processes started with parameters used - to bypass the local execution policy for scripts. These parameters are often observed - in attacks leveraging PowerShell scripts as they override the default PowerShell - execution policy. -detect: - splunk: - correlation_rule: - notable: - drilldown_name: View powershell process information on $dest$ - drilldown_search: '| from datamodel:Endpoint.Processes | search dest="$dest$" process_id=$process_id$' - nes_fields: dest, user, process_name - rule_description: The system $dest$ executed a PowerShell process with parameters - to bypass the local execution policy. - rule_title: PowerShell process with -executionpolicy bypass detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 50 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process_id) as process_id, - values(Processes.parent_process_id) as parent_process_id values(Processes.process) as process - min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where Processes.process_name=powershell.exe AND (Processes.process="* -ex*" OR Processes.process="* bypass *") by - Processes.process_id, Processes.user, Processes.dest - | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process_name - suppress_period: 14400s -eli5: This search looks for PowerShell processes that were launched using a parameter - designed to bypass the local PowerShell execution policy. By default, the policy - is set to "Restricted," which disables the execution of PowerShell scripts. In environments - that make heavy use of PowerShell, the policy can be set to allow only scripts signed - by a trusted publisher. Malicious PowerShell use almost always includes the parameter - `-ExecutionPolicy bypass`. PowerShell is very liberal when it comes to interpreting - command-line parameters passed to it. For example, the parameter we look for, `-ExecutionPolicy`, - can be abbreviated to `-Execution`, `-Exec`, or even `-ex`. As such, we look for - `* -ex*`, which should catch all variations of this parameter, followed by the keyword - `bypass`. This search will return the host, the user the process ran under, the - process and its command-line arguments, the number of times it has seen this process, - and the first and last times it saw this process. -entities: - - dest - - process_id - - process - - parent_process_id -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: 9be56c82-b1cc-4318-87eb-d138afaaca39 -investigations: - - id: d8362a34-b78a-4364-9733-59b505f5b8d5 - name: Get Process Registry Activity - type: splunk - - id: 6a9ad4d9-6ef2-4b85-953f-a37ab256acd5 - name: Get Process File Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk -known_false_positives: There may be legitimate reasons to bypass the PowerShell execution - policy. The PowerShell script being run with this parameter should be validated - to ensure that it is legitimate. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 7 - - CIS 8 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - - PowerShell - - Scripting - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2018-12-03' -name: Malicious PowerShell Process - Execution Policy Bypass -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/malicious_powershell_process_multiple_suspicious_arguments.yml b/detections/malicious_powershell_process_multiple_suspicious_arguments.yml deleted file mode 100644 index 8627097c10..0000000000 --- a/detections/malicious_powershell_process_multiple_suspicious_arguments.yml +++ /dev/null @@ -1,123 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-18' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for PowerShell processes started with a base64 encoded - command-line passed to it, with parameters to modify the execution policy for the - process, and those that prevent the display of an interactive prompt to the user. - This combination of command-line options is suspicious because it overrides the - default PowerShell execution policy, attempts to hide itself from the user, and - passes an encoded script to be run on the command-line. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process, process_name - rule_description: The system $dest$ executed a PowerShell that had an encoded - command on the command-line, attempted to bypass local execution policy, - and prevented the display of an interactive prompt to the user. - rule_title: PowerShell process with multiple suspicious command-line arguments - detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - schedule: - cron_schedule: 50 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe - by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| - search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI*' - suppress: - suppress_fields: dest, process_name - suppress_period: 14400s -eli5: This search looks for PowerShell processes that have a number of suspicious - flags on the command-line. It is looking for flags are passing encoded commands - on the command-line. The flags `-EncodedCommand` and `-enc` are two different possible - flags that can be used to pass base64 encoded commands to PowerShell. The `*-Exec*` - flag looks to see it the default execution policy of PowerShell is being overridden, - while the `*-NonI*` flag tells the PowerShell process that this will be a noninteractive - process, so the user doesn't know about the process. This search will return the - host, the user the process ran under, the process and it's command-line arguments, - the number of times it's seen this process, and the first and last times it saw - this process. -entities: - - dest - - process_name - - user -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: 2cdb91d2-542c-497f-b252-be495e71f38c -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Legitimate process can have this combination of command-line - options, but it's not common. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 7 - - CIS 8 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - - PowerShell - - Scripting - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2018-12-03' -name: Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/malicious_powershell_process_obfuscation_techniques.yml b/detections/malicious_powershell_process_obfuscation_techniques.yml deleted file mode 100644 index 20ce13cf37..0000000000 --- a/detections/malicious_powershell_process_obfuscation_techniques.yml +++ /dev/null @@ -1,117 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-04-25' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for PowerShell processes launched with arguments that - have characters indicative of obfuscation on the command-line. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name, process - rule_description: The system $dest$ executed a PowerShell process that has - evidence of obfuscation on the command-line - rule_title: PowerShell process with an obfuscation techniques detected on - $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe - by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| - eval num_obfuscation = (mvcount(split(process, "`"))-1) + (mvcount(split(process, - "^"))-1) | `malicious_powershell_process_obfuscation_techniques_output_filter` | search num_obfuscation > 0' - suppress: - suppress_fields: dest,process_name,process - suppress_period: 14400s -eli5: This search looks for PowerShell processes that are passing command-line arguments - with unusual characters (backticks and carets) that are PowerShell specific escape - characters. Attackers use this obfuscation technique since it does not affect the - functionality of PowerShell and it will bypass standard security controls that look - for straight up malicious strings and commands. The search counts the occurrence - of these obfuscation characters and lists out destination IPs running these PowerShell - commands. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: cde75cf6-3c7a-4dd6-af01-27cdb4511fd4 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: These characters might be legitimately on the command-line, - but it is not common. -maintainers: - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 7 - - CIS 8 - kill_chain_phases: - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - - PowerShell - - Scripting - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2020-01-17' -name: Malicious PowerShell Process With Obfuscation Techniques -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/malicious_powershell_process_with_obfuscation_techniques.yml b/detections/malicious_powershell_process_with_obfuscation_techniques.yml new file mode 100644 index 0000000000..3bce4a70e9 --- /dev/null +++ b/detections/malicious_powershell_process_with_obfuscation_techniques.yml @@ -0,0 +1,41 @@ +name: Malicious PowerShell Process With Obfuscation Techniques +id: cde75cf6-3c7a-4dd6-af01-27cdb4511fd4 +version: '2.0' +date: '2020-01-17' +description: This search looks for PowerShell processes launched with arguments that + have characters indicative of obfuscation on the command-line. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe + by Processes.user Processes.process_name Processes.parent_process_name Processes.dest + Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process, + "`"))-1) + (mvcount(split(process, "^"))-1) | `malicious_powershell_process_obfuscation_techniques_output_filter` + | search num_obfuscation > 0' +known_false_positives: These characters might be legitimately on the command-line, + but it is not common. +tags: + analytics_story: + - Malicious PowerShell + mitre_attack_id: + - T1086 + - T1064 + kill_chain_phases: + - Command and Control + - Actions on Objectives + cis20: + - CIS 3 + - CIS 7 + - CIS 8 + nist: + - PR.PT + - DE.CM + - PR.IP diff --git a/detections/malicious_requests_to_exploit_jboss_servers.yml b/detections/malicious_requests_to_exploit_jboss_servers.yml deleted file mode 100644 index 9a517bdc51..0000000000 --- a/detections/malicious_requests_to_exploit_jboss_servers.yml +++ /dev/null @@ -1,100 +0,0 @@ -asset_type: Web Server -confidence: high -creation_date: '2016-10-04' -data_metadata: - data_models: - - Web - data_source: - - Network Communications - - Web Server - providing_technologies: - - Splunk Stream - - Palo Alto Firewall - - Apache - - Bro -description: This search is used to detect malicious HTTP requests crafted to exploit - jmx-console in JBoss servers. The malicious requests have a long URL length, as - the payload is embedded in the URL. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, dest_ip - rule_description: A search for detecting malicious requests made to exploit - jmx-console in JBoss servers. The bad requests have a long url length since - it serves the payload via the url - rule_title: Detected malicious requests to exploit JBoss servers - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") - by Web.http_method, Web.url,Web.url_length Web.src, Web.dest | search Web.url="*jmx-console/HtmlAdaptor?action=invokeOpByName&name=jboss.admin*import*" - AND Web.url_length > 200 | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | table src, dest_ip, http_method, url, firstTime, lastTime' - suppress: - suppress_fields: dest,url,src - suppress_period: 14400s -eli5: This search looks for HTTP requests for a URL that has been used to exploit - JBoss servers. -entities: - - dest -how_to_implement: You must ingest data from the web server or capture network data - that contains web specific information with solutions such as Bro or Splunk Stream, - and populating the Web data model -id: c8bff7a4-11ea-4416-a27d-c5bca472913d -investigations: - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: No known false positives for this detection. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 12 - - CIS 4 - - CIS 18 - kill_chain_phases: - - Delivery - mitre_attack: - - Defense Evasion - - Exploitation of Vulnerability - nist: - - ID.RA - - PR.PT - - PR.IP - - DE.AE - - PR.MA - - DE.CM -modification_date: '2017-09-23' -name: Detect malicious requests to exploit JBoss servers -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/monitor_dns_for_brand_abuse.yml b/detections/monitor_dns_for_brand_abuse.yml new file mode 100644 index 0000000000..825e1fcfd5 --- /dev/null +++ b/detections/monitor_dns_for_brand_abuse.yml @@ -0,0 +1,26 @@ +name: Monitor DNS For Brand Abuse +id: 24dd17b1-e2fb-4c31-878c-d4f746595bfa +version: '1.0' +date: '2017-09-23' +description: This search looks for DNS requests for faux domains similar to the domains + that you want to have monitored for abuse. +how_to_implement: You need to ingest data from your DNS logs. Specifically you must + ingest the domain that is being queried and the IP of the host originating the request. + Ideally, you should also be ingesting the answer to the query and the query type. + This approach allows you to also create your own localized passive DNS capability + which can aid you in future investigations. You also need to have run the search + "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that + will be checked for. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` values(DNS.answer) as IPs min(_time) + as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` + | `security_content_ctime(firstTime)`| `brand_abuse_dns`' +known_false_positives: None at this time +tags: + analytics_story: + - Brand Monitoring + kill_chain_phases: + - Delivery + - Actions on Objectives diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml new file mode 100644 index 0000000000..3213a12b6f --- /dev/null +++ b/detections/monitor_email_for_brand_abuse.yml @@ -0,0 +1,31 @@ +name: Monitor Email For Brand Abuse +id: b2ea1f38-3a3e-4b8a-9cf1-82760d86a6b8 +version: '2.0' +date: '2018-01-05' +description: This search looks for emails claiming to be sent from a domain similar + to one that you want to have monitored for abuse. +how_to_implement: You need to ingest email header data. Specifically the sender's + address (src_user) must be populated. You also need to have run the search "ESCU + - DNSTwist Domain Names", which creates the permutations of the domain that will + be checked for. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` values(All_Email.recipient) as + recipients, min(_time) as firstTime, max(_time) as lastTime from datamodel=Email + by All_Email.src_user, All_Email.message_id | `drop_dm_object_name("All_Email")` + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval + temp=split(src_user, "@") | eval email_domain=mvindex(temp, 1) | lookup update=true + brandMonitoring_lookup domain as email_domain OUTPUT domain_abuse | search domain_abuse=true + | table message_id, src_user, email_domain, recipients, firstTime, lastTime' +known_false_positives: None at this time +tags: + analytics_story: + - Brand Monitoring + - Suspicious Emails + kill_chain_phases: + - Delivery + cis20: + - CIS 7 + nist: + - PR.IP diff --git a/detections/monitor_registry_keys_for_print_monitors.yml b/detections/monitor_registry_keys_for_print_monitors.yml new file mode 100644 index 0000000000..3cb8cf4713 --- /dev/null +++ b/detections/monitor_registry_keys_for_print_monitors.yml @@ -0,0 +1,38 @@ +name: Monitor Registry Keys for Print Monitors +id: f5f6af30-7ba7-4295-bfe9-07de87c01bbc +version: '1.0' +date: '2018-11-02' +description: This search looks for registry activity associated with modifications + to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this + scenario, an attacker can load an arbitrary .dll into the print-monitor registry + by giving the full path name to the after.dll. The system will execute the .dll + with elevated (SYSTEM) permissions and will persist after reboot. +how_to_implement: To successfully implement this search, you must be ingesting data + that records registry activity from your hosts to populate the endpoint data model + in the registry node. This is typically populated via endpoint detection-and-response + products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. + The data used for this search is typically generated via logs that report registry + modifications. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Registry where Registry.action=modified AND + Registry.registry_path="*CurrentControlSet\\Control\\Print\\Monitors*" by Registry.dest, + Registry.registry_key_name Registry.status Registry.user Registry.registry_path + Registry.action | `drop_dm_object_name(Registry)`' +known_false_positives: You will encounter noise from legitimate print-monitor registry + entries. +tags: + analytics_story: + - Windows Persistence Techniques + - Suspicious Windows Registry Activities + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + - CIS 5 + nist: + - PR.PT + - DE.CM + - PR.AC diff --git a/detections/monitor_web_traffic_for_brand_abuse.yml b/detections/monitor_web_traffic_for_brand_abuse.yml new file mode 100644 index 0000000000..c99524e943 --- /dev/null +++ b/detections/monitor_web_traffic_for_brand_abuse.yml @@ -0,0 +1,26 @@ +name: Monitor Web Traffic For Brand Abuse +id: 134da869-e264-4a8f-8d7e-fcd0ec88f301 +version: '1.0' +date: '2017-09-23' +description: This search looks for Web requests to faux domains similar to the one + that you want to have monitored for abuse. +how_to_implement: You need to ingest data from your web traffic. This can be accomplished + by indexing data from a web proxy, or using a network traffic analysis tool, such + as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain + Names", which creates the permutations of the domain that will be checked for. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` values(Web.url) as urls min(_time) + as firstTime from datamodel=Web by Web.src | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` + | `brand_abuse_web`' +known_false_positives: None at this time +tags: + analytics_story: + - Brand Monitoring + kill_chain_phases: + - Delivery + cis20: + - CIS 7 + nist: + - PR.IP diff --git a/detections/mshta_launching_scripts.yml b/detections/mshta_launching_scripts.yml deleted file mode 100644 index 6d916059a4..0000000000 --- a/detections/mshta_launching_scripts.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-08-07' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for the execution of "mshta.exe" with command-line - arguments that launch a script. The search will return the first time and last time - these command-line arguments were used for these executions, as well as the target - system, the user, process "mshta.exe" and its parent process. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, parent_process_name - rule_description: Mshta.exe is seen to be executing scripts via the command-line - arguments - rule_title: Mshta.exe is executing scripts on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=mshta.exe - by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| - search (process=*vbscript* OR process=*javascript*)' - suppress: - suppress_fields: dest, process, parent_process_name - suppress_period: 86400s -eli5: Mshta.exe is a built-in Windows utility that can launch HTML files with .hta - extensions (HTML applications), javascript, or VBScript. The search detects this - behavior by looking for events where the process mshta.exe is executed with command-line - arguments that indicate that a script is invoked -entities: - - dest -how_to_implement: To successfully implement this search, you need to be ingesting - logs with the process name, parent process, and command-line executions from your - endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the - Sysmon TA. -id: b89919ed-fe5f-492c-b139-95dqb161039e -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Although unlikely, some legitimate applications may exhibit - this behavior, triggering a false positive. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Exploitation - mitre_attack: - - Execution - - Command-Line Interface - - Persistence - nist: - - PR.PT - - DE.CM -modification_date: '2018-12-03' -name: Detect mshta.exe running scripts in command-line arguments -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml new file mode 100644 index 0000000000..ae03106743 --- /dev/null +++ b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml @@ -0,0 +1,29 @@ +name: Multiple Okta Users With Invalid Credentails From The Same IP +id: 19cba45f-cad3-4032-8911-0c09e0444552 +version: '1' +date: '2020-04-01' +description: This search detects Okta login failures due to bad credentials for multiple + users originating from the same ip address. +how_to_implement: This search is specific to Okta and requires Okta logs are being + ingested in your Splunk deployment. +type: ESCU +author: Rico Valdez, Splunk +search: eventtype=okta_log outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country + as country, client.geographicalContext.state as state, client.geographicalContext.city + as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users + values(user) as users by src_ip, displayMessage, outcome.reason, country, state, + city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter` +known_false_positives: A single public IP address servicing multiple legitmate users + may trigger this search. In addition, the threshold of 5 distinct users may be too + low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise + the threshold or except specific IP adresses from triggering this search. +tags: + analytics_story: + - Suspicious Okta Activity + mitre_attack_id: + - T1078 + cis20: + - CIS 16 + nist: + - DE.CM diff --git a/detections/netbackup_failed_backup.yml b/detections/netbackup_failed_backup.yml deleted file mode 100644 index 37a464c981..0000000000 --- a/detections/netbackup_failed_backup.yml +++ /dev/null @@ -1,86 +0,0 @@ -asset_type: Endpoint -baselines: - - id: b2178fed-592f-492b-b851-74161678aa56 - name: Monitor Unsuccessful Backups - type: splunk - - id: b4d0dfb2-2195-4f6e-93a3-48468ed9734e - name: Monitor Successful Backups - type: splunk -confidence: high -creation_date: '2017-06-15' -data_metadata: - data_source: - - Backup Systems - data_sourcetypes: - - netbackup_logs - providing_technologies: - - Netbackup -description: This search gives you the hosts where a backup was attempted and then - failed. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: The system $dest$ attempted a backup but encountered an - error. - rule_title: Failed backup attempt by $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 10 - schedule: - cron_schedule: 0 7 * * * - earliest_time: -24h@h - latest_time: -10m@m - search: sourcetype="netbackup_logs" | stats latest(_time) as latestTime by COMPUTERNAME, - MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` - | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, - signature - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: This search looks across the most recent backup events for each host, and returns - those messages that indicate there was a backup failure. -entities: - - dest -how_to_implement: To successfully implement this search you need to obtain data from - your backup solution, either from the backup logs on your endpoints or from a central - server responsible for performing the backups. If you do not use Netbackup, you - can modify this search for your specific backup solution. -id: a34aae96-ccf8-4aaa-952c-3ea21444444f -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-aaaa-4bb2-8140-e756cc06fd72 - name: All backup logs for host - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 10 - nist: - - PR.IP -modification_date: '2017-09-12' -name: Unsuccessful Netbackup backups -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/netbackup_no_backups_in_time_period.yml b/detections/netbackup_no_backups_in_time_period.yml deleted file mode 100644 index 07da95583a..0000000000 --- a/detections/netbackup_no_backups_in_time_period.yml +++ /dev/null @@ -1,83 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-06-15' -data_metadata: - data_source: - - Backup Systems - data_sourcetypes: - - netbackup_logs - providing_technologies: - - Netbackup -description: This search returns a list of hosts that have not successfully completed - a backup in over a week. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: The system $dest$ has not had a successful backup for an - extended period. - rule_title: Extended period of no successful backups by $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 10 - schedule: - cron_schedule: 0 0 1 * * - earliest_time: -7d@d - latest_time: -10m@m - search: sourcetype="netbackup_logs" MESSAGE="Disk/Partition backup completed - successfully." | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` - | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), - "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: This search finds all the successful backup messages in your logs, and then - looks for the most recent backup time for each system. It then identifies those - systems where the most recent successful backup time is over a week ago, and reports - on them. -entities: - - dest -how_to_implement: To successfully implement this search you need to first obtain data - from your backup solution, either from the backup logs on your hosts, or from a - central server responsible for performing the backups. If you do not use Netbackup, - you can modify this search for your backup solution. Depending on how often you - backup your systems, you may want to modify how far in the past to look for a successful - backup, other than the default of seven days. -id: a34aae96-ccf8-4aef-952c-3ea214444440 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-aaaa-4bb2-8140-e756cc06fd72 - name: All backup logs for host - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 10 - nist: - - PR.IP -modification_date: '2017-09-12' -name: Extended Period Without Successful Netbackup Backups -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/netsh_launching_process.yml b/detections/netsh_launching_process.yml deleted file mode 100644 index ece0d7e757..0000000000 --- a/detections/netsh_launching_process.yml +++ /dev/null @@ -1,108 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-01-04' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for processes launching netsh.exe to execute various - commands via the netsh command-line utility. Netsh.exe is a command-line scripting - utility that allows you to, either locally or remotely, display or modify the network - configuration of a computer that is currently running. Netsh can be used as a persistence - proxy technique to execute a helper .dll when netsh.exe is executed. In this search, - we are looking for processes spawned by netsh.exe that are executing commands via - the command line. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, parent_process - rule_description: A process, $process$, is spawned by netsh.exe. It is highly - unlikely for netsh to have any child processes. - rule_title: Process spawned by netsh.exe detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process="*C:\\Windows\\System32\\netsh.exe*" by Processes.user Processes.dest Processes.parent_process Processes.parent_process_name Processes.process_name - | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process - suppress_period: 86400s -eli5: 'This search looks for all processes with the parent process "c:\Windows\System32\netsh.exe" and returns the process, the command line used to execute it, the host - name, and the user context under which it ran.' -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting logs - with the process name, command-line arguments, and parent processes from your endpoints. - If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -id: b89919ed-fe5f-492c-b139-95dbb162041e -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: It is unusual for netsh.exe to have any child processes in - most environments. It makes sense to investigate the child process and verify whether - the process spawned is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Command-Line Interface - - Persistence - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-02' -name: Processes created by netsh -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/new_aws_console_login_by_user.yml b/detections/new_aws_console_login_by_user.yml deleted file mode 100644 index 8ba9d0620a..0000000000 --- a/detections/new_aws_console_login_by_user.yml +++ /dev/null @@ -1,97 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd03 - name: Previously seen users in CloudTrail - type: splunk - - id: 06c036e6-d6d7-4daa-bd76-411c3d356031 - name: Update previously seen users in CloudTrail - type: splunk -confidence: medium -creation_date: '2018-02-26' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events wherein a console login event - by a user was recorded within the last hour, then compares the event to a lookup - file of previously seen users (by ARN values) who have logged into the console. - The alert is fired if the user has logged into the console for the first time within - the last hour -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A new user has logged into the AWS console - rule_title: AWS Console Login by New User - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: 'sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn - as user | stats earliest(_time) as firstTime latest(_time) as lastTime by user - | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by user | eval userStatus=if(firstTime >= - relative_time(now(), "-70m@m"), "First Time Logging into AWS Console","Previously - Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| where userStatus ="First Time Logging into AWS Console" ' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: In this search, we query CloudTrail logs to look for events that indicate that - a user has attempted to log in to the AWS console and group the events using ARN - value. Using the `previously_seen_users_console_logins.csv` lookup file created - using the support search, we compare the ARN to all the previously seen users logging - into the AWS console. The `eval` and `if` functions determine whether the earliest - time we see this user ARN was seen within the last hour. The alert will be fired - only when a user is seen for first time in the last hour. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Run the "Previously seen users in CloudTrail" support search only once to - create a baseline of previously seen IAM users within the last 30 days. Run "Update - previously seen users in CloudTrail" hourly (or more frequently depending on how - often you run the detection searches) to refresh the baselines. -id: ada0f478-84a8-4641-a3f3-d82362dffd75 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk -known_false_positives: When a legitimate new user logins for the first time, this - activity will be detected. Check how old the account is and verify that the user - activity is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - nist: - - DE.DP - - DE.AE -modification_date: '2018-04-30' -name: Detect new user AWS Console Login -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/new_aws_console_login_city_by_user.yml b/detections/new_aws_console_login_city_by_user.yml deleted file mode 100644 index f6e28251ef..0000000000 --- a/detections/new_aws_console_login_city_by_user.yml +++ /dev/null @@ -1,105 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd03 - name: Previously seen users in CloudTrail - type: splunk - - id: 06c036e6-d6d7-4daa-bd76-411c3d356031 - name: Update previously seen users in CloudTrail - type: splunk -confidence: medium -creation_date: '2018-04-24' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events wherein a console login event - by a user was recorded within the last hour, then compares the event to a lookup - file of previously seen users (by ARN values) who have logged into the console. - The alert is fired if the user has logged into the console for the first time within - the last hour -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A user has logged into the AWS console from a new city. - rule_title: AWS Console Login by User from New City - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by user City | join user type=outer [| inputlookup - previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen - by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), - "@d"), "New City","Previously Seen City") | eval UserData=if(earliestseen - >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") - | where userStatus="New City" AND UserData="Old User" | `security_content_ctime(firstTime)` | - `security_content_ctime(lastTime)`| `security_content_ctime(earliestseen)` | table user City userStatus firstTime lastTime - earliestseen' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: In this search, we query CloudTrail logs to look for events that indicate that - a user has attempted to log in to the AWS console from a new city and group the - events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup - file created using the support search, we compare the ARN to all the previously - seen ARN and city combinations logging into the AWS console. The `eval` and `if` - functions determine whether the earliest time we see this user ARN was seen within - the last hour. The alert will be fired only when a user is seen for first time in - the last hour. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Run the "Previously seen users in CloudTrail" support search only once to - create a baseline of previously seen IAM users within the last 30 days. Run "Update - previously seen users in CloudTrail" hourly (or more frequently depending on how - often you run the detection searches) to refresh the baselines. -id: 121b0b11-f8ac-4ed6-a132-3800ca4fc07a -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk -known_false_positives: When a legitimate new user logins for the first time, this - activity will be detected. Check how old the account is and verify that the user - activity is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - nist: - - DE.DP - - DE.AE -modification_date: '2018-04-30' -name: Detect AWS Console Login by User from New City -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/new_aws_console_login_country_by_user.yml b/detections/new_aws_console_login_country_by_user.yml deleted file mode 100644 index 3e34a7eb5d..0000000000 --- a/detections/new_aws_console_login_country_by_user.yml +++ /dev/null @@ -1,103 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd03 - name: Previously seen users in CloudTrail - type: splunk - - id: 06c036e6-d6d7-4daa-bd76-411c3d356031 - name: Update previously seen users in CloudTrail - type: splunk -confidence: medium -creation_date: '2018-04-24' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events wherein a console login event - by a user was recorded within the last hour, then compares the event to a lookup - file of previously seen users (by ARN values) who have logged into the console. - The alert is fired if the user has logged into the console for the first time within - the last hour -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A user has logged into the AWS console from a new country. - rule_title: AWS Console Login by User from New Country - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by user Country | join user type=outer [| - inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) - AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime - >= relative_time(now(), "@d"), "New Country","Previously Seen Country") | - eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), - "New User","Old User") | where userStatus="New Country" AND UserData="Old - User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`security_content_ctime(earliestseen)` | table user Country userStatus firstTime lastTime earliestseen' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: In this search, we query CloudTrail logs to look for events that indicate that - a user has attempted to log in to the AWS console from a new country and group the - events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup - file created using the support search, we compare the ARN to all the previously - seen ARN and country combinations logging into the AWS console. The `eval` and `if` - functions determine whether the earliest time we see this user ARN was seen within - the last hour. The alert will be fired only when a user is seen for first time in - the last hour. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Run the "Previously seen users in CloudTrail" support search only once to - create a baseline of previously seen IAM users within the last 30 days. Run "Update - previously seen users in CloudTrail" hourly (or more frequently depending on how - often you run the detection searches) to refresh the baselines. -id: 67bd3def-c41c-4bf6-837b-ae196b4257c6 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk -known_false_positives: When a legitimate new user logins for the first time, this - activity will be detected. Check how old the account is and verify that the user - activity is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - nist: - - DE.DP - - DE.AE -modification_date: '2018-04-30' -name: Detect AWS Console Login by User from New Country -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/new_aws_console_login_region_by_user.yml b/detections/new_aws_console_login_region_by_user.yml deleted file mode 100644 index 5c32222880..0000000000 --- a/detections/new_aws_console_login_region_by_user.yml +++ /dev/null @@ -1,104 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd03 - name: Previously seen users in CloudTrail - type: splunk - - id: 06c036e6-d6d7-4daa-bd76-411c3d356031 - name: Update previously seen users in CloudTrail - type: splunk -confidence: medium -creation_date: '2018-04-24' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events wherein a console login event - by a user was recorded within the last hour, then compares the event to a lookup - file of previously seen users (by ARN values) who have logged into the console. - The alert is fired if the user has logged into the console for the first time within - the last hour -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A user has logged into the AWS console from a new region. - rule_title: AWS Console Login by User from New Region - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by user Region | join user type=outer [| - inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) - AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime - >= relative_time(now(), "@d"), "New Region","Previously Seen Region") | eval - UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), - "New User","Old User") | where userStatus="New Region" AND UserData="Old User" - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `security_content_ctime(earliestseen)` | table user Region userStatus firstTime lastTime earliestseen' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: In this search, we query CloudTrail logs to look for events that indicate that - a user has attempted to log in to the AWS console from a new region and group the - events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup - file created using the support search, we compare the ARN to all the previously - seen ARN and region combinations logging into the AWS console. The `eval` and `if` - functions determine whether the earliest time we see this user ARN was seen within - the last hour. The alert will be fired only when a user is seen for first time in - the last hour. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Run the "Previously seen users in CloudTrail" support search only once to - create a baseline of previously seen IAM users within the last 30 days. Run "Update - previously seen users in CloudTrail" hourly (or more frequently depending on how - often you run the detection searches) to refresh the baselines. -id: 9f31aa8e-e37c-46bc-bce1-8b3be646d026 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk -known_false_positives: When a legitimate new user logins for the first time, this - activity will be detected. Check how old the account is and verify that the user - activity is legitimate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - nist: - - DE.DP - - DE.AE -modification_date: '2018-04-30' -name: Detect AWS Console Login by User from New Region -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/new_connections_to_routers.yml b/detections/new_connections_to_routers.yml deleted file mode 100644 index 749f124cfb..0000000000 --- a/detections/new_connections_to_routers.yml +++ /dev/null @@ -1,97 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-07-18' -data_metadata: - data_models: - - Authentication - data_source: - - Network Equipment - providing_technologies: - - Active Directory - - Palo Alto Firewall -description: The search queries the authentication logs for assets that are categorized - as routers in the ES Assets and Identity Framework, to identify connections that - have not been seen before in the last 30 days. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user - rule_description: This search detects new connections made to the router devices - at $dest$ - rule_title: Detected a New Router Login - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 0 * * * - earliest_time: -30d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count earliest(_time) as earliest latest(_time) - as latest from datamodel=Authentication where Authentication.dest_category=router - by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= - relative_time(now(), "-30d@d"), 1, 0) | where isOutlier=1| `security_content_ctime(earliest)`| - `security_content_ctime(latest)` | `drop_dm_object_name("Authentication")`' - suppress: - suppress_fields: dest,user - suppress_period: 86400s -eli5: Attackers will often attempt to compromise network devices such as routers for - a variety of nefarious purposes, including modifying VPN settings or re-routing - network traffic. Typically, only a relatively small number of user accounts log - into these devices on a regular basis. This search identifies 'new' connections - to your routers by checking to see if a similar login was made in the last 30 days. - Routers are identified by checking the IP address against those categorized as a - "router" in the ES assets and identity framework. -entities: - - dest -how_to_implement: To successfully implement this search, you must ensure the network - router devices are categorized as "router" in the Assets and identity table. You - must also populate the Authentication data model with logs related to users authenticating - to routing infrastructure. -id: 104658f4-afdc-499e-9719-17243rr826f1 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Legitimate router connections may appear as new connections -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 11 - kill_chain_phases: - - Actions on Objectives - nist: - - PR.PT - - PR.AC - - PR.IP -modification_date: '2017-09-12' -name: Detect New Login Attempts to Routers -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/new_container_uploaded_to_aws_ecr.yml b/detections/new_container_uploaded_to_aws_ecr.yml new file mode 100644 index 0000000000..1878723676 --- /dev/null +++ b/detections/new_container_uploaded_to_aws_ecr.yml @@ -0,0 +1,24 @@ +name: New container uploaded to AWS ECR +id: f0f70b40-f7ad-489d-9905-23d149da8099 +version: '1.0' +date: '2020-02-20' +description: This searches show information on uploaded containers including source + user, image id, source IP user type, http user agent, region, first time, last time + of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. You must also install Cloud Infrastructure data model. Please also customize + the `container_implant_aws_detection_filter` macro to filter out the false positives. +type: ESCU +references: [] +author: Rod Soto, Rico Valdez, Splunk +search: '| tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute + where Compute.user_type!="AssumeRole" AND Compute.http_user_agent="AWS Internal" + AND Compute.event_name="PutImage" by Compute.image_id Compute.src_user Compute.src + Compute.region Compute.msg Compute.user_type | `drop_dm_object_name("Compute")` + | `container_implant_aws_detection_filter`' +known_false_positives: Uploading container is a normal behavior from developers or + users with access to container registry. +tags: + analytics_story: + - Container Implantation Monitoring & Investigation diff --git a/detections/new_open_s3_buckets.yml b/detections/new_open_s3_buckets.yml deleted file mode 100644 index 64684b7efd..0000000000 --- a/detections/new_open_s3_buckets.yml +++ /dev/null @@ -1,102 +0,0 @@ -asset_type: S3 Bucket -confidence: medium -creation_date: '2018-07-25' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where a user has created an open/public - S3 bucket. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: An open/public S3 bucket, $bucketName$, was created by $user$. - rule_title: Public S3 bucket $bucketName$ created by $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 70 - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail AllUsers eventName=PutBucketAcl | spath output=userIdentityArn - path=userIdentity.arn | spath output=bucketName path=requestParameters.bucketName - | spath output=aclControlList path=requestParameters.AccessControlPolicy.AccessControlList - | spath input=aclControlList output=grantee path=Grant{} | mvexpand grantee - | spath input=grantee | search Grantee.URI=*AllUsers | rename userIdentityArn - as user| table _time, src,awsRegion Permission, Grantee.URI, bucketName, user - suppress: - suppress_fields: user,bucketName - suppress_period: 86400s -eli5: This search queries CloudTrail logs for events with S3 bucket access controls - given to the "All Users" group, which allows anyone in the world access to the resource. - This search generates a table displaying the time when the bucket was made public, - the permission of the S3 bucket, the bucket name, and the ARN of the user who created - the bucket. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail - inputs. The threshold value should be tuned to your environment. -id: 2a9b80d3-6340-4345-b5ad-290bf3d0dac4 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: f3fb2q1c-5f33-4b01-b541-c2ah9534c242 - name: AWS S3 Bucket details via bucketName - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: While this search has no known false positives, it is possible - that an AWS admin has legitimately created a public bucket for a specific purpose. - That said, AWS strongly advises against granting full control to the "All Users" - group. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Initial Access - - Exfiltration - nist: - - PR.DS - - PR.AC - - DE.CM -modification_date: '2018-07-25' -name: Detect New Open S3 buckets -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/new_user_accounts.yml b/detections/new_user_accounts.yml deleted file mode 100644 index 7eabb40fcc..0000000000 --- a/detections/new_user_accounts.yml +++ /dev/null @@ -1,90 +0,0 @@ -asset_type: Domain Server -confidence: medium -creation_date: '2017-08-05' -data_metadata: - data_models: - - Identity_Management - data_source: - - Active Directory logs - providing_technologies: - - Active Directory -description: This detection search will help profile user accounts in your environment - by identifying newly created accounts that have been added to your network in the - past week. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: Using the identities lookup and macro from Enterprise Security - to identify (report) new users (6 month period) and temp users (3 months - until account expiration) - rule_title: Identify Temporary Users - risk: - risk_object: user - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 0 * * * - earliest_time: -24h@h - latest_time: -10m@m - search: '| from datamodel Identity_Management.All_Identities | eval empStatus=case((now()-startDate)<604800, - "Accounts created in last week") | search empStatus="Accounts created in last - week"| `security_content_ctime(endDate)` | `security_content_ctime(startDate)`| table identity empStatus endDate - startDate' - suppress: - suppress_fields: identity - suppress_period: 86400s -eli5: Adversaries will often seek to create new user accounts as a means of maintaining - access to a target environment. Using this search, we identify accounts created - in the last week by comparing the start date in the Identity_Management data model - against the current time. -entities: - - user -how_to_implement: To successfully implement this search, you need to be populating - the Enterprise Security Identity_Management data model in the assets and identity - framework. -id: 475b9e27-17e4-46e2-b7e2-648221be3b89 -investigations: - - id: 552bc86c-f72c-4d44-b3f2-06ede13af7bb - name: Get Logon Rights Modifications For User - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: If the Identity_Management data model is not updated regularly, - this search could give you false positive alerts. Please consider this and investigate - appropriately. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 16 - mitre_attack: - - Persistence - - Create Account - nist: - - PR.IP -modification_date: '2017-09-12' -name: Identify New User Accounts -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: access -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/no_win_updates_in_timeframe.yml b/detections/no_win_updates_in_timeframe.yml deleted file mode 100644 index 0b18b9d2c9..0000000000 --- a/detections/no_win_updates_in_timeframe.yml +++ /dev/null @@ -1,91 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-08-15' -data_metadata: - data_models: - - Updates - data_source: - - Windows Update Logs - providing_technologies: - - Microsoft Windows -description: This search looks for Windows endpoints that have not generated an event - indicating a successful Windows update in the last 60 days. Windows updates are - typically released monthly and applied shortly thereafter. An endpoint that has - not successfully applied an update in this time frame indicates the endpoint is - not regularly being patched for some reason. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, user - rule_description: The system $src$ has not generated a successful Windows - Update event in 60 days or more. - rule_title: No Windows updates in last 60 days on $src$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` max(_time) - as lastTime from datamodel=Updates where Updates.status=Installed Updates.vendor_product="Microsoft - Windows" by Updates.dest Updates.status Updates.vendor_product | rename Updates.dest - as Host | rename Updates.status as "Update Status" | rename Updates.vendor_product - as Product | eval isOutlier=if(lastTime <= relative_time(now(), "-60d@d"), - 1, 0) | `security_content_ctime(lastTime)` | search isOutlier=1 | rename lastTime as - "Last Update Time", | table Host, "Update Status", Product, "Last Update Time"' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: Keeping your systems up-to-date with the latest patches is an important step - in keeping your systems secured. For Windows endpoints, Microsoft typically releases - patches on the second Tuesday of every month. These patches contain fixes for vulnerabilities - in the system that could potentially be exploited by malicious actors. This search - checks for messages regarding Windows updates in the 'Update' data model. If a message - indicating a successful update has not been observed in 60 days, a notable event - will be generated. These systems should be checked to determine why it has not been - updated in that time frame. -entities: - - dest -how_to_implement: To successfully implement this search, it requires that the 'Update' - data model is being populated. This can be accomplished by ingesting Windows events - or the Windows Update log via a universal forwarder on the Windows endpoints you - wish to monitor. The Windows add-on should be also be installed and configured to - properly parse Windows events in Splunk. There may be other data sources which can - populate this data model, including vulnerability management systems. -id: 1a77c08c-2f56-409c-a2d3-7d64617edd4f -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 18 - nist: - - PR.PT - - PR.MA -modification_date: '2017-09-15' -name: No Windows Updates in a time frame -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/no_windows_updates_in_a_time_frame.yml b/detections/no_windows_updates_in_a_time_frame.yml new file mode 100644 index 0000000000..ed527a2635 --- /dev/null +++ b/detections/no_windows_updates_in_a_time_frame.yml @@ -0,0 +1,34 @@ +name: No Windows Updates in a time frame +id: 1a77c08c-2f56-409c-a2d3-7d64617edd4f +version: '1.0' +date: '2017-09-15' +description: This search looks for Windows endpoints that have not generated an event + indicating a successful Windows update in the last 60 days. Windows updates are + typically released monthly and applied shortly thereafter. An endpoint that has + not successfully applied an update in this time frame indicates the endpoint is + not regularly being patched for some reason. +how_to_implement: To successfully implement this search, it requires that the 'Update' + data model is being populated. This can be accomplished by ingesting Windows events + or the Windows Update log via a universal forwarder on the Windows endpoints you + wish to monitor. The Windows add-on should be also be installed and configured to + properly parse Windows events in Splunk. There may be other data sources which can + populate this data model, including vulnerability management systems. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` max(_time) as lastTime from datamodel=Updates + where Updates.status=Installed Updates.vendor_product="Microsoft Windows" by Updates.dest + Updates.status Updates.vendor_product | rename Updates.dest as Host | rename Updates.status + as "Update Status" | rename Updates.vendor_product as Product | eval isOutlier=if(lastTime + <= relative_time(now(), "-60d@d"), 1, 0) | `security_content_ctime(lastTime)` | + search isOutlier=1 | rename lastTime as "Last Update Time", | table Host, "Update + Status", Product, "Last Update Time"' +known_false_positives: None identified +tags: + analytics_story: + - Monitor for Updates + cis20: + - CIS 18 + nist: + - PR.PT + - PR.MA diff --git a/detections/okta_account_lockout_events.yml b/detections/okta_account_lockout_events.yml new file mode 100644 index 0000000000..4aaaa36b48 --- /dev/null +++ b/detections/okta_account_lockout_events.yml @@ -0,0 +1,25 @@ +name: Okta Account Lockout Events +id: 62b70968-a0a5-4724-8ac4-67871e6f544d +version: '1' +date: '2020-04-01' +description: Detect Okta user lockout events +how_to_implement: This search is specific to Okta and requires Okta logs are being + ingested in your Splunk deployment. +type: ESCU +author: Rico Valdez, Splunk +search: eventtype=okta_log displayMessage="Max sign in attempts exceeded" | rename + client.geographicalContext.country as country, client.geographicalContext.state + as state, client.geographicalContext.city as city | table _time, user, country, + state, city, src_ip |`okta_user_lockouts_filter` +known_false_positives: None. Account lockouts should be followed up on to determine + if the actual user was the one who caused the lockout, or if it was an unauthorized + actor. +tags: + analytics_story: + - Suspicious Okta Activity + mitre_attack_id: + - T1078 + cis20: + - CIS 16 + nist: + - DE.CM diff --git a/detections/okta_failed_sso_attempt.yml b/detections/okta_failed_sso_attempt.yml deleted file mode 100644 index 57df64ca52..0000000000 --- a/detections/okta_failed_sso_attempt.yml +++ /dev/null @@ -1,69 +0,0 @@ -asset_type: Infrastructure -confidence: high -creation_date: '2020-04-01' -data_metadata: - data_eventtypes: - - okta_log - data_source: - - Okta - providing_technologies: - - Okta -description: Detect failed Okta SSO events -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: Okta user $user$ attempted to access unauthorized app - rule_title: Okta user SSO attempt to unauthorized app - risk: - risk_object: user - risk_object_type: - - user - risk_score: 50 - macros: - - okta_failed_sso_attempt_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: 'eventtype=okta_log displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter`' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: This search looks for events that indicate a user attempted to access an app they did not have permissions to access. This could indicate attempts to access prohibited applications. Please leverage the `okta_failed_sso_attempt_filter` macro to filter out false positives -entities: - - user -how_to_implement: 'This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.' -id: 371a6545-2618-4032-ad84-93386b8698c5 -investigations: - - id: 24ff145d-4d16-420a-b047-480f2a51c403 - name: Investigate User Activities In Okta - type: splunk - - id: 420eb1b8-2992-45d1-80cf-0b1b2759524d - name: Investigate Okta Activity by App - type: splunk -known_false_positives: There may be a faulty config preventing legitmate users from accessing apps they should have access to. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 16 - mitre_attack: - - Valid Accounts - mitre_technique_id: - - T1078 - nist: - - DE.CM -modification_date: '2020-04-01' -name: Okta Failed SSO Attempts -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -security_domain: access -spec_version: 2 -type: splunk -version: "1" diff --git a/detections/okta_failed_sso_attempts.yml b/detections/okta_failed_sso_attempts.yml new file mode 100644 index 0000000000..10b34eba5b --- /dev/null +++ b/detections/okta_failed_sso_attempts.yml @@ -0,0 +1,24 @@ +name: Okta Failed SSO Attempts +id: 371a6545-2618-4032-ad84-93386b8698c5 +version: '1' +date: '2020-04-01' +description: Detect failed Okta SSO events +how_to_implement: This search is specific to Okta and requires Okta logs are being + ingested in your Splunk deployment. +type: ESCU +author: Rico Valdez, Splunk +search: eventtype=okta_log displayMessage="User attempted unauthorized access to app" + | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count + by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | + `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter` +known_false_positives: There may be a faulty config preventing legitmate users from + accessing apps they should have access to. +tags: + analytics_story: + - Suspicious Okta Activity + mitre_attack_id: + - T1078 + cis20: + - CIS 16 + nist: + - DE.CM diff --git a/detections/okta_multiple_users_with_auth_failures_from_ip.yml b/detections/okta_multiple_users_with_auth_failures_from_ip.yml deleted file mode 100644 index 854e39ddaf..0000000000 --- a/detections/okta_multiple_users_with_auth_failures_from_ip.yml +++ /dev/null @@ -1,66 +0,0 @@ -asset_type: Infrastructure -confidence: high -creation_date: '2020-04-01' -data_metadata: - data_eventtypes: - - okta_log - data_source: - - Okta - providing_technologies: - - Okta -description: This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip - rule_description: Multiple Users Failing Authenticaiton From $src_ip$ - rule_title: Multiple Okta Users With Authentication Failures From a Single IP - risk: - risk_object: system - risk_object_type: - - system - risk_score: 50 - macros: - - okta_multiple_users_with_auth_failures_from_ip_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: 'eventtype=okta_log outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter`' - suppress: - suppress_fields: src_ip - suppress_period: 86400s -eli5: This search detects instances when there are more than 5 distinct users failing Okta logins due to invalid credentails from the same IP address. This may be indicative of attack techniques such as credential stuffing or password spraying, where an attacker attempts to login using common or found passwords and attempts to authenticate with them. -entities: - - src_ip -how_to_implement: 'This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.' -id: 19cba45f-cad3-4032-8911-0c09e0444552 -investigations: - - id: 56aae066-d619-477c-93e3-3fb83b2d23c3 - name: Investigate Okta Activity by IP Address - type: splunk -known_false_positives: A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 16 - mitre_attack: - - Valid Accounts - mitre_technique_id: - - T1078 - nist: - - DE.CM -modification_date: '2020-04-01' -name: Multiple Okta Users With Invalid Credentails From The Same IP -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -security_domain: access -spec_version: 2 -type: splunk -version: "1" diff --git a/detections/okta_user_lockouts.yml b/detections/okta_user_lockouts.yml deleted file mode 100644 index 549729a2bf..0000000000 --- a/detections/okta_user_lockouts.yml +++ /dev/null @@ -1,66 +0,0 @@ -asset_type: Infrastructure -confidence: high -creation_date: '2020-04-01' -data_metadata: - data_eventtypes: - - okta_log - data_source: - - Okta - providing_technologies: - - Okta -description: Detect Okta user lockout events -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: User $user$ locked out of Okta - too many attempts - rule_title: Okta user lockout events - risk: - risk_object: user - risk_object_type: - - user - risk_score: 50 - macros: - - okta_user_lockouts_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: 'eventtype=okta_log displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip |`okta_user_lockouts_filter`' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: This search detects when a user exceeds the maximum configured Okta login attempts and the account is subsequently locked out. This is often indicative of brtue force attempts against a user account. -entities: - - user -how_to_implement: 'This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.' -id: 62b70968-a0a5-4724-8ac4-67871e6f544d -investigations: - - id: 24ff145d-4d16-420a-b047-480f2a51c403 - name: Investigate User Activity In Okta - type: splunk -known_false_positives: None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 16 - mitre_attack: - - Valid Accounts - mitre_technique_id: - - T1078 - nist: - - DE.CM -modification_date: '2020-04-01' -name: Okta Account Lockout Events -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -security_domain: access -spec_version: 2 -type: splunk -version: "1" diff --git a/detections/okta_user_logins_from_multiple_cities.yml b/detections/okta_user_logins_from_multiple_cities.yml index d2f6af2418..c8f6435c46 100644 --- a/detections/okta_user_logins_from_multiple_cities.yml +++ b/detections/okta_user_logins_from_multiple_cities.yml @@ -1,66 +1,30 @@ -asset_type: Infrastructure -confidence: high -creation_date: '2020-04-01' -data_metadata: - data_eventtypes: - - okta_log - data_source: - - Okta - providing_technologies: - - Okta -description: This search detects logins from the same user from different states in a 24 hour period. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: User $user$ logged into Okta from different cities - rule_title: Okta user login from different cities - risk: - risk_object: user - risk_object_type: - - system - risk_score: 50 - macros: - - okta_user_logins_from_multiple_cities_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -24h@h - latest_time: -5m@m - search: 'eventtype=okta_log displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`okta_user_logins_from_multiple_cities_filter`| search locations > 1' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: This search detects users logging in from multiple states in the last 24 hours. This can be indicative of an attacker using compromised credentials to log in to Okta. The efficacy of this search is highly dependant on the mobility of the users using Okta. It is particularly useful in situations where users should explicitly *not* be travelling, such as during the COVID-19 pandemic. -entities: - - user -how_to_implement: 'This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.' -id: 7594fa07-9f34-4d01-81cc-d6af6a5db9e8 -investigations: - - id: 24ff145d-4d16-420a-b047-480f2a51c403 - name: Investigate User Activity In Okta - type: splunk -known_false_positives: Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 16 - mitre_attack: - - Valid Accounts - mitre_technique_id: - - T1078 - nist: - - DE.CM -modification_date: '2020-04-01' name: Okta User Logins From Multiple Cities -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -security_domain: access -spec_version: 2 -type: splunk -version: "1" +id: 7594fa07-9f34-4d01-81cc-d6af6a5db9e8 +version: '1' +date: '2020-04-01' +description: This search detects logins from the same user from different states in + a 24 hour period. +how_to_implement: This search is specific to Okta and requires Okta logs are being + ingested in your Splunk deployment. +type: ESCU +author: Rico Valdez, Splunk +search: eventtype=okta_log displayMessage="User login to Okta" client.geographicalContext.city!=null + | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) + as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) + as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + |`okta_user_logins_from_multiple_cities_filter`| search locations > 1 +known_false_positives: Users in your enviornment may legitmately be travelling and + loggin in from different locations. This search is useful for those users that should + *not* be travelling for some reason, such as the COVID-19 pandemic. The search also + relies on the geographical information being populated in the Okta logs. It is also + possible that a connection from another region may be attributed to a login from + a remote VPN endpoint. +tags: + analytics_story: + - Suspicious Okta Activity + mitre_attack_id: + - T1078 + cis20: + - CIS 16 + nist: + - DE.CM diff --git a/detections/open_redirect_in_splunk_web.yml b/detections/open_redirect_in_splunk_web.yml index 94a841893e..599c767148 100644 --- a/detections/open_redirect_in_splunk_web.yml +++ b/detections/open_redirect_in_splunk_web.yml @@ -1,82 +1,28 @@ -asset_type: Splunk Server -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: [] - data_source: - - Splunk - data_sourcetypes: - - splunk_web_access - providing_technologies: - - Splunk Enterprise +name: Open Redirect in Splunk Web +id: d199fb99-2312-451a-9daa-e5efa6ed76a7 +version: '1.0' +date: '2017-09-19' description: This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. -detect: - splunk: - correlation_rule: - notable: - nes_fields: host - rule_description: Search for exploitation of the Splunk Open Redirect Vulnerability - rule_title: Open Redirect in Splunk Web - risk: - risk_object: host - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: index=_internal sourcetype=splunk_web_access return_to="/%09/*" - suppress: - suppress_fields: host - suppress_period: 14400s -eli5: This search looks within Splunk's internal logs for evidence of CVE-2016-4859 - open redirect exploitation attempts. -entities: - - host how_to_implement: No extra steps needed to implement this search. -id: d199fb99-2312-451a-9daa-e5efa6ed76a7 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - - CIS 4 - - CIS 18 - kill_chain_phases: - - Delivery - mitre_attack: - - Defense Evasion - - Exploitation of Vulnerability - nist: - - ID.RA - - RS.MI - - PR.PT - - PR.AC - - PR.IP - - DE.CM -modification_date: '2017-09-19' -name: Open Redirect in Splunk Web -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +type: ESCU references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' +author: Bhavin Patel, Splunk +search: index=_internal sourcetype=splunk_web_access return_to="/%09/*" +known_false_positives: None identified +tags: + analytics_story: + - Splunk Enterprise Vulnerability + kill_chain_phases: + - Delivery + cis20: + - CIS 3 + - CIS 4 + - CIS 18 + nist: + - ID.RA + - RS.MI + - PR.PT + - PR.AC + - PR.IP + - DE.CM diff --git a/detections/osquery_pack___coldroot_detection.yml b/detections/osquery_pack___coldroot_detection.yml new file mode 100644 index 0000000000..be9fd0716c --- /dev/null +++ b/detections/osquery_pack___coldroot_detection.yml @@ -0,0 +1,30 @@ +name: Osquery pack - ColdRoot detection +id: a6fffe5e-05c3-4c04-badc-887607fbb8dc +version: '1.0' +date: '2019-01-29' +description: This search looks for ColdRoot events from the osx-attacks osquery pack. +how_to_implement: In order to properly run this search, Splunk needs to ingest data + from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) + pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must + be deployed across your indexers and universal forwarders in order to have the osquery + data populate the Alerts data model +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| from datamodel Alerts.Alerts | search app=osquery:results (name=pack_osx-attacks_OSX_ColdRoot_RAT_Launchd + OR name=pack_osx-attacks_OSX_ColdRoot_RAT_Files) | rename columns.path as path | + bucket _time span=30s | stats count(path) by _time, host, user, path' +known_false_positives: There are no known false positives. +tags: + analytics_story: + - ColdRoot MacOS RAT + kill_chain_phases: + - Installation + - Command and Control + cis20: + - CIS 4 + - CIS 8 + nist: + - DE.DP + - DE.CM + - PR.PT diff --git a/detections/osx_coldroot_pack.yml b/detections/osx_coldroot_pack.yml deleted file mode 100644 index dc2cd0f89e..0000000000 --- a/detections/osx_coldroot_pack.yml +++ /dev/null @@ -1,99 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2019-01-29' -data_metadata: - data_models: - - Alerts - data_source: - - Endpoint - providing_technologies: - - OSquery -description: This search looks for ColdRoot events from the osx-attacks osquery pack. -detect: - splunk: - correlation_rule: - notable: - nes_fields: host, user - rule_description: Host $host$ generated an alert for the macOS RAT ColdRoot - rule_title: Osquery ColdRoot alert for $host$ - risk: - risk_object: host - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| from datamodel Alerts.Alerts | search app=osquery:results (name=pack_osx-attacks_OSX_ColdRoot_RAT_Launchd - OR name=pack_osx-attacks_OSX_ColdRoot_RAT_Files) | rename columns.path as - path | bucket _time span=30s | stats count(path) by _time, host, user, path' - suppress: - suppress_fields: host - suppress_period: 3600s -eli5: The search looks at the Alerts data model to identify those generated from - the osquery osx-attacks.conf pack, which search for the ColdRoot RAT. -entities: - - host -how_to_implement: In order to properly run this search, Splunk needs to ingest data - from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) - pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must - be deployed across your indexers and universal forwarders in order to have the osquery - data populate the Alerts data model -id: a6fffe5e-05c3-4c04-badc-887607fbb8dc -investigations: - - id: 9df9ca9c-a02b-4f48-9eba-0bac55179050 - name: Investigate Network Traffic From src_ip - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: 2f5b960b-71df-49c0-affc-74992ce60e45 - name: Investigate Web Activity From src_ip - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: There are no known false positives. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 4 - - CIS 8 - kill_chain_phases: - - Installation - - Command and Control - mitre_attack: - - Execution - - Persistence - - Command and Control - nist: - - DE.DP - - DE.CM - - PR.PT -modification_date: '2019-01-29' -name: Osquery pack - ColdRoot detection -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/osx_keyboard_taps.yml b/detections/osx_keyboard_taps.yml deleted file mode 100644 index 11b7e7f90c..0000000000 --- a/detections/osx_keyboard_taps.yml +++ /dev/null @@ -1,97 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2019-01-25' -data_metadata: - data_models: - - Alerts - data_source: - - Endpoint - providing_technologies: - - OSquery -description: This search looks for processes in an MacOS system that is tapping keyboard - events in MacOS, and essentially monitoring all keystrokes made by a user. This - is a common technique used by RATs to log keystrokes from a victim, although it - can also be used by legitimate processes like Siri to react on human input -detect: - splunk: - correlation_rule: - notable: - nes_fields: host, cmd, process_id - rule_description: Host $host$ has process $process_id$ tapping keyboard events - with command $cmd$ - rule_title: Host $host has process $process_id$ monitoring its keystrokes - risk: - risk_object: host - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| from datamodel Alerts.Alerts | search app=osquery:results name=pack_osx-attacks_Keyboard_Event_Taps - | rename columns.cmdline as cmd, columns.name as process_name, columns.pid - as process_id| dedup host,process_name | table host,process_name, cmd, process_id' - suppress: - suppress_fields: host - suppress_period: 3600s -eli5: The search leverages Alerts generated from the osquery osx-attacks.conf pack - search `Keyboard_Event_Taps` to detect when a process is monitoring the keystrokes - of a machine, This is a common technique used by macOS remote access trojans to - log keystrokes from a machine -entities: - - host -how_to_implement: In order to properly run this search, Splunk needs to ingest data - from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) - pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must - be deployed across your indexers and universal forwarders in order to have the osquery - data populate the Alerts data model. -id: 2a371608-331d-4034-ae2c-21dda8f1d0ec -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: There might be some false positives as keyboard event taps - are used by processes like Siri and Zoom video chat, for some good examples of processes - to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) - comment. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: - cis20: - - CIS 4 - - CIS 8 - kill_chain_phases: - - Command and Control - mitre_attack: - - Collection - nist: - - DE.DP -modification_date: '2019-01-25' -name: Processes Tapping Keyboard Events -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/outbound_smb_connections.yml b/detections/outbound_smb_connections.yml deleted file mode 100644 index 5db5723523..0000000000 --- a/detections/outbound_smb_connections.yml +++ /dev/null @@ -1,123 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-03-20' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream -description: This search looks for outbound SMB connections made by hosts within your - network to the Internet. SMB traffic is used for Windows file-sharing activity. - One of the techniques often used by attackers involves retrieving the credential - hash using an SMB request made to a compromised server controlled by the threat - actor. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, dest_ip - rule_description: Outbound SMB network traffic detected. - rule_title: Outbound SMB traffic from $src_ip$ to $dest_ip$ detected - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count earliest(_time) as earliest latest(_time) - as latest values(All_Traffic.action) from datamodel=Network_Traffic where - All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 - OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip - All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 - AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(earliest)`| - `security_content_ctime(latest)` | `outbound_smb_connections_filter` ' - suppress: - suppress_fields: src_ip - suppress_period: 28800s -eli5: In this search, we are looking for the network connections that were not blocked - by the firewall and that are destined for destination port 139 or 445. We then filter - out events that have Classless Inter-Domain Routing (CIDR) blocks categorized as - internal in the `assets_by_cidr.csv` lookup file which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. - Since we are only looking for outbound traffic from the hosts made to the Internet, - we filter out traffic whose destination IP address is private. -entities: - - src_ip -how_to_implement: 'In order to run this search effectively, we highly recommend that - you leverage the Assets and Identity framework. It is important that you have good - understanding of how your network segments are designed, and be able to distinguish - internal from external address space. Add a category named `internal` to the CIDRs - that host the company''s assets in `assets_by_cidr.csv` lookup file, which is located - in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating - this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. - This search also requires you to be ingesting your network traffic and populating - the Network_Traffic data model' -id: 7f5fb3e1-4209-414-90db-0ec21b936378 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is likely that the outbound Server Message Block (SMB) traffic - is legitimate, if the company's internal networks are not well-defined in the Assets - and Identity Framework. Categorize the internal CIDR blocks as `internal` in the - lookup file to avoid creating notable events for traffic destined to those CIDR - blocks. Any other network connection that is going out to the Internet should be - investigated and blocked. Best practices suggest preventing external communications - of all SMB versions and related protocols at the network boundary. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 12 - kill_chain_phases: - - Actions on Objectives - - Command and Control - mitre_attack: - - Commonly Used Port - - Credential Access - - Lateral Movement - mitre_technique_id: - - T1110 - - T1135 - - T1210 - nist: - - DE.CM -modification_date: '2020-01-22' -name: Detect Outbound SMB Traffic -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/outlook_writing_zip.yml b/detections/outlook_writing_zip.yml deleted file mode 100644 index 349d70a570..0000000000 --- a/detections/outlook_writing_zip.yml +++ /dev/null @@ -1,103 +0,0 @@ -asset_type: Endpoint -baselines: [] -confidence: high -creation_date: '2019-04-29' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for execution of process `outlook.exe` where the process - is writing a `.zip` file to the disk. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process_name, file_name - rule_description: Outlook.exe is writing a zip file $file_name$ on $dest$ - rule_title: Outlook.exe is writing a zip file $file_name$ on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - macros: - - outlook_writing_zip_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime - FROM datamodel=Endpoint.Processes where Processes.process_name=outlook.exe - OR Processes.process_name=explorer.exe by _time span=5m Processes.parent_process_id - Processes.process_id Processes.dest Processes.process_name Processes.parent_process_name - Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | rename process_id as malicious_id| rename parent_process_id as outlook_id| - join malicious_id type=inner[| tstats `security_content_summariesonly` count values(Filesystem.file_path) - as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem - where (Filesystem.file_path=*zip* OR Filesystem.file_name=*.lnk ) AND (Filesystem.file_path=C:\\Users* - OR Filesystem.file_path=*Local\\Temp*) by _time span=5m Filesystem.process_id - Filesystem.file_hash Filesystem.dest | `drop_dm_object_name(Filesystem)` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| - fields malicious_id outlook_id dest file_path file_name file_hash count file_id] - | table firstTime lastTime user malicious_id outlook_id process_name parent_process_name - file_name file_path | where file_name != "" | `outlook_writing_zip_filter`' - - suppress: - suppress_fields: dest,file_name - suppress_period: 86400s -eli5: In this search, we are essentially trying to detect if outlook.exe is writing - a `.zip` file to the disk. The way this search would run is, it will execute the - the subsearch first which looks for all .zip files being written to the disk and - outputs a crucial field "process_id", that we use the main search to check if that - process\_id belongs to a process_name of outlook.exe. The search uses a join command - to essentially give you an end result of the first and last time that zip file was - written by outlook.exe, the dest and user logged on the system, the hash value and - the complete path to the zip file on disk -entities: - - dest -how_to_implement: You must be ingesting data that records filesystem and process activity - from your hosts to populate the Endpoint data model. This is typically populated - via endpoint detection-and-response products, such as Carbon Black, or endpoint - data sources, such as Sysmon. -id: a51bfe1a-94f0-4822-b1e4-16ae10145893 -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk -known_false_positives: It is not uncommon for outlook to write legitimate zip files - to the disk. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 7 - - CIS 8 - kill_chain_phases: - - Installation - - Actions on Objectives - mitre_attack: - - Initial Access - - Spearphishing Attachment - nist: - - ID.AM - - PR.DS -modification_date: '2020-03-16' -name: Detect Oulook.exe writing a .zip file -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/overwrite_accessibility_binaries.yml b/detections/overwrite_accessibility_binaries.yml deleted file mode 100644 index aaad3c6666..0000000000 --- a/detections/overwrite_accessibility_binaries.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-12-07' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: Microsoft Windows contains accessibility features that can be launched - with a key combination before a user has logged in. An adversary can modify or replace - these programs so they can get a command prompt or backdoor without logging in to - the system. This search looks for modifications to these binaries. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A file, $file_name$, was created in the default shim database - directory on $dest. - rule_title: Modification to accessibility binary, $file_path$, was detected - on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) - as file_path from datamodel=Endpoint.Filesystem where (Filesystem.file_path=*\\Windows\\System32\\sethc.exe* - OR Filesystem.file_path=*\\Windows\\System32\\utilman.exe* OR Filesystem.file_path=*\\Windows\\System32\\osk.exe* - OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* - OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) - by Filesystem.file_name Filesystem.dest -| `drop_dm_object_name(Filesystem)` -| `security_content_ctime(lastTime)` -| `security_content_ctime(firstTime)`' - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: This search returns all the different accessibility binaries that have been - modified for each Windows host. -entities: - - dest -how_to_implement: You must be ingesting data that records the filesystem activity - from your hosts to populate the Endpoint file-system data model node. If you are - using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which - you want to collect data. -id: 13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Microsoft may provide updates to these binaries. Verify that - these changes do not correspond with your normal software update cycle. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Accessibility Features - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-16' -name: Overwriting Accessibility Binaries -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/overwriting_accessibility_binaries.yml b/detections/overwriting_accessibility_binaries.yml new file mode 100644 index 0000000000..2d12793ef6 --- /dev/null +++ b/detections/overwriting_accessibility_binaries.yml @@ -0,0 +1,37 @@ +name: Overwriting Accessibility Binaries +id: 13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae +version: '3.0' +date: '2020-03-16' +description: Microsoft Windows contains accessibility features that can be launched + with a key combination before a user has logged in. An adversary can modify or replace + these programs so they can get a command prompt or backdoor without logging in to + the system. This search looks for modifications to these binaries. +how_to_implement: You must be ingesting data that records the filesystem activity + from your hosts to populate the Endpoint file-system data model node. If you are + using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which + you want to collect data. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) + as file_path from datamodel=Endpoint.Filesystem where (Filesystem.file_path=*\\Windows\\System32\\sethc.exe* + OR Filesystem.file_path=*\\Windows\\System32\\utilman.exe* OR Filesystem.file_path=*\\Windows\\System32\\osk.exe* + OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* + OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) + by Filesystem.file_name Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)`' +known_false_positives: Microsoft may provide updates to these binaries. Verify that + these changes do not correspond with your normal software update cycle. +tags: + analytics_story: + - Windows Privilege Escalation + mitre_attack_id: + - T1015 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/password_sharing.yml b/detections/password_sharing.yml deleted file mode 100644 index 23341f09f3..0000000000 --- a/detections/password_sharing.yml +++ /dev/null @@ -1,90 +0,0 @@ -asset_type: account -confidence: medium -creation_date: '2018-07-12' -data_metadata: - data_source: - - Network Communications - data_sourcetypes: - - stream:http - providing_technologies: - - Splunk Stream -description: This search is used to identify user accounts that share a common password. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: This search is used to identify user accounts, $user$, that - share common passwords - rule_title: 'Web Fraud Detection: Password Sharing Across Accounts' - risk: - risk_object: user - risk_object_type: - - other - risk_score: 10 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=stream:http http_content_type=text* uri=/magento2/customer/account/loginPost* | - rex field=form_data "login\[username\]=(?[^&|^$]+)" | rex field=form_data - "login\[password\]=(?[^&|^$]+)" | stats dc(Username) as UniqueUsernames - values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5 - suppress: - suppress_fields: user - suppress_period: 3600s -eli5: A common password across user accounts generally indicates that the users are - choosing poor passwords or that a fraudster has a common password across multiple - accounts embedded within a script. The search will extract the username and password - information from the form_data field, then calculate the number and values for usernames - that have the same passwords. Finally, it outputs the values where the unique usernames - sharing passwords are greater than 5 -entities: - - user -how_to_implement: We need to start with a dataset that allows us to see the values - of usernames and passwords that users are submitting to the website hosting the - Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized - or hashed value of a password is acceptable and certainly preferable to a clear-text - password. Common data sources used for this detection are customized Apache logs, - customized IIS, and Splunk Stream. -id: 31337a1a-53b9-4e05-96e9-55c934cb71d3 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cf-35e7-4bb2-1120-e756cc06fd89 - name: Get Web Session Information via session_id - type: splunk - - id: 5df39b3f-447d-4869-b673-8f45ad4616fe - name: Get Emails From Specific Sender - type: splunk -known_false_positives: As is common with many fraud-related searches, we are usually - looking to attribute risk or synthesize relevant context with loosely written detections - that simply detect anamoluous behavior. -maintainers: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger -mappings: - cis20: - - CIS 16 - nist: - - DE.DP -modification_date: '2018-10-08' -name: Web Fraud - Password Sharing Across Accounts -original_authors: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger -references: - - https://en.wikipedia.org/wiki/Session_ID - - https://en.wikipedia.org/wiki/Session_(computer_science) - - https://en.wikipedia.org/wiki/HTTP_cookie - - https://splunkbase.splunk.com/app/1809/ -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/path_interception_program.exe.yml b/detections/path_interception_program.exe.yml deleted file mode 100644 index 60faaca524..0000000000 --- a/detections/path_interception_program.exe.yml +++ /dev/null @@ -1,110 +0,0 @@ -asset_type: '' -confidence: medium -creation_date: '2017-11-16' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Tanium - - Ziften -description: 'The search is looking for the creation of program.exe in the C: drive. The - creation of this file in that location may be driven by a motive to perform path - interception.' -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_path, file_name - rule_description: 'A potentially malicious file program.exe was detected on - the C: drive. The creation of this file is often associated with a motive - to perform a path interception attack. ' - rule_title: Path Interception attempt discovered $dest$ via creation of program.exe - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 30 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) - as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem - where Filesystem.file_path="C:\\program.exe" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` - | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`' - suppress: - suppress_fields: dest, file_path, file_name - suppress_period: 86400s -eli5: 'This search queries the Endpoint file-system data model node to list out all - the values of destination machines, as well as the values of file hashes and file - paths that have the file "program.exe" in the C: drive. Path interception occurs - when an executable is placed in a specific path so that it is executed by an application - instead of by the intended target. In this case, applications vulnerable to path - interception (because of unquoted service paths with spaces in Windows registry) - allow attackers to execute maliciously crafted program.exes.' -entities: - - dest -how_to_implement: You must be ingesting data that records the file-system activity - from your hosts to populate the Endpoint file-system data model node. This is typically - populated via endpoint detection-and-response products, such as Carbon Black, or - other endpoint data sources, such as Sysmon. The data used for this search is typically - generated via logs that report file system reads and writes. -id: c77162d3-f93c-45cc-80c8-22f6v5264g9f -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: 'It is unlikely that a normal user may create and place this - file in the C: drive. Confirm with the user.' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Privilege Escalation - - Persistence - nist: - - PR.PT - - DE.CM -modification_date: '2018-11-15' -name: Detect Path Interception By Creation Of program.exe -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/port_monitor_via_registry.yml b/detections/port_monitor_via_registry.yml deleted file mode 100644 index 82661bb377..0000000000 --- a/detections/port_monitor_via_registry.yml +++ /dev/null @@ -1,115 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-12-01' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: This search looks for registry activity associated with modifications - to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this - scenario, an attacker can load an arbitrary .dll into the print-monitor registry - by giving the full path name to the after.dll. The system will execute the .dll - with elevated (SYSTEM) permissions and will persist after reboot. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, registry_path - rule_description: A registry key associated with adding print monitors can - potentially be misused by giving it a path of a malicious .dll in the registry. - rule_title: Registry Key changes for Print Monitors detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Endpoint.Registry where Registry.action=modified AND - Registry.registry_path="*CurrentControlSet\\Control\\Print\\Monitors*" by - Registry.dest, Registry.registry_key_name Registry.status Registry.user Registry.registry_path - Registry.action | `drop_dm_object_name(Registry)`' - suppress: - suppress_fields: dest, registry_path - suppress_period: 86400s -eli5: In this search, we look for modifications to registry keys used for adding print-monitor - entries on Microsoft platforms via the `registry_path` field in the endpoint data - model. It then provides the destination, command used to initiate the change, the - user who conducted this activity, the resource affected (registry_key_name), and - the entire path of the registry. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records registry activity from your hosts to populate the endpoint data model - in the registry node. This is typically populated via endpoint detection-and-response - products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. - The data used for this search is typically generated via logs that report registry - modifications. -id: f5f6af30-7ba7-4295-bfe9-07de87c01bbc -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: You will encounter noise from legitimate print-monitor registry - entries. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - - CIS 5 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Privilege Escalation - - Local Port Monitor - nist: - - PR.PT - - DE.CM - - PR.AC -modification_date: '2018-11-02' -name: Monitor Registry Keys for Print Monitors -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/powershell_get_sedebug.yml b/detections/powershell_get_sedebug.yml deleted file mode 100644 index 4d166dff37..0000000000 --- a/detections/powershell_get_sedebug.yml +++ /dev/null @@ -1,113 +0,0 @@ -asset_type: Windows -confidence: medium -creation_date: '2018-08-28' -data_metadata: - data_eventtypes: - - wineventlog_security - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search looks for PowerShell requesting privileges consistent with - credential dumping. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, dest - rule_description: Possible attempt at credential dumping via PowerShell was - detected on $dest$ by $user$. - rule_title: Event Code 4703 Specifying PowerShell Acquiring A Token with SeDebugPrivilege - Identified on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: eventtype=wineventlog_security signature_id=4703 Process_Name=*powershell.exe - | rex field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" - | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) - as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs - as "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` - suppress: - suppress_fields: user, dest, process - suppress_period: 86400s -eli5: This search looks for Windows Event Code(signature_id) 4703 (token right adjusted), - where the process requesting the token change is PowerShell.exe and the requested - privilege is "SeDebugPrivilege". This is consistent with the use of PowerShell to - execute Mimikatz using sekurlsa::logonpasswords. It will return the host where the - activity occurred, the process and associated id, the enabled privilege, and the - message in the event. -entities: - - dest -how_to_implement: 'You must be ingesting Windows Security logs. You must also enable - the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. - Additionally, this search requires you to enable your Group Management Audit Logs - in your Local Windows Security Policy and to be ingesting those logs. More information - on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. - Finally, please make sure that the local administrator group name is "Administrators" - to be able to look for the right group membership changes.' -id: 98917be2-bfc8-475a-8618-a9bb06575188 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: The activity may be legitimate. PowerShell is often used by - administrators to perform various tasks, and it's possible this event could be generated - in those cases. In these cases, false positives should be fairly obvious and you - may need to tweak the search to eliminate noise. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - nist: - - PR.IP - - PR.AC - - DE.CM -modification_date: '2019-02-27' -name: Detect Mimikatz Via PowerShell And EventCode 4703 -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: access -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/process_execution_via_wmi.yml b/detections/process_execution_via_wmi.yml new file mode 100644 index 0000000000..4c264aaadf --- /dev/null +++ b/detections/process_execution_via_wmi.yml @@ -0,0 +1,34 @@ +name: Process Execution via WMI +id: 24869767-8579-485d-9a4f-d9ddfd8f0cac +version: '3.0' +date: '2020-03-16' +description: This search looks for processes launched via WMI. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes + where Processes.parent_process_name = *WmiPrvSE.exe by Processes.user Processes.dest + Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)`| `wmi_process_launch_filter`' +known_false_positives: Although unlikely, administrators may use wmi to execute commands + for legitimate purposes. +tags: + analytics_story: + - Suspicious WMI Use + mitre_attack_id: + - T1047 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + nist: + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/detections/process_launching_netsh.yml b/detections/process_launching_netsh.yml deleted file mode 100644 index 41ca1b7bce..0000000000 --- a/detections/process_launching_netsh.yml +++ /dev/null @@ -1,118 +0,0 @@ -asset_type: Endpoint -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd23 - name: Previously seen command line arguments - type: splunk - - id: df98763b-0b08-4281-8ef9-08db7ac572a9 - name: Baseline of SMB Traffic - MLTK - type: splunk -confidence: medium -creation_date: '2017-01-08' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for processes launching netsh.exe. Netsh is a command-line - scripting utility that allows you to, either locally or remotely, display or modify - the network configuration of a computer that is currently running. Netsh can be - used as a persistence proxy technique to execute a helper DLL when netsh.exe is - executed. In this search, we are looking for processes spawned by netsh.exe and - executing commands via the command line. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, parent_process, cmdline - rule_description: 'A process detected on $dest$ is launching netsh.exe. ' - rule_title: Process launching netsh.exe detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process=netsh.exe by Processes.parent_process Processes.process_name - Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, parent_process - suppress_period: 86400s -eli5: This search looks for all the parent processes of netsh.exe and returns that - process, the command-line used to execute it, the host name, and the user context - under which it ran. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records process activity from your hosts to populate the endpoint data model -id: b89919ed-fe5f-492c-b139-95dbb162040e -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Some VPN applications are known to launch netsh.exe. Outside - of these instances, it is unusual for an executable to launch netsh.exe and run - commands. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Command-Line Interface - - Persistence - - Defense Evasion - - Disabling Security Tools - nist: - - PR.PT - - DE.CM -modification_date: '2018-11-02' -name: Processes launching netsh -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/process_with_double_extension.yml b/detections/process_with_double_extension.yml deleted file mode 100644 index 6a081116e8..0000000000 --- a/detections/process_with_double_extension.yml +++ /dev/null @@ -1,107 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-01-26' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for processes launched from files that have double - extensions in the file name. This is typically done to obscure the "real" file extension - and make it appear as though the file being accessed is a data file, as opposed - to executable content. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process - rule_description: The system $dest$ executed a file with a double extension. - rule_title: Process With Multiple Extensions Launched on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Endpoint.Processes where Processes.process = *.doc.exe - OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process - = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe - by Processes.dest Processes.user Processes.process Processes.parent_process - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)`' - suppress: - suppress_fields: dest, process - suppress_period: 28800s -eli5: This search uses the "Application State" data model to look for process names - with specific combinations of double extensions. Relatively straightforward, the - search looks for strings in the "process" field that match what you're looking for. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records process activity from your hosts to populate the endpoint data model - in the processes node. -id: b06a555e-dce0-417d-a2eb-28a5d8d66ef7 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None identified. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Persistence - - Change Default File Association - nist: - - DE.CM - - PR.PT - - PR.IP -modification_date: '2018-11-02' -name: Execution of File with Multiple Extensions -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/process_with_spaces_before_extension.yml b/detections/process_with_spaces_before_extension.yml deleted file mode 100644 index ca037e4e37..0000000000 --- a/detections/process_with_spaces_before_extension.yml +++ /dev/null @@ -1,105 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-01-26' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for processes launched from files with at least five - spaces in the name before the extension. This is typically done to obfuscate the - file extension by pushing it outside of the default view. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: The system $dest$ executed a file with spaces before its - extension. - rule_title: Process $process$ with spaces before extension Launched on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process_path) as process_path - min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where Processes.process = "* .*" by Processes.dest Processes.user Processes.process - Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)`' - suppress: - suppress_fields: dest,process - suppress_period: 28800s -eli5: This search uses the endpoint data model to look for process names with at least - five spaces between the file name and its extension. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records process activity from your hosts to populate the endpoint data model - in the processes node. If you are using Sysmon, you must have at least version 6.0.4 - of the Sysmon TA. -id: ab0353e6-a956-420b-b724-a8b4846d5d5a -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None identified. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Persistence - - Change Default File Association - nist: - - DE.CM - - PR.PT - - PR.IP -modification_date: '2018-01-26' -name: Execution of File With Spaces Before Extension -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/processes_created_by_netsh.yml b/detections/processes_created_by_netsh.yml new file mode 100644 index 0000000000..be3b8a9857 --- /dev/null +++ b/detections/processes_created_by_netsh.yml @@ -0,0 +1,37 @@ +name: Processes created by netsh +id: b89919ed-fe5f-492c-b139-95dbb162041e +version: '3.0' +date: '2020-03-02' +description: This search looks for processes launching netsh.exe to execute various + commands via the netsh command-line utility. Netsh.exe is a command-line scripting + utility that allows you to, either locally or remotely, display or modify the network + configuration of a computer that is currently running. Netsh can be used as a persistence + proxy technique to execute a helper .dll when netsh.exe is executed. In this search, + we are looking for processes spawned by netsh.exe that are executing commands via + the command line. +how_to_implement: To successfully implement this search, you must be ingesting logs + with the process name, command-line arguments, and parent processes from your endpoints. + If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.parent_process="*C:\\Windows\\System32\\netsh.exe*" by Processes.user + Processes.dest Processes.parent_process Processes.parent_process_name Processes.process_name + | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +known_false_positives: It is unusual for netsh.exe to have any child processes in + most environments. It makes sense to investigate the child process and verify whether + the process spawned is legitimate. +tags: + analytics_story: + - Netsh Abuse + mitre_attack_id: + - T1059 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/processes_launching_netsh.yml b/detections/processes_launching_netsh.yml new file mode 100644 index 0000000000..b20a3bfa25 --- /dev/null +++ b/detections/processes_launching_netsh.yml @@ -0,0 +1,37 @@ +name: Processes launching netsh +id: b89919ed-fe5f-492c-b139-95dbb162040e +version: '2.0' +date: '2018-11-02' +description: This search looks for processes launching netsh.exe. Netsh is a command-line + scripting utility that allows you to, either locally or remotely, display or modify + the network configuration of a computer that is currently running. Netsh can be + used as a persistence proxy technique to execute a helper DLL when netsh.exe is + executed. In this search, we are looking for processes spawned by netsh.exe and + executing commands via the command line. +how_to_implement: To successfully implement this search, you must be ingesting data + that records process activity from your hosts to populate the endpoint data model +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process=netsh.exe by Processes.parent_process Processes.process_name + Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' +known_false_positives: Some VPN applications are known to launch netsh.exe. Outside + of these instances, it is unusual for an executable to launch netsh.exe and run + commands. +tags: + analytics_story: + - Disabling Security Tools + - Netsh Abuse + - DHS Report TA18-074A + mitre_attack_id: + - T1059 + - T1089 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/processes_tapping_keyboard_events.yml b/detections/processes_tapping_keyboard_events.yml new file mode 100644 index 0000000000..96432d68a3 --- /dev/null +++ b/detections/processes_tapping_keyboard_events.yml @@ -0,0 +1,33 @@ +name: Processes Tapping Keyboard Events +id: 2a371608-331d-4034-ae2c-21dda8f1d0ec +version: '1.0' +date: '2019-01-25' +description: This search looks for processes in an MacOS system that is tapping keyboard + events in MacOS, and essentially monitoring all keystrokes made by a user. This + is a common technique used by RATs to log keystrokes from a victim, although it + can also be used by legitimate processes like Siri to react on human input +how_to_implement: In order to properly run this search, Splunk needs to ingest data + from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) + pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must + be deployed across your indexers and universal forwarders in order to have the osquery + data populate the Alerts data model. +type: ESCU +references: [] +author: Jose Hernandez, Splunk +search: '| from datamodel Alerts.Alerts | search app=osquery:results name=pack_osx-attacks_Keyboard_Event_Taps + | rename columns.cmdline as cmd, columns.name as process_name, columns.pid as process_id| + dedup host,process_name | table host,process_name, cmd, process_id' +known_false_positives: There might be some false positives as keyboard event taps + are used by processes like Siri and Zoom video chat, for some good examples of processes + to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) + comment. +tags: + analytics_story: + - ColdRoot MacOS RAT + kill_chain_phases: + - Command and Control + cis20: + - CIS 4 + - CIS 8 + nist: + - DE.DP diff --git a/detections/prohibited_allowed_through_fw.yml b/detections/prohibited_allowed_through_fw.yml deleted file mode 100644 index 41f72f4099..0000000000 --- a/detections/prohibited_allowed_through_fw.yml +++ /dev/null @@ -1,116 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-04-18' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Palo Alto Firewall - - Bro - - Splunk Stream -description: This search looks for network traffic defined by port and transport layer - protocol in the Enterprise Security lookup table "lookup_interesting_ports", that - is marked as prohibited, and has an associated 'allow' action in the Network_Traffic - data model. This could be indicative of a misconfigured network device. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, dest_ip - rule_description: This search looks for network traffic defined by port and - transport in the ES lookup table "lookup_interesting_ports", that is marked - as prohibited, and yet has an 'allow' action in the Network_Traffic data - model. This should help to identify areas where a network device is not - properly configured. - rule_title: Prohibited Network Traffic Allowed from $src_ip$ - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Network_Traffic where All_Traffic.action = allowed - by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action - | lookup update=true interesting_ports_lookup dest_port as All_Traffic.dest_port - OUTPUT app is_prohibited note transport | search is_prohibited=true | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' - suppress: - suppress_fields: dest_ip,src_ip - suppress_period: 14400s -eli5: The search looks for traffic marked 'is_prohibited' in the Enterprise Security - lookup table 'interesting_ports_lookup', and then determines if any network devices - have an associated 'allow' action on that traffic by checking the Network_Traffic - data model. -entities: - - src_ip -how_to_implement: In order to properly run this search, Splunk needs to ingest data - from firewalls or other network control devices that mediate the traffic allowed - into an environment. This is necessary so that the search can identify an 'action' - taken on the traffic of interest. The search requires the Network_Traffic data model - be populated. -id: ce5a0962-849f-4720-a678-753fe6674479 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 9 - - CIS 12 - kill_chain_phases: - - Delivery - - Command and Control - mitre_attack: - - Command and Control - - Commonly Used Port - - Exfiltration - - Exfiltration Over Alternative Protocol - nist: - - DE.AE - - PR.AC -modification_date: '2017-09-11' -name: Prohibited Network Traffic Allowed -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/prohibited_apps_spawning_cmdprompt.yml b/detections/prohibited_apps_spawning_cmdprompt.yml deleted file mode 100644 index 7fd64215b3..0000000000 --- a/detections/prohibited_apps_spawning_cmdprompt.yml +++ /dev/null @@ -1,128 +0,0 @@ -asset_type: Endpoint -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd23 - name: Previously seen command line arguments - type: splunk - - id: d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459 - name: Baseline of Command Line Length - MLTK - type: splunk -confidence: medium -creation_date: '2017-10-07' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for executions of cmd.exe spawned by a process that - is often abused by attackers and that does not typically launch cmd.exe. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, parent_process - rule_description: A prohibited application from prohibited_apps_launching_cmd.csv - was leveraged to launch cmd.exe - rule_title: Prohibited application($parent_process_name$) used to launch cmd.exe - on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) - as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name - Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - |search [`prohibited_apps_launching_cmd`]' - suppress: - suppress_fields: dest, parent_process, user - suppress_period: 86400s -eli5: Obtaining access to the Command-Line Interface (CLI) is typically a primary - attacker goal. Once an attacker has obtained the ability to execute code on a target - system, they will often further manipulate the system via commands passed to the - CLI. It is also unusual for many applications to spawn a command shell during normal - operation, while it is often observed if an application has been compromised in - some way. As such, it is often beneficial to look for cmd.exe being executed by - processes that are often targeted for exploitation, or that would not spawn cmd.exe - in any other circumstances. A lookup file is provided to easily modify the processes - that are being watched for execution of cmd.exe. -entities: - - dest - - parent_process_name - - user -how_to_implement: You must be ingesting data that records process activity from your - hosts and populates the Endpoint data model with the resultant dataset. This search - includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list - of processes that should not be spawning cmd.exe. You can modify this lookup to - better suit your environment. -id: dcfd6b40-42f9-469d-a433-2e53f7486664 -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: There are circumstances where an application may legitimately - execute and interact with the Windows command-line interface. Investigate and modify - the lookup file, as appropriate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Exploitation - mitre_attack: - - Execution - - Command-Line Interface - nist: - - PR.PT - - DE.CM -modification_date: '2020-02-03' -name: Detect Prohibited Applications Spawning cmd.exe -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/prohibited_network_traffic_allowed.yml b/detections/prohibited_network_traffic_allowed.yml new file mode 100644 index 0000000000..d043f0ff7b --- /dev/null +++ b/detections/prohibited_network_traffic_allowed.yml @@ -0,0 +1,40 @@ +name: Prohibited Network Traffic Allowed +id: ce5a0962-849f-4720-a678-753fe6674479 +version: '1.0' +date: '2017-09-11' +description: This search looks for network traffic defined by port and transport layer + protocol in the Enterprise Security lookup table "lookup_interesting_ports", that + is marked as prohibited, and has an associated 'allow' action in the Network_Traffic + data model. This could be indicative of a misconfigured network device. +how_to_implement: In order to properly run this search, Splunk needs to ingest data + from firewalls or other network control devices that mediate the traffic allowed + into an environment. This is necessary so that the search can identify an 'action' + taken on the traffic of interest. The search requires the Network_Traffic data model + be populated. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Traffic where All_Traffic.action = allowed by + All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action + | lookup update=true interesting_ports_lookup dest_port as All_Traffic.dest_port + OUTPUT app is_prohibited note transport | search is_prohibited=true | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' +known_false_positives: None identified +tags: + analytics_story: + - Ransomware + - Command and Control + - Prohibited Traffic Allowed or Protocol Mismatch + mitre_attack_id: + - T1043 + - T1048 + kill_chain_phases: + - Delivery + - Command and Control + cis20: + - CIS 9 + - CIS 12 + nist: + - DE.AE + - PR.AC diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index 8addfad176..b3e27f4b51 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -1,53 +1,9 @@ -asset_type: Endpoint -baselines: - - id: 251930a5-1451-4428-bb13-eed5775be0ce - name: Add Prohibited Processes to Enterprise Security - type: splunk -confidence: high -creation_date: '2017-06-26' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Prohibited Software On Endpoint +id: a51bfe1a-94f0-48cc-b4e4-b6ae50145893 +version: '2.0' +date: '2019-10-11' description: This search looks for applications on the endpoint that you have marked as prohibited. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process_name, user - rule_description: Prohibited software $process_name$ has been detected on - $dest$. - rule_title: Prohibited Software Detected On $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user - Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` - | `prohibited_softwares`' - suppress: - suppress_fields: dest,user - suppress_period: 86400s -eli5: This search returns the number of times, as well as the first and last time, - every process has run for each endpoint and user. It then displays only those processes - that you have marked as "prohibited" in the Enterprise Security "Interesting Processes" - table. -entities: - - dest how_to_implement: To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response @@ -58,66 +14,25 @@ how_to_implement: To successfully implement this search, you must be ingesting d `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. -id: a51bfe1a-94f0-48cc-b4e4-b6ae50145893 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: d98675ed-da43-4a7e-96a7-eeca3232ba8e - name: Get Update Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 2 - kill_chain_phases: - - Installation - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - nist: - - ID.AM - - PR.DS -modification_date: '2019-10-11' -name: Prohibited Software On Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process_name + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` + | `prohibited_softwares`' +known_false_positives: None identified +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - SamSam Ransomware + - Monitor for Unauthorized Software + kill_chain_phases: + - Installation + - Command and Control + - Actions on Objectives + cis20: + - CIS 2 + nist: + - ID.AM + - PR.DS diff --git a/detections/protocol_mismatch.yml b/detections/protocol_mismatch.yml deleted file mode 100644 index d319d33413..0000000000 --- a/detections/protocol_mismatch.yml +++ /dev/null @@ -1,117 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-04-18' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Palo Alto Firewall - - Bro - - Splunk Stream -description: This search looks for network traffic on common ports where a higher - layer protocol does not match the port that is being used. For example, this search - should identify cases where protocols other than HTTP are running on TCP port 80. - This can be used by attackers to circumvent firewall restrictions, or as an attempt - to hide malicious communications over ports and protocols that are typically allowed - and not well inspected. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest_ip, src_ip - rule_description: This search looks for network traffic on common ports where - the underlying protocol does not match the port being used. For example, - this search should identify cases where protocols other than HTTP are running - on port 80. This can be used by attackers to circumvent firewall restrictions, - or as an attempt to hide malicious communications in traffic that is typically - allowed and not well inspected. - rule_title: Protocol / Port Mismatch from $src_ip$ - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Network_Traffic where (All_Traffic.app=dns NOT All_Traffic.dest_port=53) - OR ((All_Traffic.app=web-browsing OR All_Traffic.app=http) NOT (All_Traffic.dest_port=80 - OR All_Traffic.dest_port=8080 OR All_Traffic.dest_port=8000)) OR (All_Traffic.app=ssl - NOT (All_Traffic.dest_port=443 OR All_Traffic.dest_port=8443)) OR (All_Traffic.app=smtp - NOT All_Traffic.dest_port=25) by All_Traffic.src_ip, All_Traffic.dest_ip, - All_Traffic.app, All_Traffic.dest_port |`security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | `drop_dm_object_name("All_Traffic")`' - suppress: - suppress_fields: dest_ip, dest_port - suppress_period: 86400s -eli5: This search looks for instances in which the protocol observed is not consistent - with the port and transport protocol typically used for that protocol. For example, - looking for network traffic other than HTTP running over TCP port 80. Such behavior - could indicate a misconfiguration or a custom command and control protocol that - has been designed to look like ordinary web traffic. The search will also identify - if HTTP traffic is observed running on unexpected ports. This can be common in many - environments. -entities: - - src_ip -how_to_implement: Running this search properly requires a technology that can inspect - network traffic and identify common protocols. Technologies such as Bro and Palo - Alto Networks firewalls are two examples that will identify protocols via inspection, - and not just assume a specific protocol based on the transport protocol and ports. -id: 54dc1265-2f74-4b6d-b30d-49eb506a31b3 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 9 - - CIS 12 - kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Commonly Used Port - nist: - - DE.AE - - PR.AC -modification_date: '2017-09-11' -name: Protocol or Port Mismatch -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/protocol_or_port_mismatch.yml b/detections/protocol_or_port_mismatch.yml new file mode 100644 index 0000000000..4d3a774bba --- /dev/null +++ b/detections/protocol_or_port_mismatch.yml @@ -0,0 +1,40 @@ +name: Protocol or Port Mismatch +id: 54dc1265-2f74-4b6d-b30d-49eb506a31b3 +version: '1.0' +date: '2017-09-11' +description: This search looks for network traffic on common ports where a higher + layer protocol does not match the port that is being used. For example, this search + should identify cases where protocols other than HTTP are running on TCP port 80. + This can be used by attackers to circumvent firewall restrictions, or as an attempt + to hide malicious communications over ports and protocols that are typically allowed + and not well inspected. +how_to_implement: Running this search properly requires a technology that can inspect + network traffic and identify common protocols. Technologies such as Bro and Palo + Alto Networks firewalls are two examples that will identify protocols via inspection, + and not just assume a specific protocol based on the transport protocol and ports. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Traffic where (All_Traffic.app=dns NOT All_Traffic.dest_port=53) + OR ((All_Traffic.app=web-browsing OR All_Traffic.app=http) NOT (All_Traffic.dest_port=80 + OR All_Traffic.dest_port=8080 OR All_Traffic.dest_port=8000)) OR (All_Traffic.app=ssl + NOT (All_Traffic.dest_port=443 OR All_Traffic.dest_port=8443)) OR (All_Traffic.app=smtp + NOT All_Traffic.dest_port=25) by All_Traffic.src_ip, All_Traffic.dest_ip, All_Traffic.app, + All_Traffic.dest_port |`security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `drop_dm_object_name("All_Traffic")`' +known_false_positives: None identified +tags: + analytics_story: + - Command and Control + - Prohibited Traffic Allowed or Protocol Mismatch + mitre_attack_id: + - T1043 + kill_chain_phases: + - Command and Control + cis20: + - CIS 9 + - CIS 12 + nist: + - DE.AE + - PR.AC diff --git a/detections/protocols_authenticating_in_cleartext.yml b/detections/protocols_authenticating_in_cleartext.yml deleted file mode 100644 index d57f19032c..0000000000 --- a/detections/protocols_authenticating_in_cleartext.yml +++ /dev/null @@ -1,101 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-08-03' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Splunk Stream - - Bro -description: This search looks for cleartext protocols at risk of leaking credentials. - Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous - FTP sessions. While some of these protocols can be used over SSL, they typically - run on different assigned ports in those cases. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, dest, user - rule_description: This search looks for the use of cleartext protocols that - are known to pass authentication information in the clear. The cleartext - credentials are typically passed at the beginning of the session. - rule_title: Possible credential leak over cleartext protocol - risk: - risk_object: user - risk_object_type: - - user - risk_score: 60 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Network_Traffic where All_Traffic.protocol="tcp" AND - (All_Traffic.dest_port="23" OR All_Traffic.dest_port="143" OR All_Traffic.dest_port="110" - OR (All_Traffic.dest_port="21" AND All_Traffic.user != "anonymous")) groupby - All_Traffic.user All_Traffic.src All_Traffic.dest All_Traffic.dest_port | - `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: This search is checking for traffic on well-known ports that are associated - with protocols that pass authentication in cleartext. -entities: - - user -how_to_implement: This search requires you to be ingesting your network traffic, and - populating the Network_Traffic data model. -id: 6923cd64-17a0-453c-b945-81ac2d8c6db9 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Some networks may use kerberized FTP or telnet servers, however, - this is rare. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 9 - - CIS 14 - kill_chain_phases: - - Reconnaissance - - Actions on Objectives - mitre_attack: - - Credential Access - - Lateral Movement - - Collection - nist: - - PR.PT - - DE.AE - - PR.AC - - PR.DS -modification_date: '2017-09-15' -name: Protocols passing authentication in cleartext -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/protocols_passing_authentication_in_cleartext.yml b/detections/protocols_passing_authentication_in_cleartext.yml new file mode 100644 index 0000000000..50f6105b31 --- /dev/null +++ b/detections/protocols_passing_authentication_in_cleartext.yml @@ -0,0 +1,35 @@ +name: Protocols passing authentication in cleartext +id: 6923cd64-17a0-453c-b945-81ac2d8c6db9 +version: '1.0' +date: '2017-09-15' +description: This search looks for cleartext protocols at risk of leaking credentials. + Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous + FTP sessions. While some of these protocols can be used over SSL, they typically + run on different assigned ports in those cases. +how_to_implement: This search requires you to be ingesting your network traffic, and + populating the Network_Traffic data model. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Traffic where All_Traffic.protocol="tcp" AND + (All_Traffic.dest_port="23" OR All_Traffic.dest_port="143" OR All_Traffic.dest_port="110" + OR (All_Traffic.dest_port="21" AND All_Traffic.user != "anonymous")) groupby All_Traffic.user + All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' +known_false_positives: Some networks may use kerberized FTP or telnet servers, however, + this is rare. +tags: + analytics_story: + - Use of Cleartext Protocols + kill_chain_phases: + - Reconnaissance + - Actions on Objectives + cis20: + - CIS 9 + - CIS 14 + nist: + - PR.PT + - DE.AE + - PR.AC + - PR.DS diff --git a/detections/psexec_accepteula.yml b/detections/psexec_accepteula.yml deleted file mode 100644 index 4855760d28..0000000000 --- a/detections/psexec_accepteula.yml +++ /dev/null @@ -1,108 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-03-28' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Sysmon -description: This search looks for events where `PsExec.exe` is run with the `accepteula` - flag in the command line. PsExec is a built-in Windows utility that enables you - to execute processes on other systems. It is fully interactive for console applications. - This tool is widely used for launching interactive command prompts on remote systems. - Threat actors leverage this extensively for executing code on compromised systems. - If an attacker is running PsExec for the first time, they will be prompted to accept - the end-user license agreement (EULA), which can be passed as the argument `accepteula` - within the command line. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest,process_name - rule_description: The process pssxec.exe was run with the -accepteula flag - on $dest$ by $user$. - rule_title: PsExec executed with accepteula flag on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 75 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = PsExec.exe Processes.process = "*accepteula*" by - Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| - `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process_name - suppress_period: 86400s -eli5: In this search, we are looking for the PsExec process with `accepteula` on the - command line. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: b89919ed-fe5f-492c-b139-151xb162040e -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Administrators can leverage PsExec for accessing remote systems - and might pass `accepteula` as an argument if they are running this tool for the - first time. However, it is not likely that you'd see multiple occurrences of this - event on a machine -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Command-Line Interface - nist: - - PR.PT - - DE.CM -modification_date: '2019-02-26' -name: Detect PsExec With accepteula Flag -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/rare_executables_on_endpoint.yml b/detections/rare_executables_on_endpoint.yml deleted file mode 100644 index 82ce6103d9..0000000000 --- a/detections/rare_executables_on_endpoint.yml +++ /dev/null @@ -1,124 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-08-09' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search will return a table of rare processes, the names of the systems - running them, and the users who initiated each process. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process - rule_description: The process $process$ was detected running on $dest. This - process is rare in your environment. - rule_title: Rare Process $process$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - macros: - - rare_executables_on_endpoint_filter - schedule: - cron_schedule: 10 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.dest) as dest values(Processes.user) - as user min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes - by Processes.process_name | rename Processes.process_name as process | rex - field=user "(?.*)\\\\(?.*)" | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes - by Processes.process_name | rare Processes.process_name limit=30 | rename - Processes.process_name as process| `filter_rare_process_whitelist`| table - process ] | `rare_executables_on_endpoint_filter`' - suppress: - suppress_fields: dest, process - suppress_period: 86400s -eli5: This search first executes the subsearch and counts all of your processes to - determine the 10 most rare (the limit set is 10). It then filters out whitelisted - processes and outputs the first and last time a rare process was encountered, the - destination where the process is running, the count of occurrences, and the users - who initiated the processes. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records process activity from your hosts and populating the endpoint data model - with the resultant dataset. The macro `filter_rare_process_whitelist` searches two - lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` - and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, - add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from - the default lookup file, you will have to modify the macro itself to set the whitelist - value for that process to false. You can modify the limit parameter and search scheduling - to better suit your environment. -id: 44fddcb2-8d3b-454c-874e-7c6de5a4f7ac -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Some legitimate processes may be only rarely executed in your - environment. As these are identified, update `rare_process_whitelist_local.csv` - to filter them out of your search results. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 2 - - CIS 8 - kill_chain_phases: - - Installation - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - nist: - - ID.AM - - PR.PT - - PR.DS - - DE.CM -modification_date: '2020-03-16' -name: Detect Rare Executables -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '5.0' diff --git a/detections/reg_exe_manipulating_windows_services_registry_keys.yml b/detections/reg_exe_manipulating_windows_services_registry_keys.yml new file mode 100644 index 0000000000..764fd94737 --- /dev/null +++ b/detections/reg_exe_manipulating_windows_services_registry_keys.yml @@ -0,0 +1,45 @@ +name: Reg.exe Manipulating Windows Services Registry Keys +id: 8470d755-0c13-45b3-bd63-387a373c10cf +version: '2.0' +date: '2019-03-01' +description: The search looks for reg.exe modifying registry keys that define Windows + services and their configurations. +how_to_implement: To successfully implement this search you need to be ingesting information + on registry changes that include the name of the process responsible for the changes + from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` + nodes. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) + as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name + = reg.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join + [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path + count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" + by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table + process_id dest registry_path]' +known_false_positives: It is unusual for a service to be created or modified by directly + manipulating the registry. However, there may be legitimate instances of this behavior. + It is important to validate and investigate, as appropriate. +tags: + analytics_story: + - Windows Persistence Techniques + - Windows Service Abuse + mitre_attack_id: + - T1050 + - T1031 + - T1089 + kill_chain_phases: + - Installation + cis20: + - CIS 3 + - CIS 5 + - CIS 8 + nist: + - PR.IP + - PR.PT + - PR.AC + - PR.AT + - DE.CM diff --git a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml new file mode 100644 index 0000000000..cf922b058f --- /dev/null +++ b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml @@ -0,0 +1,32 @@ +name: Reg.exe used to hide files/directories via registry keys +id: c77162d3-f93c-45cc-80c8-22f6b5264x9f +version: '2.0' +date: '2019-02-27' +description: The search looks for command-line arguments used to hide a file or directory + using the reg add command. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" + Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name + Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` + |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)"' +known_false_positives: None at the moment +tags: + analytics_story: + - Windows Persistence Techniques + - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/reg_manipulating_services.yml b/detections/reg_manipulating_services.yml deleted file mode 100644 index 77ea7ffeb3..0000000000 --- a/detections/reg_manipulating_services.yml +++ /dev/null @@ -1,124 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: 2018-6-29 -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: The search looks for reg.exe modifying registry keys that define Windows - services and their configurations. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process - rule_description: A registry key associated with Windows services was modified - via reg.exe on $dest$ by $src_user$. - rule_title: Modification of Windows Services Via Reg.exe on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) - as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name - = reg.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` - values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry - where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest - | `drop_dm_object_name("Registry")` | table process_id dest registry_path]' - suppress: - suppress_fields: dest, process - suppress_period: 28800s -eli5: This search looks for modifications to registry paths that specify the definition - and configuration of Windows services by reg.exe. Reg.exe is a Windows utility that - allows for manipulation of the registry via the command line. Malware often uses - the Windows services architecture to persist, hide in plain sight, and gain the - ability to interact with the Windows kernel. While it is common to modify the configuration - of Windows services (and new services may be created with software installs), the - use of reg.exe to create or modify a service configuration is unusual and a technique - commonly used by attackers. The search returns the count, the first time the activity - was seen, the last time activity was seen, the registry path that was modified, - the host where the modification took place, and the user that performed the modification. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting information - on registry changes that include the name of the process responsible for the changes - from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` - nodes. -id: 8470d755-0c13-45b3-bd63-387a373c10cf -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is unusual for a service to be created or modified by directly - manipulating the registry. However, there may be legitimate instances of this behavior. - It is important to validate and investigate, as appropriate. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 8 - kill_chain_phases: - - Installation - mitre_attack: - - Persistence - - Privilege Escalation - - New Service - - Modify Existing Service - - Defense Evasion - - Disabling Security Tools - nist: - - PR.IP - - PR.PT - - PR.AC - - PR.AT - - DE.CM -modification_date: '2019-03-01' -name: Reg.exe Manipulating Windows Services Registry Keys -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/reg_used_to_hide_files.yml b/detections/reg_used_to_hide_files.yml deleted file mode 100644 index 401ed5a4a2..0000000000 --- a/detections/reg_used_to_hide_files.yml +++ /dev/null @@ -1,111 +0,0 @@ -asset_type: '' -confidence: medium -creation_date: '2017-10-27' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: The search looks for command-line arguments used to hide a file or directory - using the reg add command. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process - rule_description: Regedit.exe is used by attackers to hide malware files/directories - in windows environments via registry key settings. This rule detects command-line - arguments used to hide a file/directory - rule_title: 'Regedit.exe used to hide a file/directory on $dest$ ' - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" - Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name - Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)"' - suppress: - suppress_fields: dest,process - suppress_period: 86400s -eli5: Reg.exe is a binary native to Windows platform used to edit the registry hives - of the system. Attackers can leverage this binary to hide files by passing in arguments - that are used to hide the files. In the search, we first gather results with keywords, - add, Hidden, and REG_DWORD, that will be in the raw event and filter by process - and the command-line. We then leverage regular expressions on the command-line field - to look for /d value as 2 which is responsible for hiding a file or directory. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: c77162d3-f93c-45cc-80c8-22f6b5264x9f -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None at the moment -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Persistence - nist: - - DE.CM -modification_date: '2019-02-27' -name: Reg.exe used to hide files/directories via registry keys -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/registry_keys_for_creating_shim_databases.yml b/detections/registry_keys_for_creating_shim_databases.yml new file mode 100644 index 0000000000..39247b2350 --- /dev/null +++ b/detections/registry_keys_for_creating_shim_databases.yml @@ -0,0 +1,34 @@ +name: Registry Keys for Creating SHIM Databases +id: f5f6af30-7aa7-4295-bfe9-07fe87c01bbb +version: '1.0' +date: '2017-09-15' +description: This search looks for registry activity associated with application compatibility + shims, which can be leveraged by attackers for various nefarious purposes. +how_to_implement: To successfully implement this search, you must populate the Change_Analysis + data model. This is typically populated via endpoint detection and response products, + such as Carbon Black or other endpoint data sources such as Sysmon. The data used + for this search is typically generated via logs that report reads and writes to + the registry. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry + AND (All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\Custom*" OR All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\InstalledSDB*") + by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, + All_Changes.object_path | `drop_dm_object_name("All_Changes")`' +known_false_positives: There are many legitimate applications that leverage shim databases + for compatibility purposes for legacy applications +tags: + analytics_story: + - Windows Persistence Techniques + - Suspicious Windows Registry Activities + mitre_attack_id: + - T1138 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml new file mode 100644 index 0000000000..f45c2e3109 --- /dev/null +++ b/detections/registry_keys_used_for_persistence.yml @@ -0,0 +1,47 @@ +name: Registry Keys Used For Persistence +id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b +version: '3.0' +date: '2017-10-10' +description: The search looks for modifications to registry keys that can be used + to launch an application or service at system startup. +how_to_implement: To successfully implement this search, you must be ingesting data + that records registry activity from your hosts to populate the endpoint data model + in the registry node. This is typically populated via endpoint detection-and-response + products, such as Carbon Black or endpoint data sources, such as Sysmon. The data + used for this search is typically generated via logs that report reads and writes + to the registry. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Registry.registry_key_name) + as registry_key_name values(Registry.registry_path) as registry_path min(_time) + as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path=*currentversion\\run* + OR Registry.registry_path=*currentVersion\\Windows\\Appinit_Dlls* OR Registry.registry_path=CurrentVersion\\Winlogon\\Shell* + OR Registry.registry_path=*CurrentVersion\\Winlogon\\Userinit* OR Registry.registry_path=*CurrentVersion\\Winlogon\\VmApplet* + OR Registry.registry_path=*currentversion\\policies\\explorer\\run* OR Registry.registry_path=*currentversion\\runservices* + OR Registry.registry_path=*\\CurrentControlSet\\Control\\Lsa\\* OR Registry.registry_path="*Microsoft\\Windows + NT\\CurrentVersion\\Image File Execution Options*" OR Registry.registry_path=HKLM\\SOFTWARE\\Microsoft\\Netsh\\*) + by Registry.dest , Registry.status, Registry.user | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)`' +known_false_positives: There are many legitimate applications that must execute on + system startup and will use these registry keys to accomplish that task. +tags: + analytics_story: + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Suspicious MSHTA Activity + - Windows Persistence Techniques + - Emotet Malware (DHS Report TA18-201A) + - Ransomware + - Suspicious Windows Registry Activities + - DHS Report TA18-074A + mitre_attack_id: + - T1103 + - T1131 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM + - DE.AE diff --git a/detections/registry_keys_used_for_privilege_escalation.yml b/detections/registry_keys_used_for_privilege_escalation.yml new file mode 100644 index 0000000000..f7fd7711a4 --- /dev/null +++ b/detections/registry_keys_used_for_privilege_escalation.yml @@ -0,0 +1,39 @@ +name: Registry Keys Used For Privilege Escalation +id: c9f4b923-f8af-4155-b697-1354f5bcbc5e +version: '2.0' +date: '2020-03-02' +description: This search looks for modifications to registry keys that can be used + to elevate privileges. The registry keys under "Image File Execution Options" are + used to intercept calls to an executable and can be used to attach malicious binaries + to benign system binaries. +how_to_implement: To successfully implement this search, you must be ingesting data + that records registry activity from your hosts to populate the endpoint data model + in the registry node. This is typically populated via endpoint detection-and-response + products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data + used for this search is typically generated via logs that report reads and writes + to the registry. +type: ESCU +references: +- https://blog.malwarebytes.com/101/2015/12/an-introduction-to-image-file-execution-options/ +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Registry.registry_key_name) + as registry_key_name values(Registry.registry_path) as registry_path min(_time) + as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path="*Microsoft\\Windows + NT\\CurrentVersion\\Image File Execution Options*") AND (Registry.registry_key_name=GlobalFlag + OR Registry.registry_key_name=Debugger) by Registry.dest Registry.user | `security_content_ctime(lastTime)` | + `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)`' +known_false_positives: There are many legitimate applications that must execute upon + system startup and will use these registry keys to accomplish that task. +tags: + analytics_story: + - Windows Privilege Escalation + - Suspicious Windows Registry Activities + mitre_attack_id: + - T1015 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/registry_persistence.yml b/detections/registry_persistence.yml deleted file mode 100644 index 7e30236198..0000000000 --- a/detections/registry_persistence.yml +++ /dev/null @@ -1,115 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-08-23' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: The search looks for modifications to registry keys that can be used - to launch an application or service at system startup. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, registry_path - rule_description: A registry key that is used for persistence on Windows was - modified on $dest$ by $src_user$. - rule_title: Registry Key Associated With Persistence Modified on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Registry.registry_key_name) as - registry_key_name values(Registry.registry_path) as registry_path min(_time) - as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where - (Registry.registry_path=*currentversion\\run* OR Registry.registry_path=*currentVersion\\Windows\\Appinit_Dlls* - OR Registry.registry_path=CurrentVersion\\Winlogon\\Shell* OR Registry.registry_path=*CurrentVersion\\Winlogon\\Userinit* - OR Registry.registry_path=*CurrentVersion\\Winlogon\\VmApplet* OR Registry.registry_path=*currentversion\\policies\\explorer\\run* - OR Registry.registry_path=*currentversion\\runservices* OR Registry.registry_path=*\\CurrentControlSet\\Control\\Lsa\\* - OR Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File - Execution Options*" OR Registry.registry_path=HKLM\\SOFTWARE\\Microsoft\\Netsh\\*) - by Registry.dest , Registry.status, Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - | `drop_dm_object_name(Registry)`' - suppress: - suppress_fields: dest,user,registry_path - suppress_period: 14400s -eli5: This search looks for specific registry paths that malware often uses to ensure - survivability and persistence on system startup. The search returns the count, the - first time the activity was seen, the last time the activity was seen, the registry - path that was modified, the host where the modification took place and the user - that performed the modification. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records registry activity from your hosts to populate the endpoint data model - in the registry node. This is typically populated via endpoint detection-and-response - products, such as Carbon Black or endpoint data sources, such as Sysmon. The data - used for this search is typically generated via logs that report reads and writes - to the registry. -id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: There are many legitimate applications that must execute on - system startup and will use these registry keys to accomplish that task. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Registry Run Keys / Start Folder - - AppInit DLLs - - Authentication Package - nist: - - PR.PT - - DE.CM - - DE.AE -modification_date: '2017-10-10' -name: Registry Keys Used For Persistence -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/registry_privilege_escalation.yml b/detections/registry_privilege_escalation.yml deleted file mode 100644 index 7876961fed..0000000000 --- a/detections/registry_privilege_escalation.yml +++ /dev/null @@ -1,105 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-12-07' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: This search looks for modifications to registry keys that can be used - to elevate privileges. The registry keys under "Image File Execution Options" are - used to intercept calls to an executable and can be used to attach malicious binaries - to benign system binaries. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, registry_path - rule_description: A registry key used for privilege escalation was modified - on $dest$ by $user$. - rule_title: Registry Key Associated With Privilege Escalation Modified on - $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*") AND (Registry.registry_key_name=GlobalFlag OR Registry.registry_key_name=Debugger) by Registry.dest Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)`' - suppress: - suppress_fields: dest, user, registry_path - suppress_period: 14400s -eli5: This search looks for specific registry paths that malware often uses to elevate - privileges. The search returns the count, the first time the activity was seen, - the last time the activity was seen, the registry path that was modified, the host - where the modification took place, and the user who performed the modification. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting data - that records registry activity from your hosts to populate the endpoint data model - in the registry node. This is typically populated via endpoint detection-and-response - products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data - used for this search is typically generated via logs that report reads and writes - to the registry. -id: c9f4b923-f8af-4155-b697-1354f5bcbc5e -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: There are many legitimate applications that must execute upon - system startup and will use these registry keys to accomplish that task. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Privilege Escalation - - Persistence - - Accessibility Features - mitre_technique_id: - - T1183 - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-02' -name: Registry Keys Used For Privilege Escalation -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: - - https://blog.malwarebytes.com/101/2015/12/an-introduction-to-image-file-execution-options/ -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/remote_desktop_bruteforce.yml b/detections/remote_desktop_bruteforce.yml deleted file mode 100644 index 09035f4273..0000000000 --- a/detections/remote_desktop_bruteforce.yml +++ /dev/null @@ -1,104 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-12-14' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream -description: This search looks for RDP application network traffic and filters any - source/destination pair generating more than twice the standard deviation of the - average traffic. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, src - rule_description: Remote-desktop traffic detected from $src$ to $dest$. This - activity is consistent with a brute-force attack. - rule_title: Bruteforce Remote Desktop Network Traffic detected from $src$ - to $dest$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 75 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Network_Traffic where All_Traffic.app=rdp by All_Traffic.src - All_Traffic.dest All_Traffic.dest_port | eventstats stdev(count) AS stdev - avg(count) AS avg p50(count) AS p50 | where count>(avg + stdev*2) | rename All_Traffic.src - AS src All_Traffic.dest AS dest | table firstTime lastTime src dest count - avg p50 stdev' - suppress: - suppress_fields: dest,src - suppress_period: 28800s -eli5: This search monitors for abnormal amounts of remote-desktop (RDP) traffic from - a source to a destination that may be indicative of a brute-force attack. It does - this by filtering out RDP traffic from the Network_Traffic.All_Traffic data model, - using twice the standard deviation of all source-to-destination connections. If - any tuple is within more than two standard deviations of all other usual RDP traffic - flows, it is indicative of a brute-force attack. -entities: - - src -how_to_implement: You must ensure that your network traffic data is populating the - Network_Traffic data model. -id: a98727cc-286b-4ff2-b898-41df64695923 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc - name: Investigate Successful Remote Desktop Authentications - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk -known_false_positives: RDP gateways may have unusually high amounts of traffic from - all other hosts' RDP applications in the network. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: - cis20: - - CIS 12 - - CIS 9 - - CIS 16 - kill_chain_phases: - - Reconnaissance - - Delivery - mitre_attack: - - Credential Access - - Remote Desktop Protocol - - Lateral Movement - nist: - - DE.AE - - PR.AC - - PR.IP -modification_date: '2018-12-14' -name: Remote Desktop Network Bruteforce -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/remote_desktop_network_bruteforce.yml b/detections/remote_desktop_network_bruteforce.yml new file mode 100644 index 0000000000..0d65a51af3 --- /dev/null +++ b/detections/remote_desktop_network_bruteforce.yml @@ -0,0 +1,36 @@ +name: Remote Desktop Network Bruteforce +id: a98727cc-286b-4ff2-b898-41df64695923 +version: '1.0' +date: '2018-12-14' +description: This search looks for RDP application network traffic and filters any + source/destination pair generating more than twice the standard deviation of the + average traffic. +how_to_implement: You must ensure that your network traffic data is populating the + Network_Traffic data model. +type: ESCU +references: [] +author: Jose Hernandez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Traffic where All_Traffic.app=rdp by All_Traffic.src + All_Traffic.dest All_Traffic.dest_port | eventstats stdev(count) AS stdev avg(count) + AS avg p50(count) AS p50 | where count>(avg + stdev*2) | rename All_Traffic.src + AS src All_Traffic.dest AS dest | table firstTime lastTime src dest count avg p50 + stdev' +known_false_positives: RDP gateways may have unusually high amounts of traffic from + all other hosts' RDP applications in the network. +tags: + analytics_story: + - SamSam Ransomware + mitre_attack_id: + - T1076 + kill_chain_phases: + - Reconnaissance + - Delivery + cis20: + - CIS 12 + - CIS 9 + - CIS 16 + nist: + - DE.AE + - PR.AC + - PR.IP diff --git a/detections/remote_desktop_network_traffic.yml b/detections/remote_desktop_network_traffic.yml index 3a2b2913c0..6e3c768340 100644 --- a/detections/remote_desktop_network_traffic.yml +++ b/detections/remote_desktop_network_traffic.yml @@ -1,53 +1,12 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream +name: Remote Desktop Network Traffic +id: 272b8407-842d-4b3d-bead-a704584003d3 +version: '2.0' +date: '2020-01-10' description: This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, src - rule_description: Remote Desktop Traffic detected between $src$ and $dest$. These - two systems typically do not communicate with RDP - rule_title: Uncommon Remote Desktop Network Traffic between $src$ and $dest$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 50 - macros: - - remote_desktop_network_traffic_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Network_Traffic where All_Traffic.dest_port=3389 AND - All_Traffic.dest_category!=common_rdp_destination AND All_Traffic.src_category!=common_rdp_source - by All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `remote_desktop_network_traffic_filter` ' - suppress: - suppress_fields: dest,src - suppress_period: 28800s -eli5: This search finds systems that do not commonly communicate use remote desktop. It - does this by filtering out all systems that have the "common_rdp_source" or "common_rdp_destination" - category applied to that system. Categories are applied to systems using the Assets - and Identity framework. -entities: - - src how_to_implement: To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating @@ -57,67 +16,29 @@ how_to_implement: To successfully implement this search you need to identify sys to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. -id: 272b8407-842d-4b3d-bead-a704584003d3 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc - name: Investigate Successful Remote Desktop Authentications - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Remote Desktop may be used legitimately by users on the network. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 9 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Lateral Movement - - Remote Desktop Protocol - mitre_technique_id: - - T1076 - nist: - - DE.AE - - PR.AC - - PR.IP -modification_date: '2020-01-10' -name: Remote Desktop Network Traffic -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +type: ESCU references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Traffic where All_Traffic.dest_port=3389 AND + All_Traffic.dest_category!=common_rdp_destination AND All_Traffic.src_category!=common_rdp_source + by All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `remote_desktop_network_traffic_filter` ' +known_false_positives: Remote Desktop may be used legitimately by users on the network. +tags: + analytics_story: + - Hidden Cobra Malware + - SamSam Ransomware + - Lateral Movement + mitre_attack_id: + - T1076 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 9 + - CIS 16 + nist: + - DE.AE + - PR.AC + - PR.IP diff --git a/detections/remote_desktop_process_running_on_system.yml b/detections/remote_desktop_process_running_on_system.yml index 211667b562..32c10efafc 100644 --- a/detections/remote_desktop_process_running_on_system.yml +++ b/detections/remote_desktop_process_running_on_system.yml @@ -1,53 +1,11 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Remote Desktop Process Running On System +id: f5939373-8054-40ad-8c64-cec478a22a4a +version: '4.0' +date: '2020-01-13' description: This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: The system $dest$ is running the remote desktop process, - mstsc.exe. This system does not commonly run this application. - rule_title: Remote Desktop Process Running On $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 40 - macros: - - remote_desktop_process_running_on_system_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Endpoint.Processes where Processes.process=*mstsc.exe - AND Processes.dest_category!=common_rdp_source by Processes.dest Processes.user - Processes.process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `drop_dm_object_name(Processes)` | `remote_desktop_process_running_on_system_filter` ' - suppress: - suppress_fields: dest,user - suppress_period: 28800s -eli5: This search finds systems that do not commonly use remote desktop, but which - begin using it. It filters out all systems that have the "common_rdp_source" category - applied. Categories are applied to systems using the Assets and Identity framework. -entities: - - dest how_to_implement: To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly @@ -56,64 +14,28 @@ how_to_implement: To successfully implement this search, you must be ingesting d to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. -id: f5939373-8054-40ad-8c64-cec478a22a4a -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Remote Desktop may be used legitimately by users on the network. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - - CIS 9 - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Lateral Movement - - Remote Desktop Protocol - mitre_technique_id: - - T1076 - nist: - - DE.AE - - PR.AC - - PR.IP -modification_date: '2020-01-13' -name: Remote Desktop Process Running On System -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '4.0' +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process=*mstsc.exe + AND Processes.dest_category!=common_rdp_source by Processes.dest Processes.user + Processes.process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `drop_dm_object_name(Processes)` | `remote_desktop_process_running_on_system_filter` ' +known_false_positives: Remote Desktop may be used legitimately by users on the network. +tags: + analytics_story: + - Hidden Cobra Malware + - Lateral Movement + mitre_attack_id: + - T1076 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 9 + - CIS 16 + nist: + - DE.AE + - PR.AC + - PR.IP diff --git a/detections/remote_process_instantiation_via_wmi.yml b/detections/remote_process_instantiation_via_wmi.yml new file mode 100644 index 0000000000..5db7928183 --- /dev/null +++ b/detections/remote_process_instantiation_via_wmi.yml @@ -0,0 +1,39 @@ +name: Remote Process Instantiation via WMI +id: d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da +version: '3.0' +date: '2019-02-27' +description: This search looks for wmic.exe being launched with parameters to spawn + a process on a remote system. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = wmic.exe Processes.process="*/node*" Processes.process="*process*" + Processes.process="*call*" Processes.process="*create*" by Processes.process_name + Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`' +known_false_positives: The wmic.exe utility is a benign Windows application. It may + be used legitimately by Administrators with these parameters for remote system administration, + but it's relatively uncommon. +tags: + analytics_story: + - Ransomware + - Suspicious WMI Use + mitre_attack_id: + - T1047 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + nist: + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml new file mode 100644 index 0000000000..6324d4f27f --- /dev/null +++ b/detections/remote_registry_key_modifications.yml @@ -0,0 +1,32 @@ +name: Remote Registry Key modifications +id: c9f4b923-f8af-4155-b697-1354f5dcbc5e +version: '3.0' +date: '2020-03-02' +description: This search monitors for remote modifications to registry keys. +how_to_implement: To successfully implement this search, you must populate the `Endpoint` + data model. This is typically populated via endpoint detection-and-response products, + such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for + this search is typically generated via logs that report reads and writes to the + registry. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Registry.registry_key_name) + as registry_key_name values(Registry.registry_path) as registry_path min(_time) + as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="\\\\*" by + Registry.dest , Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + | `drop_dm_object_name(Registry)`' +known_false_positives: This technique may be legitimately used by administrators to + modify remote registries, so it's important to filter these events out. +tags: + analytics_story: + - Windows Persistence Techniques + - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/remote_registry_modifications.yml b/detections/remote_registry_modifications.yml deleted file mode 100644 index d2d8fd0b88..0000000000 --- a/detections/remote_registry_modifications.yml +++ /dev/null @@ -1,112 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-05-31' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: This search monitors for remote modifications to registry keys. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user - rule_description: A registry key was modified remotely using the machine $dest$ - by $user$. - rule_title: Remote Registry Key Modification detection on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Registry.registry_key_name) as - registry_key_name values(Registry.registry_path) as registry_path min(_time) - as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="\\\\*" by - Registry.dest , Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - | `drop_dm_object_name(Registry)`' - suppress: - suppress_fields: dest, user,registry_path - suppress_period: 14400s -eli5: This search looks for modifications made to the Windows registry from remote - locations using reg.exe—a tool used to create/update/delete/modify Windows - registry keys. It is accomplished through specifying the machine names in the registry - path, by entering double backslashes, followed by a computer name. In this search, - we look for registry changes where the registry path contains the name of a remote - computer. The search returns the number of times the remote server has been accessed, - the first and last times the activity occurred, the name of the modified registry - path, the host on which the modification took place, and the name of the user that - performed the modification. -entities: - - dest -how_to_implement: To successfully implement this search, you must populate the `Endpoint` - data model. This is typically populated via endpoint detection-and-response products, - such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for - this search is typically generated via logs that report reads and writes to the - registry. -id: c9f4b923-f8af-4155-b697-1354f5dcbc5e -investigations: - - id: fecf2918-670d-4f1c-872b-3d7317a41xf9 - name: Get Registry Activities - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: This technique may be legitimately used by administrators to - modify remote registries, so it's important to filter these events out. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Persistence - - Lateral Movement - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-02' -name: Remote Registry Key modifications -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/remote_wmi_command_attempt.yml b/detections/remote_wmi_command_attempt.yml index b77e560ef6..fca71cb36a 100644 --- a/detections/remote_wmi_command_attempt.yml +++ b/detections/remote_wmi_command_attempt.yml @@ -1,110 +1,37 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-01-13' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Remote WMI Command Attempt +id: 272df6de-61f1-4784-877c-1fbc3e2d0838 +version: '2.0' +date: '2018-12-03' description: This search looks for wmic.exe being launched with parameters to operate on remote systems. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest,user,process_name - rule_description: This search looks for wmic.exe being launched with parameters - to operate on remote systems. - rule_title: Endpoint - Remote WMI command attempt - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 50 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=wmic.exe AND - Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name - Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest,user,process_name - suppress_period: 28800s -eli5: Many a times, attackers leverage native Windows utilities that are designed - to help administrators better manage their systems, infrastructure, and auditing, - but are instead leveraged for malicious purposes. In this case, we are looking for - instances of wmic.exe being run with various parameters that are not typically used - by administrators. -entities: - - dest how_to_implement: You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -id: 272df6de-61f1-4784-877c-1fbc3e2d0838 -investigations: - - id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 - name: Get Sysmon WMI Activity for Host - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=wmic.exe AND + Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name + Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)`' known_false_positives: Administrators may use this legitimately to gather info from remote systems. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 +tags: + analytics_story: + - Suspicious WMI Use + mitre_attack_id: + - T1047 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Windows Management Instrumentation + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2018-12-03' -name: Remote WMI Command Attempt -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/detections/remote_wmi_process_instantiation.yml b/detections/remote_wmi_process_instantiation.yml deleted file mode 100644 index 5d8eb5780a..0000000000 --- a/detections/remote_wmi_process_instantiation.yml +++ /dev/null @@ -1,113 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-01-13' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - Sysmon - - Tanium - - Ziften -description: This search looks for wmic.exe being launched with parameters to spawn - a process on a remote system. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for wmic.exe being launched with parameters - to spawn a process on a remote system. - rule_title: Remote process instantiation via WMI on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = wmic.exe Processes.process="*/node*" Processes.process="*process*" - Processes.process="*call*" Processes.process="*create*" by Processes.process_name - Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest,user,process - suppress_period: 28800s -eli5: Attackers are increasingly abusing native Windows utilities such as wmic.exe - as a means to "live off the land", and avoid introducing new executables to the - target system. In this search, we are looking for instances of wmic.exe being run - with various parameters that are not typically used by administrators. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da -investigations: - - id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 - name: Get Sysmon WMI Activity for Host - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk -known_false_positives: The wmic.exe utility is a benign Windows application. It may - be used legitimately by Administrators with these parameters for remote system administration, - but it's relatively uncommon. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Windows Management Instrumentation - nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2019-02-27' -name: Remote Process Instantiation via WMI -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/rundll_loading_dll_by_ordinal.yml b/detections/rundll_loading_dll_by_ordinal.yml index 537107a7f1..e6c189182f 100644 --- a/detections/rundll_loading_dll_by_ordinal.yml +++ b/detections/rundll_loading_dll_by_ordinal.yml @@ -1,106 +1,37 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-08-09' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: RunDLL Loading DLL By Ordinal +id: 6c135f8d-5e60-454e-80b7-c56eed739833 +version: '2.0' +date: '2019-02-27' description: This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for DLLs under %AppData% being loaded - by rundll32.exe that are calling the exported function at ordinal 2. Calling - exported functions by ordinal is not as common as calling by exported name. There - was a bug fixed in IDAPro on 2016-08-08 that would not display functions - with no names. Calling functions by ordinal would overcome the lack of - name and make it harder for analyst to reverse engineer. - rule_title: Endpoint - Suspicious RunDLL usage - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = rundll32.exe Processes.process="*AppData*" Processes.process="*,#2" - by Processes.process_name Processes.parent_process_name Processes.dest Processes.user - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest,user - suppress_period: 28800s -eli5: This search looks for rundll32.exe being run, loading a DLL out of a directory - or subdirectory of AppData, and specifying the function at ordinal 2 be run. -entities: - - dest how_to_implement: You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -id: 6c135f8d-5e60-454e-80b7-c56eed739833 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = rundll32.exe Processes.process="*AppData*" Processes.process="*,#2" + by Processes.process_name Processes.parent_process_name Processes.dest Processes.user + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' known_false_positives: While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 +tags: + analytics_story: + - Unusual Processes + mitre_attack_id: + - T1085 kill_chain_phases: - - Installation - mitre_attack: - - Execution - - Rundll32 + - Installation + cis20: + - CIS 8 nist: - - PR.PT - - DE.CM -modification_date: '2019-02-27' -name: RunDLL Loading DLL By Ordinal -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' + - PR.PT + - DE.CM diff --git a/detections/s3_access_from_new_ip.yml b/detections/s3_access_from_new_ip.yml deleted file mode 100644 index 28cdd3904e..0000000000 --- a/detections/s3_access_from_new_ip.yml +++ /dev/null @@ -1,115 +0,0 @@ -asset_type: S3 Bucket -baselines: - - id: fc0edc15-fq2c-48b0-9f6f-63qa1281fd03 - name: Previously seen S3 bucket access by remote IP - type: splunk -confidence: low -creation_date: '2018-06-25' -data_metadata: - data_source: - - AWS S3 Access logs - data_sourcetypes: - - aws:s3:accesslogs - providing_technologies: - - AWS -description: This search looks at S3 bucket-access logs and detects new or previously - unseen remote IP addresses that have successfully accessed an S3 bucket. -detect: - splunk: - correlation_rule: - notable: - nes_fields: bucket_name, src_ip - rule_description: A remote IP, $src_ip$, has made a successful connection - with an S3 $bucket_name$. - rule_title: S3 bucket $bucketName$ was accessed by a new $src_ip$ - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 5 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:s3:accesslogs http_status=200 [search sourcetype=aws:s3:accesslogs - http_status=200 | stats earliest(_time) as firstTime latest(_time) as lastTime - by bucket_name remote_ip | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv - | stats min(firstTime) as firstTime, max(lastTime) as lastTime by bucket_name - remote_ip | outputlookup previously_seen_S3_access_from_remote_ip.csv | eval - newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | table bucket_name remote_ip]| - iplocation remote_ip |rename remote_ip as src_ip | table _time bucket_name - src_ip City Country operation request_uri - suppress: - suppress_fields: bucket_name, src_ip - suppress_period: 86400s -eli5: 'Here the subsearch executes first and returns all successful S3 bucket-access - attempts (HTTP code "200") within the last hour. It groups the results by the earliest - and latest times it has seen a remote IP accessing a particular bucket. It appends - this information to the historical data from the lookup file and then recalculates - the `firstTime` and `lastTime` field for each remote IP accessing an S3 bucket. - Next, it returns only those remote IP addresses that have first been seen accessing - a specific bucket within the past hour. This is combined with the main search to - return the time, bucket name, source IP, city, and country operations performed, - as well as the requested URI of the resource ' -entities: - - src_ip -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access - logs' inputs. This search works best when you run the "Previously Seen S3 Bucket - Access by Remote IP" support search once to create a history of previously seen - remote IPs and bucket names. -id: 2a9b80d3-6340-4345-b5ad-291bq3d0daq4 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: f3fb2q1c-5f33-4b01-b541-c2ah9534c242 - name: AWS S3 Bucket details via bucketName - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: S3 buckets can be accessed from any IP, as long as it can make - a successful connection. This will be a false postive, since the search is looking - for a new IP within the past hour -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 13 - - CIS 14 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Exfiltration - nist: - - PR.DS - - PR.AC - - DE.CM -modification_date: '2018-06-28' -name: Detect S3 access from a new IP -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/samsam_payload_extensions.yml b/detections/samsam_payload_extensions.yml deleted file mode 100644 index a77a2e5ee1..0000000000 --- a/detections/samsam_payload_extensions.yml +++ /dev/null @@ -1,104 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-12-14' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: The search looks for file writes with extensions consistent with a SamSam - ransomware attack. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A file with an extension associated with SamSam ransomware - was written on $dest$. - rule_title: File with known SamSam extension detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) - as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | - `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| - rex field=file_name "(?\.[^\.]+)$" | search file_extension=.stubbin - OR file_extension=.berkshire OR file_extension=.satoshi OR file_extension=.sophos - OR file_extension=.keyxml' - suppress: - suppress_fields: dest,file_name - suppress_period: 14400s -eli5: This search looks at file modifications across your hosts and creates notable - events when it identifies files with extensions associated with the SamSam ransomware, - including `.stubbin`, `.berkshire`, `.satoshi`, `.sophos`, or `.keyxml`. Files with - these extensions have been observed in SamSam attacks consisting of payload data - or keying material. -entities: - - dest -how_to_implement: You must be ingesting data that records file-system activity from - your hosts to populate the Endpoint file-system data-model node. If you are using - Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you - want to collect data. -id: 02c6cfc2-ae66-4735-bfc7-6291da834cbf -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Because these extensions are not typically used in normal operations, - you should investigate all results. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Installation - mitre_attack: [] - nist: - - PR.PT - - DE.CM -modification_date: '2018-12-14' -name: File with Samsam Extension -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/samsam_test_file_write.yml b/detections/samsam_test_file_write.yml index 4ec58941c1..2a817341bd 100644 --- a/detections/samsam_test_file_write.yml +++ b/detections/samsam_test_file_write.yml @@ -1,101 +1,29 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-12-14' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon +name: Samsam Test File Write +id: 69c12d59-d951-431e-ab77-ec426b8d65e6 +version: '1.0' +date: '2018-12-14' description: The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A file named "test.txt," which is indicative of a SamSam - ransomware attack, was written to system32 on $dest$. - rule_title: File consistent with SamSam probes detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_name) - as file_name from datamodel=Endpoint.Filesystem where Filesystem.file_path=*\\windows\\system32\\test.txt - by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)`' - suppress: - suppress_fields: dest,file_name - suppress_period: 14400s -eli5: This search looks at file modifications across your hosts and monitors for a - file named "test.txt" written to "windows\system32". This file is copied to potential - targets during SamSam ransomware attacks to test the attacker's ability to access - remote systems. If the file is successfully copied to the system, the system is - added to a list of targets on which to deploy ransomware. -entities: - - dest how_to_implement: You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -id: 69c12d59-d951-431e-ab77-ec426b8d65e6 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: No false positives have been identified. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Delivery - mitre_attack: [] - nist: - - PR.PT - - DE.CM -modification_date: '2018-12-14' -name: Samsam Test File Write -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_name) + as file_name from datamodel=Endpoint.Filesystem where Filesystem.file_path=*\\windows\\system32\\test.txt + by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)`' +known_false_positives: No false positives have been identified. +tags: + analytics_story: + - SamSam Ransomware + kill_chain_phases: + - Delivery + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/sc_exe_manipulating_windows_services.yml b/detections/sc_exe_manipulating_windows_services.yml new file mode 100644 index 0000000000..8cf1ff4f41 --- /dev/null +++ b/detections/sc_exe_manipulating_windows_services.yml @@ -0,0 +1,46 @@ +name: Sc.exe Manipulating Windows Services +id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d +version: '2.0' +date: '2019-02-27' +description: This search looks for arguments to sc.exe indicating the creation or + modification of a Windows service. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = sc.exe (Processes.process="* create *" OR Processes.process="* + config *") by Processes.process_name Processes.parent_process_name Processes.dest + Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)`' +known_false_positives: Using sc.exe to manipulate Windows services is uncommon. However, + there may be legitimate instances of this behavior. It is important to validate + and investigate as appropriate. +tags: + analytics_story: + - Disabling Security Tools + - Windows Persistence Techniques + - Windows Service Abuse + - Orangeworm Attack Group + - DHS Report TA18-074A + mitre_attack_id: + - T1050 + - T1031 + - T1089 + kill_chain_phases: + - Installation + cis20: + - CIS 3 + - CIS 5 + - CIS 8 + nist: + - PR.IP + - PR.PT + - PR.AC + - PR.AT + - DE.CM diff --git a/detections/sc_manipulating_services.yml b/detections/sc_manipulating_services.yml deleted file mode 100644 index 6da35b9a50..0000000000 --- a/detections/sc_manipulating_services.yml +++ /dev/null @@ -1,118 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-11-03' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for arguments to sc.exe indicating the creation or - modification of a Windows service. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for arguments to sc.exe indicating the - creation or modification of a Windows service. - rule_title: Sc.exe Manipulating Windows Services on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = sc.exe (Processes.process="* create *" OR Processes.process="* - config *") by Processes.process_name Processes.parent_process_name Processes.dest - Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process - suppress_period: 28800s -eli5: This search looks for the execution of sc.exe with parameters that indicate - the utility is being used to create a new Windows service, or modify an existing - one. Attackers often create a new service to host their malicious code, or they - may take a non-critical service or one that is disabled, and modify it to point - to their malware and enable the service if necessary. It is unusual for a service - to be created or modified using the sc.exe utility. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Using sc.exe to manipulate Windows services is uncommon. However, - there may be legitimate instances of this behavior. It is important to validate - and investigate as appropriate. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 8 - kill_chain_phases: - - Installation - mitre_attack: - - Persistence - - Privilege Escalation - - New Service - - Modify Existing Service - - Defense Evasion - - Disabling Security Tools - nist: - - PR.IP - - PR.PT - - PR.AC - - PR.AT - - DE.CM -modification_date: '2019-02-27' -name: Sc.exe Manipulating Windows Services -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml new file mode 100644 index 0000000000..16334aef8d --- /dev/null +++ b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml @@ -0,0 +1,32 @@ +name: Scheduled Task Name Used by Dragonfly Threat Actors +id: d5af132c-7c17-439c-9d31-13d55340f36c +version: '3.0' +date: '2020-03-16' +description: This search looks for flags passed to schtasks.exe on the command-line + that indicate a task name associated with the Dragonfly threat actor was created + or deleted. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe by + Processes.user Processes.process_name Processes.parent_process_name Processes.dest | + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | search (process=*delete* OR process=*create*) process=*reset* | `dragonfly_schtasks_filter`' +known_false_positives: No known false positives +tags: + analytics_story: + - DHS Report TA18-074A + mitre_attack_id: + - T1053 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + nist: + - PR.IP diff --git a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml new file mode 100644 index 0000000000..4ab29390e3 --- /dev/null +++ b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml @@ -0,0 +1,33 @@ +name: Scheduled tasks used in BadRabbit ransomware +id: 1297fb80-f42a-4b4a-9c8b-78c066437cf6 +version: '2.0' +date: '2019-02-28' +description: This search looks for flags passed to schtasks.exe on the command-line + that indicate that task names related to the execution of Bad Rabbit ransomware + were created or deleted. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Processes.process) as process from datamodel=Endpoint.Processes + where Processes.process_name=schtasks.exe (Processes.process= "*create*" OR Processes.process= + "*delete*") by Processes.parent_process Processes.process_name Processes.user | + `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + | search (process=*rhaegal* OR process=*drogon* OR *viserion_*)' +known_false_positives: No known false positives +tags: + analytics_story: + - Ransomware + mitre_attack_id: + - T1053 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + nist: + - PR.IP diff --git a/detections/schtasks_forced_reboot.yml b/detections/schtasks_forced_reboot.yml deleted file mode 100644 index 63be186546..0000000000 --- a/detections/schtasks_forced_reboot.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-11-03' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for flags passed to schtasks.exe on the command-line - that indicate that a forced reboot of system is scheduled. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for flags passed to schtasks.exe on the - command-line that indicate a job is scheduled to force a reboot - rule_title: Schtasks used for scheduling a force reboot - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -5h@h - latest_time: -1h@h - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = schtasks.exe Processes.process="*shutdown*" Processes.process="*/r*" - Processes.process="*/f*" by Processes.process_name Processes.parent_process_name - Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process - suppress_period: 28800s -eli5: The search looks for execution of schtasks.exe with parameters that indicate - a task is being scheduled that would cause a forced reboot on the host. Schtasks.exe - is a native windows program that is used to schedule tasks on local or remote systems. - Attackers often leverage this capability to schedule the execution of commands or - establish persistence. This tactic is leveraged by the Bad Rabbit Ransomware. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting logs - with both the process name and command-line from your endpoints. If you are using - Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -id: 1297fb80-f42a-4b4a-9c8a-88c066437cf6 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Administrators may create jobs on systems forcing reboots to - perform updates, maintenance, etc. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Execution - - Scheduled Task - nist: - - PR.IP -modification_date: '2019-02-27' -name: Schtasks used for forcing a reboot -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/schtasks_scheduling_job_on_remote_system.yml b/detections/schtasks_scheduling_job_on_remote_system.yml index ad2661b6f7..e6f986d726 100644 --- a/detections/schtasks_scheduling_job_on_remote_system.yml +++ b/detections/schtasks_scheduling_job_on_remote_system.yml @@ -1,111 +1,34 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Schtasks scheduling job on remote system +id: 1297fb80-f42a-4b4a-9c8a-88c066237cf6 +version: '3.0' +date: '2020-01-10' description: This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for flags passed to schtasks.exe on the - command-line that indicate a job is being scheduled on a remote system. - rule_title: Schtasks scheduling job on remote system - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - schtasks_scheduling_job_on_remote_system_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime - from datamodel=Endpoint.Processes where Processes.process_name = schtasks.exe Processes.process="*/create*" - Processes.process="* /s *" by Processes.process_name Processes.process Processes.parent_process_name - Processes.dest Processes.user | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | `schtasks_scheduling_job_on_remote_system_filter`' - suppress: - suppress_fields: dest,process - suppress_period: 28800s -eli5: The search looks for execution of schtasks.exe with parameters that indicate - a task is being scheduled on a remote host. Schtasks.exe is a native windows program - that is used to schedule tasks on local or remote systems. Attackers often leverage - this capability to schedule the execution of commands or malicious executables on - remote systems. -entities: - - dest how_to_implement: You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -id: 1297fb80-f42a-4b4a-9c8a-88c066237cf6 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.process_name = schtasks.exe + Processes.process="*/create*" Processes.process="* /s *" by Processes.process_name + Processes.process Processes.parent_process_name Processes.dest Processes.user | + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `schtasks_scheduling_job_on_remote_system_filter`' known_false_positives: Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 +tags: + analytics_story: + - Lateral Movement + mitre_attack_id: + - T1053 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Privilege Escalation - - Execution - - Scheduled Task - mitre_technique_id: - - T1053 + - Actions on Objectives + cis20: + - CIS 3 nist: - - PR.IP -modification_date: '2020-01-10' -name: Schtasks scheduling job on remote system -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' + - PR.IP diff --git a/detections/schtasks_used_for_forcing_a_reboot.yml b/detections/schtasks_used_for_forcing_a_reboot.yml new file mode 100644 index 0000000000..2be59ce165 --- /dev/null +++ b/detections/schtasks_used_for_forcing_a_reboot.yml @@ -0,0 +1,32 @@ +name: Schtasks used for forcing a reboot +id: 1297fb80-f42a-4b4a-9c8a-88c066437cf6 +version: '2.0' +date: '2019-02-27' +description: This search looks for flags passed to schtasks.exe on the command-line + that indicate that a forced reboot of system is scheduled. +how_to_implement: To successfully implement this search you need to be ingesting logs + with both the process name and command-line from your endpoints. If you are using + Sysmon, you must have at least version 6.0.4 of the Sysmon TA. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = schtasks.exe Processes.process="*shutdown*" Processes.process="*/r*" + Processes.process="*/f*" by Processes.process_name Processes.parent_process_name + Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)`' +known_false_positives: Administrators may create jobs on systems forcing reboots to + perform updates, maintenance, etc. +tags: + analytics_story: + - Windows Persistence Techniques + - Ransomware + mitre_attack_id: + - T1053 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + nist: + - PR.IP diff --git a/detections/script_execution_via_wmi.yml b/detections/script_execution_via_wmi.yml new file mode 100644 index 0000000000..17a0a4d172 --- /dev/null +++ b/detections/script_execution_via_wmi.yml @@ -0,0 +1,34 @@ +name: Script Execution via WMI +id: aa73f80d-d728-4077-b226-81ea0c8be589 +version: '3.0' +date: '2020-03-16' +description: This search looks for scripts launched via WMI. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes + where Processes.process_name = "scrcons.exe" by Processes.user Processes.dest Processes.process_name | + `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| + `wmi_script_execution_filter`' +known_false_positives: Although unlikely, administrators may use wmi to launch scripts + for legitimate purposes. +tags: + analytics_story: + - Suspicious WMI Use + mitre_attack_id: + - T1047 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + nist: + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/detections/shim_database_file_creation.yml b/detections/shim_database_file_creation.yml index 651ce27ba6..7375bf9713 100644 --- a/detections/shim_database_file_creation.yml +++ b/detections/shim_database_file_creation.yml @@ -1,108 +1,35 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-10-03' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon +name: Shim Database File Creation +id: 6e4c4588-ba2f-42fa-97e6-9f6f548eaa33 +version: '2.0' +date: '2018-11-02' description: This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A file, $file_name$, was created in the default shim database - directory on $dest. - rule_title: Shim database file created on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Filesystem.action) values(Filesystem.file_hash) - as file_hash values(Filesystem.file_path) as file_path min(_time) as firstTime - max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\AppPatch\Custom* - by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - |`drop_dm_object_name(Filesystem)`' - suppress: - suppress_fields: dest - suppress_period: 14400s -eli5: This search looks for files being created in `Windows\AppPatch\Custom and Windows\AppPatch\Custom64`, - the location where shim databases are installed. It will return all the files created, - as well as the time of creation for the first and last file for each endpoint. -entities: - - dest how_to_implement: You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -id: 6e4c4588-ba2f-42fa-97e6-9f6f548eaa33 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Filesystem.action) + values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path min(_time) + as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\AppPatch\Custom* + by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + |`drop_dm_object_name(Filesystem)`' known_false_positives: Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 +tags: + analytics_story: + - Windows Persistence Techniques + mitre_attack_id: + - T1138 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Application Shimming + - Actions on Objectives + cis20: + - CIS 8 nist: - - DE.CM -modification_date: '2018-11-02' -name: Shim Database File Creation -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' + - DE.CM diff --git a/detections/shim_database_installation.yml b/detections/shim_database_installation.yml deleted file mode 100644 index e5ba23da80..0000000000 --- a/detections/shim_database_installation.yml +++ /dev/null @@ -1,107 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-10-03' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search detects the process execution and arguments required to silently - create a shim database. The sdbinst.exe application is used to install shim database - files (.sdb). A shim is a small library which transparently intercepts an API, changes - the parameters passed, handles the operation itself, or redirects the operation - elsewhere. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: The system $dest$ had a shim database installed. - rule_title: Shim Database Installation on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = sdbinst.exe Processes.process="*-p*" Processes.process="*-q*" - by Processes.process_name Processes.parent_process_name Processes.dest Processes.user - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest,user - suppress_period: 14400s -eli5: This search looks for the execution of sdbinst.exe with command-line arguments - of -q and -p. The -q option performs a silent installation with no visible window, - status, or warning information. The -p option allows the shim database to contain - patches. It will return the count, the first time, and the last time these command-line - arguments were seen on each endpoint and by each user. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: 404620de-46d8-48b6-90cc-8a8d7b0876a3 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Persistence - - Application Shimming - nist: - - DE.CM -modification_date: '2019-03-01' -name: Shim Database Installation With Suspicious Parameters -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/shim_database_installation_with_suspicious_parameters.yml b/detections/shim_database_installation_with_suspicious_parameters.yml new file mode 100644 index 0000000000..0384566636 --- /dev/null +++ b/detections/shim_database_installation_with_suspicious_parameters.yml @@ -0,0 +1,34 @@ +name: Shim Database Installation With Suspicious Parameters +id: 404620de-46d8-48b6-90cc-8a8d7b0876a3 +version: '2.0' +date: '2019-03-01' +description: This search detects the process execution and arguments required to silently + create a shim database. The sdbinst.exe application is used to install shim database + files (.sdb). A shim is a small library which transparently intercepts an API, changes + the parameters passed, handles the operation itself, or redirects the operation + elsewhere. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = sdbinst.exe Processes.process="*-p*" Processes.process="*-q*" + by Processes.process_name Processes.parent_process_name Processes.dest Processes.user + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +known_false_positives: None identified +tags: + analytics_story: + - Windows Persistence Techniques + mitre_attack_id: + - T1138 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/short_lived_accounts.yml b/detections/short_lived_accounts.yml deleted file mode 100644 index d169f9b149..0000000000 --- a/detections/short_lived_accounts.yml +++ /dev/null @@ -1,99 +0,0 @@ -asset_type: Windows -confidence: medium -creation_date: '2018-01-05' -data_metadata: - data_models: - - Change - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search detects accounts that were created and deleted in a short - time period. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: The account $user$ was created and deleted in a short amount - of time. - rule_title: Short lived account $user$ on $dest - risk: - risk_object: user - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 0,4,8,12,16,20 * * * - earliest_time: -245m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(All_Changes.result_id) as result_id - count min(_time) as firstTime max(_time) as lastTime from datamodel=Change - where All_Changes.result_id=4720 OR All_Changes.result_id=4726 by _time span=4h - All_Changes.user All_Changes.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - | `drop_dm_object_name("All_Changes")` | search result_id = 4720 result_id=4726 - | transaction user connected=false maxspan=240m | table firstTime lastTime count user dest - result_id' - suppress: - suppress_fields: user - suppress_period: 86400s -eli5: This search looks for Windows Event Logs 4720 (account creation) and 4726 (account - deletion) and determines if they happen for the same user within 4 hours of each - other. It will report the user and machine that reported the events and the time - it first and last saw this activity. -entities: - - user -how_to_implement: 'This search requires you to have enabled your Group Management - Audit Logs in your Local Windows Security Policy and be ingesting those logs. More - information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/' -id: b25f6f62-0782-43c1-b403-083231ffd97d -investigations: - - id: 552bc86c-f72c-4d44-b3f2-06ede13af7bb - name: Get Logon Rights Modifications For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: 03bffe94-ec7a-4cbe-b677-6af40d1c4505 - name: Get Logon Rights Modifications For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is possible that an administrator created and deleted an - account in a short time period. Verifying activity with an administrator is advised. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 16 - mitre_attack: - - Persistence - - Create Account - nist: - - PR.IP -modification_date: '2018-01-05' -name: Short Lived Windows Accounts -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: access -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/short_lived_windows_accounts.yml b/detections/short_lived_windows_accounts.yml new file mode 100644 index 0000000000..b450ad1338 --- /dev/null +++ b/detections/short_lived_windows_accounts.yml @@ -0,0 +1,30 @@ +name: Short Lived Windows Accounts +id: b25f6f62-0782-43c1-b403-083231ffd97d +version: '1.0' +date: '2018-01-05' +description: This search detects accounts that were created and deleted in a short + time period. +how_to_implement: 'This search requires you to have enabled your Group Management + Audit Logs in your Local Windows Security Policy and be ingesting those logs. More + information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/' +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` values(All_Changes.result_id) as + result_id count min(_time) as firstTime max(_time) as lastTime from datamodel=Change + where All_Changes.result_id=4720 OR All_Changes.result_id=4726 by _time span=4h + All_Changes.user All_Changes.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + | `drop_dm_object_name("All_Changes")` | search result_id = 4720 result_id=4726 + | transaction user connected=false maxspan=240m | table firstTime lastTime count + user dest result_id' +known_false_positives: It is possible that an administrator created and deleted an + account in a short time period. Verifying activity with an administrator is advised. +tags: + analytics_story: + - Account Monitoring and Controls + mitre_attack_id: + - T1136 + cis20: + - CIS 16 + nist: + - PR.IP diff --git a/detections/single_letter_executables.yml b/detections/single_letter_executables.yml deleted file mode 100644 index 74a63bb0cd..0000000000 --- a/detections/single_letter_executables.yml +++ /dev/null @@ -1,103 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-03-22' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for process names that consist only of a single letter. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, user - rule_description: A process with a single letter, $process_name$ was detected - on $dest$ - rule_title: Single-letter executable $process_name$ on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Endpoint.Processes by Processes.dest, Processes.user, - Processes.process, Processes.process_name | `drop_dm_object_name(Processes)` - | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | eval process_name_length = len(process_name), - endExe = if(substr(process_name, -4) == ".exe", 1, 0) | search process_name_length=5 - AND endExe=1 | table count, firstTime, lastTime, dest, user, process, process_name' - suppress: - suppress_fields: dest, user - suppress_period: 86400s -eli5: This search returns all the processes for each endpoint and user and filters - out any process that isn't 5 characters long and ends with .exe. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: a4214f0b-e01c-41bc-8cc4-d2b71e3056b4 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Single-letter executables are not always malicious. Investigate - this activity with your normal incident-response process. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 2 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - ID.AM - - PR.DS -modification_date: '2019-04-01' -name: Single Letter Process On Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/single_letter_process_on_endpoint.yml b/detections/single_letter_process_on_endpoint.yml new file mode 100644 index 0000000000..9848d4ae3e --- /dev/null +++ b/detections/single_letter_process_on_endpoint.yml @@ -0,0 +1,31 @@ +name: Single Letter Process On Endpoint +id: a4214f0b-e01c-41bc-8cc4-d2b71e3056b4 +version: '2.0' +date: '2019-04-01' +description: This search looks for process names that consist only of a single letter. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes by Processes.dest, Processes.user, + Processes.process, Processes.process_name | `drop_dm_object_name(Processes)` | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)` | eval process_name_length = len(process_name), + endExe = if(substr(process_name, -4) == ".exe", 1, 0) | search process_name_length=5 + AND endExe=1 | table count, firstTime, lastTime, dest, user, process, process_name' +known_false_positives: Single-letter executables are not always malicious. Investigate + this activity with your normal incident-response process. +tags: + analytics_story: + - DHS Report TA18-074A + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 2 + nist: + - ID.AM + - PR.DS diff --git a/detections/smb_traffic_spike.yml b/detections/smb_traffic_spike.yml index c020114844..49d36a9f3d 100644 --- a/detections/smb_traffic_spike.yml +++ b/detections/smb_traffic_spike.yml @@ -1,119 +1,35 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-08-20' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream +name: SMB Traffic Spike +id: 7f5fb3e1-4209-4914-90db-0ec21b936378 +version: '2.0' +date: '2020-01-22' description: This search looks for spikes in the number of Server Message Block (SMB) traffic connections. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src - rule_description: There was a spike in SMB traffic from $src$. - rule_title: SMB Traffic Spike from $src$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -7d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic where - All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb - by _time span=1h, All_Traffic.src | `drop_dm_object_name("All_Traffic")` | - eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time - >= relative_time(maxtime, "-70m@m"), count, null))) as count avg(eval(if(_time upperBound AND num_data_samples >=50, 1, 0) | where isOutlier=1 - | table src count | `smb_traffic_spike_filter` ' - suppress: - suppress_fields: src - suppress_period: 28800s -eli5: Server Message Block (SMB) traffic, a protocol used for Windows file sharing-activity, - is often leveraged by attackers. One example of SMB abuse was the WannaCry ransomware, - which leveraged a vulnerability in the SMB protocol to propagate to other systems. - Attackers have also used SMB for lateral movement with a target environment and - to test credentials against target systems. While SMB is highly prevalent in Windows - environments, a spike in SMB traffic may still be indicative of this type of malicious - activity. This search looks for a traffic spike in SMB traffic from a particular - system. If such a spike is detected, you may want to investigate the source and - analyze the cause of the abnormal traffic. -entities: - - src how_to_implement: This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. -id: 7f5fb3e1-4209-4914-90db-0ec21b936378 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Network_Traffic + where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb + by _time span=1h, All_Traffic.src | `drop_dm_object_name("All_Traffic")` | eventstats + max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, + "-70m@m"), count, null))) as count avg(eval(if(_time upperBound + AND num_data_samples >=50, 1, 0) | where isOutlier=1 | table src count | `smb_traffic_spike_filter` ' known_false_positives: A file server may experience high-demand loads that could cause this analytic to trigger. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - Ransomware + - DHS Report TA18-074A + - Hidden Cobra Malware + mitre_attack_id: + - T1043 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Lateral Movement - - Execution - - Command and Control - - Commonly Used Port - mitre_technique_id: - - T1110 - - T1135 - - T1210 + - Actions on Objectives + cis20: + - CIS 8 nist: - - DE.CM -modification_date: '2020-01-22' -name: SMB Traffic Spike -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' + - DE.CM diff --git a/detections/smb_traffic_spike___mltk.yml b/detections/smb_traffic_spike___mltk.yml new file mode 100644 index 0000000000..b88a4b6650 --- /dev/null +++ b/detections/smb_traffic_spike___mltk.yml @@ -0,0 +1,56 @@ +name: SMB Traffic Spike - MLTK +id: d25773ba-9ad8-48d1-858e-07ad0bbeb828 +version: '2.0' +date: '2020-01-22' +description: This search uses the Machine Learning Toolkit (MLTK) to identify spikes + in the number of Server Message Block (SMB) connections. +how_to_implement: 'To successfully implement this search, you will need to ensure + that DNS data is populating the Network_Resolution data model. In addition, the + Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your + search heads, along with any required dependencies. Finally, the support search + "Baseline of SMB Traffic - MLTK" must be executed before this detection search, + because it builds a machine-learning (ML) model over the historical data used by + this search. It is important that this search is run in the same app context as + the associated support search, so that the model created by the support search is + available for use. You should periodically re-run the support search to rebuild + the model with the latest data available in your environment.\ + + This search produces a field (Number of events,count) that are not yet supported + by ES Incident Review and therefore cannot be viewed when a notable event is raised. + This field contributes additional context to the notable. To see the additional + metadata, add the following field, if not already present, to Incident Review - + Event Attributes (Configure > Incident Management > Incident Review Settings > Add + New Entry): \ + + 1. **Label:** Number of events, **Field:** count\ + + Detailed documentation on how to create a new field within Incident Review is found + here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count values(All_Traffic.dest_ip) + as dest values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where + All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by + _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, + "%A") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 + | rename "IsOutlier(count)" as isOutlier | search isOutlier > 0 | sort -count | + table _time src dest port count | `smb_traffic_spike_mltk_filter` ' +known_false_positives: If you are seeing more results than desired, you may consider + reducing the value of the threshold in the search. You should also periodically + re-run the support search to re-build the ML model on the latest data. Please update + the `smb_traffic_spike_mltk_filter` macro to filter out false positive results +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - Ransomware + - DHS Report TA18-074A + - Hidden Cobra Malware + mitre_attack_id: + - T1043 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/smb_traffic_spike_mltk.yml b/detections/smb_traffic_spike_mltk.yml deleted file mode 100644 index b5b44c2251..0000000000 --- a/detections/smb_traffic_spike_mltk.yml +++ /dev/null @@ -1,147 +0,0 @@ -asset_type: Endpoint -baselines: - - id: df98763b-0b08-4281-8ef9-08db7ac572a9 - name: Baseline of SMB Traffic - MLTK - type: splunk -confidence: medium -creation_date: '2019-05-08' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Bro - - Splunk Stream -description: This search uses the Machine Learning Toolkit (MLTK) to identify spikes - in the number of Server Message Block (SMB) connections. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src - rule_description: There was a spike in SMB traffic from $src$ - rule_title: SMB Traffic Spike from $src$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 50 - macros: - - smb_traffic_spike_mltk_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(All_Traffic.dest_ip) as dest - values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where - All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb - by _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | - eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name(All_Traffic)` - | apply smb_pdfmodel threshold=0.001 | rename "IsOutlier(count)" as isOutlier - | search isOutlier > 0 | sort -count | table _time src dest port count | `smb_traffic_spike_mltk_filter` ' - suppress: - suppress_fields: src - suppress_period: 28800s -eli5: Attackers often leverage Server Message Block (SMB) traffic, a protocol used - for Windows file-sharing activity. A high-profile example of SMB abuse was the WannaCry - ransomware, which leveraged a vulnerability in the SMB protocol to propagate to - other systems. Attackers have also used SMB for lateral movement with a target environment - and to test credentials against target systems. While SMB is highly prevalent in - Windows environments, a spike in SMB traffic may still be indicative of this type - of malicious activity. This search leverages Splunk's Machine Learning Toolkit (MLTK) - to identify spikes in SMB traffic that are unusual for a given hour of day/day of - week combination. If such a spike is detected, you may want to investigate the source - and analyze the cause of the abnormal traffic. The determination of what is considered - an outlier may be adjusted via the threshold parameter in the search. More information - on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -entities: - - src -how_to_implement: 'To successfully implement this search, you will need to ensure - that DNS data is populating the Network_Resolution data model. In addition, the - Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your - search heads, along with any required dependencies. Finally, the support search - "Baseline of SMB Traffic - MLTK" must be executed before this detection search, - because it builds a machine-learning (ML) model over the historical data used by - this search. It is important that this search is run in the same app context as - the associated support search, so that the model created by the support search is - available for use. You should periodically re-run the support search to rebuild - the model with the latest data available in your environment.\ - - This search produces a field (Number of events,count) that are not yet supported - by ES Incident Review and therefore cannot be viewed when a notable event is raised. - This field contributes additional context to the notable. To see the additional - metadata, add the following field, if not already present, to Incident Review - - Event Attributes (Configure > Incident Management > Incident Review Settings > Add - New Entry): \ - - 1. **Label:** Number of events, **Field:** count\ - - Detailed documentation on how to create a new field within Incident Review is found - here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: d25773ba-9ad8-48d1-858e-07ad0bbeb828 -investigations: - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: If you are seeing more results than desired, you may consider - reducing the value of the threshold in the search. You should also periodically - re-run the support search to re-build the ML model on the latest data. Please update the `smb_traffic_spike_mltk_filter` macro to filter out false positive results -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Lateral Movement - - Execution - - Command and Control - - Commonly Used Port - mitre_technique_id: - - T1110 - - T1135 - - T1210 - nist: - - DE.CM -modification_date: '2020-01-22' -name: SMB Traffic Spike - MLTK -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/sncd_processes.yml b/detections/sncd_processes.yml deleted file mode 100644 index 9511f0174b..0000000000 --- a/detections/sncd_processes.yml +++ /dev/null @@ -1,112 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-11-04' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for fast execution of processes used for system network - configuration discovery on the endpoint. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, user - rule_description: Fast execution of processes $related to network system configuration - discovery seen on $dest$. - rule_title: Fast execution of processes $process_name$ related to network - discovery seen on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest - Processes.process_name Processes.user _time | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` - | transaction dest connected=false maxpause=5m |where eventcount>=5 | table firstTime lastTime - dest user process_name process parent_process eventcount' - suppress: - suppress_fields: dest,user - suppress_period: 86400s -eli5: Attackers have a range of built-in Windows tools they leverage to ascertain - the topography of a network from the point of view of a compromised machine. It - is uncommon to see these commands execute quickly within short periods of time. - This search returns the number of times, as well as the first time and last times, - that every process has run for each endpoint. It then executes the macro `system_network_configuration_discovery_tools`, - which looks for processes that are typically used for network configuration discovery. - Once you have a list of suspicious process launches for each destination, you can - leverage the transaction command to see what processes are fired within a five-minute - span on an endpoint and detect only those events where the count of these processes - is greater than five. -entities: - - dest -how_to_implement: You must be ingesting data that records registry activity from your - hosts to populate the Endpoint data model in the processes node. This is typically - populated via endpoint detection-and-response products, such as Carbon Black, or - endpoint data sources, such as Sysmon. The data used for this search is usually - generated via logs that report reads and writes to the registry or that are populated - via Windows event logs, after enabling process tracking in your Windows audit settings. -id: a51bfe1a-94f0-48cc-b1e4-16ae10145893 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is uncommon for normal users to execute a series of commands - used for network discovery. System administrators often use scripts to execute these - commands. These can generate false positives. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 2 - kill_chain_phases: - - Installation - - Command and Control - - Actions on Objectives - mitre_attack: - - Execution - nist: - - ID.AM - - PR.DS -modification_date: '2018-11-20' -name: Detect processes used for System Network Configuration Discovery -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/spectre_and_meltdown_vulnerable_systems.yml b/detections/spectre_and_meltdown_vulnerable_systems.yml new file mode 100644 index 0000000000..eef397f8c9 --- /dev/null +++ b/detections/spectre_and_meltdown_vulnerable_systems.yml @@ -0,0 +1,27 @@ +name: Spectre and Meltdown Vulnerable Systems +id: 354be8e0-32cd-4da0-8c47-796de13b60ea +version: '1.0' +date: '2017-01-07' +description: The search is used to detect systems that are still vulnerable to the + Spectre and Meltdown vulnerabilities. +how_to_implement: The search requires that you are ingesting your vulnerability-scanner + data and that it reports the CVE of the vulnerability identified. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) + as lastTime from datamodel=Vulnerabilities where Vulnerabilities.cve ="CVE-2017-5753" + OR Vulnerabilities.cve ="CVE-2017-5715" OR Vulnerabilities.cve ="CVE-2017-5754" + by Vulnerabilities.dest| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +known_false_positives: It is possible that your vulnerability scanner is not detecting + that the patches have been applied. +tags: + analytics_story: + - Spectre And Meltdown Vulnerabilities + cis20: + - CIS 4 + nist: + - ID.RA + - RS.MI + - PR.IP + - DE.CM diff --git a/detections/spectre_meltdown_vulnerabilities.yml b/detections/spectre_meltdown_vulnerabilities.yml deleted file mode 100644 index 5afc6fd45e..0000000000 --- a/detections/spectre_meltdown_vulnerabilities.yml +++ /dev/null @@ -1,91 +0,0 @@ -asset_type: Endpoint -baselines: - - id: fc0edc95-ff2b-48b0-9f6f-63da3789fd61 - name: Systems Ready for Spectre-Meltdown Windows Patch - type: splunk -confidence: high -creation_date: '2018-01-07' -data_metadata: - data_models: - - Vulnerabilities - data_source: - - Vulnerability Scanner - providing_technologies: - - Nessus - - Qualys -description: The search is used to detect systems that are still vulnerable to the - Spectre and Meltdown vulnerabilities. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: $dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities. - rule_title: $dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 100 - schedule: - cron_schedule: 0 6 * * * - earliest_time: -25h@h - latest_time: -1h@h - search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime - from datamodel=Vulnerabilities where Vulnerabilities.cve ="CVE-2017-5753" - OR Vulnerabilities.cve ="CVE-2017-5715" OR Vulnerabilities.cve ="CVE-2017-5754" - by Vulnerabilities.dest| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: This search looks for the three CVEs associated with the Spectre and Meltdown - vulnerabilities. -entities: - - dest -how_to_implement: The search requires that you are ingesting your vulnerability-scanner - data and that it reports the CVE of the vulnerability identified. -id: 354be8e0-32cd-4da0-8c47-796de13b60ea -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is possible that your vulnerability scanner is not detecting - that the patches have been applied. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 4 - nist: - - ID.RA - - RS.MI - - PR.IP - - DE.CM -modification_date: '2017-01-07' -name: Spectre and Meltdown Vulnerable Systems -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/spike_aws_api_call_per_account.yml b/detections/spike_aws_api_call_per_account.yml deleted file mode 100644 index 3643f7b7d2..0000000000 --- a/detections/spike_aws_api_call_per_account.yml +++ /dev/null @@ -1,155 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edc96-ff2b-48b0-9f6f-63da3783fd63 - name: Baseline of API Calls per User ARN - type: splunk -confidence: medium -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search will detect users creating spikes of API activity in your - AWS environment. It will also update the cache file that factors in the latest - data. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A spike in the number of AWS API calls by $user$ was detected. - rule_title: Spike in AWS API activity detected by $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventType=AwsApiCall [search sourcetype=aws:cloudtrail - eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count - as apiCalls by arn | inputlookup api_call_by_user_baseline append=t | fields - - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount - | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, - 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval - avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, - stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) - | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup - api_call_by_user_baseline | eval dataPointThreshold = 15, deviationThreshold - = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) - AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn - as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn - | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) - as uniqueApisCalled by user - suppress: - suppress_fields: user - suppress_period: 14400s -eli5: 'This search and its corresponding subsearch run through a series of steps, - as per the following: \ - - 1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls.\ - - 1. Kicks off a subsearch that retrieves the same data and pulls out the ARN into - a more friendly format.\ - - 1. Counts the number of API calls per ARN.\ - - 1. Loads the cache file that contains the number of data points, the count from - the latest hour, the API call average, and the standard deviation for each ARN.\ - - 1. Drops the count from the latest hour, since it is not necessary, and merges the - rest of the data with the results of the stats command. \ - - 1. Renames `apiCalls` as `latestCount`.\ - - 1. Calculates the new average value for each ARN with the latest count, weighting - the past much more heavily than the current hour. It does the same for the standard - deviation--weighting the past more heavily than the current.\ - - 1. Updates the cache file with the latest results.\ - - 1. Sets the minimum threshold for the number of data points and sets the number - of standard deviations away from the mean it must be to be considered a spike.\ - - 1. Makes a determination regarding whether or not the current count is a spike by - checking to see if the minimum data-point threshold has been met and the count is - a sufficient number of standard deviations away from the average.\ - - 1. Filters out anything that it determines is not a spike and returns the list of - ARNs to the main search. The main search subsequently gets the names of all the - API calls, the number of unique API calls, and the total number of API calls for - each of these ARNs. Finally, it looks up the average and standard deviation and - returns both the average and the number of standard deviations the spike is from - the average.' -entities: - - user -how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit - your environment. The `dataPointThreshold` variable is the minimum number of data - points required to have a statistically significant amount of data to determine. - The `deviationThreshold` variable is the number of standard deviations away from - the mean that the value must be to be considered a spike.\ - - This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) - that are not yet supported by ES Incident Review and therefore cannot be viewed - when a notable event is raised. These fields contribute additional context to the - notable. To see the additional metadata, add the following fields, if not already - present, to Incident Review - Event Attributes (Configure > Incident Management - > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** - eventName\ - - 1. \ - - 1. **Label:** Number of API Calls, **Field:** numberOfApiCalls\ - - 1. \ - - 1. **Label:** Unique API Calls, **Field:** uniqueApisCalled\ - - Detailed documentation on how to create a new field within Incident Review may be - found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: ada0f478-84a8-4641-a3f1-d32362d4bd55 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 - name: Investigate AWS User Activities by user field - type: splunk -known_false_positives: '' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Execution - nist: - - DE.DP - - DE.CM - - PR.AC -modification_date: '2018-04-09' -name: Detect Spike in AWS API Activity -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/spike_aws_security_group_activity.yml b/detections/spike_aws_security_group_activity.yml deleted file mode 100644 index fa38773664..0000000000 --- a/detections/spike_aws_security_group_activity.yml +++ /dev/null @@ -1,142 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edd96-ff2b-48b0-9f1f-63da3783fd63 - name: Baseline of Security Group Activity by ARN - type: splunk -confidence: medium -creation_date: '2018-04-17' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search will detect users creating spikes in API activity related - to security groups in your AWS environment. It will also update the cache file - that factors in the latest data. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A spike in the number of AWS API calls related to security - groups by $user$ was detected. - rule_title: Spike in AWS Security Group activity detected by $user$ - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail `security_group_api_calls` [search sourcetype=aws:cloudtrail - `security_group_api_calls` | spath output=arn path=userIdentity.arn | stats count - as apiCalls by arn | inputlookup security_group_activity_baseline append=t - | fields - latestCount | stats values(*) as * by arn | rename apiCalls as - latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 - | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) - | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, - stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) - | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup - security_group_activity_baseline | eval dataPointThreshold = 15, deviationThreshold - = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) - AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn - as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn - | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) - as uniqueApisCalled by user - suppress: - suppress_fields: user - suppress_period: 14400s -eli5: 'This search and its corresponding subsearch run through the following series - of steps: \ - - 1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls - specifically for security groups.\ - - 1. Kicks off a subsearch that retrieves the same data and pulls out the ARN into - a more friendly format.\ - - 1. Counts the number of API calls per ARN.\ - - 1. Loads the cache file that contains the number of data points, the count from - the latest hour, the API call average, and the standard deviation for each ARN.\ - - 1. Drops the count from the latest hour, since it is not necessary, and merges the - rest of the data with the results of the stats command. \ - - 1. Renames `apiCalls` as `latestCount`.\ - - 1. Calculates the new average value for each ARN with the latest count, weighting - the past much more heavily than the current hour. It does the same for the standard - deviation--weighting the past more heavily than the current.\ - - 1. Updates the cache file with the latest results.\ - - 1. Sets the minimum threshold for the number of data points and sets the number - of standard deviations away from the mean it must be to be considered a spike.\ - - 1. Makes a determination regarding whether or not the current count is a spike by - checking to see if the minimum data-point threshold has been met and the count is - a sufficient number of standard deviations away from the average.\ - - 1. Filters out anything that it determines is not a spike and returns the list of - ARNs to the main search. The main search subsequently gets the names of all the - API calls, the number of unique API calls, and the total number of API calls for - each of these ARNs. Finally, it looks up the average and standard deviation and - returns both the average and the number of standard deviations the spike is from - the average.' -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit - your environment. The `dataPointThreshold` variable is the minimum number of data - points required to have a statistically significant amount of data to determine. - The `deviationThreshold` variable is the number of standard deviations away from - the mean that the value must be to be considered a spike.This search works best - when you run the "Baseline of Security Group Activity by ARN" support search once - to create a history of previously seen Security Group Activity. To add or remove - API event names for security groups, edit the macro `security_group_api_calls`. -id: ada0f478-84a8-4641-a3f1-e32372d4bd53 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 - name: Investigate AWS User Activities by user field - type: splunk -known_false_positives: Based on the values of`dataPointThreshold` and `deviationThreshold`, - the false positive rate may vary. Please modify this according the your environment. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 16 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Execution - nist: - - DE.DP - - DE.CM - - PR.AC -modification_date: '2018-04-18' -name: Detect Spike in Security Group Activity -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/spike_in_file_writes.yml b/detections/spike_in_file_writes.yml new file mode 100644 index 0000000000..c05d115b27 --- /dev/null +++ b/detections/spike_in_file_writes.yml @@ -0,0 +1,34 @@ +name: Spike in File Writes +id: fdb0f805-74e4-4539-8c00-618927333aae +version: '3.0' +date: '2020-03-16' +description: The search looks for a sharp increase in the number of files written + to a particular host +how_to_implement: In order to implement this search, you must populate the Endpoint + file-system data model node. This is typically populated via endpoint detection + and response products, such as Carbon Black or endpoint data sources such as Sysmon. + The data used for this search is typically generated via logs that report reads + and writes to the file system. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Filesystem + where Filesystem.action=created by _time span=1h, Filesystem.dest | `drop_dm_object_name(Filesystem)` + | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time + >= relative_time(maxtime, "-1d@d"), count, null))) as "count" avg(eval(if(_time upperBound) AND num_data_samples >=20, 1, 0) | search isOutlier=1 | `file_write_spikes_filter`' +known_false_positives: It is important to understand that if you happen to install + any new applications on your hosts or are copying a large number of files, you can + expect to see a large increase of file modifications. +tags: + analytics_story: + - SamSam Ransomware + - Ransomware + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/spike_s3_deletion.yml b/detections/spike_s3_deletion.yml deleted file mode 100644 index 79327bbbca..0000000000 --- a/detections/spike_s3_deletion.yml +++ /dev/null @@ -1,152 +0,0 @@ -asset_type: S3 Bucket -baselines: - - id: fc0edd96-ff2b-48b0-9f1f-63eq3783fd63 - name: Baseline of S3 Bucket deletion activity by ARN - type: splunk -confidence: medium -creation_date: '2018-07-17' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search detects users creating spikes in API activity related to - deletion of S3 buckets in your AWS environment. It will also update the cache file - that factors in the latest data. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: A spike in the number of S3 buckets deleted by $user$ was - detected. - rule_title: Spike detected in S3 bucket deletion activity by $user$. - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudtrail eventName=DeleteBucket [search sourcetype=aws:cloudtrail - eventName=DeleteBucket | spath output=arn path=userIdentity.arn | stats count - as apiCalls by arn | inputlookup s3_deletion_baseline append=t | fields - - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount - | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, - 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval - avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, - stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) - | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup - s3_deletion_baseline | eval dataPointThreshold = 15, deviationThreshold = - 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) - AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn - as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn - | spath output=bucketName path=requestParameters.bucketName | stats values(bucketName) - as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled - by user - suppress: - suppress_fields: user - suppress_period: 14400s -eli5: 'This search and its corresponding subsearch run through the following series - of steps: \ - - 1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls - specifically for deletion of S3 buckets.\ - - 1. Kick off a subsearch that retrieves the same data and pulls out and converts - the ARN into a more friendly format.\ - - 1. Count the number of API calls per ARN.\ - - 1. Load the cache file that contains the number of data points, the count from the - latest hour, the API call average, and the standard deviation for each ARN.\ - - 1. Drop the count from the latest hour, since it is unnecessary, and merge the rest - of the data with the results of the `stats` command. \ - - 1. Rename `apiCalls` as `latestCount`.\ - - 1. Calculate the new average value for each ARN with the latest count, weighting - the past more heavily than the current hour. It does the same for the standard deviation—weighting - the past more heavily than the current.\ - - 1. Update the cache file with the latest results.\ - - 1. Set the minimum threshold for the number of data points and the number of standard - deviations away from the mean it must be to be considered a spike.\ - - 1. Make a determination regarding whether or not the current count is a spike by - checking to see if the minimum data-point threshold has been met and if the count - is a sufficient number of standard deviations away from the average.\ - - 1. Filter out anything that it determines is not a spike and returns the list of - ARNs to the main search. The main search subsequently gets the names of the deleted - S3 buckets, the number of unique API calls, and the total number of API calls for - each of these user ARNs.' -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit - your environment. The `dataPointThreshold` variable is the minimum number of data - points required to have a statistically significant amount of data to determine. - The `deviationThreshold` variable is the number of standard deviations away from - the mean that the value must be to be considered a spike. This search works best - when you run the "Baseline of S3 Bucket deletion activity by ARN" support search - once to create a baseline of previously seen S3 bucket-deletion activity. -id: ad12w478-84a8-4641-a3w1-e32372q4bd53 -investigations: - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: f3fb2q1c-5f33-4b01-b541-c2ah9534c242 - name: AWS S3 Bucket details via bucketName - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 - name: Investigate AWS activities via region name - type: splunk -known_false_positives: Based on the values of`dataPointThreshold` and `deviationThreshold`, - the false positive rate may vary. Please modify this according the your environment. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Execution - nist: - - DE.DP - - DE.CM - - PR.AC -modification_date: '2018-11-27' -name: Detect Spike in S3 Bucket deletion -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/spike_vpc_blocked_traffic.yml b/detections/spike_vpc_blocked_traffic.yml deleted file mode 100644 index a53de4f848..0000000000 --- a/detections/spike_vpc_blocked_traffic.yml +++ /dev/null @@ -1,183 +0,0 @@ -asset_type: AWS Instance -baselines: - - id: fc0edd96-ff2b-48b0-9f1f-63da3782fd63 - name: Baseline of blocked outbound traffic from AWS - type: splunk -confidence: medium -creation_date: '2018-04-26' -data_metadata: - data_source: - - AWS VPC Flow Logs - data_sourcetypes: - - aws:cloudwatchlogs:vpcflow - providing_technologies: - - AWS -description: This search will detect spike in blocked outbound network connections - originating from within your AWS environment. It will also update the cache file - that factors in the latest data. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip - rule_description: A spike in the blocked outbound connection is detected from - source $src_ip$. - rule_title: Spike in blocked outbound network connections from $src_ip$ detected. - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 - OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND - dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) [search sourcetype=aws:cloudwatchlogs:vpcflow - action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) - ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | - stats count as numberOfBlockedConnections by src_ip | inputlookup baseline_blocked_outbound_connections - append=t | fields - latestCount | stats values(*) as * by src_ip | rename - numberOfBlockedConnections as latestCount | eval newAvgBlockedConnections=avgBlockedConnections - + (latestCount-avgBlockedConnections)/720 | eval newStdevBlockedConnections=sqrt(((pow(stdevBlockedConnections, - 2)*719 + (latestCount-newAvgBlockedConnections)*(latestCount-avgBlockedConnections))/720)) - | eval avgBlockedConnections=coalesce(newAvgBlockedConnections, avgBlockedConnections), - stdevBlockedConnections=coalesce(newStdevBlockedConnections, stdevBlockedConnections), - numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table - src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections - | outputlookup baseline_blocked_outbound_connections | eval dataPointThreshold - = 5, deviationThreshold = 3 | eval isSpike=if((latestCount > avgBlockedConnections+deviationThreshold*stdevBlockedConnections) - AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | table src_ip] - | stats values(dest_ip) as "Blocked Destination IPs", values(interface_id) - as "resourceId" count as numberOfBlockedConnections, dc(dest_ip) as uniqueDestConnections - by src_ip - suppress: - suppress_fields: src_ip - suppress_period: 14400s -eli5: 'This search retrieves all the VPC Flow log entries that have recorded a blocked - outbound network connection originating from your AWS environment. Then it kicks - off a subsearch, which looks at the same data and performs the following series - of steps: \ - - 1. Counts the number of blocked outbound connections by each source IP\ - - 1. Loads the cache file that contains the number of data points, the count from - the latest hour, the average blocked connections, and the standard deviation for - each source IP.\ - - 1. Drops the count from the latest hour, since it is not necessary, and merges the - rest of the data with the results of the stats command. \ - - 1. Renames `numberOfBlockedConnections` as `latestCount`.\ - - 1. Calculates the new average value for each source IP with the latest count, weighting - the past much more heavily than the current hour. It does the same for the standard - deviation, weighting the past more heavily than the current.\ - - 1. Updates the cache file with the latest results.\ - - 1. Sets the minimum threshold for the number of data points and sets the number - of standard deviations away from the mean it must be to be considered a spike.\ - - 1. Makes a determination regarding whether or not the current count is a spike by - checking to see if the minimum data-point threshold has been met and the count is - a sufficient number of standard deviations away from the average.\ - - 1. Filters out anything that it determines is not a spike and returns the list of - source IPs to the main search. The main search subsequently gets the list of all - destination IPs for which the traffic was blocked, the network interface ID, the - number of unique destination IP, and the total number of blocked connections for - each of these source IP addresses. Finally, it looks up the average and standard - deviation and returns both the average and the number of standard deviations the - spike is from the average.' -entities: - - src_ip -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow - logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit - your environment. The `dataPointThreshold` variable is the number of data points - required to meet the definition of "spike." The `deviationThreshold` variable is - the number of standard deviations away from the mean that the value must be to be - considered a spike. This search works best when you run the "Baseline of Blocked - Outbound Connection" support search once to create a history of previously seen - blocked outbound connections. -id: ada0f278-84a8-46w1-a3f1-w32372d4bd53 -investigations: - - id: 910e6512-edc9-4f93-ba24-5b786f47a672 - name: Get Process Responsible For The DNS Traffic - type: splunk - - id: 9925d08f-561e-4faa-8912-e3888a842341 - name: Get Process Information For Port Activity - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 - name: AWS Investigate User Activities By ARN - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: f3fb4d1c-5f33-4b01-b541-c3ah9534c241 - name: AWS Network Interface details via resourceId - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7ah9534c242 - name: AWS Network ACL Details from ID - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 446ec87a-85c6-40d4-b060-bea4498281d6 - name: Get All AWS Activity From IP Address - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 - name: Get DNS traffic ratio - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: The false-positive rate may vary based on the values of`dataPointThreshold` - and `deviationThreshold`. Additionally, false positives may result when AWS administrators - roll out policies enforcing network blocks, causing sudden increases in the number - of blocked outbound connections. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 11 - kill_chain_phases: - - Actions on Objectives - - Command and Control - mitre_attack: - - Exfiltration - - Command and Control - nist: - - DE.AE - - DE.CM - - PR.AC -modification_date: '2018-05-07' -name: Detect Spike in blocked Outbound Traffic from your AWS -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/splunk_enterprise_information_disclosure.yml b/detections/splunk_enterprise_information_disclosure.yml new file mode 100644 index 0000000000..20ec94b66d --- /dev/null +++ b/detections/splunk_enterprise_information_disclosure.yml @@ -0,0 +1,35 @@ +name: Splunk Enterprise Information Disclosure +id: f6a26b7b-7e80-4963-a9a8-d836e7534ebd +version: '1.0' +date: '2018-06-14' +description: This search allows you to look for evidence of exploitation for CVE-2018-11409, + a Splunk Enterprise Information Disclosure Bug. +how_to_implement: The REST endpoint that exposes system information is also necessary + for the proper operation of Splunk clustering and instrumentation. Whitelisting + your Splunk systems will reduce false positives. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: index=_internal sourcetype=splunkd_ui_access server-info | search clientip!=127.0.0.1 + uri_path="*raw/services/server/info/server-info" | rename clientip as src_ip, splunk_server + as dest | stats earliest(_time) as firstTime, latest(_time) as lastTime, values(uri) + as uri, values(useragent) as http_user_agent, values(user) as user by src_ip, dest + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +known_false_positives: Retrieving server information may be a legitimate API request. + Verify that the attempt is a valid request for information. +tags: + analytics_story: + - Splunk Enterprise Vulnerability CVE-2018-11409 + kill_chain_phases: + - Delivery + cis20: + - CIS 3 + - CIS 4 + - CIS 18 + nist: + - ID.RA + - RS.MI + - PR.PT + - PR.AC + - PR.IP + - DE.CM diff --git a/detections/splunk_information_disclosure.yml b/detections/splunk_information_disclosure.yml deleted file mode 100644 index c6e4ea2d3b..0000000000 --- a/detections/splunk_information_disclosure.yml +++ /dev/null @@ -1,96 +0,0 @@ -asset_type: Splunk Server -confidence: medium -creation_date: '2018-06-14' -data_metadata: - data_source: - - Splunk - data_sourcetypes: - - splunk_web_access - providing_technologies: - - Splunk Enterprise -description: This search allows you to look for evidence of exploitation for CVE-2018-11409, - a Splunk Enterprise Information Disclosure Bug. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, src_ip - rule_description: The Splunk Server $dest$ had a possible Splunk information-disclosure - possibility from $src_ip$ - rule_title: Possible Splunk Information Disclosure Exploitation Attempt from - $src_ip$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: index=_internal sourcetype=splunkd_ui_access server-info | search clientip!=127.0.0.1 - uri_path="*raw/services/server/info/server-info" | rename clientip as src_ip, - splunk_server as dest | stats earliest(_time) as firstTime, latest(_time) - as lastTime, values(uri) as uri, values(useragent) as http_user_agent, values(user) - as user by src_ip, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - suppress: - suppress_fields: dest, src_ip - suppress_period: 14400s -eli5: This search searches Splunk's internal logs for evidence of CVE-2018-11409 exploitation - attempts. -entities: - - dest -how_to_implement: The REST endpoint that exposes system information is also necessary - for the proper operation of Splunk clustering and instrumentation. Whitelisting - your Splunk systems will reduce false positives. -id: f6a26b7b-7e80-4963-a9a8-d836e7534ebd -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: 2f5b960b-71df-49c0-affc-74992ce60e45 - name: Investigate Web Activity From src_ip - type: splunk - - id: 9df9ca9c-a02b-4f48-9eba-0bac55179050 - name: Investigate Network Traffic From src_ip - type: splunk -known_false_positives: Retrieving server information may be a legitimate API request. - Verify that the attempt is a valid request for information. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 4 - - CIS 18 - kill_chain_phases: - - Delivery - mitre_attack: - - Defense Evasion - - Exploitation of Vulnerability - nist: - - ID.RA - - RS.MI - - PR.PT - - PR.AC - - PR.IP - - DE.CM -modification_date: '2018-06-14' -name: Splunk Enterprise Information Disclosure -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/sql_injection_with_long_urls.yml b/detections/sql_injection_with_long_urls.yml index d4dd4349f9..8c8a2a72f0 100644 --- a/detections/sql_injection_with_long_urls.yml +++ b/detections/sql_injection_with_long_urls.yml @@ -1,107 +1,47 @@ -asset_type: Database Server -confidence: medium -creation_date: '2016-09-13' -data_metadata: - data_models: - - Web - data_source: - - Network Communication - providing_technologies: - - Splunk Stream - - Bro +name: SQL Injection with Long URLs +id: e0aad4cf-0790-423b-8328-7564d0d938f9 +version: '1.0' +date: '2017-09-19' description: This search looks for long URLs that have several SQL commands visible within them. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, src, url - rule_description: Using the length of url or user agent to identify SQL injection - rule_title: SQL Injection with Long URLs - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 30 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Web where Web.dest_category=web_server - AND (Web.url_length > 1024 OR Web.http_user_agent_length > 200) by Web.src - Web.dest Web.url Web.url_length Web.http_user_agent | `drop_dm_object_name("Web")` - | eval num_sql_cmds=mvcount(split(url, "alter%20table")) + mvcount(split(url, - "between")) + mvcount(split(url, "create%20table")) + mvcount(split(url, "create%20database")) - + mvcount(split(url, "create%20index")) + mvcount(split(url, "create%20view")) - + mvcount(split(url, "delete")) + mvcount(split(url, "drop%20database")) + - mvcount(split(url, "drop%20index")) + mvcount(split(url, "drop%20table")) - + mvcount(split(url, "exists")) + mvcount(split(url, "exec")) + mvcount(split(url, - "group%20by")) + mvcount(split(url, "having")) + mvcount(split(url, "insert%20into")) - + mvcount(split(url, "inner%20join")) + mvcount(split(url, "left%20join")) - + mvcount(split(url, "right%20join")) + mvcount(split(url, "full%20join")) - + mvcount(split(url, "select")) + mvcount(split(url, "distinct")) + mvcount(split(url, - "select%20top")) + mvcount(split(url, "union")) + mvcount(split(url, "xp_cmdshell")) - - 24 | where num_sql_cmds > 3' - suppress: - suppress_fields: dest,src,url - suppress_period: 14400s -eli5: This search looks only at your web servers and returns the source, the web server, - the URL and its length, and the user agent associated with HTTP GET requests for - extremely long URLs or user agent lengths with more than three common SQL commands - found within the URL. -entities: - - dest how_to_implement: To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. -id: e0aad4cf-0790-423b-8328-7564d0d938f9 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count from datamodel=Web where + Web.dest_category=web_server AND (Web.url_length > 1024 OR Web.http_user_agent_length + > 200) by Web.src Web.dest Web.url Web.url_length Web.http_user_agent | `drop_dm_object_name("Web")` + | eval num_sql_cmds=mvcount(split(url, "alter%20table")) + mvcount(split(url, "between")) + + mvcount(split(url, "create%20table")) + mvcount(split(url, "create%20database")) + + mvcount(split(url, "create%20index")) + mvcount(split(url, "create%20view")) + + mvcount(split(url, "delete")) + mvcount(split(url, "drop%20database")) + mvcount(split(url, + "drop%20index")) + mvcount(split(url, "drop%20table")) + mvcount(split(url, "exists")) + + mvcount(split(url, "exec")) + mvcount(split(url, "group%20by")) + mvcount(split(url, + "having")) + mvcount(split(url, "insert%20into")) + mvcount(split(url, "inner%20join")) + + mvcount(split(url, "left%20join")) + mvcount(split(url, "right%20join")) + mvcount(split(url, + "full%20join")) + mvcount(split(url, "select")) + mvcount(split(url, "distinct")) + + mvcount(split(url, "select%20top")) + mvcount(split(url, "union")) + mvcount(split(url, + "xp_cmdshell")) - 24 | where num_sql_cmds > 3' known_false_positives: It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 4 - - CIS 13 - - CIS 18 +tags: + analytics_story: + - SQL Injection + mitre_attack_id: + - T1043 kill_chain_phases: - - Delivery - mitre_attack: - - Defense Evasion - - Exploitation of Vulnerability - - Execution - - Commonly Used Port + - Delivery + cis20: + - CIS 4 + - CIS 13 + - CIS 18 nist: - - PR.DS - - ID.RA - - PR.PT - - PR.IP - - DE.CM -modification_date: '2017-09-19' -name: SQL Injection with Long URLs -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' + - PR.DS + - ID.RA + - PR.PT + - PR.IP + - DE.CM diff --git a/detections/stop_security_services.yml b/detections/stop_security_services.yml deleted file mode 100644 index 2fa53a4352..0000000000 --- a/detections/stop_security_services.yml +++ /dev/null @@ -1,117 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-04-09' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for attempts to stop security-related services on the - endpoint. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, user - rule_description: Attempt to stop a security-related service on $dest$ - rule_title: Attempt to Stop Security Service On $dest$ - risk: - risk_object: src - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - (Processes.process_name = net.exe OR Processes.process_name = sc.exe) Processes.process="* - stop *" by Processes.process_name Processes.parent_process_name Processes.dest - Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - |lookup security_services_lookup service as process OUTPUTNEW category, description - | search category=security' - suppress: - suppress_fields: dest, user - suppress_period: 86400s -eli5: This search looks for the processes **net.exe** and **sc.exe** with a parameter - of `"stop"`. It then searches a list of security-related services included in a - lookup file for matches on the command line. Results are subsequently returned in - table format. The included lookup file can be modified to update the services to - monitor. -entities: - - src -how_to_implement: You must be ingesting data that records the file-system activity - from your hosts to populate the Endpoint file-system data-model node. If you are - using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which - you want to collect data. The search is shipped with a lookup file, `security_services.csv`, - that can be edited to update the list of services to monitor. This lookup file can - be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, - or via the Splunk console. You should add the names of services an attacker might - use on the command line and surround with asterisks (*****), so that they work properly - when searching the command line. The file should be updated with the names of any - services you would like to monitor for attempts to stop the service., -id: c8e349c6-b97c-486e-8949-bd7bcd1f3910 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None identified. Attempts to disable security-related services - should be identified and understood. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 8 - kill_chain_phases: - - Installation - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Disabling Security Tools - nist: - - PR.PT - - DE.CM - - PR.IP -modification_date: '2017-09-15' -name: Attempt To Stop Security Service -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/suspicious_changes_to_file_associations.yml b/detections/suspicious_changes_to_file_associations.yml new file mode 100644 index 0000000000..92ecf1328b --- /dev/null +++ b/detections/suspicious_changes_to_file_associations.yml @@ -0,0 +1,41 @@ +name: Suspicious Changes to File Associations +id: 1b989a0e-0129-4446-a695-f193a5b746fc +version: '3.0' +date: '2020-03-16' +description: This search looks for changes to registry values that control Windows + file associations, executed by a process that is not typical for legitimate, routine + changes to this area. +how_to_implement: To successfully implement this search you need to be ingesting information + on registry changes that include the name of the process responsible for the changes + from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` + nodes. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) + as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name!=Explorer.exe + AND Processes.process_name!=OpenWith.exe by Processes.process_id Processes.dest + | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | join [| tstats `security_content_summariesonly` values(Registry.registry_path) + as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* + by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table + process_id dest registry_path]| `change_file_association_filter`' +known_false_positives: There may be other processes in your environment that users + may legitimately use to modify file associations. If this is the case and you are + finding false positives, you can modify the search to add those processes as exceptions. +tags: + analytics_story: + - Windows File Extension and Association Abuse + - Suspicious Windows Registry Activities + mitre_attack_id: + - T1042 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 8 + nist: + - DE.CM + - PR.PT + - PR.IP diff --git a/detections/suspicious_email___uba_anomaly.yml b/detections/suspicious_email___uba_anomaly.yml new file mode 100644 index 0000000000..b5ceff52f0 --- /dev/null +++ b/detections/suspicious_email___uba_anomaly.yml @@ -0,0 +1,32 @@ +name: Suspicious Email - UBA Anomaly +id: 56e877a6-1455-4479-ad16-0550dc1e33f8 +version: '2.0' +date: '2019-07-21' +description: This detection looks for emails that are suspicious because of their + sender, domain rareness, or behavior differences. This is an anomaly generated by + Splunk User Behavior Analytics (UBA). +how_to_implement: You must be ingesting data from email logs and have Splunk integrated + with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." + Ensure that this model is enabled on your UBA instance. +type: ESCU +author: Bhavin Patel, Splunk +search: '|tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(All_UEBA_Events.category) as category from datamodel=UEBA where + nodename=All_UEBA_Events.UEBA_Anomalies All_UEBA_Events.UEBA_Anomalies.uba_model + = "SuspiciousEmailDetectionModel" by All_UEBA_Events.description All_UEBA_Events.severity + All_UEBA_Events.user All_UEBA_Events.uba_event_type All_UEBA_Events.link All_UEBA_Events.signature + All_UEBA_Events.url All_UEBA_Events.UEBA_Anomalies.uba_model | `drop_dm_object_name(All_UEBA_Events)` + | `drop_dm_object_name(UEBA_Anomalies)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' +known_false_positives: This detection model will alert on any sender domain that is + seen for the first time. This could be a potential false positive. The next step + is to investigate and whitelist the URL if you determine that it is a legitimate + sender. +tags: + analytics_story: + - Suspicious Emails + kill_chain_phases: + - Delivery + cis20: + - CIS 7 + nist: + - PR.IP diff --git a/detections/suspicious_email_attachment_extensions.yml b/detections/suspicious_email_attachment_extensions.yml new file mode 100644 index 0000000000..33213762cf --- /dev/null +++ b/detections/suspicious_email_attachment_extensions.yml @@ -0,0 +1,39 @@ +name: Suspicious Email Attachment Extensions +id: 473bd65f-06ca-4dfe-a2b8-ba04ab4a0084 +version: '2.0' +date: '2020-01-27' +description: This search looks for emails that have attachments with suspicious file + extensions. +how_to_implement: "You need to ingest data from emails. Specifically, the sender's\ + \ address and the file names of any attachments must be mapped to the Email data\ + \ model. \\\n **Splunk Phantom Playbook Integration**\\\nIf Splunk Phantom is also\ + \ configured in your environment, a Playbook called \"Suspicious Email Attachment\ + \ Investigate and Delete\" can be configured to run when any results are found by\ + \ this detection search. To use this integration, install the Phantom App for Splunk\ + \ `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the\ + \ \"Phantom Instance\" field in the Adaptive Response Actions when configuring this\ + \ detection search. The notable event will be sent to Phantom and the playbook will\ + \ gather further information about the file attachment and its network behaviors.\ + \ If Phantom finds malicious behavior and an analyst approves of the results, the\ + \ email will be deleted from the user's inbox." +type: ESCU +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, + All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | + `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | `suspicious_email_attachments` + | `suspicious_email_attachments_filter` ' +known_false_positives: None identified +tags: + analytics_story: + - Emotet Malware (DHS Report TA18-201A) + - Suspicious Emails + kill_chain_phases: + - Delivery + cis20: + - CIS 3 + - CIS 7 + - CIS 12 + nist: + - DE.AE + - PR.IP diff --git a/detections/suspicious_email_attachments.yml b/detections/suspicious_email_attachments.yml deleted file mode 100644 index 0841e15c51..0000000000 --- a/detections/suspicious_email_attachments.yml +++ /dev/null @@ -1,93 +0,0 @@ -asset_type: Endpoint -channel: ESCU -confidence: high -creation_date: '2017-04-20' -data_metadata: - data_models: - - Email - data_source: - - Email - providing_technologies: - - Microsoft Exchange -description: This search looks for emails that have attachments with suspicious file - extensions. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_user, file_name - rule_description: The sender $src_user$ has sent an email with a suspicious - file named $file_name$ - rule_title: Suspicious Email Attachment from $src_user$ - risk: - risk_object: src_user - risk_object_type: - - user - risk_score: 60 - macros: - - suspicious_email_attachments - - suspicious_email_attachments_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, - All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | `drop_dm_object_name("All_Email")` | `suspicious_email_attachments` | `suspicious_email_attachments_filter` ' - suppress: - suppress_fields: src_user,message_id - suppress_period: 86400s -eli5: This search looks at any email messages with attachments and checks the file - names of those attachments against an included lookup file to see if it has a suspicious - file extension. -entities: - - src_user - - message_id -how_to_implement: "You need to ingest data from emails. Specifically, the sender's\ - \ address and the file names of any attachments must be mapped to the Email data\ - \ model. \\\n **Splunk Phantom Playbook Integration**\\\nIf Splunk Phantom is also\ - \ configured in your environment, a Playbook called \"Suspicious Email Attachment\ - \ Investigate and Delete\" can be configured to run when any results are found by\ - \ this detection search. To use this integration, install the Phantom App for Splunk\ - \ `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the\ - \ \"Phantom Instance\" field in the Adaptive Response Actions when configuring this\ - \ detection search. The notable event will be sent to Phantom and the playbook will\ - \ gather further information about the file attachment and its network behaviors.\ - \ If Phantom finds malicious behavior and an analyst approves of the results, the\ - \ email will be deleted from the user's inbox." -id: 473bd65f-06ca-4dfe-a2b8-ba04ab4a0084 -investigations: - - id: 3096f721-8842-42ce-2fc7-742d8372b712 - name: Suspicious Email Attachment Investigate and Delete - type: phantom -known_false_positives: None identified -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 7 - - CIS 12 - kill_chain_phases: - - Delivery - mitre_attack: - - Execution - - Defense Evasion - mitre_technique_id: - - T1193 - nist: - - DE.AE - - PR.IP -modification_date: '2020-01-27' -name: Suspicious Email Attachment Extensions -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/suspicious_file_write.yml b/detections/suspicious_file_write.yml new file mode 100644 index 0000000000..23f6d303d0 --- /dev/null +++ b/detections/suspicious_file_write.yml @@ -0,0 +1,38 @@ +name: Suspicious File Write +id: 57f76b8a-32f0-42ed-b358-d9fa3ca7bac8 +version: '3.0' +date: '2019-04-25' +description: The search looks for files created with names that have been linked to + malicious activity. +how_to_implement: You must be ingesting data that records the filesystem activity + from your hosts to populate the Endpoint file-system data model node. This is typically + populated via endpoint detection-and-response products, such as Carbon Black, or + via other endpoint data sources, such as Sysmon. The data used for this search is + typically generated via logs that report file system reads and writes. In addition, + this search leverages an included lookup file that contains the names of the files + to watch for, as well as a note to communicate why that file name is being monitored. + This lookup file can be edited to add or remove file the file names you want to + monitor. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count values(Filesystem.action) + as action values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.dest + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Filesystem)` + | `suspicious_writes`' +known_false_positives: It's possible for a legitimate file to be created with the + same name as one noted in the lookup file. Filenames listed in the lookup file should + be unique enough that collisions are rare. Looking at the location of the file and + the process responsible for the activity can help determine whether or not the activity + is legitimate. +tags: + analytics_story: + - Hidden Cobra Malware + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/suspicious_file_writes.yml b/detections/suspicious_file_writes.yml deleted file mode 100644 index 9c5ac9bc35..0000000000 --- a/detections/suspicious_file_writes.yml +++ /dev/null @@ -1,113 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2018-06-14' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon -description: The search looks for files created with names that have been linked to - malicious activity. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name - rule_description: A write to a filename associated with malicious activity - detected on $dest$. - rule_title: Suspicious File Write Detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Filesystem.action) as action - values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) - as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.dest - | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Filesystem)` - | `suspicious_writes`' - suppress: - suppress_fields: dest,file_name - suppress_period: 14400s -eli5: This search looks at files being created or modified in the Endpoint file-system - data model. The names of those files are checked against an included lookup file, - which contains the names of files associated with malware or attack activity. The - search returns any files with matching names, along with a note (also specified - in the lookup file) that gives or points to more information about the files. -entities: - - dest -how_to_implement: You must be ingesting data that records the filesystem activity - from your hosts to populate the Endpoint file-system data model node. This is typically - populated via endpoint detection-and-response products, such as Carbon Black, or - via other endpoint data sources, such as Sysmon. The data used for this search is - typically generated via logs that report file system reads and writes. In addition, - this search leverages an included lookup file that contains the names of the files - to watch for, as well as a note to communicate why that file name is being monitored. - This lookup file can be edited to add or remove file the file names you want to - monitor. -id: 57f76b8a-32f0-42ed-b358-d9fa3ca7bac8 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It's possible for a legitimate file to be created with the - same name as one noted in the lookup file. Filenames listed in the lookup file should - be unique enough that collisions are rare. Looking at the location of the file and - the process responsible for the activity can help determine whether or not the activity - is legitimate. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: [] - nist: - - PR.PT - - DE.CM -modification_date: '2019-04-25' -name: Suspicious File Write -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/suspicious_java_classes.yml b/detections/suspicious_java_classes.yml index 08d5e59734..5c62d8bb70 100644 --- a/detections/suspicious_java_classes.yml +++ b/detections/suspicious_java_classes.yml @@ -1,102 +1,28 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-12-06' -data_metadata: - data_source: - - Web Traffic - data_sourcetypes: - - stream:http - providing_technologies: - - Splunk Stream - - Bro - - Bluecoat - - Apache +name: Suspicious Java Classes +id: if1fea6da-3c86-4c1d-b255-fc3b2781a491 +version: '1.0' +date: '2018-12-06' description: This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, url, http_user_agent - rule_description: The host $src$ with user agent $http_user_agent$ is sending - web traffic to $url$, which contains suspicious Java classes. These classes - may be indicative of remote code execution in Java frameworks, such as Apache - Struts. - rule_title: 'Suspicious Java Classes: Possible RCE against Struts or similar - Java framework from $src$' - risk: - risk_object: src - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype="stream:http" http_method=POST http_content_length>1 | regex - form_data="(?i)java\.lang\.(?:runtime|processbuilder)" | rename src_ip as - src | stats count earliest(_time) as firstTime, latest(_time) as lastTime, - values(url) as uri, values(status) as status, values(http_user_agent) as http_user_agent - by src, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - suppress: - suppress_fields: src, url, http_user_agent - suppress_period: 3600s -eli5: The search leverages HTTP form data from typically POST events that can be captured - with Splunk streams or similar wire data capture tools. The search looks for java - classes like `processbuilder` and `runtime` are used to create a new process and - execute commands inside java, and are synonymous with spawning a shell. There are - very exceptional reasons to ever these classes in Java via an HTTP API and hence - when seen are highly suspicious. Also, this is a common vectors leverage to exploit - Apache Struts. -entities: - - src how_to_implement: In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. -id: if1fea6da-3c86-4c1d-b255-fc3b2781a491 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: f5c39fac-205c-4e07-9004-8fd61ea3431a - name: Investigate Web POSTs From src - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd89 - name: Investigate Suspicious Strings in HTTP Header - type: splunk -known_false_positives: There are no known false positives. -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -mappings: - cis20: - - CIS 7 - - CIS 12 - kill_chain_phases: - - Exploitation - mitre_attack: - - Execution - nist: - - DE.AE -modification_date: '2018-12-06' -name: Suspicious Java Classes -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez +type: ESCU references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: '1.0' +author: Jose Hernandez, Splunk +search: sourcetype="stream:http" http_method=POST http_content_length>1 | regex form_data="(?i)java\.lang\.(?:runtime|processbuilder)" + | rename src_ip as src | stats count earliest(_time) as firstTime, latest(_time) + as lastTime, values(url) as uri, values(status) as status, values(http_user_agent) + as http_user_agent by src, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +known_false_positives: There are no known false positives. +tags: + analytics_story: + - Apache Struts Vulnerability + kill_chain_phases: + - Exploitation + cis20: + - CIS 7 + - CIS 12 + nist: + - DE.AE diff --git a/detections/suspicious_lnk_file_launching_a_process.yml b/detections/suspicious_lnk_file_launching_a_process.yml new file mode 100644 index 0000000000..413f44bee9 --- /dev/null +++ b/detections/suspicious_lnk_file_launching_a_process.yml @@ -0,0 +1,41 @@ +name: Suspicious LNK file launching a process +id: 5d814af1-1041-47b5-a9ac-d754e82e9a26 +version: '2.0' +date: '2020-03-16' +description: This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` + executing a process. This is common behavior used by various spear phishing tools. +how_to_implement: You must be ingesting data that records filesystem and process activity + from your hosts to populate the Endpoint data model. This is typically populated + via endpoint detection-and-response products, such as Carbon Black, or endpoint + data sources, such as Sysmon. +type: ESCU +author: Jose Hernandez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_name="*.lnk" + AND (Filesystem.file_path="C:\\Users*" OR Filesystem.file_path="*Local\\Temp*") by + _time span=1h Filesystem.process_id Filesystem.file_name Filesystem.file_path Filesystem.file_hash + Filesystem.user | `drop_dm_object_name(Filesystem)` | rename process_id as lnk_pid + | join lnk_pid, _time [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes + where Processes.process_name=* by _time span=1h Processes.parent_process_id Processes.process_id + Processes.process_name Processes.dest Processes.process_path Processes.process | + `drop_dm_object_name(Processes)` | rename parent_process_id as lnk_pid | fields + _time lnk_pid process_id dest process_name process_path process] | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | table firstTime, lastTime, lnk_pid, process_id, + user, dest, file_name, file_path, process_name, process, process_path, file_hash + | `lnk_executing_a_process_filter`' +known_false_positives: This detection should yield little or no false positive results. + It is uncommon for LNK files to execute process from temporary or user directories. +tags: + analytics_story: + - Phishing Payloads + mitre_attack_id: + - T1193 + kill_chain_phases: + - Installation + - Actions on Objectives + cis20: + - CIS 7 + - CIS 8 + nist: + - ID.AM + - PR.DS diff --git a/detections/suspicious_reg_exe_process.yml b/detections/suspicious_reg_exe_process.yml new file mode 100644 index 0000000000..3c745fd333 --- /dev/null +++ b/detections/suspicious_reg_exe_process.yml @@ -0,0 +1,43 @@ +name: Suspicious Reg.exe Process +id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 +version: '3.0' +date: '2020-03-16' +description: This search looks for reg.exe being launched from a command prompt not + started by the user. When a user launches cmd.exe, the parent process is usually + explorer.exe. This search filters out those instances. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: +- https://car.mitre.org/wiki/CAR-2013-03-001 +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name + != explorer.exe Processes.process_name =cmd.exe by Processes.user Processes.process_name + Processes.parent_process_name Processes.dest Processes.process_id Processes.parent_process_id + | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | search [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes + where Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe by Processes.parent_process_id + Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | rename parent_process_id as process_id |dedup + process_id| table process_id dest] | `suspicious_reg_process_filter`' +known_false_positives: It's possible for system administrators to write scripts that + exhibit this behavior. If this is the case, the search will need to be modified + to filter them out. +tags: + analytics_story: + - Disabling Security Tools + - DHS Report TA18-074A + - Windows Defense Evasion Tactics + mitre_attack_id: + - T1112 + - T1089 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/suspicious_reg_process.yml b/detections/suspicious_reg_process.yml deleted file mode 100644 index 3d511293b6..0000000000 --- a/detections/suspicious_reg_process.yml +++ /dev/null @@ -1,118 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-10-11' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for reg.exe being launched from a command prompt not - started by the user. When a user launches cmd.exe, the parent process is usually - explorer.exe. This search filters out those instances. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process_name - rule_description: The system $dest$ had reg.exe process run not initiated - by a user. - rule_title: Suspicious reg.exe process detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 80 - macros: - - suspicious_reg_process_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name - != explorer.exe Processes.process_name =cmd.exe by Processes.user Processes.process_name - Processes.parent_process_name Processes.dest Processes.process_id Processes.parent_process_id - | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | search [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes - where Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe - by Processes.parent_process_id Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename parent_process_id as process_id - |dedup process_id| table process_id dest] | `suspicious_reg_process_filter`' - suppress: - suppress_fields: dest, user - suppress_period: 14400s -eli5: This search looks for the execution of reg.exe with a parent process of cmd.exe. - It then executes a subsearch looking for those cmd.exe processes with a parent that - is not explorer.exe. It then joins those two searches to make sure that the reg.exe - process is a grandchild of the non explorer.exe process. The search will return - the number of such instances and the first and last time this activity has been - seen on each endpoint and user. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. -id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It's possible for system administrators to write scripts that - exhibit this behavior. If this is the case, the search will need to be modified - to filter them out. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Modify Registry - - Disabling Security Tools - nist: - - DE.CM -modification_date: '2020-03-16' -name: Suspicious Reg.exe Process -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: - - https://car.mitre.org/wiki/CAR-2013-03-001 -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/suspicious_wevtutil_usage.yml b/detections/suspicious_wevtutil_usage.yml index 79f7644979..a574dbacc6 100644 --- a/detections/suspicious_wevtutil_usage.yml +++ b/detections/suspicious_wevtutil_usage.yml @@ -1,120 +1,42 @@ -asset_type: '' -confidence: medium -creation_date: '2017-02-17' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Suspicious wevtutil Usage +id: 2827c0fd-e1be-4868-ae25-59d28e0f9d4f +version: '2.0' +date: '2019-02-28' description: The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. -detect: - splunk: - correlation_rule: - notable: - drilldown_name: View wevtutil process information on $dest$ - drilldown_search: '| from datamodel:Endpoint.Processes | search dest="$dest$" process=*wevtutil*' - nes_fields: dest, process, user - rule_description: wevtutil is the windows event log tool. This searches for - wevtutil clearing the security or system logs. - rule_title: Suspicious wevtutil Usage - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name = wevtutil.exe Processes.process="*cl*" (Processes.process="*System*" - OR Processes.process="*Security*" OR Processes.process="*Setup*" OR Processes.process="*Application*") - by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest,process - suppress_period: 28800s -eli5: This search looks for execution of wevtutil.exe with command-line arguments - that indicate that it has been used to delete the setup, application, security, - or system event logs. The search returns the number of times the behavior was observed, - the first and last time it was seen, the host exhibiting the behavior and the user - context of the process execution. -entities: - - dest how_to_implement: You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -id: 2827c0fd-e1be-4868-ae25-59d28e0f9d4f -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` values(Processes.process) as process + min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes + where Processes.process_name = wevtutil.exe Processes.process="*cl*" (Processes.process="*System*" + OR Processes.process="*Security*" OR Processes.process="*Setup*" OR Processes.process="*Application*") + by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`' known_false_positives: The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 6 +tags: + analytics_story: + - Ransomware + - Windows Log Manipulation + mitre_attack_id: + - T1070 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Indicator Removal on Host + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 6 nist: - - DE.DP - - PR.IP - - PR.PT - - PR.AC - - PR.AT - - DE.AE -modification_date: '2019-02-28' -name: Suspicious wevtutil Usage -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' + - DE.DP + - PR.IP + - PR.PT + - PR.AC + - PR.AT + - DE.AE diff --git a/detections/suspicious_write_to_recycler.yml b/detections/suspicious_write_to_recycler.yml deleted file mode 100644 index ccc9ea126a..0000000000 --- a/detections/suspicious_write_to_recycler.yml +++ /dev/null @@ -1,107 +0,0 @@ -asset_type: Windows -confidence: medium -creation_date: '2018-01-08' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Sysmon -description: This search detects writes to the recycle bin by a process other than - explorer.exe. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name, process_name - rule_description: The process $process_name$ on $dest$ wrote $file_name$ to - the Recycle Bin. - rule_title: Suspicious process $process_name$ wrote to the Recycle Bin on - $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(Filesystem.file_path) as file_path values(Filesystem.file_name) - as file_name FROM datamodel=Endpoint.Filesystem where Filesystem.file_path - = "*$Recycle.Bin*" by Filesystem.process_id Filesystem.dest | `drop_dm_object_name("Filesystem")`| - search [| tstats `security_content_summariesonly` values(Processes.user) as user values(Processes.process_name) - as process_name values(Processes.parent_process_name) as parent_process_name - FROM datamodel=Endpoint.Processes where Processes.process_name != "explorer.exe" - by Processes.process_id Processes.dest| `drop_dm_object_name("Processes")` - | table process_id dest]' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: This search uses data on file writes captured via Sysmon to watch for writes - to the Recycle Bin by processes other than explorer.exe. The search looks for event - code 11 in the Sysmon events, which indicates a file-creation event. Next, it looks - for files created with a path that includes the string "$Recycle.Bin" by processes - other than explorer.exe, which is the process responsible for copying files to the - Recycle Bin on delete. It will report the system where the activity occurred, the - path to which the file was written, the process responsible for the write, and the - times it first and last saw this activity. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting information - on filesystem and process logs responsible for the changes from your endpoints into - the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. -id: b5541828-8ffd-4070-9d95-b3da4de924cb -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Because the Recycle Bin is a hidden folder in modern versions - of Windows, it would be unusual for a process other than explorer.exe to write to - it. Incidents should be investigated as appropriate. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - mitre_attack: - - Collection - - Data Staged - nist: - - DE.CM -modification_date: '2020-02-03' -name: Suspicious writes to windows Recycle Bin -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/suspicious_write_to_sysvol.yml b/detections/suspicious_write_to_sysvol.yml deleted file mode 100644 index 4f7c3cca3f..0000000000 --- a/detections/suspicious_write_to_sysvol.yml +++ /dev/null @@ -1,103 +0,0 @@ -asset_type: Windows -confidence: medium -creation_date: '2018-01-08' -data_metadata: - data_source: - - Endpoint Intel - data_sourcetypes: - - XmlWinEventLog:Microsoft-Windows-Sysmon/Operational - providing_technologies: - - Sysmon -description: This search detects writes to the 'System Volume Information' folder - by something other than the System process. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, file_name, process - rule_description: The process $process$ on $dest$ wrote $file_name$ to 'System - Volume Information'. - rule_title: Suspicious process $process$ wrote to 'System Volume Information' - on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: (sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational OR tag=process) - EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats - count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: This search uses data on file writes captured via Sysmon to watch for writes - to the "System Volume Information" folder by processes other than the system process. - The search looks for event code 11 in the Sysmon events, which indicates a file-creation - event. It then looks for a file created with a path that includes "System Volume - Information" and a process ID (PID) other than 4. PID 4 is assigned to the System - process on Windows systems. Excluding these writes allows us to filter out legitimate - activity. It will report the system where the activity occurred, the path to which - the file was written, the process responsible for the write, and the times it first - and last saw this activity. -entities: - - dest -how_to_implement: You need to be ingesting logs with both the process name and command-line - from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 - of the Sysmon TA. -id: cd6297cd-2bdd-4aa1-84aa-5d2f84228fac -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: It is possible that other utilities or system processes may - legitimately write to this folder. Investigate and modify the search to include - exceptions as appropriate. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - mitre_attack: - - Collection - - Data Staged - nist: - - DE.CM -modification_date: '2018-01-08' -name: Suspicious writes to System Volume Information -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/suspicious_writes_to_system_volume_information.yml b/detections/suspicious_writes_to_system_volume_information.yml new file mode 100644 index 0000000000..de3d750cb0 --- /dev/null +++ b/detections/suspicious_writes_to_system_volume_information.yml @@ -0,0 +1,28 @@ +name: Suspicious writes to System Volume Information +id: cd6297cd-2bdd-4aa1-84aa-5d2f84228fac +version: '1.0' +date: '2018-01-08' +description: This search detects writes to the 'System Volume Information' folder + by something other than the System process. +how_to_implement: You need to be ingesting logs with both the process name and command-line + from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 + of the Sysmon TA. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: (sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational OR tag=process) + EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats count + min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)` +known_false_positives: It is possible that other utilities or system processes may + legitimately write to this folder. Investigate and modify the search to include + exceptions as appropriate. +tags: + analytics_story: + - Collection and Staging + mitre_attack_id: + - T1074 + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/suspicious_writes_to_windows_recycle_bin.yml b/detections/suspicious_writes_to_windows_recycle_bin.yml new file mode 100644 index 0000000000..901200f1cc --- /dev/null +++ b/detections/suspicious_writes_to_windows_recycle_bin.yml @@ -0,0 +1,33 @@ +name: Suspicious writes to windows Recycle Bin +id: b5541828-8ffd-4070-9d95-b3da4de924cb +version: '3.0' +date: '2020-02-03' +description: This search detects writes to the recycle bin by a process other than + explorer.exe. +how_to_implement: To successfully implement this search you need to be ingesting information + on filesystem and process logs responsible for the changes from your endpoints into + the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime values(Filesystem.file_path) as file_path values(Filesystem.file_name) + as file_name FROM datamodel=Endpoint.Filesystem where Filesystem.file_path = "*$Recycle.Bin*" + by Filesystem.process_id Filesystem.dest | `drop_dm_object_name("Filesystem")`| + search [| tstats `security_content_summariesonly` values(Processes.user) as user + values(Processes.process_name) as process_name values(Processes.parent_process_name) + as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name + != "explorer.exe" by Processes.process_id Processes.dest| `drop_dm_object_name("Processes")` + | table process_id dest]' +known_false_positives: Because the Recycle Bin is a hidden folder in modern versions + of Windows, it would be unusual for a process other than explorer.exe to write to + it. Incidents should be investigated as appropriate. +tags: + analytics_story: + - Collection and Staging + mitre_attack_id: + - T1074 + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index 9cf09a64e1..afe453b685 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -1,111 +1,34 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2016-08-24' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: System Processes Run From Unexpected Locations +id: a34aae96-ccf8-4aef-952c-3ea21444444d +version: '5.0' +date: '2020-02-04' description: This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user, process_name, dest - rule_description: The system $dest$ has a process that normally runs out of - Windows\System32\ that is not being run from that location. - rule_title: System Processes Run From Unexpected Location on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - is_windows_system_file - lookups: - - is_windows_system_file - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Endpoint.Processes where Processes.process_path !="C:\\Windows\\System32*" - Processes.process_path !="C:\\Windows\\SysWOW64*" by Processes.user Processes.dest - Processes.process_name Processes.process_id Processes.process_path Processes.parent_process_name Processes.process_hash| `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `is_windows_system_file`' - suppress: - suppress_fields: dest,process_name - suppress_period: 86400s -eli5: This search returns all the processes that are not executing out of the C:\Windows\System32 - or C:\Windows\SysWOW64 directories. Next, it takes the filename and looks it up - in a table `is_windows_system_file` of files that should normally run out of the C:\Windows\System32 or C:\Windows\SysWOW64 - directory. Any matches are then returned. -entities: - - dest how_to_implement: To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. -id: a34aae96-ccf8-4aef-952c-3ea21444444d -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Masquerading - nist: - - PR.PT - - DE.CM -modification_date: '2020-02-04' -name: System Processes Run From Unexpected Locations -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '5.0' +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Processes where Processes.process_path !="C:\\Windows\\System32*" + Processes.process_path !="C:\\Windows\\SysWOW64*" by Processes.user Processes.dest + Processes.process_name Processes.process_id Processes.process_path Processes.parent_process_name + Processes.process_hash| `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)`| `is_windows_system_file`' +known_false_positives: None identified +tags: + analytics_story: + - Ransomware + - Unusual Processes + - Suspicious Command-Line Executions + mitre_attack_id: + - T1036 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/tor_traffic.yml b/detections/tor_traffic.yml index 48501ff2eb..724473cce9 100644 --- a/detections/tor_traffic.yml +++ b/detections/tor_traffic.yml @@ -1,101 +1,34 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2017-08-21' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Palo Alto Firewall - - Bro - - Splunk Stream +name: TOR Traffic +id: ea688274-9c06-4473-b951-e4cb7a5d7a45 +version: '1.0' +date: '2017-09-11' description: This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, dest_ip - rule_description: Network traffic accessing TOR detected from $src_ip$ - rule_title: TOR Network Traffic Allowed from $src_ip$ - risk: - risk_object: src_ip - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Network_Traffic where All_Traffic.app=tor AND All_Traffic.action=allowed - by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' - suppress: - suppress_fields: src_ip - suppress_period: 28800s -eli5: The search leverages the Enterprise Security Network_Traffic data model to look - for network traffic that has been identified as TOR and marked as 'allowed'. -entities: - - src_ip how_to_implement: In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -id: ea688274-9c06-4473-b951-e4cb7a5d7a45 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: None at this time -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 9 - - CIS 12 - kill_chain_phases: - - Command and Control - mitre_attack: - - Command and Control - - Commonly Used Port - - Exfiltration - nist: - - DE.AE -modification_date: '2017-09-11' -name: TOR Traffic -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +type: ESCU references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Traffic where All_Traffic.app=tor AND All_Traffic.action=allowed + by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' +known_false_positives: None at this time +tags: + analytics_story: + - Ransomware + - Command and Control + - Prohibited Traffic Allowed or Protocol Mismatch + mitre_attack_id: + - T1043 + kill_chain_phases: + - Command and Control + cis20: + - CIS 9 + - CIS 12 + nist: + - DE.AE diff --git a/detections/uba_email_anomaly.yml b/detections/uba_email_anomaly.yml deleted file mode 100644 index 387ed39649..0000000000 --- a/detections/uba_email_anomaly.yml +++ /dev/null @@ -1,84 +0,0 @@ -asset_type: Endpoint -channel: ESCU -confidence: medium -creation_date: '2019-07-21' -data_metadata: - data_models: - - UEBA - data_source: - - Email - providing_technologies: - - Microsoft Exchange -description: This detection looks for emails that are suspicious because of their - sender, domain rareness, or behavior differences. This is an anomaly generated by - Splunk User Behavior Analytics (UBA). -detect: - uba: - correlation_rule: - notable: - nes_fields: user, url - rule_description: Newly observed email domain $url$ sent an email to $user$. - rule_title: Suspicious Email Anomaly - risk: - risk_object: user - risk_object_type: - - user - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '|tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime values(All_UEBA_Events.category) as category from datamodel=UEBA - where nodename=All_UEBA_Events.UEBA_Anomalies All_UEBA_Events.UEBA_Anomalies.uba_model - = "SuspiciousEmailDetectionModel" by All_UEBA_Events.description All_UEBA_Events.severity - All_UEBA_Events.user All_UEBA_Events.uba_event_type All_UEBA_Events.link All_UEBA_Events.signature - All_UEBA_Events.url All_UEBA_Events.UEBA_Anomalies.uba_model | `drop_dm_object_name(All_UEBA_Events)` - | `drop_dm_object_name(UEBA_Anomalies)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' - suppress: - suppress_fields: user - suppress_period: 86400s - event_type: anomaly - model: SuspiciousEmailDetectionModel - model_version: 0.0.1 - threat_category: Email -eli5: This detection monitors for emails that are suspicious because of their sender, - domain rareness, or behavior differences, as determined by Splunk UBA. In this search, - we query the "UEBA" data model to look for anomalies that are raised by the "SuspiciousEmailDetectionModel" - and will output the count, description of the anomaly, signature, the type of event - in UBA, the severity, and the user who received a potentially suspicious email from - a newly seen domain. It will also output all the categories associated with that - anomaly. -entities: - - user - - url -how_to_implement: You must be ingesting data from email logs and have Splunk integrated - with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." - Ensure that this model is enabled on your UBA instance. -id: 56e877a6-1455-4479-ad16-0550dc1e33f8 -known_false_positives: This detection model will alert on any sender domain that is - seen for the first time. This could be a potential false positive. The next step - is to investigate and whitelist the URL if you determine that it is a legitimate - sender. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 7 - kill_chain_phases: - - Delivery - mitre_attack: [] - nist: - - PR.IP -modification_date: '2019-07-21' -name: Suspicious Email - UBA Anomaly -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -security_domain: threat -spec_version: 2 -type: uba -version: '2.0' diff --git a/detections/unauthorized_assets_via_mac_address.yml b/detections/unauthorized_assets_via_mac_address.yml deleted file mode 100644 index 257d0e2049..0000000000 --- a/detections/unauthorized_assets_via_mac_address.yml +++ /dev/null @@ -1,100 +0,0 @@ -asset_type: Infrastructure -baselines: - - id: dcfd6b40-42f9-469d-a433-2e53f7489ff9 - name: Count of assets by category - type: splunk -confidence: medium -creation_date: '2017-06-11' -data_metadata: - data_models: - - Network_Sessions - data_source: - - Network Communication - providing_technologies: - - Splunk Stream - - Bro -description: By populating the organization's assets within the assets_by_str.csv, - we will be able to detect unauthorized devices that are trying to connect with the - organization's network by inspecting DHCP request packets, which are issued by devices - when they attempt to obtain an IP address from the DHCP server. The MAC address - associated with the source of the DHCP request is checked against the list of known - devices, and reports on those that are not found. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src, query - rule_description: The host $src$ issued a DHCP request to connect with your - network that does not belong to the list of authorized devices - rule_title: 'Unauthorized Asset found with mac address: $src_mac$' - risk: - risk_object: src - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Sessions where - nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST by All_Sessions.src_ip - All_Sessions.src_mac | dedup All_Sessions.src_mac| `drop_dm_object_name("Network_Sessions")`|`drop_dm_object_name("All_Sessions")` - | search NOT [| inputlookup asset_lookup_by_str |rename mac as src_mac | fields - + src_mac]' - suppress: - suppress_fields: src_mac,src_ip - suppress_period: 86400s -eli5: 'This search requires you to leverage the Enterprise Security Assets and Identity - framework to populate assets_by_str.csv. Once the assets_by_str.csv is populated, - we then query your DHCP logs to detect unknown systems connecting to your network. - More documentation is available at: http://docs.splunk.com/Documentation/ES/4.7.1/Admin/Verifyassetandidentitydata.' -entities: - - src -how_to_implement: This search uses the Network_Sessions data model shipped with Enterprise - Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv - file located in SA-IdentityManagement, which will contain a list of known authorized - organizational assets including their MAC addresses. Ensure that all inventoried - systems have their MAC address populated. -id: dcfd6b40-42f9-469d-a433-2e53f7489ff4 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd33 - name: Get First Occurrence and Last Occurrence of a MAC Address - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk -known_false_positives: This search might be prone to high false positives. Please - consider this when conducting analysis or investigations. Authorized devices may - be detected as unauthorized. If this is the case, verify the MAC address of the - system responsible for the false positive and add it to the Assets and Identity - framework with the proper information. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 1 - kill_chain_phases: - - Reconnaissance - - Delivery - - Actions on Objectives - mitre_attack: - - Defense Evasion - nist: - - ID.AM - - PR.DS -modification_date: '2017-09-13' -name: Detect Unauthorized Assets by MAC address -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/unauthorized_dns_servers.yml b/detections/unauthorized_dns_servers.yml deleted file mode 100644 index d5607a928c..0000000000 --- a/detections/unauthorized_dns_servers.yml +++ /dev/null @@ -1,89 +0,0 @@ -asset_type: Endpoint -baselines: [] -confidence: medium -creation_date: '2017-07-08' -data_metadata: - data_models: - - Network_Resolution - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: This search will detect DNS requests resolved by unauthorized DNS servers. - Legitimate DNS servers should be identified in the Enterprise Security Assets and - Identity Framework. -detect: - splunk: - correlation_rule: - macros: - - unauthorized_dns_servers_filter - notable: - nes_fields: dest, src - rule_description: The table represents a list of unauthorized DNS servers - interacting with hosts in your network - rule_title: DNS requests resolved by unauthorized DNS servers - risk: - risk_object: src - risk_object_type: - - system - risk_score: 40 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution where - DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src - DNS.dest | `drop_dm_object_name("DNS")` | `unauthorized_dns_servers_filter`' - suppress: - suppress_fields: dest,src - suppress_period: 28800s -eli5: Clients should be resolving their DNS requests via a trusted DNS server. This - search will identify DNS queries being sent to unauthorized DNS servers by comparing - the destination and source of the traffic with assets marked as DNS servers. -entities: - - dest - - src -how_to_implement: To successfully implement this search you will need to ensure that - DNS data is populating the Network_Resolution data model. It also requires that - your DNS servers are identified correctly in the Assets and Identity table of Enterprise - Security. -id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f6 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 - name: Get DNS Server History for a host - type: splunk -known_false_positives: Legitimate DNS activity can be detected in this search. Investigate, - verify and update the list of authorized DNS servers as appropriate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 1 - - CIS 3 - - CIS 8 - - CIS 12 - kill_chain_phases: - - Command and Control - mitre_attack: - - Exfiltration - - Defense Evasion - nist: - - ID.AM - - PR.DS - - PR.IP - - DE.AE - - DE.CM -modification_date: '2020-01-17' -name: DNS Query Requests Resolved by Unauthorized DNS Servers -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -responses: [] -security_domain: network -spec_version: 2 -type: splunk -version: '2.0' diff --git a/detections/uncommon_processes.yml b/detections/uncommon_processes.yml deleted file mode 100644 index 5b3232f774..0000000000 --- a/detections/uncommon_processes.yml +++ /dev/null @@ -1,112 +0,0 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-12-08' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search looks for applications on the endpoint that you have marked - as uncommon. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process_name, user - rule_description: Prohibited software $process_name$ has been detected on - $dest$ - rule_title: Prohibited Software Detected On $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - uncommon_processes_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user - Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_filter`' - suppress: - suppress_fields: dest, user - suppress_period: 86400s -eli5: This search returns the number of times, as well as the first and last time, - it has seen every process run for each endpoint and user, and then displays only - those processes that you have marked as uncommon in the `uncommon_processes_default.csv` - table. -entities: - - dest -how_to_implement: You must be ingesting data that records process activity from your - hosts to populate the Endpoint data model in the Processes node. You must also be - ingesting logs with both the process name and command line from your endpoints. - The command-line arguments are mapped to the "process" field in the Endpoint data - model. This search uses a lookup file `uncommon_processes_default.csv` to track - various features of process names that are usually uncommon in most environments. - Please consider updating `uncommon_processes_local.csv` to hunt for processes that - are uncommon in your environment. -id: 29ccce64-a10c-4389-a45f-337cb29ba1f7 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: None identified -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 2 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Accessibility Features - nist: - - ID.AM - - PR.DS -modification_date: '2020-03-16' -name: Uncommon Processes On Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/uncommon_processes_on_endpoint.yml b/detections/uncommon_processes_on_endpoint.yml new file mode 100644 index 0000000000..14725aa441 --- /dev/null +++ b/detections/uncommon_processes_on_endpoint.yml @@ -0,0 +1,35 @@ +name: Uncommon Processes On Endpoint +id: 29ccce64-a10c-4389-a45f-337cb29ba1f7 +version: '3.0' +date: '2020-03-16' +description: This search looks for applications on the endpoint that you have marked + as uncommon. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. This search uses a lookup file `uncommon_processes_default.csv` to track + various features of process names that are usually uncommon in most environments. + Please consider updating `uncommon_processes_local.csv` to hunt for processes that + are uncommon in your environment. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process + Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_filter`' +known_false_positives: None identified +tags: + analytics_story: + - Windows Privilege Escalation + - Unusual Processes + mitre_attack_id: + - T1015 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 2 + nist: + - ID.AM + - PR.DS diff --git a/detections/unload_sysmon_filter_driver.yml b/detections/unload_sysmon_filter_driver.yml index 9030137c47..947efd3943 100644 --- a/detections/unload_sysmon_filter_driver.yml +++ b/detections/unload_sysmon_filter_driver.yml @@ -1,103 +1,35 @@ -asset_type: '' -confidence: medium -creation_date: '2017-10-23' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. - rule_title: 'Unload Sysmon Filter Driver on $dest$ ' - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - unload_sysmon_filter_driver_filter - - schedule: - cron_schedule: 30 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) - as process max(_time) as lastTime from datamodel=Endpoint.Processes where - Processes.process_name=fltMC.exe AND Processes.process=*unload* AND Processes.process=*SysmonDrv* by - Processes.process_name Processes.process_id Processes.parent_process_name Processes.process Processes.dest Processes.user | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` |`unload_sysmon_filter_driver_filter`| table firstTime lastTime dest user count process_name process_id parent_process_name process' - suppress: - suppress_fields: dest, process - suppress_period: 86400s -eli5: This search is looking to detect execution of `fltMC.exe` that specifically used for unloading the Sysmon Filter Driver -entities: - - dest +name: Unload Sysmon Filter Driver +id: c77162d3-f93c-45cc-80c8-22f665664g9f +version: '2.0' +date: '2020-01-13' +description: Attackers often disable security tools to avoid detection. This search + looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop + sysmon from collecting the data. how_to_implement: You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data - model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. -id: c77162d3-f93c-45cc-80c8-22f665664g9f -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: '' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Disabling Security Tools - mitre_technique_id: - - T1089 - nist: - - DE.CM -modification_date: '2020-01-13' -name: Unload Sysmon Filter Driver -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel + model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, + update this macro to filter out false positives. +type: ESCU references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '2.0' +author: Bhavin Patel, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) + as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fltMC.exe + AND Processes.process=*unload* AND Processes.process=*SysmonDrv* by Processes.process_name + Processes.process_id Processes.parent_process_name Processes.process Processes.dest + Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + |`unload_sysmon_filter_driver_filter`| table firstTime lastTime dest user count + process_name process_id parent_process_name process' +known_false_positives: '' +tags: + analytics_story: + - Disabling Security Tools + mitre_attack_id: + - T1089 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - DE.CM diff --git a/detections/unsigned_image_loaded_by_LSASS.yml b/detections/unsigned_image_loaded_by_LSASS.yml index 4d6561618e..282f189dc9 100644 --- a/detections/unsigned_image_loaded_by_LSASS.yml +++ b/detections/unsigned_image_loaded_by_LSASS.yml @@ -1,89 +1,33 @@ -asset_type: Windows -confidence: medium -creation_date: '2019-12-06' -data_metadata: - data_eventtypes: - - wineventlog_sysmon - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search detects loading of unsigned images by LSASS. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: Possible attempt at credential dumping was detected on $dest$. - rule_title: unsigned images loaded by LSASS on $dest$. - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - sysmon - - unsigned_image_loaded_by_LSASS_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '`sysmon` EventID=7 Image=*lsass.exe Signed=false - | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 - | rename Computer as dest - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `unsigned_image_loaded_by_LSASS_filter`' - suppress: - suppress_fields: dest, ImageLoaded - suppress_period: 86400s -eli5: This search detects unsigned images loaded by LSASS (Local Security Authrity Subsystem Service). - Normally, LSASS only loads signed images. Therefore, it is a malicious indicator when unsigned images are loaded by LSASS. - This can be an indicator for credential dumping using tools like Windows Credential Editor. -entities: - - dest -how_to_implement: 'This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives.' +name: Unsigned Image Loaded by LSASS id: 56ef054c-76ef-45f9-af4a-a634695dcd65 -investigations: - - id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad - name: Investigate Previous Unseen User - type: splunk - - id: 097e8030-8662-4254-a735-bf0bdda696e3 - name: Investigate Failed Logins for Multiple Destinations - type: splunk - - id: ed3fff45-cba6-4990-983f-6fac72bee659 - name: Investigate Pass the Hash Attempts - type: splunk - - id: 990007ad-d798-4b29-ab2f-f0034144c937 - name: Investigate Pass the Ticket Attempts - type: splunk +version: '1' +date: '2019-12-06' +description: This search detects loading of unsigned images by LSASS. +how_to_implement: This search needs Sysmon Logs with a sysmon configuration, which + includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. + We strongly recommend that you specify your environment-specific configurations + (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition + with configurations for your Splunk environment. The search also uses a post-filter + macro designed to filter out known false positives. +type: ESCU +references: +- https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf +author: Patrick Bareiss, Splunk +search: '`sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) + as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 + | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `unsigned_image_loaded_by_LSASS_filter`' known_false_positives: Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -mappings: - cis20: - - CIS 8 - - CIS 16 +tags: + analytics_story: + - Credential Dumping + mitre_attack_id: + - T1003 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Credential Access - - Credential Dumping - mitre_technique_id: - - T1003 + - Actions on Objectives + cis20: + - CIS 8 + - CIS 16 nist: - - DE.CM -modification_date: '2019-12-06' -name: Unsigned Image Loaded by LSASS -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -references: - - https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf -security_domain: endpoint -spec_version: 2 -type: splunk -version: "1" + - DE.CM diff --git a/detections/unsuccessful_netbackup_backups.yml b/detections/unsuccessful_netbackup_backups.yml new file mode 100644 index 0000000000..a4bb87d0aa --- /dev/null +++ b/detections/unsuccessful_netbackup_backups.yml @@ -0,0 +1,24 @@ +name: Unsuccessful Netbackup backups +id: a34aae96-ccf8-4aaa-952c-3ea21444444f +version: '1.0' +date: '2017-09-12' +description: This search gives you the hosts where a backup was attempted and then + failed. +how_to_implement: To successfully implement this search you need to obtain data from + your backup solution, either from the backup logs on your endpoints or from a central + server responsible for performing the backups. If you do not use Netbackup, you + can modify this search for your specific backup solution. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: sourcetype="netbackup_logs" | stats latest(_time) as latestTime by COMPUTERNAME, + MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` + | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature +known_false_positives: None identified +tags: + analytics_story: + - Monitor Backup Solution + cis20: + - CIS 10 + nist: + - PR.IP diff --git a/detections/unusually_long_command_line.yml b/detections/unusually_long_command_line.yml new file mode 100644 index 0000000000..a080766ae9 --- /dev/null +++ b/detections/unusually_long_command_line.yml @@ -0,0 +1,35 @@ +name: Unusually Long Command Line +id: c77162d3-f93c-45cc-80c8-22f6a4264e7f +version: '4.0' +date: '2020-03-16' +description: Command lines that are extremely long may be indicative of malicious + activity on your hosts. +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships, from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name + Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) + as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) + as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| + `unusually_long_commandlines_filter`| eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + + avgperhost)' +known_false_positives: Some legitimate applications start with long command lines. +tags: + analytics_story: + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Ransomware + - Unusual Processes + - Suspicious Command-Line Executions + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml new file mode 100644 index 0000000000..7c3788f126 --- /dev/null +++ b/detections/unusually_long_command_line___mltk.yml @@ -0,0 +1,48 @@ +name: Unusually Long Command Line - MLTK +id: 57edaefa-a73b-45e5-bbae-f39c1473f941 +version: '1.0' +date: '2019-05-08' +description: Command lines that are extremely long may be indicative of malicious + activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) + to help identify command lines with lengths that are unusual for a given user. +how_to_implement: You must be ingesting endpoint data that monitors command lines + and populates the Endpoint data model in the Processes node. The command-line arguments + are mapped to the "process" field in the Endpoint data model. In addition, MLTK + version >= 4.2 must be installed on your search heads, along with any required dependencies. + Finally, the support search "Baseline of Command Line Length - MLTK" must be executed + before this detection search, as it builds an ML model over the historical data + used by this search. It is important that this search is run in the same app context + as the associated support search, so that the model created by the support search + is available for use. You should periodically re-run the support search to rebuild + the model with the latest data available in your environment. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name + Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| + `security_content_ctime(lastTime)`| eval processlen=len(process) | search user!=unknown + | apply cmdline_pdfmodel threshold=0.01 | rename "IsOutlier(processlen)" as isOutlier + | search isOutlier > 0 | table firstTime lastTime user dest process_name process + processlen count' +known_false_positives: Some legitimate applications use long command lines for installs + or updates. You should review identified command lines for legitimacy. You may modify + the first part of the search to omit legitimate command lines from consideration. + If you are seeing more results than desired, you may consider changing the value + of threshold in the search to a smaller value. You should also periodically re-run + the support search to re-build the ML model on the latest data. You may get unexpected + results if the user identified in the results is not present in the data used to + build the associated model. +tags: + analytics_story: + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Ransomware + - Unusual Processes + - Suspicious Command-Line Executions + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 8 + nist: + - PR.PT + - DE.CM diff --git a/detections/unusually_long_commandlines.yml b/detections/unusually_long_commandlines.yml deleted file mode 100644 index cbebca5e07..0000000000 --- a/detections/unusually_long_commandlines.yml +++ /dev/null @@ -1,112 +0,0 @@ -asset_type: '' -confidence: medium -creation_date: '2017-08-23' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: Command lines that are extremely long may be indicative of malicious - activity on your hosts. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, user - rule_description: An unusually long command line $cmdline$ was found on $dest$ - rule_title: Unusually Long Command Line on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - macros: - - unusually_long_commandlines_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -1d@d - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest - Processes.process_name Processes.process | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats - stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) - as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, - user, process_name, process| `unusually_long_commandlines_filter`| eval threshold = 10 | where maxlen > ((threshold*stdevperhost) - + avgperhost)' - suppress: - suppress_fields: dest,user,process - suppress_period: 28800s -eli5: This search calculates the average and standard deviation for the length of - the command lines on each of your endpoints and alerts when it detects a command - line with a length over 10 times the standard deviation larger than the average - command line. -entities: - - dest - - process_name - - user -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships, from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: c77162d3-f93c-45cc-80c8-22f6a4264e7f -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Some legitimate applications start with long command lines. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - PR.PT - - DE.CM -modification_date: '2020-03-16' -name: Unusually Long Command Line -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '4.0' diff --git a/detections/unusually_long_commandlines_mltk.yml b/detections/unusually_long_commandlines_mltk.yml deleted file mode 100644 index bd665287b7..0000000000 --- a/detections/unusually_long_commandlines_mltk.yml +++ /dev/null @@ -1,123 +0,0 @@ -asset_type: '' -baselines: - - id: d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459 - name: Baseline of Command Line Length - MLTK - type: splunk -confidence: medium -creation_date: '2019-05-08' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: Command lines that are extremely long may be indicative of malicious - activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) - to help identify command lines with lengths that are unusual for a given user. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, process, user - rule_description: An unusually long command line $cmdline$ was found on $dest$ - rule_title: Unusually Long Command Line on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 50 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | search user!=unknown | apply cmdline_pdfmodel threshold=0.01 | rename "IsOutlier(processlen)" as isOutlier | search isOutlier > 0 | table firstTime lastTime user dest process_name process processlen count' - suppress: - suppress_fields: dest,user,process_name - suppress_period: 28800s -eli5: This search leverages the Machine Learning Toolkit (MLTK) to identify outliers - in the length of the command lines observed to be used by a specific user. The companion - search, "Baseline of Command Line Length - MLTK," creates a machine-learning (ML) - model built over the historical data used by this search. The determination of what - is considered an outlier may be adjusted via the threshold parameter in the search. - More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -entities: - - dest - - process_name - - user -how_to_implement: You must be ingesting endpoint data that monitors command lines - and populates the Endpoint data model in the Processes node. The command-line arguments - are mapped to the "process" field in the Endpoint data model. In addition, MLTK - version >= 4.2 must be installed on your search heads, along with any required dependencies. - Finally, the support search "Baseline of Command Line Length - MLTK" must be executed - before this detection search, as it builds an ML model over the historical data - used by this search. It is important that this search is run in the same app context - as the associated support search, so that the model created by the support search - is available for use. You should periodically re-run the support search to rebuild - the model with the latest data available in your environment. -id: 57edaefa-a73b-45e5-bbae-f39c1473f941 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 - name: Investigate Web Activity From Host - type: splunk -known_false_positives: Some legitimate applications use long command lines for installs - or updates. You should review identified command lines for legitimacy. You may modify - the first part of the search to omit legitimate command lines from consideration. - If you are seeing more results than desired, you may consider changing the value - of threshold in the search to a smaller value. You should also periodically re-run - the support search to re-build the ML model on the latest data. You may get unexpected - results if the user identified in the results is not present in the data used to - build the associated model. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 8 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - nist: - - PR.PT - - DE.CM -modification_date: '2019-05-08' -name: Unusually Long Command Line - MLTK -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/unusually_long_content-type_length.yml b/detections/unusually_long_content-type_length.yml deleted file mode 100644 index cc4acc246e..0000000000 --- a/detections/unusually_long_content-type_length.yml +++ /dev/null @@ -1,98 +0,0 @@ -asset_type: Web Server -confidence: high -creation_date: '2017-03-14' -data_metadata: - data_source: - - Web Server - data_sourcetypes: - - stream:http - providing_technologies: - - Splunk Stream -description: This search looks for unusually long strings in the Content-Type http - header that the client sends the server. -detect: - splunk: - correlation_rule: - notable: - nes_fields: src_ip, dest_ip, url - rule_description: This search looks for unusually long strings in the Content-Type - http header - rule_title: Unusually Long Content-Type Length - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 75 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype=stream:http | eval cs_content_type_length = len(cs_content_type) - | where cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length - cs_content_type url - suppress: - suppress_fields: dest_ip - suppress_period: 28800s -eli5: This detection search uses HTTP traffic data captured with Splunk Stream. The - search is constructed to use "stream:http" sourcetype and counts of the number of - times an HTTP request is received by a destination which the length of the Content-Type - header value the client sends the server is greater than 100 characters long. We - calculate this content_type_length field and output the results. -entities: - - dest -how_to_implement: This particular search leverages data extracted from Stream:HTTP. - You must configure the http stream using the Splunk Stream App on your Splunk Stream - deployment server to extract the cs_content_type field. -id: 57a0a2bf-353f-40c1-84dc-29293f3c35b7 -investigations: - - id: f5c39fac-205c-4e07-9004-8fd61ea3431a - name: Investigate Web POSTs From src - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd89 - name: Investigate Suspicious Strings in HTTP Header - type: splunk -known_false_positives: Very few legitimate Content-Type fields will have a length - greater than 100 characters. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 3 - - CIS 4 - - CIS 18 - - CIS 12 - kill_chain_phases: - - Delivery - mitre_attack: - - Defense Evasion - - Exploitation of Vulnerability - nist: - - ID.RA - - RS.MI - - PR.PT - - PR.IP - - DE.AE - - PR.MA - - DE.CM -modification_date: '2017-10-13' -name: Unusually Long Content-Type Length -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/unusually_long_content_type_length.yml b/detections/unusually_long_content_type_length.yml new file mode 100644 index 0000000000..277fb1ce1a --- /dev/null +++ b/detections/unusually_long_content_type_length.yml @@ -0,0 +1,35 @@ +name: Unusually Long Content-Type Length +id: 57a0a2bf-353f-40c1-84dc-29293f3c35b7 +version: '1.0' +date: '2017-10-13' +description: This search looks for unusually long strings in the Content-Type http + header that the client sends the server. +how_to_implement: This particular search leverages data extracted from Stream:HTTP. + You must configure the http stream using the Splunk Stream App on your Splunk Stream + deployment server to extract the cs_content_type field. +type: ESCU +references: [] +author: Bhavin Patel, Splunk +search: sourcetype=stream:http | eval cs_content_type_length = len(cs_content_type) + | where cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length + cs_content_type url +known_false_positives: Very few legitimate Content-Type fields will have a length + greater than 100 characters. +tags: + analytics_story: + - Apache Struts Vulnerability + kill_chain_phases: + - Delivery + cis20: + - CIS 3 + - CIS 4 + - CIS 18 + - CIS 12 + nist: + - ID.RA + - RS.MI + - PR.PT + - PR.IP + - DE.AE + - PR.MA + - DE.CM diff --git a/detections/usb_insertion.yml b/detections/usb_insertion.yml deleted file mode 100644 index 23886ea679..0000000000 --- a/detections/usb_insertion.yml +++ /dev/null @@ -1,106 +0,0 @@ -asset_type: Endpoint -confidence: low -creation_date: '2017-08-03' -data_metadata: - data_models: - - Change_Analysis - data_source: - - Windows Security Audit logs - providing_technologies: - - Microsoft Windows -description: The search is used to detect hosts that generate Windows Event ID 4663 - for successful attempts to write to or read from a removable storage and Event ID - 4656 for failures, which occurs when a USB drive is plugged in. In this scenario - we are querying the Change_Analysis data model to look for Windows Event ID 4656 - or 4663 where the priority of the affected host is marked as high in the ES Assets - and Identity Framework. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: Read/Write attempt to a USB was detected on this host - rule_title: Read/Write attempt to a USB detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 20 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count earliest(_time) AS earliest latest(_time) - AS latest from datamodel=Change_Analysis where (nodename = All_Changes) All_Changes.result="Removable - Storage device" (All_Changes.result_id=4663 OR All_Changes.result_id=4656) - (All_Changes.src_priority=high) by All_Changes.dest | `drop_dm_object_name("All_Changes")`| - `security_content_ctime(earliest)`| `security_content_ctime(latest)` ' - suppress: - suppress_fields: dest - suppress_period: 86400s -eli5: USB is a common attack vector for delivering or propagating malicious code, - or the exfiltration of data. Your corporation may have a policy of not allowing - removable media at all, or may only allow approved media to be used on specific - hosts by specific users. By logging USB activity from Windows and other endpoints - gathered using the Universal Forwarder, you can gain an understanding of what systems - might be vulnerable to attack via removable media, or what users might need additional - security training. This search is looking for event_id 4656 for failure and 4663 - for successful USB read/write attempts from Windows Security Event logs, which is - the event code generated when a files are read from and written to a removable storage - device -entities: - - dest -how_to_implement: To successfully implement this search, you must ingest Windows Security - Event logs and track event code 4663 and 4656. Ensure that the field from the event - logs is being mapped to the result_id field in the Change_Analysis data model. To - minimize the alert volume, this search leverages the Assets and Identity framework - to filter out events from those assets not marked high priority in the Enterprise - Security Assets and Identity Framework. -id: 104658f4-afdc-499f-9719-17a43f9826f5 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Legitimate USB activity will also be detected. Please verify - and investigate as appropriate. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 13 - kill_chain_phases: - - Installation - - Actions on Objectives - mitre_attack: - - Exfiltration - nist: - - PR.PT - - PR.DS -modification_date: '2017-11-27' -name: Detect USB device insertion -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/users_without_mfa.yml b/detections/users_without_mfa.yml deleted file mode 100644 index f7f12d6842..0000000000 --- a/detections/users_without_mfa.yml +++ /dev/null @@ -1,111 +0,0 @@ -asset_type: AWS Instance -confidence: medium -creation_date: '2018-05-17' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search looks for CloudTrail events where a user logged into the - AWS account, is making API calls and has not enabled Multi Factor authentication. - Multi factor authentication adds a layer of security by forcing the users to type - a unique authentication code from an approved authentication device when they access - AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged - IAM users. -detect: - splunk: - correlation_rule: - notable: - nes_fields: user - rule_description: API Activity detected from $user$ without MFA enabled. - rule_title: API Activity detected from $user$ without MFA enabled - risk: - risk_object: user - risk_object_type: - - user - risk_score: 30 - schedule: - cron_schedule: 0 8 * * * - earliest_time: -1d@d - latest_time: -10m@m - search: sourcetype=aws:cloudtrail userIdentity.sessionContext.attributes.mfaAuthenticated=false - | search NOT [| inputlookup aws_service_accounts | fields identity | rename - identity as user]| stats count min(_time) as firstTime max(_time) as lastTime - values(eventName) as eventName by userIdentity.arn userIdentity.type user - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - suppress: - suppress_fields: user - suppress_period: 84600s -eli5: ' In this search, we query CloudTrail logs and specifically look for events - where the multi factor authentication context of the user''s session is false which - basically means, that the user does not have MFA enabled on AWS. We then filter - out all the known AWS service accounts since service accounts typically do not have - MFA enabled. The search then creates a table of the first and last time a user without - MFA was detected, the values and count of the API calls made, the type of user identity, - ARN and the name of the user.' -entities: - - user -how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. Leverage the support search `Create a list of approved AWS service accounts`: - run it once every 30 days to create a list of service accounts and validate them.\ - - This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) - that are not yet supported by ES Incident Review and therefore cannot be viewed - when a notable event is raised. These fields contribute additional context to the - notable. To see the additional metadata, add the following fields, if not already - present, to Incident Review - Event Attributes (Configure > Incident Management - > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** - eventName\ - - 1. \ - - 1. **Label:** AWS User ARN, **Field:** userIdentity.arn\ - - 1. \ - - 1. **Label:** AWS User Type, **Field:** userIdentity.type\ - - Detailed documentation on how to create a new field within Incident Review may be - found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details`' -id: 2a9b80d3-6340-4345-w5ad-212bf5d1dac4 -investigations: - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 - name: Investigate AWS User Activities by user field - type: splunk -known_false_positives: Many service accounts configured within an AWS infrastructure - do not have multi factor authentication enabled. Please ignore the service accounts, - if triggered and instead add them to the aws_service_accounts.csv file to fine tune - the detection. It is also possible that the search detects users in your environment - using Single Sign-On systems, since the MFA is not handled by AWS. -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -mappings: - cis20: - - CIS 16 - mitre_attack: - - Execution - nist: - - DE.DP - - PR.AC -modification_date: '2018-05-17' -name: Detect API activity from users without MFA -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: [] -security_domain: network -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/usn_journal_deletion.yml b/detections/usn_journal_deletion.yml new file mode 100644 index 0000000000..dcb45a6c81 --- /dev/null +++ b/detections/usn_journal_deletion.yml @@ -0,0 +1,41 @@ +name: USN Journal Deletion +id: b6e0ff70-b122-4227-9368-4cf322ab43c3 +version: '2.0' +date: '2018-12-03' +description: The fsutil.exe application is a legitimate Windows utility used to perform + tasks related to the file allocation table (FAT) and NTFS file systems. The update + sequence number (USN) change journal provides a log of all changes made to the files + on the disk. This search looks for fsutil.exe deleting the USN journal. +how_to_implement: You must be ingesting data that records process activity from your + hosts to populate the Endpoint data model in the Processes node. You must also be + ingesting logs with both the process name and command line from your endpoints. + The command-line arguments are mapped to the "process" field in the Endpoint data + model. +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count values(Processes.process) + as process values(Processes.parent_process) as parent_process min(_time) as firstTime + max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fsutil.exe + by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | search process="*deletejournal*" AND process="*usn*"' +known_false_positives: None identified +tags: + analytics_story: + - Ransomware + - Windows Log Manipulation + mitre_attack_id: + - T1070 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 6 + - CIS 8 + - CIS 10 + nist: + - DE.CM + - PR.PT + - DE.AE + - DE.DP + - PR.IP diff --git a/detections/web_fraud___account_harvesting.yml b/detections/web_fraud___account_harvesting.yml new file mode 100644 index 0000000000..f8b3e7c7a3 --- /dev/null +++ b/detections/web_fraud___account_harvesting.yml @@ -0,0 +1,47 @@ +name: Web Fraud - Account Harvesting +id: 31337aaa-941d-4ada-81ac-q2a17be5bf0d +version: '1.0' +date: '2018-10-08' +description: This search is used to identify the creation of multiple user accounts + using the same email domain name. +how_to_implement: We start with a dataset that provides visibility into the email + address used for the account creation. In this example, we are narrowing our search + down to the single web page that hosts the Magento2 e-commerce platform (via URI) + used for account creation, the single http content-type to grab only the user's + clicks, and the http field that provides the username (form_data), for performance + reasons. After we have the username and email domain, we look for numerous account + creations per email domain. Common data sources used for this detection are customized + Apache logs or Splunk Stream. +type: ESCU +references: +- https://splunkbase.splunk.com/app/2734/ +- https://splunkbase.splunk.com/app/1809/ +author: Jim Apger, Splunk +search: sourcetype=stream:http http_content_type=text* uri="/magento2/customer/account/loginPost/" + | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" + | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) + as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> + 25 +known_false_positives: As is common with many fraud-related searches, we are usually + looking to attribute risk or synthesize relevant context with loosely written detections + that simply detect anamolous behavior. This search will need to be customized to + fit your environment—improving its fidelity by counting based on something + much more specific, such as a device ID that may be present in your dataset. Consideration + for whether the large number of registrations are occuring from a first-time seen + domain may also be important. Extending the search window to look further back + in time, or even calculating the average per hour/day for each email domain to look + for an anomalous spikes, will improve this search. You can also use Shannon entropy + or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness + or similarity of the email name or email domain, as the names are often machine-generated. +tags: + analytics_story: + - Web Fraud Detection + mitre_attack_id: + - T1136 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 16 + nist: + - DE.CM + - DE.DP diff --git a/detections/web_fraud___anomalous_user_clickspeed.yml b/detections/web_fraud___anomalous_user_clickspeed.yml new file mode 100644 index 0000000000..2273a0e28b --- /dev/null +++ b/detections/web_fraud___anomalous_user_clickspeed.yml @@ -0,0 +1,42 @@ +name: Web Fraud - Anomalous User Clickspeed +id: 31337bbb-bc22-4752-b599-ef192df2dc7a +version: '1.0' +date: '2018-10-08' +description: This search is used to examine web sessions to identify those where the + clicks are occurring too quickly for a human or are occurring with a near-perfect + cadence (high periodicity or low standard deviation), resembling a script driven + session. +how_to_implement: Start with a dataset that allows you to see clickstream data for + each user click on the website. That data must have a time stamp and must contain + a reference to the session identifier being used by the website. This ties the clicks + together into clickstreams. This value is usually found in the http cookie. With + a bit of tuning, a version of this search could be used in high-volume scenarios, + such as scraping, crawling, application DDOS, credit-card testing, account takeover, + etc. Common data sources used for this detection are customized Apache logs, customized + IIS, and Splunk Stream. +type: ESCU +references: +- https://en.wikipedia.org/wiki/Session_ID +- https://en.wikipedia.org/wiki/Session_(computer_science) +- https://en.wikipedia.org/wiki/HTTP_cookie +- https://splunkbase.splunk.com/app/1809/ +author: Jim Apger, Splunk +search: sourcetype=stream:http http_content_type=text* | rex field=cookie "form_key=(?\w+)" + | streamstats window=2 current=1 range(_time) as TimeDelta by session_id | where + TimeDelta>0 |stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) as + ClickSpeedAvg by session_id | where count>5 AND (ClickSpeedStdDev<.5 OR ClickSpeedAvg<.5) +known_false_positives: As is common with many fraud-related searches, we are usually + looking to attribute risk or synthesize relevant context with loosly written detections + that simply detect anamoluous behavior. +tags: + analytics_story: + - Web Fraud Detection + mitre_attack_id: + - T1078 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 6 + nist: + - DE.AE + - DE.CM diff --git a/detections/web_fraud___password_sharing_across_accounts.yml b/detections/web_fraud___password_sharing_across_accounts.yml new file mode 100644 index 0000000000..85139358ff --- /dev/null +++ b/detections/web_fraud___password_sharing_across_accounts.yml @@ -0,0 +1,32 @@ +name: Web Fraud - Password Sharing Across Accounts +id: 31337a1a-53b9-4e05-96e9-55c934cb71d3 +version: '1.0' +date: '2018-10-08' +description: This search is used to identify user accounts that share a common password. +how_to_implement: We need to start with a dataset that allows us to see the values + of usernames and passwords that users are submitting to the website hosting the + Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized + or hashed value of a password is acceptable and certainly preferable to a clear-text + password. Common data sources used for this detection are customized Apache logs, + customized IIS, and Splunk Stream. +type: ESCU +references: +- https://en.wikipedia.org/wiki/Session_ID +- https://en.wikipedia.org/wiki/Session_(computer_science) +- https://en.wikipedia.org/wiki/HTTP_cookie +- https://splunkbase.splunk.com/app/1809/ +author: Jim Apger, Splunk +search: sourcetype=stream:http http_content_type=text* uri=/magento2/customer/account/loginPost* | + rex field=form_data "login\[username\]=(?[^&|^$]+)" | rex field=form_data + "login\[password\]=(?[^&|^$]+)" | stats dc(Username) as UniqueUsernames + values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5 +known_false_positives: As is common with many fraud-related searches, we are usually + looking to attribute risk or synthesize relevant context with loosely written detections + that simply detect anamoluous behavior. +tags: + analytics_story: + - Web Fraud Detection + cis20: + - CIS 16 + nist: + - DE.DP diff --git a/detections/web_servers_executing_suspicious_processes.yml b/detections/web_servers_executing_suspicious_processes.yml index a07602837a..a0c4be6264 100644 --- a/detections/web_servers_executing_suspicious_processes.yml +++ b/detections/web_servers_executing_suspicious_processes.yml @@ -1,108 +1,34 @@ -asset_type: Web Server -confidence: medium -creation_date: '2017-03-14' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften +name: Web Servers Executing Suspicious Processes +id: ec3b7601-689a-4463-94e0-c9f45638efb9 +version: '1.0' +date: '2019-04-01' description: This search looks for suspicious processes on all systems labeled as web servers. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for suspicious processes on all systems - labeled as web servers - rule_title: Web Servers Executing Suspicious Processes - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 75 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Endpoint.Processes where Processes.dest_category="web_server" - AND (Processes.process="*whoami*" OR Processes.process="*ping*" OR Processes.process="*iptables*" - OR Processes.process="*wget*" OR Processes.process="*service*" OR Processes.process="*curl*") - by Processes.process Processes.process_name, Processes.dest Processes.user| - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' - suppress: - suppress_fields: dest, process - suppress_period: 28800s -eli5: This detection search uses the Enterprise Security Endpoint data model. The - search uses tstats to search within an accelerated data model to find suspicious - applications or processes such as whoami, ping, iptables, wget, service, or curl, - running on hosts which are marked as web servers in the Assets and Identity Framework - of ES. -entities: - - dest how_to_implement: You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. -id: ec3b7601-689a-4463-94e0-c9f45638efb9 -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd89 - name: Investigate Suspicious Strings in HTTP Header - type: splunk +type: ESCU +references: [] +author: David Dorsey, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Endpoint.Processes where Processes.dest_category="web_server" + AND (Processes.process="*whoami*" OR Processes.process="*ping*" OR Processes.process="*iptables*" + OR Processes.process="*wget*" OR Processes.process="*service*" OR Processes.process="*curl*") + by Processes.process Processes.process_name, Processes.dest Processes.user| `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' known_false_positives: Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -mappings: - cis20: - - CIS 3 +tags: + analytics_story: + - Apache Struts Vulnerability + mitre_attack_id: + - T1082 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Exploitation of Vulnerability - - Execution - - Discovery - - System Information Discovery + - Actions on Objectives + cis20: + - CIS 3 nist: - - PR.IP -modification_date: '2019-04-01' -name: Web Servers Executing Suspicious Processes -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' + - PR.IP diff --git a/detections/windows_event_log_cleared.yml b/detections/windows_event_log_cleared.yml index a36d4cb362..f3b3769543 100644 --- a/detections/windows_event_log_cleared.yml +++ b/detections/windows_event_log_cleared.yml @@ -1,108 +1,35 @@ -asset_type: Endpoint -confidence: high -creation_date: '2017-02-17' -data_metadata: - data_eventtypes: - - wineventlog_security - - wineventlog_system - data_source: - - Microsoft Windows - providing_technologies: - - Microsoft Windows +name: Windows Event Log Cleared +id: ad517544-aff9-4c96-bd99-d6eb43bfbb6a +version: '3.0' +date: '2019-02-27' description: This search looks for Windows events that indicate one of the Windows event logs has been purged. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: The Event Logging System has been cleared or shutdown on - $dest$ - rule_title: Windows Event Log Cleared on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 60 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: ((eventtype=wineventlog_security) AND (signature_id=1102 OR signature_id=1100)) - OR ((eventtype=wineventlog_system) AND signature_id=104) | stats count min(_time) - as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` - suppress: - suppress_fields: dest, signature_id - suppress_period: 28800s -eli5: This search looks at the Windows security and system event logs. EventCode 1002 - in the security log indicates that the log has been cleared, EventCode 1000 in the - security log indicates the event logging service has been shut down, and EventCode - 104 in the system log indicates the application log has been cleared. If any of - these events are found, a notable will be generated. -entities: - - dest how_to_implement: To successfully implement this search, you need to be ingesting Windows event logs from your hosts. -id: ad517544-aff9-4c96-bd99-d6eb43bfbb6a -investigations: - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 - name: Get Vulnerability Logs For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk - - id: fecf2918-670d-4f1c-872b-3d7317a41bf9 - name: Get Parent Process Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: ((eventtype=wineventlog_security) AND (signature_id=1102 OR signature_id=1100)) + OR ((eventtype=wineventlog_system) AND signature_id=104) | stats count min(_time) + as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` known_false_positives: It is possible that these logs may be legitimately cleared by Administrators. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - - CIS 6 +tags: + analytics_story: + - Ransomware + - Windows Log Manipulation + mitre_attack_id: + - T1070 kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Defense Evasion - - Indicator Removal on Host + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + - CIS 6 nist: - - DE.DP - - PR.IP - - PR.AC - - PR.AT - - DE.AE -modification_date: '2019-02-27' -name: Windows Event Log Cleared -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' + - DE.DP + - PR.IP + - PR.AC + - PR.AT + - DE.AE diff --git a/detections/windows_hosts_file_modification.yml b/detections/windows_hosts_file_modification.yml new file mode 100644 index 0000000000..25f9da5816 --- /dev/null +++ b/detections/windows_hosts_file_modification.yml @@ -0,0 +1,37 @@ +name: Windows hosts file modification +id: 06a6fc63-a72d-41dc-8736-7e3dd9612116 +version: '1.0' +date: '2018-11-02' +description: The search looks for modifications to the hosts file on all Windows endpoints + across your environment. +how_to_implement: To successfully implement this search, you must be ingesting data + that records the file-system activity from your hosts to populate the Endpoint.Filesystem + data model node. This is typically populated via endpoint detection-and-response + products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. + The data used for this search is typically generated via logs that report file-system + reads and writes. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.file_path + Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + | search Filesystem.file_name=hosts AND Filesystem.file_path=*Windows\\System32\\* + | `drop_dm_object_name(Filesystem)`' +known_false_positives: There may be legitimate reasons for system administrators to + add entries to this file. +tags: + analytics_story: + - Host Redirection + kill_chain_phases: + - Command and Control + cis20: + - CIS 3 + - CIS 8 + - CIS 12 + nist: + - PR.IP + - PR.PT + - PR.AC + - DE.AE + - DE.CM diff --git a/detections/wmi_perm_event_subscription.yml b/detections/wmi_perm_event_subscription.yml deleted file mode 100644 index 2538d0e370..0000000000 --- a/detections/wmi_perm_event_subscription.yml +++ /dev/null @@ -1,105 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-10-23' -data_metadata: - data_source: - - Microsoft Windows - data_sourcetypes: - - WinEventLog://Microsoft-Windows-WMI-Activity/Operational - providing_technologies: - - Microsoft Windows -description: This search looks for the creation of WMI permanent event subscriptions. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest - rule_description: This search looks for the creation of a permanent WMI event - subscription via Windows event logs. - rule_title: WMI Event Subscription Detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" - EventCode=5861 Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" - | search consumer!="NTEventLogEventConsumer=\"SCM Event Log Consumer\"" | - stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, - consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | rename ComputerName - as dest - suppress: - suppress_fields: dest - suppress_period: 28800s -eli5: Attackers are increasingly abusing Windows Management Infrastructure (WMI) for - stealth, persistence, lateral movement, or just to leverage its functionality. This - search looks for the creation of a WMI event subscription by watching for Windows - event ID 5861. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting the - Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on - the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -id: 71bfdb13-f200-4c6c-b2c9-a2e07adf437d -investigations: - - id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 - name: Get Sysmon WMI Activity for Host - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Although unlikely, administrators may use event subscriptions - for legitimate purposes. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Windows Management Instrumentation - - Persistence - - Windows Management Instrumentation Event Subscription - nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2018-10-23' -name: WMI Permanent Event Subscription -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/wmi_perm_event_subscription_sysmon.yml b/detections/wmi_perm_event_subscription_sysmon.yml deleted file mode 100644 index 91c8543eb0..0000000000 --- a/detections/wmi_perm_event_subscription_sysmon.yml +++ /dev/null @@ -1,103 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-10-23' -data_metadata: - data_source: - - Microsoft Windows - data_sourcetypes: - - WinEventLog://Microsoft-Windows-WMI-Activity/Operational - providing_technologies: - - Microsoft Windows -description: This search looks for the creation of WMI permanent event subscriptions. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user - rule_description: This search looks for the creation of a permanent WMI event - subscription via Sysmon logs. - rule_title: WMI Event Subscription Detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode=21 - | rename host as dest | table _time, dest, user, Operation, EventType, Query, - Consumer, Filter - suppress: - suppress_fields: dest,user - suppress_period: 28800s -eli5: Attackers are increasingly abusing Windows Management Infrastructure (WMI) for - stealth, persistence, lateral movement, or just to leverage its functionality. This - search looks for the creation of a WMI event subscription by watching for Sysmon - event ID 21. -entities: - - dest -how_to_implement: To successfully implement this search, you must be collecting Sysmon - data using Sysmon version 6.1 or greater and have Sysmon configured to generate - alerts for WMI activity. In addition, you must have at least version 6.0.4 of the - Sysmon TA installed to properly parse the fields. -id: ad05aae6-3b2a-4f73-af97-57bd26cee3b9 -investigations: - - id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 - name: Get Sysmon WMI Activity for Host - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Although unlikely, administrators may use event subscriptions - for legitimate purposes. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Windows Management Instrumentation - - Persistence - - Windows Management Instrumentation Event Subscription - nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2018-10-23' -name: WMI Permanent Event Subscription - Sysmon -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/wmi_permanent_event_subscription.yml b/detections/wmi_permanent_event_subscription.yml new file mode 100644 index 0000000000..fb1e8904a9 --- /dev/null +++ b/detections/wmi_permanent_event_subscription.yml @@ -0,0 +1,34 @@ +name: WMI Permanent Event Subscription +id: 71bfdb13-f200-4c6c-b2c9-a2e07adf437d +version: '1.0' +date: '2018-10-23' +description: This search looks for the creation of WMI permanent event subscriptions. +how_to_implement: To successfully implement this search, you must be ingesting the + Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on + the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" EventCode=5861 + Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" | search consumer!="NTEventLogEventConsumer=\"SCM + Event Log Consumer\"" | stats count min(_time) as firstTime max(_time) as lastTime + by ComputerName, consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | rename ComputerName as dest +known_false_positives: Although unlikely, administrators may use event subscriptions + for legitimate purposes. +tags: + analytics_story: + - Suspicious WMI Use + mitre_attack_id: + - T1047 + - T1084 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + nist: + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/detections/wmi_permanent_event_subscription___sysmon.yml b/detections/wmi_permanent_event_subscription___sysmon.yml new file mode 100644 index 0000000000..0ae4c2027b --- /dev/null +++ b/detections/wmi_permanent_event_subscription___sysmon.yml @@ -0,0 +1,33 @@ +name: WMI Permanent Event Subscription - Sysmon +id: ad05aae6-3b2a-4f73-af97-57bd26cee3b9 +version: '1.0' +date: '2018-10-23' +description: This search looks for the creation of WMI permanent event subscriptions. +how_to_implement: To successfully implement this search, you must be collecting Sysmon + data using Sysmon version 6.1 or greater and have Sysmon configured to generate + alerts for WMI activity. In addition, you must have at least version 6.0.4 of the + Sysmon TA installed to properly parse the fields. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode=21 + | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, + Filter +known_false_positives: Although unlikely, administrators may use event subscriptions + for legitimate purposes. +tags: + analytics_story: + - Suspicious WMI Use + mitre_attack_id: + - T1047 + - T1084 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + nist: + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/detections/wmi_process_launch.yml b/detections/wmi_process_launch.yml deleted file mode 100644 index 91f82dea31..0000000000 --- a/detections/wmi_process_launch.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-10-23' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - Sysmon - - Tanium - - Ziften -description: This search looks for processes launched via WMI. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for child processes of WmiPrvSE.exe, which - indicates that a process was launched via WMI. - rule_title: Process launched via WMI on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - macros: - - wmi_process_launch_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes - where Processes.parent_process_name = *WmiPrvSE.exe by Processes.user Processes.dest - Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)`| `wmi_process_launch_filter`' - suppress: - suppress_fields: dest, user - suppress_period: 28800s -eli5: Attackers are increasingly abusing Windows Management Infrastructure (WMI) for - stealth, persistence, lateral movement, or just to leverage its functionality. This - search looks for processes launched via WMI, either remotely or locally, by looking - for processes launched by WmiPrvSE.exe, which is the process WMI uses to execute - new processes and commands. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: 24869767-8579-485d-9a4f-d9ddfd8f0cac -investigations: - - id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 - name: Get Sysmon WMI Activity for Host - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Although unlikely, administrators may use wmi to execute commands - for legitimate purposes. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Windows Management Instrumentation - nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2020-03-16' -name: Process Execution via WMI -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/wmi_script_execution.yml b/detections/wmi_script_execution.yml deleted file mode 100644 index 6af5245b33..0000000000 --- a/detections/wmi_script_execution.yml +++ /dev/null @@ -1,109 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-10-23' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - Sysmon - - Tanium - - Ziften -description: This search looks for scripts launched via WMI. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for scrcons.exe, which indicates that - a script was launched via WMI. - rule_title: Script execution via WMI on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - macros: - - wmi_script_execution_filter - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: '| tstats `security_content_summariesonly` count values(Processes.process) as process - min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes - where Processes.process_name = "scrcons.exe" by Processes.user Processes.dest - Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)`| `wmi_script_execution_filter`' - suppress: - suppress_fields: dest,process - suppress_period: 28800s -eli5: Attackers are increasingly abusing Windows Management Infrastructure for stealth, - persistence, lateral movement, or just to leverage its functionality. This search - looks for scripts launched via WMI, either remotely or locally, by looking for the - execution of scrcons.exe, which is the scripting host used by WMI, similar to wscript - or cscript. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: aa73f80d-d728-4077-b226-81ea0c8be589 -investigations: - - id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 - name: Get Sysmon WMI Activity for Host - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Although unlikely, administrators may use wmi to launch scripts - for legitimate purposes. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Windows Management Instrumentation - nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2020-03-16' -name: Script Execution via WMI -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '3.0' diff --git a/detections/wmi_temp_event_subscription.yml b/detections/wmi_temp_event_subscription.yml deleted file mode 100644 index 7501e676c1..0000000000 --- a/detections/wmi_temp_event_subscription.yml +++ /dev/null @@ -1,108 +0,0 @@ -asset_type: Endpoint -confidence: medium -creation_date: '2018-10-23' -data_metadata: - data_source: - - Microsoft Windows - data_sourcetypes: - - WinEventLog://Microsoft-Windows-WMI-Activity/Operational - providing_technologies: - - Microsoft Windows -description: This search looks for the creation of WMI temporary event subscriptions. -detect: - splunk: - correlation_rule: - notable: - nes_fields: dest, user, process - rule_description: This search looks for the creation of a temporary WMI event - subscription via Windows event logs. - rule_title: Temporary WMI Event Subscription Detected on $dest$ - risk: - risk_object: dest - risk_object_type: - - system - risk_score: 70 - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" - EventCode=5860 Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" - | search query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = - 'wsmprovhost.exe'" AND query!="SELECT * FROM __InstanceOperationEvent WHERE - TargetInstance ISA 'AntiVirusProduct' OR TargetInstance ISA 'FirewallProduct' - OR TargetInstance ISA 'AntiSpywareProduct'" | stats count min(_time) as firstTime - max(_time) as lastTime by ComputerName, query | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - suppress: - suppress_fields: dest,user - suppress_period: 28800s -eli5: Attackers are increasingly abusing Windows Management Infrastructure (WMI) for - stealth, persistence, lateral movement, or just to leverage its functionality. This - search looks for the creation of a WMI temporary event subscription by watching - for Windows event ID 5860. -entities: - - dest -how_to_implement: To successfully implement this search, you must be ingesting the - Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on - the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -id: 38cbd42c-1098-41bb-99cf-9d6d2b296d83 -investigations: - - id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 - name: Get Sysmon WMI Activity for Host - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 - name: Get Authentication Logs For Endpoint - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d55 - name: Get Risk Modifiers For User - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 - name: Get Process Info - type: splunk - - id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 - name: Get Notable History - type: splunk - - id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 - name: Get Notable Info - type: splunk - - id: fdcfb369-1725-4c24-824a-22972d7f0d65 - name: Get Risk Modifiers For Endpoint - type: splunk - - id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 - name: Get User Information from Identity Table - type: splunk -known_false_positives: Some software may create WMI temporary event subscriptions - for various purposes. The included search contains an exception for two of these - that occur by default on Windows 10 systems. You may need to modify the search to - create exceptions for other legitimate events. -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -mappings: - cis20: - - CIS 3 - - CIS 5 - kill_chain_phases: - - Actions on Objectives - mitre_attack: - - Execution - - Windows Management Instrumentation - - Persistence - - Windows Management Instrumentation Event Subscription - nist: - - PR.PT - - PR.AT - - PR.AC - - PR.IP -modification_date: '2018-10-23' -name: WMI Temporary Event Subscription -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: [] -security_domain: endpoint -spec_version: 2 -type: splunk -version: '1.0' diff --git a/detections/wmi_temporary_event_subscription.yml b/detections/wmi_temporary_event_subscription.yml new file mode 100644 index 0000000000..75849c9be5 --- /dev/null +++ b/detections/wmi_temporary_event_subscription.yml @@ -0,0 +1,38 @@ +name: WMI Temporary Event Subscription +id: 38cbd42c-1098-41bb-99cf-9d6d2b296d83 +version: '1.0' +date: '2018-10-23' +description: This search looks for the creation of WMI temporary event subscriptions. +how_to_implement: To successfully implement this search, you must be ingesting the + Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on + the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. +type: ESCU +references: [] +author: Rico Valdez, Splunk +search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" EventCode=5860 + Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" | search + query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = 'wsmprovhost.exe'" + AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' + OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'" + | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | + `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +known_false_positives: Some software may create WMI temporary event subscriptions + for various purposes. The included search contains an exception for two of these + that occur by default on Windows 10 systems. You may need to modify the search to + create exceptions for other legitimate events. +tags: + analytics_story: + - Suspicious WMI Use + mitre_attack_id: + - T1047 + - T1084 + kill_chain_phases: + - Actions on Objectives + cis20: + - CIS 3 + - CIS 5 + nist: + - PR.PT + - PR.AT + - PR.AC + - PR.IP diff --git a/investigations/aws_activity_via_region.yml b/investigations/aws_activity_via_region.yml deleted file mode 100644 index 228f66bcb0..0000000000 --- a/investigations/aws_activity_via_region.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2018-02-09' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search lists all the user activities logged by CloudTrail for a - specific region in question and will create a table of the values of parameters - requested, the type of the event and the response from the AWS API by each user -entities: - - awsRegion -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 -investigate: - splunk: - fields_required: - - awsRegion - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId - as instanceId| stats values(eventName) by userName instanceId' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-02-09' -name: Investigate AWS activities via region name -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/aws_network_interface_details.yml b/investigations/aws_network_interface_details.yml deleted file mode 100644 index 76b0093d91..0000000000 --- a/investigations/aws_network_interface_details.yml +++ /dev/null @@ -1,42 +0,0 @@ -creation_date: '2018-05-07' -data_metadata: - data_source: - - AWS Configuration Logs - data_sourcetypes: - - aws:config - providing_technologies: - - AWS -description: This search queries AWS configuration logs and returns the information - about a specific network interface via network interface ID. The information will - include the ARN of the network interface, its relationships with other AWS resources, - the public and the private IP associated with the network interface. -entities: - - resourceId -how_to_implement: In order to implement this search, you must install the AWS App - for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) - and configure your AWS configuration inputs -id: f3fb4d1c-5f33-4b01-b541-c3ah9534c241 -investigate: - splunk: - fields_required: - - resourceId - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '0' - search: '| search sourcetype=aws:config resourceId={resourceId} | table _time - ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress - configuration.privateIpAddresses{}.association.publicIp' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-05-07' -name: AWS Network Interface details via resourceId -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/aws_s3_bucket_details.yml b/investigations/aws_s3_bucket_details.yml deleted file mode 100644 index f2c6117727..0000000000 --- a/investigations/aws_s3_bucket_details.yml +++ /dev/null @@ -1,42 +0,0 @@ -creation_date: '2018-06-26' -data_metadata: - data_source: - - AWS Configuration Logs - data_sourcetypes: - - aws:config - providing_technologies: - - AWS -description: This search queries AWS configuration logs and returns the information - about a specific S3 bucket. The information returned includes the time the S3 bucket - was created, the resource ID, the region it belongs to, the value of action performed, - AWS account ID, and configuration values of the access-control lists associated - with the bucket. -entities: - - bucketName -how_to_implement: To implement this search, you must install the AWS App for Splunk - (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later) and - configure your AWS inputs. -id: f3fb2q1c-5f33-4b01-b541-c2ah9534c242 -investigate: - splunk: - fields_required: - - bucketName - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '0' - search: '| search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime - resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-06-26' -name: AWS S3 Bucket details via bucketName -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/aws_user_activities_by_user_field.yml b/investigations/aws_user_activities_by_user_field.yml deleted file mode 100644 index b80adfa1f4..0000000000 --- a/investigations/aws_user_activities_by_user_field.yml +++ /dev/null @@ -1,42 +0,0 @@ -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search lists all the logged CloudTrail activities by a specific - user and will create a table containing the source of the user, the region of the - activity, the name and type of the event, the action taken, and the user's identity - information. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 -investigate: - splunk: - fields_required: - - user - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type - userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName - eventType ' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-03-12' -name: Investigate AWS User Activities by user field -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/aws_user_activity_by_accesskeyid.yml b/investigations/aws_user_activity_by_accesskeyid.yml deleted file mode 100644 index 214f208838..0000000000 --- a/investigations/aws_user_activity_by_accesskeyid.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2018-06-08' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search retrieves the times, ARN, source IPs, AWS regions, event - names, and the result of the event for specific credentials. -entities: - - accessKeyId -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: 703b65a4-a0ae-4171-965d-45507506c64f -investigate: - splunk: - fields_required: - - accessKeyId - schedule: - cron_schedule: '' - earliest_time: '0' - latest_time: '14400' - search: '| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} - | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip - | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-06-08' -name: AWS Investigate User Activities By AccessKeyId -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/aws_user_activity_by_src_user.yml b/investigations/aws_user_activity_by_src_user.yml deleted file mode 100644 index da5b6349de..0000000000 --- a/investigations/aws_user_activity_by_src_user.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2018-06-08' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search retrieves the times, ARN, source IPs, AWS regions, event - names, and the result of the event for specific ARNs. -entities: - - src_user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: b0d2e6a8-75fa-4b1b-9486-3d32acadf891 -investigate: - splunk: - fields_required: - - src_user - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath - output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table - _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-06-08' -name: AWS Investigate User Activities By Source User -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/container_listing_aws_investigation.yml b/investigations/container_listing_aws_investigation.yml deleted file mode 100644 index 0ce5b1c5a9..0000000000 --- a/investigations/container_listing_aws_investigation.yml +++ /dev/null @@ -1,35 +0,0 @@ -creation_date: '2020-02-20' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - AWS CloudTrail logs - providing_technologies: - - AWS -description: This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. -entities: - - src_user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.You must also install Cloud Infrastructure Data Model. -id: 6027623f-7d10-4847-af3b-8d7e87970451 -investigate: - splunk: - fields_required: - - Compute.event_name - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '|tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1' -maintainers: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -modification_date: '2020-02-20' -name: Investigate AWS ECR container listing activity -original_authors: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/dns_server_history.yml b/investigations/dns_server_history.yml deleted file mode 100644 index f70538a61c..0000000000 --- a/investigations/dns_server_history.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2017-04-10' -data_metadata: - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: While investigating any detections it is important to understand which - and how many DNS servers a host has connected to in the past. This search uses data - that is tagged as DNS and gives you a count and list of DNS servers that a particular - host has connected to the previous 24 hours. -entities: - - src_ip -how_to_implement: To successfully implement this search, you must be ingesting your - DNS traffic -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 -investigate: - splunk: - fields_required: - - src_ip - schedule: - cron_schedule: '' - earliest_time: '0' - latest_time: '86400' - search: '| search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d - count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count - | sort -count' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-11-09' -name: Get DNS Server History for a host -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/dns_traffic_stats.yml b/investigations/dns_traffic_stats.yml deleted file mode 100644 index dc3d435032..0000000000 --- a/investigations/dns_traffic_stats.yml +++ /dev/null @@ -1,45 +0,0 @@ -creation_date: '2017-04-10' -data_metadata: - data_models: - - Network_Traffic - data_source: - - DNS - providing_technologies: - - Splunk Stream - - Bro -description: 'This search calculates the ratio of DNS traffic originating and coming - from a host to a list of DNS servers over the last 24 hours. A high value of this - ratio could be very useful to quickly understand if a src_ip (host) is sending a - high volume of data out via port 53, could be an indicator of data exfiltration - via DNS. ' -entities: - - src_ip - - dest_ip -how_to_implement: You must be ingesting your network traffic -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 -investigate: - splunk: - fields_required: - - src_ip - - dest_ip - schedule: - cron_schedule: '' - earliest_time: '0' - latest_time: '86400' - search: '| tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" - sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where - nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} - | eval ratio = (bytes_out/bytes_in) | table ratio' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-11-09' -name: Get DNS traffic ratio -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/email_sent_to_hidden_cobra_actors.yml b/investigations/email_sent_to_hidden_cobra_actors.yml deleted file mode 100644 index f62814d94e..0000000000 --- a/investigations/email_sent_to_hidden_cobra_actors.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2018-06-14' -data_metadata: - data_models: - - Email - data_source: - - Email - providing_technologies: - - Microsoft Exchange -description: 'This search returns the information of the users that sent emails to - the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, - and from `redhat@gmail.com`.' -entities: - - src_user - - recipient -how_to_implement: To successfully implement this search you must ingest your email - logs or capture unencrypted email communications within network traffic, and populate - the Email data model. -id: 5df39b3f-347d-4869-b673-8r45ad4616fe -investigate: - splunk: - fields_required: - - src_user - - recipient - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '0' - search: '| from datamodel Email.All_Email | search recipient=misswang8107@gmail.com - OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) - as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)`' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-06-14' -name: Get Outbound Emails to Hidden Cobra Threat Actors -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/first_occurrence_mac_address.yml b/investigations/first_occurrence_mac_address.yml deleted file mode 100644 index 60338ef9c0..0000000000 --- a/investigations/first_occurrence_mac_address.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2017-06-14' -data_metadata: - data_models: - - Network_Sessions - data_source: - - IP Address Assignment - providing_technologies: - - Splunk Stream - - Bro - - Microsoft Windows -description: This search allows you to gather more context around a notable which - has detected a new device connecting to your network. Use this search to determine - the first and last occurrences of the suspicious device attempting to connect with - your network. -entities: - - src_mac -how_to_implement: To successfully implement this search, you must be ingesting the - logs from your DHCP server. -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd33 -investigate: - splunk: - fields_required: - - src_mac - schedule: - cron_schedule: '' - earliest_time: '864000' - latest_time: '86400' - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) - as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP - All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} - by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-13' -name: Get First Occurrence and Last Occurrence of a MAC Address -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_acl_details.yml b/investigations/get_acl_details.yml deleted file mode 100644 index 95b4f4bc0d..0000000000 --- a/investigations/get_acl_details.yml +++ /dev/null @@ -1,39 +0,0 @@ -creation_date: '2018-01-18' -data_metadata: - data_source: - - AWS Description - data_sourcetypes: - - aws:description - providing_technologies: - - AWS -description: This search queries AWS description logs and returns all the information - about a specific network ACL via network ACL ID -entities: - - networkAclId -how_to_implement: In order to implement this search, you must install the AWS App - for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) - and configure your AWS description inputs. -id: f3fb4d1b-5f33-4b01-b541-c7ah9534c242 -investigate: - splunk: - fields_required: - - networkAclId - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '0' - search: '| search sourcetype=aws:description id={networkAclId} | table id account_id - vpc_id network_acl_entries{}.*' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-01-22' -name: AWS Network ACL Details from ID -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_all_aws_activitiy_from_city.yml b/investigations/get_all_aws_activitiy_from_city.yml deleted file mode 100644 index 4ae77e68f7..0000000000 --- a/investigations/get_all_aws_activitiy_from_city.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2018-03-19' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search retrieves all the activity from a specific city and will - create a table containing the time, city, ARN, username, the type of user, the source - IP address, the AWS region the activity was in, the API called, and whether or not - the API call was successful. -entities: - - City -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: 0abeeb40-1255-4b68-91d1-7a7eb410c4b8 -investigate: - splunk: - fields_required: - - City - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName - path=userIdentity.userName | spath output=userType path=userIdentity.type | - rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, - src_ip, awsRegion, eventName, errorCode' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-19' -name: Get All AWS Activity From City -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_all_aws_activitiy_from_country.yml b/investigations/get_all_aws_activitiy_from_country.yml deleted file mode 100644 index 556e55c8dc..0000000000 --- a/investigations/get_all_aws_activitiy_from_country.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2018-03-19' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search retrieves all the activity from a specific country and will - create a table containing the time, country, ARN, username, the type of user, the - source IP address, the AWS region the activity was in, the API called, and whether - or not the API call was successful. -entities: - - Country -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: e763cdb9-00da-41e0-9bda-444debc9501a -investigate: - splunk: - fields_required: - - Country - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName - path=userIdentity.userName | spath output=userType path=userIdentity.type | - rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, - src_ip, awsRegion, eventName, errorCode' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-19' -name: Get All AWS Activity From Country -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_all_aws_activitiy_from_region.yml b/investigations/get_all_aws_activitiy_from_region.yml deleted file mode 100644 index 09317efe01..0000000000 --- a/investigations/get_all_aws_activitiy_from_region.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2018-03-19' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search retrieves all the activity from a specific geographic region - and will create a table containing the time, geographic region, ARN, username, the - type of user, the source IP address, the AWS region the activity was in, the API - called, and whether or not the API call was successful. -entities: - - Region -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: 5b794bef-1743-4f6f-804a-43915a2702ff -investigate: - splunk: - fields_required: - - Region - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName - path=userIdentity.userName | spath output=userType path=userIdentity.type | - rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, - src_ip, awsRegion, eventName, errorCode' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-19' -name: Get All AWS Activity From Region -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_all_aws_activitiy_from_src_ip.yml b/investigations/get_all_aws_activitiy_from_src_ip.yml deleted file mode 100644 index c91728bf7d..0000000000 --- a/investigations/get_all_aws_activitiy_from_src_ip.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2018-03-19' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search retrieves all the activity from a specific IP address and - will create a table containing the time, ARN, username, the type of user, the IP - address, the AWS region the activity was in, the API called, and whether or not - the API call was successful. -entities: - - src_ip -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: 446ec87a-85c6-40d4-b060-bea4498281d6 -investigate: - splunk: - fields_required: - - src_ip - schedule: - cron_schedule: '' - earliest_time: '14400' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName - path=userIdentity.userName | spath output=userType path=userIdentity.type | - rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, - awsRegion, eventName, errorCode' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-19' -name: Get All AWS Activity From IP Address -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_all_backup_data_for_host.yml b/investigations/get_all_backup_data_for_host.yml deleted file mode 100644 index 0613cba076..0000000000 --- a/investigations/get_all_backup_data_for_host.yml +++ /dev/null @@ -1,37 +0,0 @@ -creation_date: '2017-06-19' -data_metadata: - data_source: - - Backup Systems - data_sourcetypes: - - netbackup_logs - providing_technologies: - - Netbackup -description: Retrieve the backup logs for the last 2 weeks for a specific host in - order to investigate why backups are not completing successfully. -entities: - - dest -how_to_implement: The successfully implement this search you must first send your - backup logs to Splunk. -id: bc91a8cf-aaaa-4bb2-8140-e756cc06fd72 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '1209600' - latest_time: '0' - search: '| search sourcetype="netbackup_logs" dest={dest}' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2017-09-12' -name: All backup logs for host -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_authentication_logs_for_endpoint.yml b/investigations/get_authentication_logs_for_endpoint.yml deleted file mode 100644 index 1cf090beb4..0000000000 --- a/investigations/get_authentication_logs_for_endpoint.yml +++ /dev/null @@ -1,41 +0,0 @@ -creation_date: '2017-04-10' -data_metadata: - data_models: - - Authentication - data_source: - - Authentication - providing_technologies: - - Microsoft Windows - - Linux - - macOS -description: This search returns all users that have attempted to access a particular - endpoint. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting authentication - logs from your various systems and populating the Authentication data model. -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '43200' - latest_time: '1' - search: '| tstats count from datamodel=Authentication where Authentication.dest={dest} - by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action - | `drop_dm_object_name("Authentication")`' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-11-01' -name: Get Authentication Logs For Endpoint -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_backup_logs_for_endpoint.yml b/investigations/get_backup_logs_for_endpoint.yml deleted file mode 100644 index b383a610d2..0000000000 --- a/investigations/get_backup_logs_for_endpoint.yml +++ /dev/null @@ -1,37 +0,0 @@ -creation_date: '2017-08-24' -data_metadata: - data_source: - - Backup Systems - data_sourcetypes: - - netbackup_logs - providing_technologies: - - Netbackup -description: This search will tell you the backup status from your netbackup_logs - of a specific endpoint for the last week. -entities: - - dest -how_to_implement: You must be ingesting your backup logs. -id: fdcfb369-1725-4c24-824a-22972d7f0d44 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '604800' - latest_time: '0' - search: '| search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME - as dest, MESSAGE as signature | table _time, dest, signature' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-14' -name: Get Backup Logs For Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_certificate_for_domain.yml b/investigations/get_certificate_for_domain.yml deleted file mode 100644 index eeeae6a09b..0000000000 --- a/investigations/get_certificate_for_domain.yml +++ /dev/null @@ -1,45 +0,0 @@ -channel: ESCU -creation_date: '2019-04-29' -data_metadata: - data_models: - - Certificates - data_source: - - Certificate Logs - providing_technologies: - - Splunk Stream - - Bro -description: This search queries the Certificates datamodel and give you all the information - for a specific domain. Please note that the certificates issued by "Let's Encrypt" - are widely used by attackers. -entities: - - domain -how_to_implement: You must be ingesting your certificates or SSL logs from your network - traffic into your Certificates datamodel. Please note the wildcard(*) before domain - in the search syntax, we use to match for all domain and subdomain combinations -id: bc91a8cf-35e7-4bb2-2240-e756cc06fd73 -investigate: - splunk: - fields_required: - - domain - schedule: - earliest_time: "36000" - latest_time: "0" - search: '| tstats `summariesonly` count min(_time) as firstTime max(_time) as - lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by - All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name - All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | - `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename - ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-04-29' -name: Get Certificate logs for a domain -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_ec2_details_by_instance_id.yml b/investigations/get_ec2_details_by_instance_id.yml deleted file mode 100644 index 1c3982d28f..0000000000 --- a/investigations/get_ec2_details_by_instance_id.yml +++ /dev/null @@ -1,45 +0,0 @@ -creation_date: '2018-02-12' -data_metadata: - data_source: - - AWS Description - data_sourcetypes: - - aws:description - providing_technologies: - - AWS -description: This search queries AWS description logs and returns all the information - about a specific instance via the instanceId field -entities: - - instanceId -how_to_implement: In order to implement this search, you must install the AWS App - for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) - and configure your AWS description inputs. -id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 -investigate: - splunk: - fields_required: - - instanceId - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '0' - search: '| search sourcetype="aws:description" source="*:ec2_instances"| dedup - id sortby -_time | search id={instanceId} | spath output=tags path=tags | eval - tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) - | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, - launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account - ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as - "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", - state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-02-12' -name: Get EC2 Instance Details by instanceId -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_ec2_launch_details.yml b/investigations/get_ec2_launch_details.yml deleted file mode 100644 index 6a17644298..0000000000 --- a/investigations/get_ec2_launch_details.yml +++ /dev/null @@ -1,42 +0,0 @@ -creation_date: '2018-03-12' -data_metadata: - data_source: - - AWS CloudTrail Logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search returns some of the launch details for a EC2 instance. -entities: - - dest -how_to_implement: In order to implement this search, you must install the AWS App - for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) - and configure your AWS description inputs. -id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '7200' - latest_time: '0' - search: '| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} - |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId - as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, - responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture - as architecture, responseElements.instancesSet.items{}.keyName as keyName | - table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-03-12' -name: Get EC2 Launch Details -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_email_info.yml b/investigations/get_email_info.yml deleted file mode 100644 index a89117402a..0000000000 --- a/investigations/get_email_info.yml +++ /dev/null @@ -1,37 +0,0 @@ -creation_date: '2017-04-21' -data_metadata: - data_models: - - Email - data_source: - - Email - providing_technologies: - - Microsoft Exchange -description: This search returns all the information Splunk might have collected a - specific email message over the last 2 hours. -entities: - - message_id -how_to_implement: To successfully implement this search you must be ingesting your - email logs or capturing unencrypted network traffic which contains email communications. -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd75 -investigate: - splunk: - fields_required: - - message_id - schedule: - cron_schedule: '' - earliest_time: '0' - latest_time: '7200' - search: '| from datamodel Email.All_Email | search message_id={message_id}' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-11-09' -name: Get Email Info -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_emails_from_sender.yml b/investigations/get_emails_from_sender.yml deleted file mode 100644 index 4d7e9a875f..0000000000 --- a/investigations/get_emails_from_sender.yml +++ /dev/null @@ -1,38 +0,0 @@ -creation_date: '2017-04-21' -data_metadata: - data_models: - - Email - data_source: - - Email - providing_technologies: - - Microsoft Exchange -description: This search returns all the emails from a specific sender over the last - 24 and next hours. -entities: - - src_user -how_to_implement: To successfully implement this search you must ingest your email - logs or capture unencrypted email communications within network traffic, and populate - the Email data model. -id: 5df39b3f-447d-4869-b673-8f45ad4616fe -investigate: - splunk: - fields_required: - - src_user - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '86400' - search: '| from datamodel Email.All_Email | search src_user={src_user}' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-11-09' -name: Get Emails From Specific Sender -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_emails_from_source.yml b/investigations/get_emails_from_source.yml deleted file mode 100644 index 8b87108b36..0000000000 --- a/investigations/get_emails_from_source.yml +++ /dev/null @@ -1,41 +0,0 @@ -creation_date: '2019-02-21' -data_metadata: - data_models: - - Email - data_source: - - Email - providing_technologies: - - Microsoft Exchange -description: This search returns a list of all email sources seen in the 48 hours - prior to the notable event to 24 hours after, and the number of emails from each - source. -entities: - - src -how_to_implement: To successfully implement this search you must ingest your email - logs or capture unencrypted email communications within network traffic, and populate - the Email data model. -id: ddc7af28-c34d-4392-af93-7f29a4e8806c -investigate: - splunk: - fields_required: - - src - schedule: - cron_schedule: '' - earliest_time: '172800' - latest_time: '86400' - search: '|tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) - as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email - by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2019-02-21' -name: Get History Of Email Sources -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_logon_rights_modifications_for_endpoint.yml b/investigations/get_logon_rights_modifications_for_endpoint.yml deleted file mode 100644 index 8dc928e47e..0000000000 --- a/investigations/get_logon_rights_modifications_for_endpoint.yml +++ /dev/null @@ -1,39 +0,0 @@ -creation_date: '2017-08-16' -data_metadata: - data_eventtypes: - - wineventlog_security - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search allows you to retrieve any modifications to logon rights - associated with a specific host. -entities: - - dest -how_to_implement: To successfully implement this search you must be ingesting your - Windows event logs -id: 03bffe94-ec7a-4cbe-b677-6af40d1c4505 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '86400' - search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) - dest={dest} | rename user as "Account Modified" | table _time, dest, "Account - Modified", Access_Right, signature' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-12' -name: Get Logon Rights Modifications For Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_logon_rights_modifications_for_user.yml b/investigations/get_logon_rights_modifications_for_user.yml deleted file mode 100644 index f7b482e888..0000000000 --- a/investigations/get_logon_rights_modifications_for_user.yml +++ /dev/null @@ -1,39 +0,0 @@ -creation_date: '2017-08-16' -data_metadata: - data_eventtypes: - - wineventlog_security - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search allows you to retrieve any modifications to logon rights - for a specific user account. -entities: - - user -how_to_implement: To successfully implement this search you must be ingesting your - Windows event logs -id: 552bc86c-f72c-4d44-b3f2-06ede13af7bb -investigate: - splunk: - fields_required: - - user - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '86400' - search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) - user={user} | rename user as "Account Modified" | table _time, dest, "Account - Modified", Access_Right, signature' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-02-27' -name: Get Logon Rights Modifications For User -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_network_traffic_from_src_ip.yml b/investigations/get_network_traffic_from_src_ip.yml deleted file mode 100644 index 0f537671bf..0000000000 --- a/investigations/get_network_traffic_from_src_ip.yml +++ /dev/null @@ -1,39 +0,0 @@ -creation_date: '2018-06-15' -data_metadata: - data_models: - - Network_Traffic - data_source: - - Network Communications - providing_technologies: - - Splunk Stream - - Bro - - Palo Alto Firewall -description: This search allows you to find all the network traffic from a specific - IP address. -entities: - - src_ip -how_to_implement: To successfully implement this search, you must be ingesting your - web-traffic logs and populating the web data model. -id: 9df9ca9c-a02b-4f48-9eba-0bac55179050 -investigate: - splunk: - fields_required: - - src_ip - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '3600' - search: '| from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip}' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-06-15' -name: Investigate Network Traffic From src_ip -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_notable_history_for_endpoint.yml b/investigations/get_notable_history_for_endpoint.yml deleted file mode 100644 index c0766f5023..0000000000 --- a/investigations/get_notable_history_for_endpoint.yml +++ /dev/null @@ -1,37 +0,0 @@ -creation_date: '2017-03-15' -data_metadata: - data_source: - - Notable Events - providing_technologies: - - Splunk Enterprise Security -description: This search queries the notable index and returns all the Notable Events - for the particular destination host, giving the analyst an overview of the incidents - that may have occurred with the host under investigation. -entities: - - dest -how_to_implement: If you are using Enterprise Security you are likely already creating - notable events with your correlation rules. No additional configuration is necessary. -id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '864000' - latest_time: '86400' - search: '| search `notable` | search dest={dest} | table _time, rule_name, owner, - priority, severity, status_description' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-20' -name: Get Notable History -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_notable_info.yml b/investigations/get_notable_info.yml deleted file mode 100644 index 229580c3bb..0000000000 --- a/investigations/get_notable_info.yml +++ /dev/null @@ -1,37 +0,0 @@ -creation_date: '2017-03-15' -data_metadata: - data_source: - - Notable Events - providing_technologies: - - Splunk Enterprise Security -description: This search queries the notable index to retrieve detailed information - captured within the notable. Every notable has a unique ID associated with it, which - is used to point us directly to the notable event under investigation. -entities: - - event_id -how_to_implement: If you are using Enterprise Security you are likely already creating - notable events with your correlation rules. No additional configuration is necessary. -id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 -investigate: - splunk: - fields_required: - - event_id - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '3600' - search: '| search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, - dest_owner, priority, severity, owner, status_description' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-20' -name: Get Notable Info -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_okta_activity_by_app.yml b/investigations/get_okta_activity_by_app.yml deleted file mode 100644 index 3cc1ea16e9..0000000000 --- a/investigations/get_okta_activity_by_app.yml +++ /dev/null @@ -1,34 +0,0 @@ -creation_date: '2020-04-02' -data_metadata: - eventtype: - - okta_log - data_source: - - Okta - providing_technologies: - - Okta -description: This search returns all okta events associated with a specific app -entities: - - app -how_to_implement: You must be ingesting Okta logs -id: 420eb1b8-2992-45d1-80cf-0b1b2759524d -investigate: - splunk: - fields_required: - - app - schedule: - earliest_time: "86400" - latest_time: "14400" - search: 'eventtype=okta_log app={app} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-04-02' -name: Investigate Okta Activity by app -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_okta_activity_by_ip.yml b/investigations/get_okta_activity_by_ip.yml deleted file mode 100644 index d99a0baa32..0000000000 --- a/investigations/get_okta_activity_by_ip.yml +++ /dev/null @@ -1,34 +0,0 @@ -creation_date: '2020-04-02' -data_metadata: - eventtype: - - okta_log - data_source: - - Okta - providing_technologies: - - Okta -description: This search returns all okta events from a specific IP address. -entities: - - src_ip -how_to_implement: You must be ingesting Okta logs -id: 56aae066-d619-477c-93e3-3fb83b2d23c3 -investigate: - splunk: - fields_required: - - user - schedule: - earliest_time: "86400" - latest_time: "14400" - search: 'eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-04-02' -name: Investigate Okta Activity by IP Address -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_okta_user_activity.yml b/investigations/get_okta_user_activity.yml deleted file mode 100644 index 05ec99314d..0000000000 --- a/investigations/get_okta_user_activity.yml +++ /dev/null @@ -1,34 +0,0 @@ -creation_date: '2020-04-02' -data_metadata: - eventtype: - - okta_log - data_source: - - Okta - providing_technologies: - - Okta -description: This search returns all okta events by a specific user -entities: - - user -how_to_implement: You must be ingesting Okta logs -id: 24ff145d-4d16-420a-b047-480f2a51c403 -investigate: - splunk: - fields_required: - - user - schedule: - earliest_time: "86400" - latest_time: "14400" - search: 'eventtype=okta_log user={user} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason' -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-04-02' -name: Investigate User Activities In Okta -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_parent_process_info.yml b/investigations/get_parent_process_info.yml deleted file mode 100644 index e8f110bb04..0000000000 --- a/investigations/get_parent_process_info.yml +++ /dev/null @@ -1,49 +0,0 @@ -creation_date: '2017-08-22' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search queries the Endpoint data model to give you details about - the parent process of a process running on a host which is under investigation. - Enter the values of the process name in question and the dest -entities: - - process_name - - dest -how_to_implement: You must be ingesting endpoint data that tracks process activity, - including parent-child relationships from your endpoints to populate the Endpoint - data model in the Processes node. The command-line arguments are mapped to the "process" - field in the Endpoint data model. -id: fecf2918-670d-4f1c-872b-3d7317a41bf9 -investigate: - splunk: - fields_required: - - process_name - - dest - schedule: - earliest_time: "86400" - latest_time: "0" - search: '| tstats `summariesonly` count values(Processes.process) as process min(_time) - as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where - Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user - Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-02-28' -name: Get Parent Process Info -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_process_creating_dns_traffic.yml b/investigations/get_process_creating_dns_traffic.yml deleted file mode 100644 index 1b8c400601..0000000000 --- a/investigations/get_process_creating_dns_traffic.yml +++ /dev/null @@ -1,50 +0,0 @@ -creation_date: '2017-04-10' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: While investigating, an analyst will want to know what process and parent_process - is responsible for generating suspicious DNS traffic. Use the following search and - enter the value of `dest` in the search to get specific details on the process responsible - for creating the DNS traffic. -entities: - - dest -how_to_implement: You must be ingesting endpoint data that associates processes with - network events into the Endpoint datamodel. This can come from endpoint protection - products such as carbon black, or endpoint data sources such as Sysmon. -id: 910e6512-edc9-4f93-ba24-5b786f47a672 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '86400' - search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from - datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process - Processes.process_name Processes.user Processes.dest Processes.process_id | - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search - [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 - by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as - dest]' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-04-01' -name: Get Process Responsible For The DNS Traffic -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_process_file_activity.yml b/investigations/get_process_file_activity.yml deleted file mode 100644 index c525a3e26c..0000000000 --- a/investigations/get_process_file_activity.yml +++ /dev/null @@ -1,47 +0,0 @@ -creation_date: '2019-11-06' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search returns the file activity for a specific process on a specific endpoint -entities: - - process_id - - dest -how_to_implement: To successfully implement this search you must be ingesting endpoint - data and populating the Endpoint data model. -id: 6a9ad4d9-6ef2-4b85-953f-a37ab256acd5 -investigate: - splunk: - fields_required: - - process_id - - dest - schedule: - cron_schedule: '' - earliest_time: '7200' - latest_time: '7200' - search: '| tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, - values(Filesystem.process_id) as process_id from - datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} - by Filesystem.file_path, Filesystem.action, _time - | `drop_dm_object_name(Filesystem)` | sort _time - | table _time, process_id, dest, action, file_name, file_path' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-11-06' -name: Get Process File Activity -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_process_info.yml b/investigations/get_process_info.yml deleted file mode 100644 index b1fdd1e0fd..0000000000 --- a/investigations/get_process_info.yml +++ /dev/null @@ -1,47 +0,0 @@ -creation_date: '2017-03-15' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search queries the Endpoint data model to give you details about - the process running on a host which is under investigation. To gather the process - info, enter the values for the process name in question and the destination IP address. -entities: - - process_name - - dest -how_to_implement: To successfully implement this search you must be ingesting endpoint - data and populating the Endpoint data model. -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 -investigate: - splunk: - fields_required: - - process_name - - dest - schedule: - cron_schedule: '' - earliest_time: '7200' - latest_time: '7200' - search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from - datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} - by Processes.parent_process Processes.process_name Processes.user Processes.dest - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` ' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-04-01' -name: Get Process Info -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_process_info_for_port.yml b/investigations/get_process_info_for_port.yml deleted file mode 100644 index 2fc5085186..0000000000 --- a/investigations/get_process_info_for_port.yml +++ /dev/null @@ -1,47 +0,0 @@ -creation_date: '2017-06-25' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Splunk Stream - - Bro - - Bluecoat - - Palo Alto Firewall -description: This search will return information about the process associated with - observed network traffic to a specific destination port from a specific host. -entities: - - dest_port - - dest -how_to_implement: To successfully implement this search you must be ingesting endpoint - data that associates processes with network events and populate the Endpoint Datamodel -id: 9925d08f-561e-4faa-8912-e3888a842341 -investigate: - splunk: - fields_required: - - dest_port - - dest - schedule: - cron_schedule: '' - earliest_time: '7200' - latest_time: '7200' - search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from - datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name - Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count - from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id - Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-04-01' -name: Get Process Information For Port Activity -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_process_registry_activity.yml b/investigations/get_process_registry_activity.yml deleted file mode 100644 index ebe7a47ca8..0000000000 --- a/investigations/get_process_registry_activity.yml +++ /dev/null @@ -1,47 +0,0 @@ -creation_date: '2019-11-06' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint Intel - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search returns the registry activity for a specific process on a specific endpoint -entities: - - process_id - - dest -how_to_implement: To successfully implement this search you must be ingesting endpoint - data and populating the Endpoint data model. -id: d8362a34-b78a-4364-9733-59b505f5b8d5 -investigate: - splunk: - fields_required: - - process_id - - dest - schedule: - cron_schedule: '' - earliest_time: '7200' - latest_time: '7200' - search: '| tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, - values(Registry.dest) as dest, values(Registry.process_id) as process_id from - datamodel=Endpoint.Registry where Registry.process_id={process_id} AND Registry.dest={dest} - by Registry.registry_path, Registry.action, _time - | `drop_dm_object_name(Registry)` | sort _time - | table _time, process_id, dest, action, registry_key_name, registry_path' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-11-06' -name: Get Process Registry Activity -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_rdp_authentications.yml b/investigations/get_rdp_authentications.yml deleted file mode 100644 index 70cb55493a..0000000000 --- a/investigations/get_rdp_authentications.yml +++ /dev/null @@ -1,43 +0,0 @@ -creation_date: '2018-12-14' -data_metadata: - data_models: - - Authentication - data_source: - - Authentication - providing_technologies: - - Microsoft Windows -description: 'This search returns the source, destination, and user for all successful - remote-desktop authentications. A successful authentication after a brute-force - attack on a destination machine is suspicious behavior. ' -entities: - - dest -how_to_implement: You must be populating the Authentication data model with security - events from your Windows event logs. -id: b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '86400' - latest_time: '0' - search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as - lastTime from datamodel=Authentication where Authentication.signature_id=4624 - Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app - Authentication.user Authentication.signature Authentication.src_nt_domain | - `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| - table firstTime lastTime src src_nt_domain dest user app count | sort count' -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -modification_date: '2018-12-14' -name: Investigate Successful Remote Desktop Authentications -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_registry_activities.yml b/investigations/get_registry_activities.yml deleted file mode 100644 index e15083c7e1..0000000000 --- a/investigations/get_registry_activities.yml +++ /dev/null @@ -1,49 +0,0 @@ -creation_date: '2018-08-07' -data_metadata: - data_models: - - Endpoint - data_source: - - Endpoint - providing_technologies: - - Carbon Black Response - - CrowdStrike Falcon - - Sysmon - - Tanium - - Ziften -description: This search queries the Endpoint Datamodel to give you details of the - latest registry values for a specific destination computer. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting information - on registry changes that include the name of the process responsible for the changes - from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` - nodes. -id: fecf2918-670d-4f1c-872b-3d7317a41xf9 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '0' - latest_time: '86400' - search: '| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path - values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry - where Registry.dest = "{dest}" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` - | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) - as process_name values(Processes.parent_process_name) as parent_process_name - FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by - Processes.process_id | `drop_dm_object_name("Processes")`]' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-03-01' -name: Get Registry Activities -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/get_risk_for_endpoint.yml b/investigations/get_risk_for_endpoint.yml deleted file mode 100644 index 37292208d3..0000000000 --- a/investigations/get_risk_for_endpoint.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2017-10-14' -data_metadata: - data_models: - - Risk - data_source: - - Risk Scores - providing_technologies: - - Splunk Enterprise Security -description: 'For the last 7 days, the search will query the Risk data model in Splunk - Enterprise Security and calculate the count, sum of the risk\_scores, names of the - correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) ' -entities: - - dest -how_to_implement: Enable the correlation searches included in Splunk Enterprise Security - that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -id: fdcfb369-1725-4c24-824a-22972d7f0d65 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '604800' - latest_time: '0' - search: '| from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} - | stats count sum(risk_score) as risk_score values(search_name) min(_time) - as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-10-19' -name: Get Risk Modifiers For Endpoint -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_risk_for_user.yml b/investigations/get_risk_for_user.yml deleted file mode 100644 index 5ebb23dce1..0000000000 --- a/investigations/get_risk_for_user.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2017-10-14' -data_metadata: - data_models: - - Risk - data_source: - - Risk Scores - providing_technologies: - - Splunk Enterprise Security -description: 'For the last 7 days, the search will query the Risk data model in Splunk - Enterprise Security and calculate the count, sum of the risk_scores, names of the - correlation searches that contributed to create a risk score for a specific user ' -entities: - - user -how_to_implement: Enable the correlation searches included in Splunk Enterprise Security - that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -id: fdcfb369-1725-4c24-824a-22972d7f0d55 -investigate: - splunk: - fields_required: - - user - schedule: - cron_schedule: '' - earliest_time: '604800' - latest_time: '0' - search: '| from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} - | stats count sum(risk_score) as risk_score values(search_name) min(_time) - as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` ' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-10-19' -name: Get Risk Modifiers For User -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_update_logs_for_endpoint.yml b/investigations/get_update_logs_for_endpoint.yml deleted file mode 100644 index 8408ba0307..0000000000 --- a/investigations/get_update_logs_for_endpoint.yml +++ /dev/null @@ -1,39 +0,0 @@ -creation_date: '2017-08-24' -data_metadata: - data_models: - - Updates - data_source: - - Update Logs - providing_technologies: - - Microsoft Windows - - Linux - - macOS -description: This search will tell you give you the update logs for a specific endpoint - for the last week. -entities: - - dest -how_to_implement: You need to be ingesting the update logs from your various systems. -id: d98675ed-da43-4a7e-96a7-eeca3232ba8e -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '604800' - latest_time: '0' - search: '| from datamodel Updates.Updates | search (vendor_product="Microsoft - Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest}' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-08-24' -name: Get Update Logs For Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_user_info_from_identity_table.yml b/investigations/get_user_info_from_identity_table.yml deleted file mode 100644 index 1fe5c05b27..0000000000 --- a/investigations/get_user_info_from_identity_table.yml +++ /dev/null @@ -1,35 +0,0 @@ -creation_date: '2017-04-10' -data_metadata: - data_source: - - Identity Table - providing_technologies: - - Splunk Enterprise Security -description: Gather more information about the user identified in the Notable Event. -entities: - - user -how_to_implement: To successfully implement this search you must have populated the - identity table with information about your users. -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 -investigate: - splunk: - fields_required: - - user - schedule: - cron_schedule: '' - earliest_time: '864000' - latest_time: '86400' - search: '| `identities` | search identity={user} | table _time, identity, first, - last, email, category, watchlist' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-20' -name: Get User Information from Identity Table -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_vulnerability_logs_for_endpoint.yml b/investigations/get_vulnerability_logs_for_endpoint.yml deleted file mode 100644 index b5d136ab85..0000000000 --- a/investigations/get_vulnerability_logs_for_endpoint.yml +++ /dev/null @@ -1,36 +0,0 @@ -creation_date: '2017-08-24' -data_metadata: - data_models: - - Vulnerabilities - data_source: - - Vulnerability Scanner - providing_technologies: - - Nessus -description: This search will show you any vulnerabilities noted for a specific endpoint - for the last week. -entities: - - dest -how_to_implement: You need to be ingesting the logs from your vulnerability scanner. -id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '604800' - latest_time: '0' - search: '| from datamodel Vulnerabilities.Vulnerabilities | search dest={dest}' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-10' -name: Get Vulnerability Logs For Endpoint -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_web_activity.yml b/investigations/get_web_activity.yml deleted file mode 100644 index d35f92610e..0000000000 --- a/investigations/get_web_activity.yml +++ /dev/null @@ -1,41 +0,0 @@ -creation_date: '2017-04-21' -data_metadata: - data_models: - - Web - data_source: - - Web - providing_technologies: - - Splunk Stream - - Bro - - Bluecoat - - Palo Alto Firewall -description: This search allows you to find all the web activity from a specific host. - During an investigation, it is important to profile web activity to characterize - user or host activity. -entities: - - dest -how_to_implement: To successfully implement this search you must be ingesting your - web traffic and populating the Web data model. -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '3600' - search: '| from datamodel Web.Web | search src={dest}' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-11-09' -name: Investigate Web Activity From Host -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_web_activity_by_src_ip.yml b/investigations/get_web_activity_by_src_ip.yml deleted file mode 100644 index 9aa2fbb583..0000000000 --- a/investigations/get_web_activity_by_src_ip.yml +++ /dev/null @@ -1,41 +0,0 @@ -creation_date: '2018-06-15' -data_metadata: - data_models: - - Web - data_source: - - Web - providing_technologies: - - Splunk Stream - - Bro - - Bluecoat - - Palo Alto Firewall -description: This search searches for all web activity from a specific host. During - an investigation, it is important to profile web activity to characterize user or - host activity. -entities: - - src_ip -how_to_implement: To successfully implement this search, you must be ingesting your - web traffic and populating the web data model. -id: 2f5b960b-71df-49c0-affc-74992ce60e45 -investigate: - splunk: - fields_required: - - src_ip - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '3600' - search: '| from datamodel Web.Web | search src={src_ip}' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-06-15' -name: Investigate Web Activity From src_ip -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_web_posts_by_src.yml b/investigations/get_web_posts_by_src.yml deleted file mode 100644 index e562201b4f..0000000000 --- a/investigations/get_web_posts_by_src.yml +++ /dev/null @@ -1,43 +0,0 @@ -creation_date: '2018-12-06' -data_metadata: - data_models: - - Web - data_source: - - Web - providing_technologies: - - Splunk Stream - - Bro - - Bluecoat - - Palo Alto Firewall -description: 'This investigative search retrieves POST requests from a specified source - IP or hostname. Identifying the POST requests, as well as their associated destination - URLs and user agent(s), may help you scope and characterize the suspicious traffic. ' -entities: - - src -how_to_implement: To successfully implement this search, you must be ingesting your - web-traffic logs and populating the web data model. -id: f5c39fac-205c-4e07-9004-8fd61ea3431a -investigate: - splunk: - fields_required: - - src - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '3600' - search: '| tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by - Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| - where like(src, "{src}") and like(http_method, "POST")' -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -modification_date: '2018-12-06' -name: Investigate Web POSTs From src -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_web_session_info.yml b/investigations/get_web_session_info.yml deleted file mode 100644 index 06d1178bd9..0000000000 --- a/investigations/get_web_session_info.yml +++ /dev/null @@ -1,41 +0,0 @@ -creation_date: '2018-10-08' -data_metadata: - data_source: - - Network Communications - data_sourcetypes: - - stream:http - providing_technologies: - - Splunk Stream -description: This search helps an analyst investigate a notable event to find out - more about a specific web session. The search looks for a specific web session ID - in the HTTP web traffic and outputs the URL and user agents, grouped by source IP - address and HTTP status code. -entities: - - session_id -how_to_implement: This search leverages data extracted from Stream:HTTP. You must - configure the HTTP stream using the Splunk Stream App on your Splunk Stream deployment - server. -id: bc91a8cf-35e7-4bb2-1120-e756cc06fd89 -investigate: - splunk: - fields_required: - - session_id - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '3600' - search: '| search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) - by src_ip status' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-10-08' -name: Get Web Session Information via session_id -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/get_wmi_sysmon_events.yml b/investigations/get_wmi_sysmon_events.yml deleted file mode 100644 index 08437b88ed..0000000000 --- a/investigations/get_wmi_sysmon_events.yml +++ /dev/null @@ -1,42 +0,0 @@ -creation_date: '2018-10-23' -data_metadata: - data_source: - - Endpoint Intel - data_sourcetypes: - - XmlWinEventLog:Microsoft-Windows-Sysmon/Operational - providing_technologies: - - Sysmon -description: This search queries Sysmon WMI events for the host of interest. -entities: - - process - - dest -how_to_implement: To successfully implement this search, you must be collecting Sysmon - data using Sysmon version 6.1 or greater and have Sysmon configured to generate - events for WMI activity. In addition, you must have at least version 6.0.4 of the - Sysmon TA installed to properly parse the fields. -id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 -investigate: - splunk: - fields_required: - - process - - dest - schedule: - cron_schedule: '' - earliest_time: '7200' - latest_time: '7200' - search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 - EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, - Operation, EventType, Type, Query, Consumer, Filter -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2018-10-23' -name: Get Sysmon WMI Activity for Host -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/investigate_cloud_compute_instance_activities.yml b/investigations/investigate_cloud_compute_instance_activities.yml deleted file mode 100644 index e53eed6247..0000000000 --- a/investigations/investigate_cloud_compute_instance_activities.yml +++ /dev/null @@ -1,38 +0,0 @@ -creation_date: '2019-10-02' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: This search returns a logs of events that operated on the compute instance. -entities: - - dest -how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs - and have the Security Research cloud data model installed. -id: 33a95cf2-900c-4636-8fca-5c5f71474720 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '7200' - latest_time: '0' - search: '| from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields - _*' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-12' -name: Investigate Cloud Compute Instance Activities -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/investigate_failed_logins_for_multiple_destinations.yml b/investigations/investigate_failed_logins_for_multiple_destinations.yml deleted file mode 100644 index 18c1f8b129..0000000000 --- a/investigations/investigate_failed_logins_for_multiple_destinations.yml +++ /dev/null @@ -1,41 +0,0 @@ -creation_date: '2019-12-10' -data_metadata: - data_models: - - Authentication - data_source: - - Authentication - providing_technologies: - - Microsoft Windows - - Linux - - macOS -description: This search returns failed logins to multiple destinations by user. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting authentication - logs from your various systems and populating the Authentication data model. -id: 097e8030-8662-4254-a735-bf0bdda696e3 -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '-7d' - latest_time: 'now' - search: '| tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user - | where distinct_count_dest > 1 - | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` - | `drop_dm_object_name("Authentication")`' -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -modification_date: '2019-12-10' -name: Investigate Failed Logins for Multiple Destinations -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/investigate_pass_the_hash_attempts.yml b/investigations/investigate_pass_the_hash_attempts.yml deleted file mode 100644 index 747ac49248..0000000000 --- a/investigations/investigate_pass_the_hash_attempts.yml +++ /dev/null @@ -1,39 +0,0 @@ -creation_date: '2019-12-10' -data_metadata: - data_eventtypes: - - wineventlog_security - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search hunts for dumped NTLM hashes used for pass the hash. -entities: - - dest -how_to_implement: To successfully implement this search you need be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -id: ed3fff45-cba6-4990-983f-6fac72bee659 -investigate: - splunk: - fields_required: - - dest - macros: - - wineventlog_security - schedule: - cron_schedule: '' - earliest_time: '-24h' - latest_time: 'now' - search: '`wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate - | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest - | `security_content_ctime(first_login)` | `security_content_ctime(last_login)`' -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -modification_date: '2019-12-10' -name: Investigate Pass the Hash Attempts -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/investigate_pass_the_ticket_attempts.yml b/investigations/investigate_pass_the_ticket_attempts.yml deleted file mode 100644 index 5e7c124aad..0000000000 --- a/investigations/investigate_pass_the_ticket_attempts.yml +++ /dev/null @@ -1,43 +0,0 @@ -creation_date: '2019-12-10' -data_metadata: - data_eventtypes: - - wineventlog_security - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows -description: This search hunts for dumped kerberos ticket from LSASS memory. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. - -id: 990007ad-d798-4b29-ab2f-f0034144c937 -investigate: - splunk: - fields_required: - - dest - macros: - - wineventlog_security - schedule: - cron_schedule: '' - earliest_time: '-24h' - latest_time: 'now' - search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 - | rex field=user "(?[^\@]+)" - | stats count BY new_user, dest, EventCode - | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest - | where sum_count/max_count!=2 - | rename new_user AS user' -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -modification_date: '2019-12-10' -name: Investigate Pass the Ticket Attempts -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/investigate_previous_unseen_user.yml b/investigations/investigate_previous_unseen_user.yml deleted file mode 100644 index 5c02e1e00f..0000000000 --- a/investigations/investigate_previous_unseen_user.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2019-12-10' -data_metadata: - data_models: - - Authentication - data_source: - - Authentication - providing_technologies: - - Microsoft Windows - - Linux - - macOS -description: This search returns previous unseen user, which didn't log in for 30 days. -entities: - - dest -how_to_implement: To successfully implement this search you need to be ingesting authentication - logs from your various systems and populating the Authentication data model. -id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad -investigate: - splunk: - fields_required: - - dest - schedule: - cron_schedule: '' - earliest_time: '-60d' - latest_time: 'now' - search: '| tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user - | bucket _time span=30d - | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user - | where count=1 - | where first_login >= relative_time(now(), "-30d") - | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` - | `drop_dm_object_name("Authentication")`' -maintainers: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -modification_date: '2019-12-10' -name: Investigate Previous Unseen User -original_authors: - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/investigate_user_activities_in_all_cloud_regions.yml b/investigations/investigate_user_activities_in_all_cloud_regions.yml deleted file mode 100644 index 1e1a22fab5..0000000000 --- a/investigations/investigate_user_activities_in_all_cloud_regions.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2019-10-02' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: This search lists all the logged cloud infrastructure activities by a - specific cloud user -entities: - - region - - src_user -how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs - and have the Security Research cloud data model installed. -id: 2ef6310f-8e79-42af-b20b-b4eeaba9608a -investigate: - splunk: - fields_required: - - region - - src_user - schedule: - earliest_time: "86400" - latest_time: "14400" - search: '| from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | fields - _*' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-04-30' -name: Investigate User Activities In All Cloud Regions -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/investigate_user_activities_in_single_cloud_region.yml b/investigations/investigate_user_activities_in_single_cloud_region.yml deleted file mode 100644 index 2bac31dd9b..0000000000 --- a/investigations/investigate_user_activities_in_single_cloud_region.yml +++ /dev/null @@ -1,40 +0,0 @@ -creation_date: '2019-10-02' -data_metadata: - data_models: - - Cloud_Infrastructure - data_source: - - Cloud Infrastructure Logs - providing_technologies: - - AWS - - Azure - - GCP -description: This search lists all the logged cloud infrastructure activities by a - specific cloud user in a specific cloud region -entities: - - region - - src_user -how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs - and have the Security Research cloud data model installed. -id: 3dc3a8e7-394b-44ae-8262-4ef8e90b723d -investigate: - splunk: - fields_required: - - region - - src_user - schedule: - earliest_time: "86400" - latest_time: "14400" - search: '| from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} | fields - _*' -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-04-30' -name: Investigate User Activities In Single Cloud Region -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -spec_version: 2 -type: splunk -version: '2.0' diff --git a/investigations/kubernetes_aws_activity_by_src_ip.yml b/investigations/kubernetes_aws_activity_by_src_ip.yml deleted file mode 100644 index 832a98c410..0000000000 --- a/investigations/kubernetes_aws_activity_by_src_ip.yml +++ /dev/null @@ -1,37 +0,0 @@ -creation_date: "2020-03-24" -data_metadata: - data_source: - - AWS CloudWatch EKS Logs - data_sourcetypes: - - aws:cloudwatchlogs:eks - providing_technologies: - - AWS -description: This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address -entities: - - src_ip -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your Cloud Watch EKS inputs. -id: a636cca4-7434-4a15-a278-c70734938e39 -investigate: - splunk: - fields_required: - - src_ip - schedule: - cron_schedule: 0 * * * * - earliest_time: -70m@m - latest_time: -10m@m - search: sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip -maintainers: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -modification_date: "2020-04-13" -name: Amazon EKS Kubernetes activity by src_ip -original_authors: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -references: [] -security_domain: threat -spec_version: 2 -type: splunk -version: "1.0" diff --git a/investigations/kubernetes_gcp_activity_by_src_ip.yml b/investigations/kubernetes_gcp_activity_by_src_ip.yml deleted file mode 100644 index 89c384a208..0000000000 --- a/investigations/kubernetes_gcp_activity_by_src_ip.yml +++ /dev/null @@ -1,35 +0,0 @@ -creation_date: "2020-03-24" -data_metadata: - data_source: - - "GCP Stackdriver logs" - data_sourcetypes: - - "google:gcp:pubsub:message" - providing_technologies: - - GCP -description: This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address -entities: - - src_user -how_to_implement: "You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs." -id: c00e7626-92cc-4e06-9a51-b6db0a50bd1f -investigate: - splunk: - fields_required: - - src_user - schedule: - cron_schedule: "0 * * * *" - earliest_time: "-70m@m" - latest_time: "-10m@m" - search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type -maintainers: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -modification_date: "2020-04-13" -name: GCP Kubernetes activity by src_ip -original_authors: - - company: Splunk - email: rsoto@splunk.com - name: "Rod Soto" -spec_version: 2 -type: splunk -version: "1.0" diff --git a/investigations/suspicious_email_attachment_investigate_and_delete.yml b/investigations/suspicious_email_attachment_investigate_and_delete.yml deleted file mode 100644 index 646d691584..0000000000 --- a/investigations/suspicious_email_attachment_investigate_and_delete.yml +++ /dev/null @@ -1,49 +0,0 @@ -creation_date: '2019-06-03' -data_metadata: - data_source: - - Microsoft Exchange - - SMTP - - Cuckoo - - Splunk Enterprise Security - - VirusTotal - - DeepSight - providing_technologies: - - Microsoft Exchange - - SMTP - - Cuckoo - - Splunk Enterprise Security - - VirusTotal - - DeepSight -description: Investigate an email with a suspicious file attachment detected by Splunk - Enterprise Security. Detonate the file attachment in a sandbox, gather network behavior - from the sandbox results, and pivot on those network indicators with both external - reputation queries and internal Splunk Common Information Model searches. After - confirming the results with an analyst prompt, delete the email from the user's - inbox, hopefully before they have opened it. -how_to_implement: Synchronize the community playbook repository in Phantom, then open - the playbook and follow the deployment notes to configure it for your environment. -id: 3096f721-8842-42ce-2fc7-742d8372b712 -investigate: - phantom: - phantom_server: automation (hostname) - playbook_name: community/suspicious_email_attachment_investigate_and_delete - playbook_url: https://my.phantom.us/4.2/playbook/suspicious-email-attachment-investigate-and-delete/ - schedule: - cron_schedule: 0 * * * * - earliest_time: '0' - latest_time: '86400' - sensitivity: green - severity: medium -maintainers: - - company: Splunk - email: proyer@splunk.com - name: Philip Royer -modification_date: '2019-06-03' -name: Suspicious Email Attachment Investigate and Delete -original_authors: - - company: Splunk - email: proyer@splunk.com - name: Philip Royer -spec_version: 2 -type: phantom -version: '1.0' diff --git a/investigations/suspicious_strings_in_HTTP_header.yml b/investigations/suspicious_strings_in_HTTP_header.yml deleted file mode 100644 index ae696d9707..0000000000 --- a/investigations/suspicious_strings_in_HTTP_header.yml +++ /dev/null @@ -1,49 +0,0 @@ -creation_date: '2017-06-26' -data_metadata: - data_source: - - Network Communications - data_sourcetypes: - - stream:http - providing_technologies: - - Splunk Stream -description: This search helps an analyst investigate a notable event related to a - potential Apache Struts exploitation. To investigate, we will want to isolate and - analyze the "payload" or the commands that were passed to the vulnerable hosts by - creating a few regular expressions to carve out the commands focusing on common - keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns - these suspicious strings found in the HTTP logs of the system of interest. -entities: - - src_ip - - dest_ip -how_to_implement: This particular search leverages data extracted from Stream:HTTP. - You must configure the http stream using the Splunk Stream App on your Splunk Stream - deployment server to extract the cs_content_type field. -id: bc91a8cf-35e7-4bb2-8140-e756cc06fd89 -investigate: - splunk: - fields_required: - - src_ip - - dest_ip - schedule: - cron_schedule: '' - earliest_time: '3600' - latest_time: '3600' - search: '| search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" - | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length - > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, - "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious - Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, - suspicious_strings, cs_content_type, cs_content_type_length, url' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-10-20' -name: Investigate Suspicious Strings in HTTP Header -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '1.0' diff --git a/investigations/user_activity_via_cloudtrail.yml b/investigations/user_activity_via_cloudtrail.yml deleted file mode 100644 index 895d3e6e14..0000000000 --- a/investigations/user_activity_via_cloudtrail.yml +++ /dev/null @@ -1,44 +0,0 @@ -creation_date: '2018-01-22' -data_metadata: - data_source: - - AWS CloudTrail logs - data_sourcetypes: - - aws:cloudtrail - providing_technologies: - - AWS -description: This search lists all the logged CloudTrail activities by a specific - user ARN and will create a table containing the source of the user, the region of - the activity, the name and type of the event, the action taken, and all the user's - identity information. -entities: - - user -how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) - and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail - inputs. -id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 -investigate: - splunk: - fields_required: - - user - schedule: - earliest_time: "72000" - latest_time: "36000" - search: '| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time - userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src - awsRegion eventName eventType' -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -modification_date: '2019-04-30' -name: AWS Investigate User Activities By ARN -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: splunk -version: '2.0' diff --git a/response_tasks/all_backup_logs_for_host.yml b/response_tasks/all_backup_logs_for_host.yml new file mode 100644 index 0000000000..baa68a138a --- /dev/null +++ b/response_tasks/all_backup_logs_for_host.yml @@ -0,0 +1,12 @@ +name: All backup logs for host +id: bc91a8cf-aaaa-4bb2-8140-e756cc06fd72 +version: '1.0' +date: '2017-09-12' +description: Retrieve the backup logs for the last 2 weeks for a specific host in + order to investigate why backups are not completing successfully. +how_to_implement: The successfully implement this search you must first send your + backup logs to Splunk. +author: Rico Valdez, Splunk +inputs: +- dest +search: '| search sourcetype="netbackup_logs" dest={dest}' diff --git a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml new file mode 100644 index 0000000000..0a2ca269b2 --- /dev/null +++ b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml @@ -0,0 +1,17 @@ +name: Amazon EKS Kubernetes activity by src_ip +id: a636cca4-7434-4a15-a278-c70734938e39 +version: '1.0' +date: '2020-04-13' +description: This search provides investigation data about requests via user agent, + authentication request URI, verb and cluster name data against Kubernetes cluster + from a specific IP address +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your Cloud Watch + EKS inputs. +author: Rod Soto, Splunk +inputs: +- src_ip +search: sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIPs{} + as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) + values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision + src_ip diff --git a/response_tasks/analyze_malicious_file.yml b/response_tasks/analyze_malicious_file.yml new file mode 100644 index 0000000000..0a606082e7 --- /dev/null +++ b/response_tasks/analyze_malicious_file.yml @@ -0,0 +1,6 @@ +name: Analyze Malicious File +id: 6ee5c067-8228-4926-abb2-54f2c59d726e +version: 1 +date: '2020-04-29' +description: Perform a static and dynamic malware analysis for the malicious file. Use the findings for further response tasks. +author: Patrick Bareiss, Splunk diff --git a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml new file mode 100644 index 0000000000..def4a36fda --- /dev/null +++ b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml @@ -0,0 +1,15 @@ +name: AWS Investigate User Activities By AccessKeyId +id: 703b65a4-a0ae-4171-965d-45507506c64f +version: '1.0' +date: '2018-06-08' +description: This search retrieves the times, ARN, source IPs, AWS regions, event + names, and the result of the event for specific credentials. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: David Dorsey, Splunk +inputs: +- accessKeyId +search: '| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} + | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | + table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' diff --git a/response_tasks/aws_investigate_user_activities_by_arn.yml b/response_tasks/aws_investigate_user_activities_by_arn.yml new file mode 100644 index 0000000000..c438136f91 --- /dev/null +++ b/response_tasks/aws_investigate_user_activities_by_arn.yml @@ -0,0 +1,17 @@ +name: AWS Investigate User Activities By ARN +id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 +version: '2.0' +date: '2019-04-30' +description: This search lists all the logged CloudTrail activities by a specific + user ARN and will create a table containing the source of the user, the region of + the activity, the name and type of the event, the action taken, and all the user's + identity information. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: Bhavin Patel, Splunk +inputs: +- user +search: '| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time + userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion + eventName eventType' diff --git a/response_tasks/aws_investigate_user_activities_by_source_user.yml b/response_tasks/aws_investigate_user_activities_by_source_user.yml new file mode 100644 index 0000000000..5bee3726e3 --- /dev/null +++ b/response_tasks/aws_investigate_user_activities_by_source_user.yml @@ -0,0 +1,15 @@ +name: AWS Investigate User Activities By Source User +id: b0d2e6a8-75fa-4b1b-9486-3d32acadf891 +version: '1.0' +date: '2018-06-08' +description: This search retrieves the times, ARN, source IPs, AWS regions, event + names, and the result of the event for specific ARNs. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: Bhavin Patel, Splunk +inputs: +- src_user +search: '| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user + path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, + awsRegion, eventName, errorCode, errorMessage' diff --git a/response_tasks/aws_network_acl_details_from_id.yml b/response_tasks/aws_network_acl_details_from_id.yml new file mode 100644 index 0000000000..a1b99183f6 --- /dev/null +++ b/response_tasks/aws_network_acl_details_from_id.yml @@ -0,0 +1,14 @@ +name: AWS Network ACL Details from ID +id: f3fb4d1b-5f33-4b01-b541-c7ah9534c242 +version: '1.0' +date: '2017-01-22' +description: This search queries AWS description logs and returns all the information + about a specific network ACL via network ACL ID +how_to_implement: In order to implement this search, you must install the AWS App + for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) + and configure your AWS description inputs. +author: Bhavin Patel, Splunk +inputs: +- networkAclId +search: '| search sourcetype=aws:description id={networkAclId} | table id account_id + vpc_id network_acl_entries{}.*' diff --git a/response_tasks/aws_network_interface_details_via_resourceid.yml b/response_tasks/aws_network_interface_details_via_resourceid.yml new file mode 100644 index 0000000000..777e3169f4 --- /dev/null +++ b/response_tasks/aws_network_interface_details_via_resourceid.yml @@ -0,0 +1,17 @@ +name: AWS Network Interface details via resourceId +id: f3fb4d1c-5f33-4b01-b541-c3ah9534c241 +version: '1.0' +date: '2018-05-07' +description: This search queries AWS configuration logs and returns the information + about a specific network interface via network interface ID. The information will + include the ARN of the network interface, its relationships with other AWS resources, + the public and the private IP associated with the network interface. +how_to_implement: In order to implement this search, you must install the AWS App + for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) + and configure your AWS configuration inputs +author: Bhavin Patel, Splunk +inputs: +- resourceId +search: '| search sourcetype=aws:config resourceId={resourceId} | table _time ARN + relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress + configuration.privateIpAddresses{}.association.publicIp' diff --git a/response_tasks/aws_s3_bucket_details_via_bucketname.yml b/response_tasks/aws_s3_bucket_details_via_bucketname.yml new file mode 100644 index 0000000000..2f9e4b4243 --- /dev/null +++ b/response_tasks/aws_s3_bucket_details_via_bucketname.yml @@ -0,0 +1,17 @@ +name: AWS S3 Bucket details via bucketName +id: f3fb2q1c-5f33-4b01-b541-c2ah9534c242 +version: '1.0' +date: '2018-06-26' +description: This search queries AWS configuration logs and returns the information + about a specific S3 bucket. The information returned includes the time the S3 bucket + was created, the resource ID, the region it belongs to, the value of action performed, + AWS account ID, and configuration values of the access-control lists associated + with the bucket. +how_to_implement: To implement this search, you must install the AWS App for Splunk + (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later) and + configure your AWS inputs. +author: Bhavin Patel, Splunk +inputs: +- bucketName +search: '| search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime + resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList' diff --git a/investigations/dns_hijack_enrichment.yml b/response_tasks/dns_hijack_enrichment.yml similarity index 71% rename from investigations/dns_hijack_enrichment.yml rename to response_tasks/dns_hijack_enrichment.yml index 19976edfd4..a7ad943a26 100644 --- a/investigations/dns_hijack_enrichment.yml +++ b/response_tasks/dns_hijack_enrichment.yml @@ -1,12 +1,7 @@ -creation_date: '2017-04-10' -data_metadata: - data_source: - - Censys - - Passive Total - - WHOIS - providing_technologies: - - Splunk Stream - - Bro +name: DNS Hijack Enrichment +id: c096f721-8842-42ce-bfc7-74bd9a72c712 +version: '1.0' +date: '2019-02-14' description: 'This Playbook is part of the Splunk Analytic Story called DNS Hijacking. It is made to be run when the Detection Search within that story called "DNS Record Changed" is used to identify DNS record changes for cloud and corporate domains @@ -31,27 +26,8 @@ how_to_implement: 'If Splunk>Phantom is also configured in your environment, a P (Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\ ' -id: c096f721-8842-42ce-bfc7-74bd9a72c712 -investigate: - phantom: - phantom_server: automation (hostname) - playbook_name: community/dns_hijack_enrichment - playbook_url: https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/ - schedule: - earliest_time: "7200" - latest_time: "0" - sensitivity: green - severity: medium -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -modification_date: '2019-02-14' -name: DNS Hijack Enrichment -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: phantom -version: '1.0' +author: Bhavin Patel, Splunk +playbook: + name: dns_hijack_enrichment + url_json: https://github.com/phantomcyber/playbooks/blob/4.6/dns_hijack_enrichment.json + url_py: https://github.com/phantomcyber/playbooks/blob/4.6/dns_hijack_enrichment.py diff --git a/investigations/domain_cert_investigation.yml b/response_tasks/domain_certificate_investigation.yml similarity index 57% rename from investigations/domain_cert_investigation.yml rename to response_tasks/domain_certificate_investigation.yml index 6910a196a3..8957391034 100644 --- a/investigations/domain_cert_investigation.yml +++ b/response_tasks/domain_certificate_investigation.yml @@ -1,9 +1,7 @@ -creation_date: '2019-04-29' -data_metadata: - data_source: - - Censys - providing_technologies: - - Censys +name: Domain Certificate Investigation +id: c096f721-8842-42ce-2fc7-742d8272b712 +version: '1.0' +date: '2019-04-29' description: Investigate domain names and URLs of a potentially malicious website. These domain names and URLs could come from anywhere, but this Playbook was designed to work with the Splunk Analytic Story focused on evilginx2 phishing techniques @@ -18,34 +16,8 @@ how_to_implement: To successfully implement this phantom playbook, you must inte Enterprise Security with Phantom. Configure this playbook in the correlation search `Detect DNS requests to Phishing Sites leveraging EvilGinx2` ,as an adaptive response action. -id: c096f721-8842-42ce-2fc7-742d8272b712 -investigate: - phantom: - phantom_server: automation (hostname) - playbook_name: community/lets_encrypt_domain_investigate - playbook_url: https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/ - schedule: - cron_schedule: 0 * * * * - earliest_time: '0' - latest_time: '86400' - sensitivity: green - severity: medium -maintainers: - - company: Splunk - email: rnolen@splunk.com - name: 'Russell Nolen ' - - company: Splunk - email: proyer@splunk.com - name: Philip Royer -modification_date: '2019-04-29' -name: Domain Certificate Investigation -original_authors: - - company: Splunk - email: rnolen@splunk.com - name: 'Russell Nolen ' - - company: Splunk - email: proyer@splunk.com - name: Philip Royer -spec_version: 2 -type: phantom -version: '1.0' +author: Philip Royer, Splunk +playbook: + name: lets_encrypt_domain_investigate + url_json: https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json + url_py: https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py diff --git a/investigations/excessive_account_lockouts_enrichment.yml b/response_tasks/excessive_account_lockouts_enrichment_and_response.yml similarity index 56% rename from investigations/excessive_account_lockouts_enrichment.yml rename to response_tasks/excessive_account_lockouts_enrichment_and_response.yml index eec5119daa..6c998e1e9a 100644 --- a/investigations/excessive_account_lockouts_enrichment.yml +++ b/response_tasks/excessive_account_lockouts_enrichment_and_response.yml @@ -1,11 +1,7 @@ -creation_date: '2017-08-17' -data_metadata: - data_models: - - Change - data_source: - - Windows Event Logs - providing_technologies: - - Microsoft Windows +name: Excessive Account Lockouts Enrichment And Response +id: ab62b5c1-95d4-4e71-8fd7-53a55db33da4 +version: '2.0' +date: '2019-02-14' description: This Playbook is part of the Splunk Analytic Story called Account Monitoring and Controls. It is made to be run when the Detection Search within that story called "Detect Excessive Account Lockouts From Endpoint" is used to identify a potential @@ -17,28 +13,8 @@ description: This Playbook is part of the Splunk Analytic Story called Account M to login to the source of the lockouts, gather more information, and allow Phantom to shutdown the server after prompting an analyst or responder. how_to_implement: Import playbook into phantom -id: ab62b5c1-95d4-4e71-8fd7-53a55db33da4 -investigate: - phantom: - phantom_server: automation (hostname) - playbook_name: community/excessive_account_lockouts_enrichment_and_response - playbook_url: https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/ - schedule: - cron_schedule: 0 * * * * - earliest_time: -4h@h - latest_time: -5m@m - sensitivity: green - severity: medium -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2019-02-14' -name: Excessive Account Lockouts Enrichment And Response -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -spec_version: 2 -type: phantom -version: '2.0' +author: Bhavin Patel, Splunk +playbook: + name: excessive_account_lockouts_enrichment_and_response + url_json: https://github.com/phantomcyber/playbooks/blob/4.6/excessive_account_lockouts_enrichment_and_response.json + url_py: https://github.com/phantomcyber/playbooks/blob/4.6/excessive_account_lockouts_enrichment_and_response.py diff --git a/response_tasks/gcp_kubernetes_activity_by_src_ip.yml b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml new file mode 100644 index 0000000000..a3e109e80b --- /dev/null +++ b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml @@ -0,0 +1,21 @@ +name: GCP Kubernetes activity by src_ip +id: c00e7626-92cc-4e06-9a51-b6db0a50bd1f +version: '1.0' +date: '2020-04-13' +description: This search provides investigation data about requests via user agent, + authentication request URI, resource path and cluster name data against Kubernetes + cluster from a specific IP address +how_to_implement: You must install the GCP App for Splunk (version 2.0.0 or later), + then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. + You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection + to filter out FPs. +author: Rod Soto, Splunk +inputs: +- src_user +search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} + | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) + as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names + values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) + as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as + user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name + data.resource.type diff --git a/response_tasks/get_all_aws_activity_from_city.yml b/response_tasks/get_all_aws_activity_from_city.yml new file mode 100644 index 0000000000..b407996b86 --- /dev/null +++ b/response_tasks/get_all_aws_activity_from_city.yml @@ -0,0 +1,19 @@ +name: Get All AWS Activity From City +id: 0abeeb40-1255-4b68-91d1-7a7eb410c4b8 +version: '1.0' +date: '2018-03-19' +description: This search retrieves all the activity from a specific city and will + create a table containing the time, city, ARN, username, the type of user, the source + IP address, the AWS region the activity was in, the API called, and whether or not + the API call was successful. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: David Dorsey, Splunk +inputs: +- City +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search + City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName + path=userIdentity.userName | spath output=userType path=userIdentity.type | rename + sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, + awsRegion, eventName, errorCode' diff --git a/response_tasks/get_all_aws_activity_from_country.yml b/response_tasks/get_all_aws_activity_from_country.yml new file mode 100644 index 0000000000..66dce86c53 --- /dev/null +++ b/response_tasks/get_all_aws_activity_from_country.yml @@ -0,0 +1,19 @@ +name: Get All AWS Activity From Country +id: e763cdb9-00da-41e0-9bda-444debc9501a +version: '1.0' +date: '2018-03-19' +description: This search retrieves all the activity from a specific country and will + create a table containing the time, country, ARN, username, the type of user, the + source IP address, the AWS region the activity was in, the API called, and whether + or not the API call was successful. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: David Dorsey, Splunk +inputs: +- Country +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search + Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName + path=userIdentity.userName | spath output=userType path=userIdentity.type | rename + sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, + awsRegion, eventName, errorCode' diff --git a/response_tasks/get_all_aws_activity_from_ip_address.yml b/response_tasks/get_all_aws_activity_from_ip_address.yml new file mode 100644 index 0000000000..c3b78c5e51 --- /dev/null +++ b/response_tasks/get_all_aws_activity_from_ip_address.yml @@ -0,0 +1,19 @@ +name: Get All AWS Activity From IP Address +id: 446ec87a-85c6-40d4-b060-bea4498281d6 +version: '1.0' +date: '2018-03-19' +description: This search retrieves all the activity from a specific IP address and + will create a table containing the time, ARN, username, the type of user, the IP + address, the AWS region the activity was in, the API called, and whether or not + the API call was successful. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: David Dorsey, Splunk +inputs: +- src_ip +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search + sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName + path=userIdentity.userName | spath output=userType path=userIdentity.type | rename + sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, + eventName, errorCode' diff --git a/response_tasks/get_all_aws_activity_from_region.yml b/response_tasks/get_all_aws_activity_from_region.yml new file mode 100644 index 0000000000..a9d74e75a7 --- /dev/null +++ b/response_tasks/get_all_aws_activity_from_region.yml @@ -0,0 +1,19 @@ +name: Get All AWS Activity From Region +id: 5b794bef-1743-4f6f-804a-43915a2702ff +version: '1.0' +date: '2018-03-19' +description: This search retrieves all the activity from a specific geographic region + and will create a table containing the time, geographic region, ARN, username, the + type of user, the source IP address, the AWS region the activity was in, the API + called, and whether or not the API call was successful. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: David Dorsey, Splunk +inputs: +- Region +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search + Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName + path=userIdentity.userName | spath output=userType path=userIdentity.type | rename + sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, + awsRegion, eventName, errorCode' diff --git a/response_tasks/get_authentication_logs_for_endpoint.yml b/response_tasks/get_authentication_logs_for_endpoint.yml new file mode 100644 index 0000000000..8dfeb3fa32 --- /dev/null +++ b/response_tasks/get_authentication_logs_for_endpoint.yml @@ -0,0 +1,14 @@ +name: Get Authentication Logs For Endpoint +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 +version: '1.0' +date: '2017-11-01' +description: This search returns all users that have attempted to access a particular + endpoint. +how_to_implement: To successfully implement this search you need to be ingesting authentication + logs from your various systems and populating the Authentication data model. +author: Bhavin Patel, Splunk +inputs: +- dest +search: '| tstats count from datamodel=Authentication where Authentication.dest={dest} + by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action + | `drop_dm_object_name("Authentication")`' diff --git a/response_tasks/get_backup_logs_for_endpoint.yml b/response_tasks/get_backup_logs_for_endpoint.yml new file mode 100644 index 0000000000..75b280dc0f --- /dev/null +++ b/response_tasks/get_backup_logs_for_endpoint.yml @@ -0,0 +1,12 @@ +name: Get Backup Logs For Endpoint +id: fdcfb369-1725-4c24-824a-22972d7f0d44 +version: '1.0' +date: '2017-09-14' +description: This search will tell you the backup status from your netbackup_logs + of a specific endpoint for the last week. +how_to_implement: You must be ingesting your backup logs. +author: David Dorsey, Splunk +inputs: +- dest +search: '| search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME + as dest, MESSAGE as signature | table _time, dest, signature' diff --git a/response_tasks/get_certificate_logs_for_a_domain.yml b/response_tasks/get_certificate_logs_for_a_domain.yml new file mode 100644 index 0000000000..822e0b0ae3 --- /dev/null +++ b/response_tasks/get_certificate_logs_for_a_domain.yml @@ -0,0 +1,19 @@ +name: Get Certificate logs for a domain +id: bc91a8cf-35e7-4bb2-2240-e756cc06fd73 +version: '2.0' +date: '2019-04-29' +description: This search queries the Certificates datamodel and give you all the information + for a specific domain. Please note that the certificates issued by "Let's Encrypt" + are widely used by attackers. +how_to_implement: You must be ingesting your certificates or SSL logs from your network + traffic into your Certificates datamodel. Please note the wildcard(*) before domain + in the search syntax, we use to match for all domain and subdomain combinations +author: Bhavin Patel, Splunk +inputs: +- domain +search: '| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime + FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by + All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name + All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` + | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)`' diff --git a/response_tasks/get_dns_server_history_for_a_host.yml b/response_tasks/get_dns_server_history_for_a_host.yml new file mode 100644 index 0000000000..2062e634a2 --- /dev/null +++ b/response_tasks/get_dns_server_history_for_a_host.yml @@ -0,0 +1,16 @@ +name: Get DNS Server History for a host +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 +version: '1.0' +date: '2017-11-09' +description: While investigating any detections it is important to understand which + and how many DNS servers a host has connected to in the past. This search uses data + that is tagged as DNS and gives you a count and list of DNS servers that a particular + host has connected to the previous 24 hours. +how_to_implement: To successfully implement this search, you must be ingesting your + DNS traffic +author: Bhavin Patel, Splunk +inputs: +- src_ip +search: '| search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d + count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort + -count' diff --git a/response_tasks/get_dns_traffic_ratio.yml b/response_tasks/get_dns_traffic_ratio.yml new file mode 100644 index 0000000000..87078796ca --- /dev/null +++ b/response_tasks/get_dns_traffic_ratio.yml @@ -0,0 +1,18 @@ +name: Get DNS traffic ratio +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 +version: '1.0' +date: '2017-11-09' +description: 'This search calculates the ratio of DNS traffic originating and coming + from a host to a list of DNS servers over the last 24 hours. A high value of this + ratio could be very useful to quickly understand if a src_ip (host) is sending a + high volume of data out via port 53, could be an indicator of data exfiltration + via DNS. ' +how_to_implement: You must be ingesting your network traffic +author: Bhavin Patel, Splunk +inputs: +- src_ip +- dest_ip +search: '| tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" + sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic + All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval + ratio = (bytes_out/bytes_in) | table ratio' diff --git a/response_tasks/get_ec2_instance_details_by_instanceid.yml b/response_tasks/get_ec2_instance_details_by_instanceid.yml new file mode 100644 index 0000000000..4d54493250 --- /dev/null +++ b/response_tasks/get_ec2_instance_details_by_instanceid.yml @@ -0,0 +1,20 @@ +name: Get EC2 Instance Details by instanceId +id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 +version: '1.0' +date: '2018-02-12' +description: This search queries AWS description logs and returns all the information + about a specific instance via the instanceId field +how_to_implement: In order to implement this search, you must install the AWS App + for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) + and configure your AWS description inputs. +author: Bhavin Patel, Splunk +inputs: +- instanceId +search: '| search sourcetype="aws:description" source="*:ec2_instances"| dedup id + sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value," + = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table + id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, + state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, + instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time + as "Launch Time", placement as "Availability Zone", state as State, subnet_id as + Subnet, "tags.Name" as Name, vpc_id as VPC' diff --git a/response_tasks/get_ec2_launch_details.yml b/response_tasks/get_ec2_launch_details.yml new file mode 100644 index 0000000000..bfdced961a --- /dev/null +++ b/response_tasks/get_ec2_launch_details.yml @@ -0,0 +1,17 @@ +name: Get EC2 Launch Details +id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 +version: '1.0' +date: '2018-03-12' +description: This search returns some of the launch details for a EC2 instance. +how_to_implement: In order to implement this search, you must install the AWS App + for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) + and configure your AWS description inputs. +author: Bhavin Patel, Splunk +inputs: +- dest +search: '| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} + |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId + as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, + responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture + as architecture, responseElements.instancesSet.items{}.keyName as keyName | table + arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName' diff --git a/response_tasks/get_email_info.yml b/response_tasks/get_email_info.yml new file mode 100644 index 0000000000..aff77d9278 --- /dev/null +++ b/response_tasks/get_email_info.yml @@ -0,0 +1,12 @@ +name: Get Email Info +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd75 +version: '1.0' +date: '2017-11-09' +description: This search returns all the information Splunk might have collected a + specific email message over the last 2 hours. +how_to_implement: To successfully implement this search you must be ingesting your + email logs or capturing unencrypted network traffic which contains email communications. +author: Bhavin Patel, Splunk +inputs: +- message_id +search: '| from datamodel Email.All_Email | search message_id={message_id}' diff --git a/response_tasks/get_emails_from_specific_sender.yml b/response_tasks/get_emails_from_specific_sender.yml new file mode 100644 index 0000000000..80cfc6a695 --- /dev/null +++ b/response_tasks/get_emails_from_specific_sender.yml @@ -0,0 +1,13 @@ +name: Get Emails From Specific Sender +id: 5df39b3f-447d-4869-b673-8f45ad4616fe +version: '1.0' +date: '2017-11-09' +description: This search returns all the emails from a specific sender over the last + 24 and next hours. +how_to_implement: To successfully implement this search you must ingest your email + logs or capture unencrypted email communications within network traffic, and populate + the Email data model. +author: David Dorsey, Splunk +inputs: +- src_user +search: '| from datamodel Email.All_Email | search src_user={src_user}' diff --git a/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml new file mode 100644 index 0000000000..ba126b7dad --- /dev/null +++ b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml @@ -0,0 +1,17 @@ +name: Get First Occurrence and Last Occurrence of a MAC Address +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd33 +version: '1.0' +date: '2017-09-13' +description: This search allows you to gather more context around a notable which + has detected a new device connecting to your network. Use this search to determine + the first and last occurrences of the suspicious device attempting to connect with + your network. +how_to_implement: To successfully implement this search, you must be ingesting the + logs from your DHCP server. +author: Bhavin Patel, Splunk +inputs: +- src_mac +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST + All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`' diff --git a/response_tasks/get_history_of_email_sources.yml b/response_tasks/get_history_of_email_sources.yml new file mode 100644 index 0000000000..725c13cd52 --- /dev/null +++ b/response_tasks/get_history_of_email_sources.yml @@ -0,0 +1,17 @@ +name: Get History Of Email Sources +id: ddc7af28-c34d-4392-af93-7f29a4e8806c +version: '1.0' +date: '2019-02-21' +description: This search returns a list of all email sources seen in the 48 hours + prior to the notable event to 24 hours after, and the number of emails from each + source. +how_to_implement: To successfully implement this search you must ingest your email + logs or capture unencrypted email communications within network traffic, and populate + the Email data model. +author: Rico Valdez, Splunk +inputs: +- src +search: '|tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) + as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email + by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)`' diff --git a/response_tasks/get_logon_rights_modifications_for_endpoint.yml b/response_tasks/get_logon_rights_modifications_for_endpoint.yml new file mode 100644 index 0000000000..7ea9d9de8a --- /dev/null +++ b/response_tasks/get_logon_rights_modifications_for_endpoint.yml @@ -0,0 +1,14 @@ +name: Get Logon Rights Modifications For Endpoint +id: 03bffe94-ec7a-4cbe-b677-6af40d1c4505 +version: '2.0' +date: '2017-09-12' +description: This search allows you to retrieve any modifications to logon rights + associated with a specific host. +how_to_implement: To successfully implement this search you must be ingesting your + Windows event logs +author: David Dorsey, Splunk +inputs: +- dest +search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) + dest={dest} | rename user as "Account Modified" | table _time, dest, "Account Modified", + Access_Right, signature' diff --git a/response_tasks/get_logon_rights_modifications_for_user.yml b/response_tasks/get_logon_rights_modifications_for_user.yml new file mode 100644 index 0000000000..57dd2eeaca --- /dev/null +++ b/response_tasks/get_logon_rights_modifications_for_user.yml @@ -0,0 +1,14 @@ +name: Get Logon Rights Modifications For User +id: 552bc86c-f72c-4d44-b3f2-06ede13af7bb +version: '2.0' +date: '2019-02-27' +description: This search allows you to retrieve any modifications to logon rights + for a specific user account. +how_to_implement: To successfully implement this search you must be ingesting your + Windows event logs +author: David Dorsey, Splunk +inputs: +- user +search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) + user={user} | rename user as "Account Modified" | table _time, dest, "Account Modified", + Access_Right, signature' diff --git a/response_tasks/get_notable_history.yml b/response_tasks/get_notable_history.yml new file mode 100644 index 0000000000..04968ccd83 --- /dev/null +++ b/response_tasks/get_notable_history.yml @@ -0,0 +1,14 @@ +name: Get Notable History +id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 +version: '2.0' +date: '2017-09-20' +description: This search queries the notable index and returns all the Notable Events + for the particular destination host, giving the analyst an overview of the incidents + that may have occurred with the host under investigation. +how_to_implement: If you are using Enterprise Security you are likely already creating + notable events with your correlation rules. No additional configuration is necessary. +author: Bhavin Patel, Splunk +inputs: +- dest +search: '| search `notable` | search dest={dest} | table _time, rule_name, owner, + priority, severity, status_description' diff --git a/response_tasks/get_notable_info.yml b/response_tasks/get_notable_info.yml new file mode 100644 index 0000000000..5fe0d39f0e --- /dev/null +++ b/response_tasks/get_notable_info.yml @@ -0,0 +1,14 @@ +name: Get Notable Info +id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 +version: '1.0' +date: '2017-09-20' +description: This search queries the notable index to retrieve detailed information + captured within the notable. Every notable has a unique ID associated with it, which + is used to point us directly to the notable event under investigation. +how_to_implement: If you are using Enterprise Security you are likely already creating + notable events with your correlation rules. No additional configuration is necessary. +author: Bhavin Patel, Splunk +inputs: +- event_id +search: '| search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, + dest_owner, priority, severity, owner, status_description' diff --git a/response_tasks/get_outbound_emails_to_hidden_cobra_threat_actors.yml b/response_tasks/get_outbound_emails_to_hidden_cobra_threat_actors.yml new file mode 100644 index 0000000000..1a2a00b1b1 --- /dev/null +++ b/response_tasks/get_outbound_emails_to_hidden_cobra_threat_actors.yml @@ -0,0 +1,18 @@ +name: Get Outbound Emails to Hidden Cobra Threat Actors +id: 5df39b3f-347d-4869-b673-8r45ad4616fe +version: '1.0' +date: '2018-06-14' +description: 'This search returns the information of the users that sent emails to + the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, + and from `redhat@gmail.com`.' +how_to_implement: To successfully implement this search you must ingest your email + logs or capture unencrypted email communications within network traffic, and populate + the Email data model. +author: Bhavin Patel, Splunk +inputs: +- src_user +- recipient +search: '| from datamodel Email.All_Email | search recipient=misswang8107@gmail.com + OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) + as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)`' diff --git a/response_tasks/get_parent_process_info.yml b/response_tasks/get_parent_process_info.yml new file mode 100644 index 0000000000..c9e287f9c9 --- /dev/null +++ b/response_tasks/get_parent_process_info.yml @@ -0,0 +1,19 @@ +name: Get Parent Process Info +id: fecf2918-670d-4f1c-872b-3d7317a41bf9 +version: '2.0' +date: '2019-02-28' +description: This search queries the Endpoint data model to give you details about + the parent process of a process running on a host which is under investigation. + Enter the values of the process name in question and the dest +how_to_implement: You must be ingesting endpoint data that tracks process activity, + including parent-child relationships from your endpoints to populate the Endpoint + data model in the Processes node. The command-line arguments are mapped to the "process" + field in the Endpoint data model. +author: Bhavin Patel, Splunk +inputs: +- process_name +- dest +search: '| tstats `summariesonly` count values(Processes.process) as process min(_time) + as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name + = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | + `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' diff --git a/response_tasks/get_process_file_activity.yml b/response_tasks/get_process_file_activity.yml new file mode 100644 index 0000000000..9c9cfe7952 --- /dev/null +++ b/response_tasks/get_process_file_activity.yml @@ -0,0 +1,17 @@ +name: Get Process File Activity +id: 6a9ad4d9-6ef2-4b85-953f-a37ab256acd5 +version: '2.0' +date: '2019-11-06' +description: This search returns the file activity for a specific process on a specific + endpoint +how_to_implement: To successfully implement this search you must be ingesting endpoint + data and populating the Endpoint data model. +author: David Dorsey, Splunk +inputs: +- process_id +- dest +search: '| tstats `security_content_summariesonly` values(Filesystem.file_name) as + file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id + from datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} + by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | + sort _time | table _time, process_id, dest, action, file_name, file_path' diff --git a/response_tasks/get_process_info.yml b/response_tasks/get_process_info.yml new file mode 100644 index 0000000000..355d953b7e --- /dev/null +++ b/response_tasks/get_process_info.yml @@ -0,0 +1,17 @@ +name: Get Process Info +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 +version: '2.0' +date: '2019-04-01' +description: This search queries the Endpoint data model to give you details about + the process running on a host which is under investigation. To gather the process + info, enter the values for the process name in question and the destination IP address. +how_to_implement: To successfully implement this search you must be ingesting endpoint + data and populating the Endpoint data model. +author: Bhavin Patel, Splunk +inputs: +- process_name +- dest +search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as + lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} + by Processes.parent_process Processes.process_name Processes.user Processes.dest + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` ' diff --git a/response_tasks/get_process_information_for_port_activity.yml b/response_tasks/get_process_information_for_port_activity.yml new file mode 100644 index 0000000000..bb55876f40 --- /dev/null +++ b/response_tasks/get_process_information_for_port_activity.yml @@ -0,0 +1,19 @@ +name: Get Process Information For Port Activity +id: 9925d08f-561e-4faa-8912-e3888a842341 +version: '2.0' +date: '2019-04-01' +description: This search will return information about the process associated with + observed network traffic to a specific destination port from a specific host. +how_to_implement: To successfully implement this search you must be ingesting endpoint + data that associates processes with network events and populate the Endpoint Datamodel +author: Bhavin Patel, Splunk +inputs: +- dest_port +- dest +search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as + lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name + Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search + [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where + Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` + | rename src as dest]' diff --git a/response_tasks/get_process_registry_activity.yml b/response_tasks/get_process_registry_activity.yml new file mode 100644 index 0000000000..2655682cc3 --- /dev/null +++ b/response_tasks/get_process_registry_activity.yml @@ -0,0 +1,17 @@ +name: Get Process Registry Activity +id: d8362a34-b78a-4364-9733-59b505f5b8d5 +version: '2.0' +date: '2019-11-06' +description: This search returns the registry activity for a specific process on a + specific endpoint +how_to_implement: To successfully implement this search you must be ingesting endpoint + data and populating the Endpoint data model. +author: David Dorsey, Splunk +inputs: +- process_id +- dest +search: '| tstats `security_content_summariesonly` values(Registry.registry_key_name) + as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) + as process_id from datamodel=Endpoint.Registry where Registry.process_id={process_id} + AND Registry.dest={dest} by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` + | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path' diff --git a/response_tasks/get_process_responsible_for_the_dns_traffic.yml b/response_tasks/get_process_responsible_for_the_dns_traffic.yml new file mode 100644 index 0000000000..1de953a101 --- /dev/null +++ b/response_tasks/get_process_responsible_for_the_dns_traffic.yml @@ -0,0 +1,21 @@ +name: Get Process Responsible For The DNS Traffic +id: 910e6512-edc9-4f93-ba24-5b786f47a672 +version: '2.0' +date: '2019-04-01' +description: While investigating, an analyst will want to know what process and parent_process + is responsible for generating suspicious DNS traffic. Use the following search and + enter the value of `dest` in the search to get specific details on the process responsible + for creating the DNS traffic. +how_to_implement: You must be ingesting endpoint data that associates processes with + network events into the Endpoint datamodel. This can come from endpoint protection + products such as carbon black, or endpoint data sources such as Sysmon. +author: Bhavin Patel, Splunk +inputs: +- dest +search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as + lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process + Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` + | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search + [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where + Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` + | rename src as dest]' diff --git a/response_tasks/get_registry_activities.yml b/response_tasks/get_registry_activities.yml new file mode 100644 index 0000000000..a49cdb6504 --- /dev/null +++ b/response_tasks/get_registry_activities.yml @@ -0,0 +1,20 @@ +name: Get Registry Activities +id: fecf2918-670d-4f1c-872b-3d7317a41xf9 +version: '2.0' +date: '2019-03-01' +description: This search queries the Endpoint Datamodel to give you details of the + latest registry values for a specific destination computer. +how_to_implement: To successfully implement this search you need to be ingesting information + on registry changes that include the name of the process responsible for the changes + from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` + nodes. +author: Bhavin Patel, Splunk +inputs: +- dest +search: '| tstats `security_content_summariesonly` values(Registry.registry_path) + as registry_path values(Registry.registry_key_name) as registry_key_name count FROM + datamodel=Endpoint.Registry where Registry.dest = "{dest}" by Registry.process_id + Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` + count values(Processes.user) as user values(Processes.process_name) as process_name + values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes + where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`]' diff --git a/response_tasks/get_risk_modifiers_for_endpoint.yml b/response_tasks/get_risk_modifiers_for_endpoint.yml new file mode 100644 index 0000000000..5de22cad42 --- /dev/null +++ b/response_tasks/get_risk_modifiers_for_endpoint.yml @@ -0,0 +1,15 @@ +name: Get Risk Modifiers For Endpoint +id: fdcfb369-1725-4c24-824a-22972d7f0d65 +version: '1.0' +date: '2017-10-19' +description: 'For the last 7 days, the search will query the Risk data model in Splunk + Enterprise Security and calculate the count, sum of the risk\_scores, names of the + correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) ' +how_to_implement: Enable the correlation searches included in Splunk Enterprise Security + that include Risk Analysis alert actions by leveraging the Risk Analysis Framework +author: Bhavin Patel, Splunk +inputs: +- dest +search: '| from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} + | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime + max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' diff --git a/response_tasks/get_risk_modifiers_for_user.yml b/response_tasks/get_risk_modifiers_for_user.yml new file mode 100644 index 0000000000..78ca702357 --- /dev/null +++ b/response_tasks/get_risk_modifiers_for_user.yml @@ -0,0 +1,15 @@ +name: Get Risk Modifiers For User +id: fdcfb369-1725-4c24-824a-22972d7f0d55 +version: '1.0' +date: '2017-10-19' +description: 'For the last 7 days, the search will query the Risk data model in Splunk + Enterprise Security and calculate the count, sum of the risk_scores, names of the + correlation searches that contributed to create a risk score for a specific user ' +how_to_implement: Enable the correlation searches included in Splunk Enterprise Security + that include Risk Analysis alert actions by leveraging the Risk Analysis Framework +author: Bhavin Patel, Splunk +inputs: +- user +search: '| from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} + | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime + max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` ' diff --git a/response_tasks/get_sysmon_wmi_activity_for_host.yml b/response_tasks/get_sysmon_wmi_activity_for_host.yml new file mode 100644 index 0000000000..4e8fa68613 --- /dev/null +++ b/response_tasks/get_sysmon_wmi_activity_for_host.yml @@ -0,0 +1,16 @@ +name: Get Sysmon WMI Activity for Host +id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 +version: '1.0' +date: '2018-10-23' +description: This search queries Sysmon WMI events for the host of interest. +how_to_implement: To successfully implement this search, you must be collecting Sysmon + data using Sysmon version 6.1 or greater and have Sysmon configured to generate + events for WMI activity. In addition, you must have at least version 6.0.4 of the + Sysmon TA installed to properly parse the fields. +author: Rico Valdez, Splunk +inputs: +- process +- dest +search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 + EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, + Operation, EventType, Type, Query, Consumer, Filter diff --git a/response_tasks/get_update_logs_for_endpoint.yml b/response_tasks/get_update_logs_for_endpoint.yml new file mode 100644 index 0000000000..e7d01d053b --- /dev/null +++ b/response_tasks/get_update_logs_for_endpoint.yml @@ -0,0 +1,12 @@ +name: Get Update Logs For Endpoint +id: d98675ed-da43-4a7e-96a7-eeca3232ba8e +version: '1.0' +date: '2017-08-24' +description: This search will tell you give you the update logs for a specific endpoint + for the last week. +how_to_implement: You need to be ingesting the update logs from your various systems. +author: David Dorsey, Splunk +inputs: +- dest +search: '| from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" + OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest}' diff --git a/response_tasks/get_user_information_from_identity_table.yml b/response_tasks/get_user_information_from_identity_table.yml new file mode 100644 index 0000000000..42b8dc91a0 --- /dev/null +++ b/response_tasks/get_user_information_from_identity_table.yml @@ -0,0 +1,12 @@ +name: Get User Information from Identity Table +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 +version: '1.0' +date: '2017-09-20' +description: Gather more information about the user identified in the Notable Event. +how_to_implement: To successfully implement this search you must have populated the + identity table with information about your users. +author: Bhavin Patel, Splunk +inputs: +- user +search: '| `identities` | search identity={user} | table _time, identity, first, last, + email, category, watchlist' diff --git a/response_tasks/get_vulnerability_logs_for_endpoint.yml b/response_tasks/get_vulnerability_logs_for_endpoint.yml new file mode 100644 index 0000000000..e364d66ff7 --- /dev/null +++ b/response_tasks/get_vulnerability_logs_for_endpoint.yml @@ -0,0 +1,11 @@ +name: Get Vulnerability Logs For Endpoint +id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 +version: '1.0' +date: '2017-09-10' +description: This search will show you any vulnerabilities noted for a specific endpoint + for the last week. +how_to_implement: You need to be ingesting the logs from your vulnerability scanner. +author: David Dorsey, Splunk +inputs: +- dest +search: '| from datamodel Vulnerabilities.Vulnerabilities | search dest={dest}' diff --git a/response_tasks/get_web_session_information_via_session_id.yml b/response_tasks/get_web_session_information_via_session_id.yml new file mode 100644 index 0000000000..b4d36131c7 --- /dev/null +++ b/response_tasks/get_web_session_information_via_session_id.yml @@ -0,0 +1,16 @@ +name: Get Web Session Information via session_id +id: bc91a8cf-35e7-4bb2-1120-e756cc06fd89 +version: '1.0' +date: '2018-10-08' +description: This search helps an analyst investigate a notable event to find out + more about a specific web session. The search looks for a specific web session ID + in the HTTP web traffic and outputs the URL and user agents, grouped by source IP + address and HTTP status code. +how_to_implement: This search leverages data extracted from Stream:HTTP. You must + configure the HTTP stream using the Splunk Stream App on your Splunk Stream deployment + server. +author: Bhavin Patel, Splunk +inputs: +- session_id +search: '| search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) + by src_ip status' diff --git a/response_tasks/investigate_aws_activities_via_region_name.yml b/response_tasks/investigate_aws_activities_via_region_name.yml new file mode 100644 index 0000000000..c40cfe8db4 --- /dev/null +++ b/response_tasks/investigate_aws_activities_via_region_name.yml @@ -0,0 +1,15 @@ +name: Investigate AWS activities via region name +id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 +version: '1.0' +date: '2018-02-09' +description: This search lists all the user activities logged by CloudTrail for a + specific region in question and will create a table of the values of parameters + requested, the type of the event and the response from the AWS API by each user +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: Bhavin Patel, Splunk +inputs: +- awsRegion +search: '| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId + as instanceId| stats values(eventName) by userName instanceId' diff --git a/response_tasks/investigate_aws_ecr_container_listing_activity.yml b/response_tasks/investigate_aws_ecr_container_listing_activity.yml new file mode 100644 index 0000000000..2a543520ef --- /dev/null +++ b/response_tasks/investigate_aws_ecr_container_listing_activity.yml @@ -0,0 +1,20 @@ +name: Investigate AWS ECR container listing activity +id: 6027623f-7d10-4847-af3b-8d7e87970451 +version: '1.0' +date: '2020-02-20' +description: This search lists all the users performing a list image operation on + AWS Elastic Container Registry. Listing source user, image id, source IP, user type, + http user agent. This search also gives counts of unique user agents per listing + source. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs.You must also install Cloud Infrastructure Data Model. +author: Rod Soto, Rico Valdez, Splunk +inputs: +- Compute.event_name +search: '|tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute + where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id + Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename + "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) + as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count + > 1' diff --git a/response_tasks/investigate_aws_user_activities_by_user_field.yml b/response_tasks/investigate_aws_user_activities_by_user_field.yml new file mode 100644 index 0000000000..dfe55b22fd --- /dev/null +++ b/response_tasks/investigate_aws_user_activities_by_user_field.yml @@ -0,0 +1,16 @@ +name: Investigate AWS User Activities by user field +id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 +version: '1.0' +date: '2018-03-12' +description: This search lists all the logged CloudTrail activities by a specific + user and will create a table containing the source of the user, the region of the + activity, the name and type of the event, the action taken, and the user's identity + information. +how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) + and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail + inputs. +author: Bhavin Patel, Splunk +inputs: +- user +search: '| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type + userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType ' diff --git a/response_tasks/investigate_cloud_compute_instance_activities.yml b/response_tasks/investigate_cloud_compute_instance_activities.yml new file mode 100644 index 0000000000..1e393c68b1 --- /dev/null +++ b/response_tasks/investigate_cloud_compute_instance_activities.yml @@ -0,0 +1,12 @@ +name: Investigate Cloud Compute Instance Activities +id: 33a95cf2-900c-4636-8fca-5c5f71474720 +version: '1.0' +date: '2018-03-12' +description: This search returns a logs of events that operated on the compute instance. +how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs + and have the Security Research cloud data model installed. +author: David Dorsey, Splunk +inputs: +- dest +search: '| from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields + - _*' diff --git a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml new file mode 100644 index 0000000000..2ec144b15d --- /dev/null +++ b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml @@ -0,0 +1,16 @@ +name: Investigate Failed Logins for Multiple Destinations +id: 097e8030-8662-4254-a735-bf0bdda696e3 +version: '1.0' +date: '2019-12-10' +description: This search returns failed logins to multiple destinations by user. +how_to_implement: To successfully implement this search you need to be ingesting authentication + logs from your various systems and populating the Authentication data model. +author: Patrick Bareiss, Splunk +inputs: +- dest +search: '| tstats count `security_content_summariesonly` earliest(_time) as first_login + latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) + AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication + where Authentication.action=failure by Authentication.user | where distinct_count_dest + > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` + | `drop_dm_object_name("Authentication")`' diff --git a/response_tasks/investigate_network_traffic_from_src_ip.yml b/response_tasks/investigate_network_traffic_from_src_ip.yml new file mode 100644 index 0000000000..7d691a147a --- /dev/null +++ b/response_tasks/investigate_network_traffic_from_src_ip.yml @@ -0,0 +1,12 @@ +name: Investigate Network Traffic From src_ip +id: 9df9ca9c-a02b-4f48-9eba-0bac55179050 +version: '1.0' +date: '2018-06-15' +description: This search allows you to find all the network traffic from a specific + IP address. +how_to_implement: To successfully implement this search, you must be ingesting your + web-traffic logs and populating the web data model. +author: David Dorsey, Splunk +inputs: +- src_ip +search: '| from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip}' diff --git a/response_tasks/investigate_okta_activity_by_app.yml b/response_tasks/investigate_okta_activity_by_app.yml new file mode 100644 index 0000000000..ae581cd6ac --- /dev/null +++ b/response_tasks/investigate_okta_activity_by_app.yml @@ -0,0 +1,12 @@ +name: Investigate Okta Activity by app +id: 420eb1b8-2992-45d1-80cf-0b1b2759524d +version: '1.0' +date: '2020-04-02' +description: This search returns all okta events associated with a specific app +how_to_implement: You must be ingesting Okta logs +author: Rico Valdez, Splunk +inputs: +- app +search: eventtype=okta_log app={app} | rename client.geographicalContext.country as + country, client.geographicalContext.state as state, client.geographicalContext.city + as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason diff --git a/response_tasks/investigate_okta_activity_by_ip_address.yml b/response_tasks/investigate_okta_activity_by_ip_address.yml new file mode 100644 index 0000000000..2b83f270d4 --- /dev/null +++ b/response_tasks/investigate_okta_activity_by_ip_address.yml @@ -0,0 +1,12 @@ +name: Investigate Okta Activity by IP Address +id: 56aae066-d619-477c-93e3-3fb83b2d23c3 +version: '1.0' +date: '2020-04-02' +description: This search returns all okta events from a specific IP address. +how_to_implement: You must be ingesting Okta logs +author: Rico Valdez, Splunk +inputs: +- user +search: eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country + as country, client.geographicalContext.state as state, client.geographicalContext.city + as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason diff --git a/response_tasks/investigate_pass_the_hash_attempts.yml b/response_tasks/investigate_pass_the_hash_attempts.yml new file mode 100644 index 0000000000..fe76888d64 --- /dev/null +++ b/response_tasks/investigate_pass_the_hash_attempts.yml @@ -0,0 +1,17 @@ +name: Investigate Pass the Hash Attempts +id: ed3fff45-cba6-4990-983f-6fac72bee659 +version: '1.0' +date: '2019-12-10' +description: This search hunts for dumped NTLM hashes used for pass the hash. +how_to_implement: To successfully implement this search you need be ingesting windows + security logs. This search uses an input macro named `wineventlog_security`. We + strongly recommend that you specify your environment-specific configurations (index, + source, sourcetype, etc.) for Windows Security logs. Replace the macro definition + with configurations for your Splunk environment. The search also uses a post-filter + macro designed to filter out known false positives. +author: Patrick Bareiss, Splunk +inputs: +- dest +search: '`wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate + | stats count earliest(_time) as first_login latest(_time) as last_login by src_user + dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)`' diff --git a/response_tasks/investigate_pass_the_ticket_attempts.yml b/response_tasks/investigate_pass_the_ticket_attempts.yml new file mode 100644 index 0000000000..3e405a2716 --- /dev/null +++ b/response_tasks/investigate_pass_the_ticket_attempts.yml @@ -0,0 +1,18 @@ +name: Investigate Pass the Ticket Attempts +id: 990007ad-d798-4b29-ab2f-f0034144c937 +version: '1.0' +date: '2019-12-10' +description: This search hunts for dumped kerberos ticket from LSASS memory. +how_to_implement: To successfully implement this search you need to be ingesting windows + security logs. This search uses an input macro named `wineventlog_security`. We + strongly recommend that you specify your environment-specific configurations (index, + source, sourcetype, etc.) for Windows Security logs. Replace the macro definition + with configurations for your Splunk environment. The search also uses a post-filter + macro designed to filter out known false positives. +author: Patrick Bareiss, Splunk +inputs: +- dest +search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user + "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) + AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 + | rename new_user AS user' diff --git a/response_tasks/investigate_previous_unseen_user.yml b/response_tasks/investigate_previous_unseen_user.yml new file mode 100644 index 0000000000..83f25dfcff --- /dev/null +++ b/response_tasks/investigate_previous_unseen_user.yml @@ -0,0 +1,19 @@ +name: Investigate Previous Unseen User +id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad +version: '1.0' +date: '2019-12-10' +description: This search returns previous unseen user, which didn't log in for 30 + days. +how_to_implement: To successfully implement this search you need to be ingesting authentication + logs from your various systems and populating the Authentication data model. +author: Patrick Bareiss, Splunk +inputs: +- dest +search: '| tstats count `security_content_summariesonly` earliest(_time) as first_login + latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) + AS Authentication.app values(Authentication.action) AS Authentication.action from + datamodel=Authentication where Authentication.action=success by _time, Authentication.user + | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) + as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user + | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` + | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")`' diff --git a/response_tasks/investigate_successful_remote_desktop_authentications.yml b/response_tasks/investigate_successful_remote_desktop_authentications.yml new file mode 100644 index 0000000000..8b2b2aae9f --- /dev/null +++ b/response_tasks/investigate_successful_remote_desktop_authentications.yml @@ -0,0 +1,18 @@ +name: Investigate Successful Remote Desktop Authentications +id: b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc +version: '1.0' +date: '2018-12-14' +description: 'This search returns the source, destination, and user for all successful + remote-desktop authentications. A successful authentication after a brute-force + attack on a destination machine is suspicious behavior. ' +how_to_implement: You must be populating the Authentication data model with security + events from your Windows event logs. +author: Jose Hernandez, Splunk +inputs: +- dest +search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) + as lastTime from datamodel=Authentication where Authentication.signature_id=4624 + Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app + Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| + table firstTime lastTime src src_nt_domain dest user app count | sort count' diff --git a/response_tasks/investigate_suspicious_strings_in_http_header.yml b/response_tasks/investigate_suspicious_strings_in_http_header.yml new file mode 100644 index 0000000000..eb9fc3a122 --- /dev/null +++ b/response_tasks/investigate_suspicious_strings_in_http_header.yml @@ -0,0 +1,23 @@ +name: Investigate Suspicious Strings in HTTP Header +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd89 +version: '1.0' +date: '2017-10-20' +description: This search helps an analyst investigate a notable event related to a + potential Apache Struts exploitation. To investigate, we will want to isolate and + analyze the "payload" or the commands that were passed to the vulnerable hosts by + creating a few regular expressions to carve out the commands focusing on common + keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns + these suspicious strings found in the HTTP logs of the system of interest. +how_to_implement: This particular search leverages data extracted from Stream:HTTP. + You must configure the http stream using the Splunk Stream App on your Splunk Stream + deployment server to extract the cs_content_type field. +author: Bhavin Patel, Splunk +inputs: +- src_ip +- dest_ip +search: '| search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | eval + cs_content_type_length = len(cs_content_type) | search cs_content_type_length > + 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, + "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious + Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, + cs_content_type, cs_content_type_length, url' diff --git a/response_tasks/investigate_user_activities_in_all_cloud_regions.yml b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml new file mode 100644 index 0000000000..96d65a134a --- /dev/null +++ b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml @@ -0,0 +1,14 @@ +name: Investigate User Activities In All Cloud Regions +id: 2ef6310f-8e79-42af-b20b-b4eeaba9608a +version: '2.0' +date: '2019-04-30' +description: This search lists all the logged cloud infrastructure activities by a + specific cloud user +how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs + and have the Security Research cloud data model installed. +author: David Dorsey, Splunk +inputs: +- region +- src_user +search: '| from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | + fields - _*' diff --git a/response_tasks/investigate_user_activities_in_okta.yml b/response_tasks/investigate_user_activities_in_okta.yml new file mode 100644 index 0000000000..3460b60952 --- /dev/null +++ b/response_tasks/investigate_user_activities_in_okta.yml @@ -0,0 +1,12 @@ +name: Investigate User Activities In Okta +id: 24ff145d-4d16-420a-b047-480f2a51c403 +version: '1.0' +date: '2020-04-02' +description: This search returns all okta events by a specific user +how_to_implement: You must be ingesting Okta logs +author: Rico Valdez, Splunk +inputs: +- user +search: eventtype=okta_log user={user} | rename client.geographicalContext.country + as country, client.geographicalContext.state as state, client.geographicalContext.city + as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason diff --git a/response_tasks/investigate_user_activities_in_single_cloud_region.yml b/response_tasks/investigate_user_activities_in_single_cloud_region.yml new file mode 100644 index 0000000000..1c97891f28 --- /dev/null +++ b/response_tasks/investigate_user_activities_in_single_cloud_region.yml @@ -0,0 +1,14 @@ +name: Investigate User Activities In Single Cloud Region +id: 3dc3a8e7-394b-44ae-8262-4ef8e90b723d +version: '2.0' +date: '2019-04-30' +description: This search lists all the logged cloud infrastructure activities by a + specific cloud user in a specific cloud region +how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs + and have the Security Research cloud data model installed. +author: David Dorsey, Splunk +inputs: +- region +- src_user +search: '| from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} + | fields - _*' diff --git a/response_tasks/investigate_web_activity_from_host.yml b/response_tasks/investigate_web_activity_from_host.yml new file mode 100644 index 0000000000..b4e77d6552 --- /dev/null +++ b/response_tasks/investigate_web_activity_from_host.yml @@ -0,0 +1,13 @@ +name: Investigate Web Activity From Host +id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 +version: '1.0' +date: '2017-11-09' +description: This search allows you to find all the web activity from a specific host. + During an investigation, it is important to profile web activity to characterize + user or host activity. +how_to_implement: To successfully implement this search you must be ingesting your + web traffic and populating the Web data model. +author: Bhavin Patel, Splunk +inputs: +- dest +search: '| from datamodel Web.Web | search src={dest}' diff --git a/response_tasks/investigate_web_activity_from_src_ip.yml b/response_tasks/investigate_web_activity_from_src_ip.yml new file mode 100644 index 0000000000..f0b82ce1bc --- /dev/null +++ b/response_tasks/investigate_web_activity_from_src_ip.yml @@ -0,0 +1,13 @@ +name: Investigate Web Activity From src_ip +id: 2f5b960b-71df-49c0-affc-74992ce60e45 +version: '1.0' +date: '2018-06-15' +description: This search searches for all web activity from a specific host. During + an investigation, it is important to profile web activity to characterize user or + host activity. +how_to_implement: To successfully implement this search, you must be ingesting your + web traffic and populating the web data model. +author: David Dorsey, Splunk +inputs: +- src_ip +search: '| from datamodel Web.Web | search src={src_ip}' diff --git a/response_tasks/investigate_web_posts_from_src.yml b/response_tasks/investigate_web_posts_from_src.yml new file mode 100644 index 0000000000..fa01e69edd --- /dev/null +++ b/response_tasks/investigate_web_posts_from_src.yml @@ -0,0 +1,15 @@ +name: Investigate Web POSTs From src +id: f5c39fac-205c-4e07-9004-8fd61ea3431a +version: '1.0' +date: '2018-12-06' +description: 'This investigative search retrieves POST requests from a specified source + IP or hostname. Identifying the POST requests, as well as their associated destination + URLs and user agent(s), may help you scope and characterize the suspicious traffic. ' +how_to_implement: To successfully implement this search, you must be ingesting your + web-traffic logs and populating the web data model. +author: Jose Hernandez, Splunk +inputs: +- src +search: '| tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web + by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where + like(src, "{src}") and like(http_method, "POST")' diff --git a/response_tasks/malware_hunt_and_contain.yml b/response_tasks/malware_hunt_and_contain.yml new file mode 100644 index 0000000000..c4be6d85eb --- /dev/null +++ b/response_tasks/malware_hunt_and_contain.yml @@ -0,0 +1,10 @@ +name: Malware Hunt and Contain +id: 1d7b437a-5114-4b94-a585-04c3362ba08f +version: '1.0' +date: '2020-04-29' +description: Use the previous identified findings and hunt for the indicators of the malicious file. +author: Patrick Bareiss, Splunk +playbook: + name: malware_hunt_and_contain + url_json: https://github.com/phantomcyber/playbooks/blob/4.6/malware_hunt_and_contain.json + url_py: https://github.com/phantomcyber/playbooks/blob/4.6/malware_hunt_and_contain.py diff --git a/response_tasks/process_chain_analysis.yml b/response_tasks/process_chain_analysis.yml new file mode 100644 index 0000000000..2d4c77f9fd --- /dev/null +++ b/response_tasks/process_chain_analysis.yml @@ -0,0 +1,9 @@ +name: Process Chain Analysis +id: c5506139-ef86-4cd9-8535-0512aa732e79 +version: 1 +date: '2020-04-29' +description: Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. +author: Patrick Bareiss, Splunk +inputs: +- process_guid +search: '`sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count' diff --git a/response_tasks/quarantaine_infected_host.yml b/response_tasks/quarantaine_infected_host.yml new file mode 100644 index 0000000000..6c004211b8 --- /dev/null +++ b/response_tasks/quarantaine_infected_host.yml @@ -0,0 +1,6 @@ +name: Quarantaine Infected Host +id: 60c4cfa5-81b7-44e2-9ad4-71524e4a3e78 +version: 1 +date: '2020-04-29' +description: Quarantine the infected hosts in order to stop the malware from spreading to further hosts. This is a short-term containment with the focus on limiting the damage as soon as possible. +author: Patrick Bareiss, Splunk diff --git a/response_tasks/suspicious_email_attachment_investigate_and_delete.yml b/response_tasks/suspicious_email_attachment_investigate_and_delete.yml new file mode 100644 index 0000000000..702c55bfa9 --- /dev/null +++ b/response_tasks/suspicious_email_attachment_investigate_and_delete.yml @@ -0,0 +1,17 @@ +name: Suspicious Email Attachment Investigate and Delete +id: 3096f721-8842-42ce-2fc7-742d8372b712 +version: '1.0' +date: '2019-06-03' +description: Investigate an email with a suspicious file attachment detected by Splunk + Enterprise Security. Detonate the file attachment in a sandbox, gather network behavior + from the sandbox results, and pivot on those network indicators with both external + reputation queries and internal Splunk Common Information Model searches. After + confirming the results with an analyst prompt, delete the email from the user's + inbox, hopefully before they have opened it. +how_to_implement: Synchronize the community playbook repository in Phantom, then open + the playbook and follow the deployment notes to configure it for your environment. +author: Philip Royer, Splunk +playbook: + name: suspicious_email_attachment_investigate_and_delete + url_json: https://github.com/phantomcyber/playbooks/blob/4.6/suspicious_email_attachment_investigate_and_delete.json + url_py: https://github.com/phantomcyber/playbooks/blob/4.6/suspicious_email_attachment_investigate_and_delete.py diff --git a/responses/README.md b/responses/README.md deleted file mode 100644 index e36fb6a2a5..0000000000 --- a/responses/README.md +++ /dev/null @@ -1,2 +0,0 @@ -### Comming soon to a theater near you - diff --git a/responses/credential_dumping_attack.yml b/responses/credential_dumping_attack.yml new file mode 100644 index 0000000000..875341c547 --- /dev/null +++ b/responses/credential_dumping_attack.yml @@ -0,0 +1,19 @@ +name: Credential Dumping Attack +id: 570dd98e-6cab-443c-bdd8-3dbb5fe4188d +version: 1 +date: '2020-04-29' +description: This response workflow guide you through the investigation of a credential dumping attack. +author: Patrick Bareiss, Splunk +response_tasks: + - identification: + - id: c5506139-ef86-4cd9-8535-0512aa732e79 + name: Process Chain Analysis + - id: 6ee5c067-8228-4926-abb2-54f2c59d726e + name: Analyze Malicious File + - id: 1d7b437a-5114-4b94-a585-04c3362ba08f + name: Malware Hunt and Contain + - containment: + - id: 60c4cfa5-81b7-44e2-9ad4-71524e4a3e78 + name: Quarantaine Infected Host +tags: + analytics_story: Credential Dumping diff --git a/stories/account_monitoring.yml b/stories/account_monitoring.yml deleted file mode 100644 index cb33f90e72..0000000000 --- a/stories/account_monitoring.yml +++ /dev/null @@ -1,50 +0,0 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2017-08-05' -description: A common attack technique is to leverage user accounts to gain unauthorized - access to the target's network. This Analytic Story minimizes opportunities for - attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle - of system and application accounts. -detections: - - detection_id: 475b9e27-17e4-46e2-b7e2-648221be3b89 - name: Identify New User Accounts - type: splunk - - detection_id: b25f6f62-0782-43c1-b403-083231ffd97d - name: Short Lived Windows Accounts - type: splunk - - detection_id: c026e3dd-7e18-4abb-8f41-929e836efe74 - name: Detect Excessive Account Lockouts From Endpoint - type: splunk - - detection_id: 95a7f9a5-6096-437e-a19e-86f42ac609bd - name: Detect Excessive User Account Lockouts - type: splunk -id: 8892a655-6205-55f7-abba-06460e38c8ae -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-06' -name: Account Monitoring and Controls -narrative: Monitoring user accounts within your enterprise is a critical analytic - function that helps ensure that credential and access policies/procedures are properly - implemented and are being enforced. Proactive ad-hoc hunting, as well as routine - monitoring, can ensure user or system accounts are not being abused by unauthorized - individuals or processes. In the event of a network event or breach, user-authentication - logs are a key resource in determining if or how an account might have been compromised - or co-opted, leading to suspicious or malicious activity. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: - - https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf -spec_version: 2 -usecase: Security Monitoring -version: '1.0' diff --git a/stories/account_monitoring_and_controls.yml b/stories/account_monitoring_and_controls.yml new file mode 100644 index 0000000000..10622b4f42 --- /dev/null +++ b/stories/account_monitoring_and_controls.yml @@ -0,0 +1,24 @@ +name: Account Monitoring and Controls +id: 8892a655-6205-55f7-abba-06460e38c8ae +version: '1.0' +date: '2017-09-06' +description: A common attack technique is to leverage user accounts to gain unauthorized + access to the target's network. This Analytic Story minimizes opportunities for + attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle + of system and application accounts. +narrative: Monitoring user accounts within your enterprise is a critical analytic + function that helps ensure that credential and access policies/procedures are properly + implemented and are being enforced. Proactive ad-hoc hunting, as well as routine + monitoring, can ensure user or system accounts are not being abused by unauthorized + individuals or processes. In the event of a network event or breach, user-authentication + logs are a key resource in determining if or how an account might have been compromised + or co-opted, leading to suspicious or malicious activity. +author: David Dorsey, Splunk +type: ESCU +references: +- https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf +tags: + analytics_story: Account Monitoring and Controls + usecase: Security Monitoring + category: + - Best Practices diff --git a/stories/apache_struts.yml b/stories/apache_struts_vulnerability.yml similarity index 89% rename from stories/apache_struts.yml rename to stories/apache_struts_vulnerability.yml index 43e3d15724..4020cbb2f2 100644 --- a/stories/apache_struts.yml +++ b/stories/apache_struts_vulnerability.yml @@ -1,27 +1,10 @@ -category: - - Vulnerability -channel: ESCU -creation_date: '2017-03-14' +name: Apache Struts Vulnerability +id: 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e +version: '1.0' +date: '2018-12-06' description: Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. -detections: - - detection_id: 57a0a2bf-353f-40c1-84dc-29293f3c35b7 - name: Unusually Long Content-Type Length - type: splunk - - detection_id: ec3b7601-689a-4463-94e0-c9f45638efb9 - name: Web Servers Executing Suspicious Processes - type: splunk - - detection_id: if1fea6da-3c86-4c1d-b255-fc3b2781a491 - name: Suspicious Java Classes - type: splunk -id: 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -modification_date: '2018-12-06' -name: Apache Struts Vulnerability narrative: 'In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months @@ -114,12 +97,12 @@ narrative: 'In March of 2017, a remote code-execution vulnerability in the Jakar process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf +tags: + analytics_story: Apache Struts Vulnerability + usecase: Advanced Threat Detection + category: + - Vulnerability diff --git a/stories/asset_tracking.yml b/stories/asset_tracking.yml index 4403bf0611..28df768a2d 100644 --- a/stories/asset_tracking.yml +++ b/stories/asset_tracking.yml @@ -1,21 +1,10 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2017-06-01' +name: Asset Tracking +id: 91c676cf-0b23-438d-abee-f6335e1fce77 +version: '1.0' +date: '2017-09-13' description: Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. -detections: - - detection_id: dcfd6b40-42f9-469d-a433-2e53f7489ff4 - name: Detect Unauthorized Assets by MAC address - type: splunk -id: 91c676cf-0b23-438d-abee-f6335e1fce77 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-13' -name: Asset Tracking narrative: This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business @@ -23,12 +12,12 @@ narrative: This Analytic Story is designed to help you develop a better understa this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/ +tags: + analytics_story: Asset Tracking + usecase: Security Monitoring + category: + - Best Practices diff --git a/stories/aws_cross_account_activity.yml b/stories/aws_cross_account_activity.yml index e50efc062c..151ef37118 100644 --- a/stories/aws_cross_account_activity.yml +++ b/stories/aws_cross_account_activity.yml @@ -1,21 +1,10 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-06-04' +name: AWS Cross Account Activity +id: 2f2f610a-d64d-48c2-b57c-967a2b49ab5a +version: '1.0' +date: '2018-06-04' description: Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. -detections: - - detection_id: 64fbbddf-fabf-4edf-80b3-0cc36ef37727 - name: AWS Cross Account Activity From Previously Unseen Account - type: splunk -id: 2f2f610a-d64d-48c2-b57c-967a2b49ab5a -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-06-04' -name: AWS Cross Account Activity narrative: 'Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS''s Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each @@ -36,12 +25,12 @@ narrative: 'Amazon Web Services (AWS) admins manage access to AWS resources and when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/ +tags: + analytics_story: AWS Cross Account Activity + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/aws_cryptomining.yml b/stories/aws_cryptomining.yml index a09ca63cfd..49fac68c79 100644 --- a/stories/aws_cryptomining.yml +++ b/stories/aws_cryptomining.yml @@ -1,34 +1,11 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-03-08' +name: AWS Cryptomining +id: ced74200-8465-4bc3-bd2c-9a782eec6750 +version: '1.0' +date: '2018-03-08' description: Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. -detections: - - detection_id: ada0f478-84a8-4641-a3f3-d82362d6fd75 - name: EC2 Instance Started In Previously Unseen Region - type: splunk - - detection_id: 2a9b80d3-6340-4345-b5ad-290bf5d0dac4 - name: Abnormally High AWS Instances Launched by User - type: splunk - - detection_id: 65541c80-03c7-4e05-83c8-1dcd57a2e1ad - name: EC2 Instance Started With Previously Unseen Instance Type - type: splunk - - detection_id: 347ec301-601b-48b9-81aa-9ddf9c829dd3 - name: EC2 Instance Started With Previously Unseen AMI - type: splunk - - detection_id: 22773e84-bac0-4595-b086-20d3f735b4f1 - name: EC2 Instance Started With Previously Unseen User - type: splunk -id: ced74200-8465-4bc3-bd2c-9a782eec6750 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-08' -name: AWS Cryptomining narrative: 'Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it''s par for the course that ambitious, @@ -53,12 +30,12 @@ narrative: 'Cryptomining is an intentionally difficult, resource-intensive busin will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +tags: + analytics_story: AWS Cryptomining + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/aws_ec2.yml b/stories/aws_ec2.yml deleted file mode 100644 index f6c1a56022..0000000000 --- a/stories/aws_ec2.yml +++ /dev/null @@ -1,51 +0,0 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-02-09' -description: Use the searches in this Analytic Story to monitor your AWS EC2 instances - for evidence of anomalous activity and suspicious behaviors, such as EC2 instances - that originate from unusual locations or those launched by previously unseen users - (among others). Included investigative searches will help you probe more deeply, - when the information warrants it. -detections: - - detection_id: ada0f478-84a8-4641-a3f3-d82362d6fd75 - name: EC2 Instance Started In Previously Unseen Region - type: splunk - - detection_id: ada0f478-84a8-4641-s3f3-d82362dffd75 - name: Abnormally High AWS Instances Terminated by User - type: splunk - - detection_id: 2a9b80d3-6340-4345-b5ad-290bf5d0dac4 - name: Abnormally High AWS Instances Launched by User - type: splunk - - detection_id: 22773e84-bac0-4595-b086-20d3f735b4f1 - name: EC2 Instance Started With Previously Unseen User - type: splunk - - detection_id: dec41ad5-d579-42cb-b4c6-f5dbb778bbe5 - name: Abnormally High AWS Instances Launched by User - MLTK - type: splunk - - detection_id: 1c02b86a-cd85-473e-a50b-014a9ac8fe3e - name: Abnormally High AWS Instances Terminated by User - MLTK - type: splunk -id: 2e8948a5-5239-406b-b56b-6c50f1268af3 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-02-09' -name: Suspicious AWS EC2 Activities -narrative: AWS CloudTrail is an AWS service that helps you enable governance, compliance, - and risk auditing within your AWS account. Actions taken by a user, role, or an - AWS service are recorded as events in CloudTrail. It is crucial for a company to - monitor events and actions taken in the AWS Console, AWS command-line interface, - and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. - This Analytic Story identifies suspicious activities in your AWS EC2 instances and - helps you respond and investigate those activities. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: - - https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -spec_version: 2 -usecase: Security Monitoring -version: '1.0' diff --git a/stories/aws_network_acl.yml b/stories/aws_network_acl.yml deleted file mode 100644 index 37eba11cb6..0000000000 --- a/stories/aws_network_acl.yml +++ /dev/null @@ -1,44 +0,0 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-01-10' -description: Monitor your AWS network infrastructure for bad configurations and malicious - activity. Investigative searches help you probe deeper, when the facts warrant it. -detections: - - detection_id: ada0f478-84a8-4641-a3f1-d82362d6bd75 - name: AWS Network Access Control List Created with All Open Ports - type: splunk - - detection_id: ada0f478-84a8-4641-a3f1-d82362d6fd75 - name: AWS Network Access Control List Deleted - type: splunk - - detection_id: ada0f278-84a8-46w1-a3f1-w32372d4bd53 - name: Detect Spike in blocked Outbound Traffic from your AWS - type: splunk - - detection_id: ada0f478-84a8-4641-a1f1-e32372d4bd53 - name: Detect Spike in Network ACL Activity - type: splunk -id: 2e8948a5-5239-406b-b56b-6c50ff268af4 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-05-21' -name: AWS Network ACL Activity -narrative: AWS CloudTrail is an AWS service that helps you enable governance, compliance, - and operational/risk auditing of your AWS account. Actions taken by a user, role, - or an AWS service are recorded as events in CloudTrail. It is crucial for a company - to monitor events and actions taken in the AWS Management Console, AWS Command Line - Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable - to attacks. This analytic story contains detection searches that leverage CloudTrail - logs from AWS to check for bad configurations and malicious activity in your AWS - network access controls. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: - - https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html - - https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/ -spec_version: 2 -usecase: Security Monitoring -version: '2.0' diff --git a/stories/aws_network_acl_activity.yml b/stories/aws_network_acl_activity.yml new file mode 100644 index 0000000000..3fa8826eaf --- /dev/null +++ b/stories/aws_network_acl_activity.yml @@ -0,0 +1,24 @@ +name: AWS Network ACL Activity +id: 2e8948a5-5239-406b-b56b-6c50ff268af4 +version: '2.0' +date: '2018-05-21' +description: Monitor your AWS network infrastructure for bad configurations and malicious + activity. Investigative searches help you probe deeper, when the facts warrant it. +narrative: AWS CloudTrail is an AWS service that helps you enable governance, compliance, + and operational/risk auditing of your AWS account. Actions taken by a user, role, + or an AWS service are recorded as events in CloudTrail. It is crucial for a company + to monitor events and actions taken in the AWS Management Console, AWS Command Line + Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable + to attacks. This analytic story contains detection searches that leverage CloudTrail + logs from AWS to check for bad configurations and malicious activity in your AWS + network access controls. +author: Bhavin Patel, Splunk +type: ESCU +references: +- https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html +- https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/ +tags: + analytics_story: AWS Network ACL Activity + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/aws_suspcious_logins.yml b/stories/aws_suspcious_logins.yml deleted file mode 100644 index 4dce0bcb9e..0000000000 --- a/stories/aws_suspcious_logins.yml +++ /dev/null @@ -1,44 +0,0 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-02-24' -description: 'Monitor your AWS authentication events using your CloudTrail logs. Searches - within this Analytic Story will help you stay aware of and investigate suspicious - logins. ' -detections: - - detection_id: ada0f478-84a8-4641-a3f3-d82362dffd75 - name: Detect new user AWS Console Login - type: splunk - - detection_id: 121b0b11-f8ac-4ed6-a132-3800ca4fc07a - name: Detect AWS Console Login by User from New City - type: splunk - - detection_id: 9f31aa8e-e37c-46bc-bce1-8b3be646d026 - name: Detect AWS Console Login by User from New Region - type: splunk - - detection_id: 67bd3def-c41c-4bf6-837b-ae196b4257c6 - name: Detect AWS Console Login by User from New Country - type: splunk -id: 2e8948a5-5239-406b-b56b-6c59f1268af3 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel - - company: Splunk - email: jbrewer@splunk.com - name: Jason Brewer -modification_date: '2019-05-01' -name: Suspicious AWS Login Activities -narrative: It is important to monitor and control who has access to your AWS infrastructure. - Detecting suspicious logins to your AWS infrastructure will provide good starting - points for investigations. Abusive behaviors caused by compromised credentials can - lead to direct monetary costs, as you will be billed for any EC2 instances created - by the attacker. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: - - https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html -spec_version: 2 -usecase: Security Monitoring -version: '1.0' diff --git a/stories/aws_provisioning.yml b/stories/aws_suspicious_provisioning_activities.yml similarity index 59% rename from stories/aws_provisioning.yml rename to stories/aws_suspicious_provisioning_activities.yml index dc06495b73..2385b0fccc 100644 --- a/stories/aws_provisioning.yml +++ b/stories/aws_suspicious_provisioning_activities.yml @@ -1,30 +1,10 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-03-16' +name: AWS Suspicious Provisioning Activities +id: 3338b567-3804-4261-9889-cf0ca4753c7f +version: '1.0' +date: '2018-03-16' description: Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. -detections: - - detection_id: ceb8d3d8-06cb-49eb-beaf-829526e33ff0 - name: AWS Cloud Provisioning From Previously Unseen Country - type: splunk - - detection_id: 7971d3df-da82-4648-a6e5-b5637bea5253 - name: AWS Cloud Provisioning From Previously Unseen Region - type: splunk - - detection_id: 344a1778-0b25-490c-adb1-de8beddf59cd - name: AWS Cloud Provisioning From Previously Unseen City - type: splunk - - detection_id: 42e15012-ac14-4801-94f4-f1acbe64880b - name: AWS Cloud Provisioning From Previously Unseen IP Address - type: splunk -id: 3338b567-3804-4261-9889-cf0ca4753c7f -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-03-16' -name: AWS Suspicious Provisioning Activities narrative: 'Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where @@ -39,12 +19,12 @@ narrative: 'Because most enterprise AWS activities originate from familiar geogr reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +tags: + analytics_story: AWS Suspicious Provisioning Activities + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/aws_user_monitoring.yml b/stories/aws_user_monitoring.yml index b308aa7d2a..0cdc936454 100644 --- a/stories/aws_user_monitoring.yml +++ b/stories/aws_user_monitoring.yml @@ -1,33 +1,10 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-03-12' +name: AWS User Monitoring +id: 2e8948a5-5239-406b-b56b-6c50f1269af3 +version: '1.0' +date: '2018-03-12' description: Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. -detections: - - detection_id: ada0f478-84a8-4641-a3f1-d82362d4bd55 - name: Detect AWS API Activities From Unapproved Accounts - type: splunk - - detection_id: ada0f478-84a8-4641-a3f1-d32362d4bd55 - name: Detect Spike in AWS API Activity - type: splunk - - detection_id: 22773e84-bac0-4595-b086-20d3f335b4f1 - name: Detect new API calls from user roles - type: splunk - - detection_id: ada0f478-84a8-4641-a3f1-e32372d4bd53 - name: Detect Spike in Security Group Activity - type: splunk - - detection_id: 2a9b80d3-6340-4345-w5ad-212bf5d1dac4 - name: Detect API activity from users without MFA - type: splunk -id: 2e8948a5-5239-406b-b56b-6c50f1269af3 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-03-12' -name: AWS User Monitoring narrative: 'It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it''s all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable @@ -48,13 +25,13 @@ narrative: 'It seems obvious that it is critical to monitor and control the user The detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - - https://redlock.io/blog/cryptojacking-tesla -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +- https://redlock.io/blog/cryptojacking-tesla +tags: + analytics_story: AWS User Monitoring + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/brand_monitoring.yml b/stories/brand_monitoring.yml index fdef9aea8f..d7cec56686 100644 --- a/stories/brand_monitoring.yml +++ b/stories/brand_monitoring.yml @@ -1,27 +1,10 @@ -category: - - Abuse -channel: ESCU -creation_date: '2017-06-01' +name: Brand Monitoring +id: 91c676cf-0b23-438d-abee-f6335e1fce78 +version: '1.0' +date: '2017-12-19' description: Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. -detections: - - detection_id: 24dd17b1-e2fb-4c31-878c-d4f746595bfa - name: Monitor DNS For Brand Abuse - type: splunk - - detection_id: b2ea1f38-3a3e-4b8a-9cf1-82760d86a6b8 - name: Monitor Email For Brand Abuse - type: splunk - - detection_id: 134da869-e264-4a8f-8d7e-fcd0ec88f301 - name: Monitor Web Traffic For Brand Abuse - type: splunk -id: 91c676cf-0b23-438d-abee-f6335e1fce78 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-12-19' -name: Brand Monitoring narrative: 'While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and @@ -40,14 +23,14 @@ narrative: 'While you can educate your users and customers about the risks and t provide you with even more actionable intelligence, including likely geographic information, contextual searches to help you scope the problem, and investigative searches.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://www.zerofox.com/blog/what-is-digital-risk-monitoring/ - - https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/ - - https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.zerofox.com/blog/what-is-digital-risk-monitoring/ +- https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/ +- https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/ +tags: + analytics_story: Brand Monitoring + usecase: Advanced Threat Detection + category: + - Abuse diff --git a/stories/cloud_cryptomining.yml b/stories/cloud_cryptomining.yml index d73312b61c..a678ebe75a 100644 --- a/stories/cloud_cryptomining.yml +++ b/stories/cloud_cryptomining.yml @@ -1,34 +1,11 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2019-10-02' +name: Cloud Cryptomining +id: 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a +version: '1.0' +date: '2019-10-02' description: Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. -detections: - - detection_id: fa4089e2-50e3-40f7-8469-d2cc1564ca59 - name: Cloud Compute Instance Started In Previously Unused Region - type: splunk - - detection_id: c6ddbf53-9715-49f3-bb4c-fb2e8a309cda - name: Cloud Compute Instance Created With Previously Unseen Instance Type - type: splunk - - detection_id: bc24922d-987c-4645-b288-f8c73ec194c4 - name: Cloud Compute Instance Created With Previously Unseen Image - type: splunk - - detection_id: 76988f6a-3935-48f6-a9e5-6fca8b3ed843 - name: Cloud Compute Instance Created By Previously Unseen User - type: splunk - - detection_id: dec41ad5-d579-42cb-b4c6-f5dbb778bbe5 - name: Abnormally High AWS Instances Launched by User - MLTK - type: splunk -id: 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2019-10-02' -name: Cloud Cryptomining narrative: 'Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it''s par for the course that ambitious, @@ -44,21 +21,21 @@ narrative: 'Cryptomining is an intentionally difficult, resource-intensive busin usage, and hiding the mining pool''s IP address behind a free CDN. \ When malicious miners appropriate a cloud instance, often spinning up hundreds of - new instances, the costs can become astronomical for the account holder. So it - is critically important to monitor your systems for suspicious activities that could + new instances, the costs can become astronomical for the account holder. So it is + critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ This Analytic Story is focused on detecting suspicious new instances in your cloud - environment to help prevent cryptominers from gaining a foothold. It contains detection searches that - will detect when a previously unused instance type or AMI is used. It also contains - support searches to build lookup files to ensure proper execution of the detection - searches.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey + environment to help prevent cryptominers from gaining a foothold. It contains detection + searches that will detect when a previously unused instance type or AMI is used. + It also contains support searches to build lookup files to ensure proper execution + of the detection searches.' +author: David Dorsey, Splunk +type: ESCU references: - - https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +tags: + analytics_story: Cloud Cryptomining + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/coldroot.yml b/stories/coldroot_macos_rat.yml similarity index 74% rename from stories/coldroot.yml rename to stories/coldroot_macos_rat.yml index c205c366b1..87e3132b30 100644 --- a/stories/coldroot.yml +++ b/stories/coldroot_macos_rat.yml @@ -1,26 +1,12 @@ -category: - - Malware -channel: ESCU -creation_date: '2019-01-29' +name: ColdRoot MacOS RAT +id: bd91a2bc-d20b-4f44-a982-1bea98e86390 +version: '1.0' +date: '2019-01-09' description: Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. -detections: - - detection_id: 2a371608-331d-4034-ae2c-21dda8f1d0ec - name: Processes Tapping Keyboard Events - type: splunk - - detection_id: a6fffe5e-05c3-4c04-badc-887607fbb8dc - name: Osquery pack - ColdRoot detection - type: splunk -id: bd91a2bc-d20b-4f44-a982-1bea98e86390 -maintainers: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez -modification_date: '2019-01-09' -name: ColdRoot MacOS RAT narrative: 'Conventional wisdom holds that Apple''s MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this @@ -45,14 +31,14 @@ narrative: 'Conventional wisdom holds that Apple''s MacOS operating system is si Searches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger.' -original_authors: - - company: Splunk - email: jhernandez@splunk.com - name: Jose Hernandez +author: Jose Hernandez, Splunk +type: ESCU references: - - https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/ - - https://objective-see.com/blog/blog_0x2A.html - - https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/ +- https://objective-see.com/blog/blog_0x2A.html +- https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/ +tags: + analytics_story: ColdRoot MacOS RAT + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/collection_and_staging.yml b/stories/collection_and_staging.yml index adaf727b97..7f913b2bbb 100644 --- a/stories/collection_and_staging.yml +++ b/stories/collection_and_staging.yml @@ -1,34 +1,11 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2018-01-08' +name: Collection and Staging +id: 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a +version: '1.1' +date: '2020-02-03' description: 'Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. ' -detections: - - detection_id: b5541828-8ffd-4070-9d95-b3da4de924cb - name: Suspicious writes to windows Recycle Bin - type: splunk - - detection_id: cd6297cd-2bdd-4aa1-84aa-5d2f84228fac - name: Suspicious writes to System Volume Information - type: splunk - - detection_id: ee18ed37-0802-4268-9435-b3b91aaa18xx - name: Email files written outside of the Outlook directory - type: splunk - - detection_id: 7f5fb3e1-4209-4914-90db-0ec21b556368 - name: Hosts receiving high volume of network traffic from email server - type: splunk - - detection_id: 7f5fb3e1-4209-4914-90db-0ec21b556378 - name: Email servers sending high volume traffic to hosts - type: splunk -id: 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-02-03' -name: Collection and Staging narrative: "A common adversary goal is to identify and exfiltrate data of value from\ \ a target organization. This data may include email conversations and addresses,\ \ confidential company information, links to network design/infrastructure, important\ @@ -40,13 +17,13 @@ narrative: "A common adversary goal is to identify and exfiltrate data of value \ encrypting) it. All of these activities provide opportunities for defenders to\ \ identify their presence. \\\nUse the searches to detect and monitor suspicious\ \ behavior related to these activities." -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://attack.mitre.org/wiki/Collection - - https://attack.mitre.org/wiki/Technique/T1074 -spec_version: 2 -usecase: Security Monitoring -version: '1.1' +- https://attack.mitre.org/wiki/Collection +- https://attack.mitre.org/wiki/Technique/T1074 +tags: + analytics_story: Collection and Staging + usecase: Security Monitoring + category: + - Adversary Tactics diff --git a/stories/command_and_control.yml b/stories/command_and_control.yml index c85f5c7969..df86d114f1 100644 --- a/stories/command_and_control.yml +++ b/stories/command_and_control.yml @@ -1,58 +1,11 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2018-06-01' +name: Command and Control +id: 943773c6-c4de-4f38-89a8-0b92f98804d8 +version: '1.0' +date: '2018-06-01' description: Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. -detections: - - detection_id: e9c102de-4d43-42a7-b1c8-8062ea297419 - name: Detect Large Outbound ICMP Packets - type: splunk - - detection_id: 54dc1265-2f74-4b6d-b30d-49eb506a31b3 - name: Protocol or Port Mismatch - type: splunk - - detection_id: 104658f4-afdc-499f-9719-17a43f9826f4 - name: Detection of DNS Tunnels - type: splunk - - detection_id: ea688274-9c06-4473-b951-e4cb7a5d7a45 - name: TOR Traffic - type: splunk - - detection_id: ce5a0962-849f-4720-a678-753fe6674479 - name: Prohibited Network Traffic Allowed - type: splunk - - detection_id: 74ec6f18-604b-4202-a567-86b2066be3ce - name: Clients Connecting to Multiple DNS Servers - type: splunk - - detection_id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f5 - name: DNS Query Length With High Standard Deviation - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6v5464g9f - name: Detect hosts connecting to dynamic domain providers - type: splunk - - detection_id: 104658f4-afdc-499e-9719-17243f9826f1 - name: Excessive DNS Failures - type: splunk - - detection_id: 05437c07-62f5-452e-afdc-04dd44815bb9 - name: Detect Long DNS TXT Record Response - type: splunk - - detection_id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f6 - name: DNS Query Requests Resolved by Unauthorized DNS Servers - type: splunk - - detection_id: ada0f278-84a8-46w1-a3f1-w32372d4bd53 - name: Detect Spike in blocked Outbound Traffic from your AWS - type: splunk - - detection_id: 85fbcfe8-9718-4911-adf6-7000d077a3a9 - name: DNS Query Length Outliers - MLTK - type: splunk -id: 943773c6-c4de-4f38-89a8-0b92f98804d8 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2018-06-01' -name: Command and Control narrative: 'Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. @@ -69,13 +22,13 @@ narrative: 'Threat actors typically architect and implement an infrastructure to Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://attack.mitre.org/wiki/Command_and_Control - - https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://attack.mitre.org/wiki/Command_and_Control +- https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware +tags: + analytics_story: Command and Control + usecase: Security Monitoring + category: + - Adversary Tactics diff --git a/stories/common_phishing_frameworks.yml b/stories/common_phishing_frameworks.yml index 87ff688f7c..a0357a1435 100644 --- a/stories/common_phishing_frameworks.yml +++ b/stories/common_phishing_frameworks.yml @@ -1,21 +1,10 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2019-04-29' +name: Common Phishing Frameworks +id: 9a64ab44-9214-4639-8163-7eaa2621bd61 +version: '1.0' +date: '2019-04-29' description: 'Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. ' -detections: - - detection_id: 24dd17b1-e2fb-4c31-878c-d4f226595bfa - name: Detect DNS requests to Phishing Sites leveraging EvilGinx2 - type: splunk -id: 9a64ab44-9214-4639-8163-7eaa2621bd61 -maintainers: - - company: Splunk - email: research@splunk.com - name: Splunk Research Team -modification_date: '2019-04-29' -name: Common Phishing Frameworks narrative: 'As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), @@ -33,14 +22,14 @@ narrative: 'As most people know, these emails use fraudulent domains, [email scr Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2.' -original_authors: - - company: Splunk - email: research@splunk.com - name: Splunk Research Team +author: Splunk Research Team, Splunk +type: ESCU references: - - https://github.com/kgretzky/evilginx2 - - https://attack.mitre.org/techniques/T1192/ - - https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://github.com/kgretzky/evilginx2 +- https://attack.mitre.org/techniques/T1192/ +- https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/ +tags: + analytics_story: Common Phishing Frameworks + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/container_implant_story.yml b/stories/container_implant_story.yml deleted file mode 100644 index 55bd8dca69..0000000000 --- a/stories/container_implant_story.yml +++ /dev/null @@ -1,38 +0,0 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2020-02-20' -description: Use the searches in this story to monitor your Kubernetes registry repositories - for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These - searches provide information on source users, destination path, container names and repository - names. The searches provide context to address Mitre T1525 which refers to container implantation - upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry - and Azure Container Registry. -detections: - - detection_id: f0f70b40-f7ad-489d-9905-23d149da8099 - name: New container uploaded to AWS ECR - type: splunk - - detection_id: 4f00ca88-e766-4605-ac65-ae51c9fd185b - name: GCP GCR container uploaded - type: splunk -id: aa0e28b1-0521-4b6f-9d2a-7b87e34af246 -maintainers: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -name: Container Implantation Monitoring & Investigation -narrative: Container Registrys provide a way for organizations to keep customized images of their - development and infrastructure environment in private. However if these repositories are misconfigured - or priviledge users credentials are compromise, attackers can potentially upload implanted containers - which can be deployed across the organization. These searches allow operator to monitor who, when and what - was uploaded to container registry. -original_authors: - - company: Splunk - email: rsoto@splunk.com, rvaldez@splunk.com - name: Rod Soto, Rico Valdez -spec_version: 2 -references: [] -usecase: Security Monitoring -version: '1.0' -references: - - https://github.com/splunk/cloud-datamodel-security-research diff --git a/stories/container_implantation_monitoring_&_investigation.yml b/stories/container_implantation_monitoring_&_investigation.yml new file mode 100644 index 0000000000..e24ac1ff58 --- /dev/null +++ b/stories/container_implantation_monitoring_&_investigation.yml @@ -0,0 +1,26 @@ +name: Container Implantation Monitoring & Investigation +id: aa0e28b1-0521-4b6f-9d2a-7b87e34af246 +version: '1.0' +date: '2020-02-20' +description: Use the searches in this story to monitor your Kubernetes registry repositories + for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. + These searches provide information on source users, destination path, container + names and repository names. The searches provide context to address Mitre T1525 + which refers to container implantation upload to a company's repository either in + Amazon Elastic Container Registry, Google Container Registry and Azure Container + Registry. +narrative: Container Registrys provide a way for organizations to keep customized + images of their development and infrastructure environment in private. However if + these repositories are misconfigured or priviledge users credentials are compromise, + attackers can potentially upload implanted containers which can be deployed across + the organization. These searches allow operator to monitor who, when and what was + uploaded to container registry. +author: Rod Soto, Rico Valdez, Splunk +type: ESCU +references: +- https://github.com/splunk/cloud-datamodel-security-research +tags: + analytics_story: Container Implantation Monitoring & Investigation + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/credential_dumping.yml b/stories/credential_dumping.yml index e921034795..a2dd2ab329 100644 --- a/stories/credential_dumping.yml +++ b/stories/credential_dumping.yml @@ -1,59 +1,12 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2018-08-08' +name: Credential Dumping +id: 854d78bf-d0e2-4f4e-b05c-640905f86d7a +version: '3.0' +date: '2020-02-04' description: Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. -detections: - - detection_id: fb4c31b0-13e8-4155-8aa5-24de4b8d6717 - name: Access LSASS Memory for Dump Creation - type: splunk - - detection_id: 67d4dbef-9564-4699-8da8-03a151529edc - name: Create Remote Thread into LSASS - type: splunk - - detection_id: 2c365e57-4414-4540-8dc0-73ab10729996 - name: Detect Credential Dumping through LSASS access - type: splunk - - detection_id: 56ef054c-76ef-45f9-af4a-a634695dcd65 - name: Unsigned Image Loaded by LSASS - type: splunk - - detection_id: 14038953-e5f2-4daf-acff-5452062baf03 - name: Attempted Credential Dump From Registry via Reg.exe - type: splunk - - detection_id: 29e307ba-40af-4ab2-91b2-3c6b392bbba0 - name: Detect Mimikatz Using Loaded Images - type: splunk - - detection_id: c2590137-0b08-4985-9ec5-6ae23d92f63d - name: Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - type: splunk - - detection_id: eb120f5f-b879-4a63-97c1-93352b5df844 - name: Creation of Shadow Copy - type: splunk - - detection_id: 2ed8b538-d284-449a-be1d-82ad1dbd186b - name: Creation of Shadow Copy with wmic and powershell - type: splunk - - detection_id: d8c406fe-23d2-45f3-a983-1abe7b83ff3b - name: Credential Dumping via Copy Command from Shadowcopy - type: splunk - - detection_id: c5eac648-fae0-4263-91a6-773df1f4c903 - name: Credential Dumping via Symlink to Shadowcopy - type: splunk - - detection_id: 8943b567-f14d-4ee8-a0bb-2121d4ce3184 - name: Dump LSASS via comsvcs DLL - type: splunk -id: 854d78bf-d0e2-4f4e-b05c-640905f86d7a -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez - - company: Splunk - email: pbareiss@splunk.com - name: Patrick Bareiss -modification_date: '2020-02-04' -name: Credential Dumping narrative: 'Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking @@ -69,13 +22,13 @@ narrative: 'Credential dumping—gathering credentials from a target system, The detection searches in this Analytic Story monitor access to the Local Security Authority Subsystem Service (LSASS) process, the usage of shadowcopies for credential dumping and some other techniques for credential dumping.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://attack.mitre.org/wiki/Technique/T1003 - - https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '3.0' +- https://attack.mitre.org/wiki/Technique/T1003 +- https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html +tags: + analytics_story: Credential Dumping + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/data_protection.yml b/stories/data_protection.yml index 196479aedd..dc387a45fc 100644 --- a/stories/data_protection.yml +++ b/stories/data_protection.yml @@ -1,41 +1,24 @@ -category: - - Abuse -channel: ESCU -creation_date: '2017-06-01' +name: Data Protection +id: 91c676cf-0b23-438d-abee-f6335e1fce33 +version: '1.0' +date: '2017-09-14' description: Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. -detections: - - detection_id: 104658f4-afdc-499f-9719-17a43f9826f4 - name: Detection of DNS Tunnels - type: splunk - - detection_id: 104658f4-afdc-499f-9719-17a43f9826f5 - name: Detect USB device insertion - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6v5464g9f - name: Detect hosts connecting to dynamic domain providers - type: splunk -id: 91c676cf-0b23-438d-abee-f6335e1fce33 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-14' -name: Data Protection narrative: Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.cisecurity.org/controls/data-protection/ - - https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022 - - https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://www.cisecurity.org/controls/data-protection/ +- https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022 +- https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ +tags: + analytics_story: Data Protection + usecase: Security Monitoring + category: + - Abuse diff --git a/stories/defense_evasion.yml b/stories/defense_evasion.yml deleted file mode 100644 index f05a1cb486..0000000000 --- a/stories/defense_evasion.yml +++ /dev/null @@ -1,44 +0,0 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-10-11' -description: 'Detect tactics used by malware to evade defenses on Windows endpoints. - A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` - and disabling user-account control, among many others ' -detections: - - detection_id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 - name: Suspicious Reg.exe Process - type: splunk - - detection_id: bbc644bc-37df-4e1a-9c88-ec9a53e2038c - name: Disabling Remote User Account Control - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6b5264g9f - name: Hiding Files And Directories With Attrib.exe - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6b5264x9f - name: Reg.exe used to hide files/directories via registry keys - type: splunk - - detection_id: c9f4b923-f8af-4155-b697-1354f5dcbc5e - name: Remote Registry Key modifications - type: splunk -id: 56e24a28-5003-4047-b2db-e8f3c4618064 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-05-31' -name: Windows Defense Evasion Tactics -narrative: Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that - adversaries employ in a variety of ways to bypass or defeat defensive security measures. - There are many techniques enumerated by the MITRE ATT&CK framework that are applicable - in this context. This Analytic Story includes searches designed to identify the - use of such techniques on Windows platforms. -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -references: - - https://attack.mitre.org/wiki/Defense_Evasion -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' diff --git a/stories/dhs_report_TA18-074A.yml b/stories/dhs_report_TA18-074A.yml deleted file mode 100644 index 7d2b3215da..0000000000 --- a/stories/dhs_report_TA18-074A.yml +++ /dev/null @@ -1,88 +0,0 @@ -category: - - Malware -channel: ESCU -creation_date: '2018-03-19' -description: Monitor for suspicious activities associated with DHS Technical Alert - US-CERT TA18-074A. Some of the activities that adversaries used in these compromises - included spearfishing attacks, malware, watering-hole domains, many and more. -detections: - - detection_id: 7f5fb3e1-4209-4914-90db-0ec21b936378 - name: SMB Traffic Spike - type: splunk - - detection_id: d25773ba-9ad8-48d1-858e-07ad0bbeb828 - name: SMB Traffic Spike - MLTK - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-95dbb162040e - name: Processes launching netsh - type: splunk - - detection_id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 - name: Suspicious Reg.exe Process - type: splunk - - detection_id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d - name: Sc.exe Manipulating Windows Services - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b - name: Registry Keys Used For Persistence - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-151bb162040e - name: Create local admin accounts using net.exe - type: splunk - - detection_id: a4214f0b-e01c-41bc-8cc4-d2b71e3056b4 - name: Single Letter Process On Endpoint - type: splunk - - detection_id: d5af132c-7c17-439c-9d31-13d55340f36c - name: Scheduled Task Name Used by Dragonfly Threat Actors - type: splunk - - detection_id: 9be56c82-b1cc-4318-87eb-d138afaaca39 - name: Malicious PowerShell Process - Execution Policy Bypass - type: splunk - - detection_id: 7f5fb3e1-4209-414-90db-0ec21b936378 - name: Detect Outbound SMB Traffic - type: splunk - - detection_id: b25f6f62-0712-43c1-b203-083231ffd97d - name: Detect New Local Admin account - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-151xb162040e - name: Detect PsExec With accepteula Flag - type: splunk - - detection_id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 - name: First time seen command line argument - type: splunk -id: 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-01-22' -name: DHS Report TA18-074A -narrative: 'The frequency of nation-state cyber attacks has increased significantly - over the last decade. Employing numerous tactics and techniques, these attacks continue - to escalate in complexity. \ - - There is a wide range of motivations for these state-sponsored hacks, including - stealing valuable corporate, military, or diplomatic dataѿall of which could - confer advantages in various arenas. They may also target critical infrastructure. - \ - - One joint Technical Alert (TA) issued by the Department of Homeland and the FBI - in mid-March of 2018 attributed some cyber activity targeting utility infrastructure - to operatives sponsored by the Russian government. The hackers executed spearfishing - attacks, installed malware, employed watering-hole domains, and more. While they - caused no physical damage, the attacks provoked fears that a nation-state could - turn off water, redirect power, or compromise a nuclear power plant.\ - - Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify - the network configuration), suspicious registry modifications, and many more--may - all be events you may wish to investigate further. While the use of these technique - may be an indication that a nation-state actor is attempting to compromise your - environment, it is important to note that these techniques are often employed by - other groups, as well.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: - - https://www.us-cert.gov/ncas/alerts/TA18-074A -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.0' diff --git a/stories/dhs_report_ta18_074a.yml b/stories/dhs_report_ta18_074a.yml new file mode 100644 index 0000000000..f7b17d326d --- /dev/null +++ b/stories/dhs_report_ta18_074a.yml @@ -0,0 +1,38 @@ +name: DHS Report TA18-074A +id: 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef +version: '2.0' +date: '2020-01-22' +description: Monitor for suspicious activities associated with DHS Technical Alert + US-CERT TA18-074A. Some of the activities that adversaries used in these compromises + included spearfishing attacks, malware, watering-hole domains, many and more. +narrative: 'The frequency of nation-state cyber attacks has increased significantly + over the last decade. Employing numerous tactics and techniques, these attacks continue + to escalate in complexity. \ + + There is a wide range of motivations for these state-sponsored hacks, including + stealing valuable corporate, military, or diplomatic dataѿall of which could + confer advantages in various arenas. They may also target critical infrastructure. + \ + + One joint Technical Alert (TA) issued by the Department of Homeland and the FBI + in mid-March of 2018 attributed some cyber activity targeting utility infrastructure + to operatives sponsored by the Russian government. The hackers executed spearfishing + attacks, installed malware, employed watering-hole domains, and more. While they + caused no physical damage, the attacks provoked fears that a nation-state could + turn off water, redirect power, or compromise a nuclear power plant.\ + + Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify + the network configuration), suspicious registry modifications, and many more--may + all be events you may wish to investigate further. While the use of these technique + may be an indication that a nation-state actor is attempting to compromise your + environment, it is important to note that these techniques are often employed by + other groups, as well.' +author: Rico Valdez, Splunk +type: ESCU +references: +- https://www.us-cert.gov/ncas/alerts/TA18-074A +tags: + analytics_story: DHS Report TA18-074A + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/disable_security_tools.yml b/stories/disable_security_tools.yml deleted file mode 100644 index 3e5f59e9de..0000000000 --- a/stories/disable_security_tools.yml +++ /dev/null @@ -1,54 +0,0 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2018-04-09' -description: Looks for activities and techniques associated with the disabling of - security tools on a Windows system, such as suspicious `reg.exe` processes, processes - launching netsh, and many others. -detections: - - detection_id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d - name: Sc.exe Manipulating Windows Services - type: splunk - - detection_id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 - name: Suspicious Reg.exe Process - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-95dbb162040e - name: Processes launching netsh - type: splunk - - detection_id: c8e349c6-b97c-486e-8949-bd7bcd1f3910 - name: Attempt To Stop Security Service - type: splunk - - detection_id: 6bc5243e-ef36-45dc-9b12-f4a6be131159 - name: Attempt To Add Certificate To Untrusted Store - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f665664g9f - name: Unload Sysmon Filter Driver - type: splunk -id: fcc27099-46a0-46b0-a271-5c7dab56b6f1 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-02-04' -name: Disabling Security Tools -narrative: Attackers employ a variety of tactics in order to avoid detection and operate - without barriers. This often involves modifying the configuration of security tools - to get around them or explicitly disabling them to prevent them from running. This - Analytic Story includes searches that look for activity consistent with attackers - attempting to disable various security mechanisms. Such activity may involve monitoring - for suspicious registry activity, as this is where much of the configuration for - Windows and various other programs reside, or explicitly attempting to shut down - security-related services. Other times, attackers attempt various tricks to prevent - specific programs from running, such as adding the certificates with which the security - tools are signed to a blacklist (which would prevent them from running). -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: - - https://attack.mitre.org/wiki/Technique/T1089 - - https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/ - - https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf -spec_version: 2 -usecase: Security Monitoring -version: '2.0' diff --git a/stories/disabling_security_tools.yml b/stories/disabling_security_tools.yml new file mode 100644 index 0000000000..00d5a808f5 --- /dev/null +++ b/stories/disabling_security_tools.yml @@ -0,0 +1,28 @@ +name: Disabling Security Tools +id: fcc27099-46a0-46b0-a271-5c7dab56b6f1 +version: '2.0' +date: '2020-02-04' +description: Looks for activities and techniques associated with the disabling of + security tools on a Windows system, such as suspicious `reg.exe` processes, processes + launching netsh, and many others. +narrative: Attackers employ a variety of tactics in order to avoid detection and operate + without barriers. This often involves modifying the configuration of security tools + to get around them or explicitly disabling them to prevent them from running. This + Analytic Story includes searches that look for activity consistent with attackers + attempting to disable various security mechanisms. Such activity may involve monitoring + for suspicious registry activity, as this is where much of the configuration for + Windows and various other programs reside, or explicitly attempting to shut down + security-related services. Other times, attackers attempt various tricks to prevent + specific programs from running, such as adding the certificates with which the security + tools are signed to a blacklist (which would prevent them from running). +author: Rico Valdez, Splunk +type: ESCU +references: +- https://attack.mitre.org/wiki/Technique/T1089 +- https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/ +- https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf +tags: + analytics_story: Disabling Security Tools + usecase: Security Monitoring + category: + - Adversary Tactics diff --git a/stories/dns_amplification_attacks.yml b/stories/dns_amplification_attacks.yml index d9a22839d2..f18885164d 100644 --- a/stories/dns_amplification_attacks.yml +++ b/stories/dns_amplification_attacks.yml @@ -1,22 +1,11 @@ -category: - - Abuse -channel: ESCU -creation_date: '2016-08-24' +name: DNS Amplification Attacks +id: e8afd39e-3294-11e6-b39d-a45e60c6700 +version: '1.0' +date: '2016-09-13' description: DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. -detections: - - detection_id: 8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb - name: Large Volume of DNS ANY Queries - type: splunk -id: e8afd39e-3294-11e6-b39d-a45e60c6700 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2016-09-13' -name: DNS Amplification Attacks narrative: 'The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification @@ -34,13 +23,13 @@ narrative: 'The Domain Name System (DNS) is the protocol used to map domain name The search in this story can help you to detect if attackers are abusing your company''s DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.us-cert.gov/ncas/alerts/TA13-088A - - https://www.imperva.com/learn/application-security/dns-amplification/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://www.us-cert.gov/ncas/alerts/TA13-088A +- https://www.imperva.com/learn/application-security/dns-amplification/ +tags: + analytics_story: DNS Amplification Attacks + usecase: Security Monitoring + category: + - Abuse diff --git a/stories/dns_hijacking.yml b/stories/dns_hijacking.yml index 71e12483fe..9f2a6fb131 100644 --- a/stories/dns_hijacking.yml +++ b/stories/dns_hijacking.yml @@ -1,29 +1,9 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-11-21' +name: DNS Hijacking +id: 8169f17b-ef68-4b59-aa28-586907301221 +version: '1.0' +date: '2020-02-04' description: Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. -detections: - - detection_id: 44d3a43e-dcd5-49f7-8356-5209bb369065 - name: DNS record changed - type: splunk - - detection_id: 74ec6f18-604b-4202-a567-86b2066be3ce - name: Clients Connecting to Multiple DNS Servers - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6v5464g9f - name: Detect hosts connecting to dynamic domain providers - type: splunk - - detection_id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f6 - name: DNS Query Requests Resolved by Unauthorized DNS Servers - type: splunk -id: 8169f17b-ef68-4b59-aa28-586907301221 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2020-02-04' -name: DNS Hijacking narrative: 'Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections @@ -73,15 +53,15 @@ narrative: 'Dubbed the Achilles heel of the Internet (see https://www.f5.com/lab The searches in this Analytic Story help you detect and investigate activities that may indicate that DNS hijacking has taken place within your environment.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html - - https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ - - http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ - - https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html +- https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ +- http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ +- https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html +tags: + analytics_story: DNS Hijacking + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/dynamic_dns.yml b/stories/dynamic_dns.yml index 0042ed1e9c..806bf27626 100644 --- a/stories/dynamic_dns.yml +++ b/stories/dynamic_dns.yml @@ -1,24 +1,10 @@ -category: - - Malware -channel: ESCU -creation_date: '2017-11-21' +name: Dynamic DNS +id: 8169f17b-ef68-4b59-aae8-586907301221 +version: '2.0' +date: '2018-09-06' description: Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. -detections: - - detection_id: c77162d3-f93c-45cc-80c8-22f6v5464g9f - name: Detect hosts connecting to dynamic domain providers - type: splunk - - detection_id: 134da869-e264-4a8f-8d7e-fcd01c18f301 - name: Detect web traffic to dynamic domain providers - type: splunk -id: 8169f17b-ef68-4b59-aae8-586907301221 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-09-06' -name: Dynamic DNS narrative: Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or @@ -30,15 +16,15 @@ narrative: Dynamic DNS services (DDNS) are legitimate low-cost or free services more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html - - https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ - - http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ - - https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html -spec_version: 2 -usecase: Security Monitoring -version: '2.0' +- https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html +- https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ +- http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ +- https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html +tags: + analytics_story: Dynamic DNS + usecase: Security Monitoring + category: + - Malware diff --git a/stories/emotet.yml b/stories/emotet_malware_(dhs_report_ta18_201a).yml similarity index 50% rename from stories/emotet.yml rename to stories/emotet_malware_(dhs_report_ta18_201a).yml index ef81af6a9f..ce7fe40866 100644 --- a/stories/emotet.yml +++ b/stories/emotet_malware_(dhs_report_ta18_201a).yml @@ -1,46 +1,11 @@ -category: - - Malware -channel: ESCU -creation_date: '2018-09-11' +name: Emotet Malware (DHS Report TA18-201A) +id: bb9f5ed2-916e-4364-bb6d-91c310efcf52 +version: '1.0' +date: '2020-01-27' description: Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. -detections: - - detection_id: 44fddcb2-8d3b-454c-874e-7c6de5a4f7ac - name: Detect Rare Executables - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b - name: Registry Keys Used For Persistence - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-95dbb162039e - name: Detect Use of cmd.exe to Launch Script Interpreters - type: splunk - - detection_id: a51bfe1a-94f0-48cc-b4e4-b6ae50145893 - name: Prohibited Software On Endpoint - type: splunk - - detection_id: 7f5fb3e1-4209-4914-90db-0ec21b936378 - name: SMB Traffic Spike - type: splunk - - detection_id: d25773ba-9ad8-48d1-858e-07ad0bbeb828 - name: SMB Traffic Spike - MLTK - type: splunk - - detection_id: 473bd65f-06ca-4dfe-a2b8-ba04ab4a0084 - name: Suspicious Email Attachment Extensions - type: splunk - - detection_id: 56e877a6-1455-4479-ada6-0550dc1e22f8 - name: Email Attachments With Lots Of Spaces - type: splunk - - detection_id: 1297fb80-f42a-4q4a-9c8b-78c061417cf6 - name: Detection of tools built by NirSoft - type: splunk -id: bb9f5ed2-916e-4364-bb6d-91c310efcf52 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2020-01-27' -name: Emotet Malware (DHS Report TA18-201A) narrative: 'The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), @@ -59,14 +24,14 @@ narrative: 'The trojan downloader known as Emotet first surfaced in 2014, when i survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. ' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.us-cert.gov/ncas/alerts/TA18-201A - - https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf - - https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.us-cert.gov/ncas/alerts/TA18-201A +- https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf +- https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html +tags: + analytics_story: Emotet Malware (DHS Report TA18-201A) + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/hidden_cobra_malware.yml b/stories/hidden_cobra_malware.yml index 0283ca376e..9039a985ac 100644 --- a/stories/hidden_cobra_malware.yml +++ b/stories/hidden_cobra_malware.yml @@ -1,49 +1,11 @@ -category: - - Malware -channel: ESCU -creation_date: '2018-06-14' +name: Hidden Cobra Malware +id: baf7580b-d4b4-4774-8173-7d198e9da335 +version: '2.0' +date: '2020-01-22' description: Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. -detections: - - detection_id: 7f5fb3e1-4209-4914-90db-0ec21b936378 - name: SMB Traffic Spike - type: splunk - - detection_id: d25773ba-9ad8-48d1-858e-07ad0bbeb828 - name: SMB Traffic Spike - MLTK - type: splunk - - detection_id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 - name: First time seen command line argument - type: splunk - - detection_id: 7f5fb3e1-4209-414-90db-0ec21b936378 - name: Detect Outbound SMB Traffic - type: splunk - - detection_id: 272b8407-842d-4b3d-bead-a704584003d3 - name: Remote Desktop Network Traffic - type: splunk - - detection_id: f5939373-8054-40ad-8c64-cec478a22a4a - name: Remote Desktop Process Running On System - type: splunk - - detection_id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f5 - name: DNS Query Length With High Standard Deviation - type: splunk - - detection_id: qw9919ed-fe5f-492c-b139-151bb162140e - name: Create or delete hidden shares using net.exe - type: splunk - - detection_id: 57f76b8a-32f0-42ed-b358-d9fa3ca7bac8 - name: Suspicious File Write - type: splunk - - detection_id: 85fbcfe8-9718-4911-adf6-7000d077a3a9 - name: DNS Query Length Outliers - MLTK - type: splunk -id: baf7580b-d4b4-4774-8173-7d198e9da335 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-01-22' -name: Hidden Cobra Malware narrative: 'North Korea''s government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group''s activity, which the US government refers to as "Hidden Cobra," has surreptitiously @@ -71,13 +33,13 @@ narrative: 'North Korea''s government-sponsored "cyber army" has been slowly bui malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity - - https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.0' +- https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity +- https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf +tags: + analytics_story: Hidden Cobra Malware + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/host_redirection.yml b/stories/host_redirection.yml index 3b16a8b7cb..6774315e9d 100644 --- a/stories/host_redirection.yml +++ b/stories/host_redirection.yml @@ -1,28 +1,11 @@ -category: - - Abuse -channel: ESCU -creation_date: '2017-06-18' +name: Host Redirection +id: 2e8948a5-5239-406b-b56b-6c50fe268af4 +version: '1.0' +date: '2017-09-14' description: Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. -detections: - - detection_id: 74ec6f18-604b-4202-a567-86b2066be3ce - name: Clients Connecting to Multiple DNS Servers - type: splunk - - detection_id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f6 - name: DNS Query Requests Resolved by Unauthorized DNS Servers - type: splunk - - detection_id: 06a6fc63-a72d-41dc-8736-7e3dd9612116 - name: Windows hosts file modification - type: splunk -id: 2e8948a5-5239-406b-b56b-6c50fe268af4 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2017-09-14' -name: Host Redirection narrative: Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) @@ -31,12 +14,12 @@ narrative: Attackers will often attempt to manipulate client communications for site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/ +tags: + analytics_story: Host Redirection + usecase: Advanced Threat Detection + category: + - Abuse diff --git a/stories/jboss_vulnerabilities.yml b/stories/jboss_vulnerability.yml similarity index 89% rename from stories/jboss_vulnerabilities.yml rename to stories/jboss_vulnerability.yml index 5d7958f397..5a6d274939 100644 --- a/stories/jboss_vulnerabilities.yml +++ b/stories/jboss_vulnerability.yml @@ -1,25 +1,11 @@ -category: - - Vulnerability -channel: ESCU -creation_date: '2016-10-04' +name: JBoss Vulnerability +id: 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd +version: '1.0' +date: '2017-09-14' description: In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. -detections: - - detection_id: c8bff7a4-11ea-4416-a27d-c5bca472913d - name: Detect malicious requests to exploit JBoss servers - type: splunk - - detection_id: 104658f4-afdc-499e-9719-17243f982681 - name: Detect attackers scanning for vulnerable JBoss servers - type: splunk -id: 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-14' -name: JBoss Vulnerability narrative: 'This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with @@ -101,12 +87,12 @@ narrative: 'This Analytic Story looks for probing and exploitation attempts targ connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html +tags: + analytics_story: JBoss Vulnerability + usecase: Advanced Threat Detection + category: + - Vulnerability diff --git a/stories/kubernetes_scanning_activity.yml b/stories/kubernetes_scanning_activity.yml index b2deb17c8c..8c7ae44194 100644 --- a/stories/kubernetes_scanning_activity.yml +++ b/stories/kubernetes_scanning_activity.yml @@ -1,33 +1,20 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2020-03-24' -description: This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. -detections: - - detection_id: db5957ec-0144-4c56-b512-9dccbe7a2d26 - name: GCP Kubernetes cluster scan detection - type: splunk - - detection_id: 294c4686-63dd-4fe6-93a2-ca807626704a - name: Amazon EKS Kubernetes cluster scan detection - type: splunk - - detection_id: dbfca1dd-b8e5-4ba4-be0e-e565e5d62002 - name: Amazon EKS Kubernetes Pod scan detection - type: splunk -id: a9ef59cf-e981-4e66-9eef-bb049f695c09 -maintainers: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -modification_date: '2020-04-15' name: Kubernetes Scanning Activity -narrative: Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. -original_authors: - - company: Splunk - email: rsoto@splunk.com - name: Rod Soto -spec_version: 2 -references: [] -usecase: Security Monitoring +id: a9ef59cf-e981-4e66-9eef-bb049f695c09 version: '1.0' +date: '2020-04-15' +description: This story addresses detection against Kubernetes cluster fingerprint + scan and attack by providing information on items such as source ip, user agent, + cluster names. +narrative: Kubernetes is the most used container orchestration platform, this orchestration + platform contains sensitve information and management priviledges of production + workloads, microservices and applications. These searches allow operator to detect + suspicious unauthenticated requests from the internet to kubernetes cluster. +author: Rod Soto, Splunk +type: ESCU references: - - https://github.com/splunk/cloud-datamodel-security-research +- https://github.com/splunk/cloud-datamodel-security-research +tags: + analytics_story: Kubernetes Scanning Activity + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/lateral_movement.yml b/stories/lateral_movement.yml index 1e01455fbb..9e535d8d09 100644 --- a/stories/lateral_movement.yml +++ b/stories/lateral_movement.yml @@ -1,30 +1,10 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2016-09-13' +name: Lateral Movement +id: 399d65dc-1f08-499b-a259-aad9051f38ad +version: '2.0' +date: '2020-02-04' description: Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. -detections: - - detection_id: 1297fb80-f42a-4b4a-9c8a-88c066237cf6 - name: Schtasks scheduling job on remote system - type: splunk - - detection_id: f5939373-8054-40ad-8c64-cec478a22a4a - name: Remote Desktop Process Running On System - type: splunk - - detection_id: 272b8407-842d-4b3d-bead-a704584003d3 - name: Remote Desktop Network Traffic - type: splunk - - detection_id: f5939373-8054-40ad-8c64-cec478a22a4b - name: Detect Activity Related to Pass the Hash Attacks - type: splunk -id: 399d65dc-1f08-499b-a259-aad9051f38ad -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2020-02-04' -name: Lateral Movement narrative: "Once attackers gain a foothold within an enterprise, they will seek to\ \ expand their accesses and leverage techniques that facilitate lateral movement.\ \ Attackers will often spend quite a bit of time and effort moving laterally. Because\ @@ -49,13 +29,13 @@ narrative: "Once attackers gain a foothold within an enterprise, they will seek \ hosts. \\\n It is also important to collect authentication logs for each host,\ \ to ensure that the offending accounts are well-documented. Analysts should account\ \ for all processes to ensure that the attackers did not install unauthorized software." -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis - - https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.0' +- https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis +- https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html +tags: + analytics_story: Lateral Movement + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/malicious_powershell.yml b/stories/malicious_powershell.yml index 179c11f175..5cb44f90d2 100644 --- a/stories/malicious_powershell.yml +++ b/stories/malicious_powershell.yml @@ -1,34 +1,11 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2016-09-18' +name: Malicious PowerShell +id: 2c8ff66e-0b57-42af-8ad7-912438a403fc +version: '4.0' +date: '2017-08-23' description: Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. -detections: - - detection_id: ee18ed37-0802-4268-9435-b3b91aaa18db - name: Malicious PowerShell Process - Connect To Internet With Hidden Window - type: splunk - - detection_id: c4db14d9-7909-48b4-a054-aa14d89dbb19 - name: Malicious PowerShell Process - Encoded Command - type: splunk - - detection_id: 2cdb91d2-542c-497f-b252-be495e71f38c - name: Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - type: splunk - - detection_id: cde75cf6-3c7a-4dd6-af01-27cdb4511fd4 - name: Malicious PowerShell Process With Obfuscation Techniques - type: splunk - - detection_id: c2590137-0b08-4985-9ec5-6ae23d92f63d - name: Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - type: splunk -id: 2c8ff66e-0b57-42af-8ad7-912438a403fc -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-08-23' -name: Malicious PowerShell narrative: 'The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these @@ -83,13 +60,13 @@ narrative: 'The searches in this Analytic Story monitor for parameters often use we suggest reviewing the browsing activity from that system around the time of the event. If categories are given for the URLs visited, that can help you zero in on possible malicious sites.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/ - - https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '4.0' +- https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/ +- https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ +tags: + analytics_story: Malicious PowerShell + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/monitor_backups.yml b/stories/monitor_backup_solution.yml similarity index 57% rename from stories/monitor_backups.yml rename to stories/monitor_backup_solution.yml index 56eafd5d71..0c5e1d1d97 100644 --- a/stories/monitor_backups.yml +++ b/stories/monitor_backup_solution.yml @@ -1,24 +1,10 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2017-06-15' +name: Monitor Backup Solution +id: abe807c7-1eb6-4304-ac32-6e7aacdb891d +version: '1.0' +date: '2017-09-12' description: Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. -detections: - - detection_id: a34aae96-ccf8-4aaa-952c-3ea21444444f - name: Unsuccessful Netbackup backups - type: splunk - - detection_id: a34aae96-ccf8-4aef-952c-3ea214444440 - name: Extended Period Without Successful Netbackup Backups - type: splunk -id: abe807c7-1eb6-4304-ac32-6e7aacdb891d -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-12' -name: Monitor Backup Solution narrative: Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. @@ -26,12 +12,12 @@ narrative: Having backups is a standard best practice that helps ensure continui have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/ -spec_version: 2 -usecase: Compliance -version: '1.0' +- https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/ +tags: + analytics_story: Monitor Backup Solution + usecase: Compliance + category: + - Best Practices diff --git a/stories/detect_unauthorized_processes.yml b/stories/monitor_for_unauthorized_software.yml similarity index 71% rename from stories/detect_unauthorized_processes.yml rename to stories/monitor_for_unauthorized_software.yml index 022c868b8d..65e1d358c7 100644 --- a/stories/detect_unauthorized_processes.yml +++ b/stories/monitor_for_unauthorized_software.yml @@ -1,20 +1,9 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2017-06-26' +name: Monitor for Unauthorized Software +id: 8892a655-6205-43f7-abba-06460e38c8ae +version: '1.0' +date: '2017-09-15' description: 'Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. ' -detections: - - detection_id: a51bfe1a-94f0-48cc-b4e4-b6ae50145893 - name: Prohibited Software On Endpoint - type: splunk -id: 8892a655-6205-43f7-abba-06460e38c8ae -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2017-09-15' -name: Monitor for Unauthorized Software narrative: 'It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within @@ -28,12 +17,12 @@ narrative: 'It is critical to identify unauthorized software and processes runni understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. ' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ -spec_version: 2 -usecase: Compliance -version: '1.0' +- https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ +tags: + analytics_story: Monitor for Unauthorized Software + usecase: Compliance + category: + - Best Practices diff --git a/stories/monitor_for_updates.yml b/stories/monitor_for_updates.yml index 195709f1df..0de634dd83 100644 --- a/stories/monitor_for_updates.yml +++ b/stories/monitor_for_updates.yml @@ -1,21 +1,10 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2017-08-15' +name: Monitor for Updates +id: 9ef8d677-7b52-4213-a038-99cfc7acc2d8 +version: '1.0' +date: '2017-09-15' description: Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. -detections: - - detection_id: 1a77c08c-2f56-409c-a2d3-7d64617edd4f - name: No Windows Updates in a time frame - type: splunk -id: 9ef8d677-7b52-4213-a038-99cfc7acc2d8 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2017-09-15' -name: Monitor for Updates narrative: 'It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important @@ -29,12 +18,12 @@ narrative: 'It is a common best practice to ensure that endpoints are being patc be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://learn.cisecurity.org/20-controls-download -spec_version: 2 -usecase: Compliance -version: '1.0' +- https://learn.cisecurity.org/20-controls-download +tags: + analytics_story: Monitor for Updates + usecase: Compliance + category: + - Best Practices diff --git a/stories/netsh_abuse.yml b/stories/netsh_abuse.yml index d799f7e603..78a84d2c65 100644 --- a/stories/netsh_abuse.yml +++ b/stories/netsh_abuse.yml @@ -1,24 +1,10 @@ -category: - - Abuse -channel: ESCU -creation_date: '2017-01-04' +name: Netsh Abuse +id: 2b1800dd-92f9-47ec-a981-fdf1351e5f65 +version: '1.0' +date: '2017-01-05' description: Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. -detections: - - detection_id: b89919ed-fe5f-492c-b139-95dbb162041e - name: Processes created by netsh - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-95dbb162040e - name: Processes launching netsh - type: splunk -id: 2b1800dd-92f9-47ec-a981-fdf1351e5f65 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-01-05' -name: Netsh Abuse narrative: 'It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you @@ -28,14 +14,14 @@ narrative: 'It is a common practice for attackers of all types to leverage nativ host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://technet.microsoft.com/library/bb490939.aspx - - https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html - - http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://technet.microsoft.com/library/bb490939.aspx +- https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html +- http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html +tags: + analytics_story: Netsh Abuse + usecase: Advanced Threat Detection + category: + - Abuse diff --git a/stories/orangeworm.yml b/stories/orangeworm_attack_group.yml similarity index 70% rename from stories/orangeworm.yml rename to stories/orangeworm_attack_group.yml index c6b3e676c3..1cb4fe7f66 100644 --- a/stories/orangeworm.yml +++ b/stories/orangeworm_attack_group.yml @@ -1,26 +1,9 @@ -category: - - Malware -channel: ESCU -creation_date: '2018-06-14' +name: Orangeworm Attack Group +id: bb9f5ed2-916e-4364-bb6d-97c370efcf52 +version: '2.0' +date: '2020-01-22' description: Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. -detections: - - detection_id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 - name: First time seen command line argument - type: splunk - - detection_id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d - name: Sc.exe Manipulating Windows Services - type: splunk - - detection_id: 823136f2-d755-4b6d-ae04-372b486a5808 - name: First Time Seen Running Windows Service - type: splunk -id: bb9f5ed2-916e-4364-bb6d-97c370efcf52 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2020-01-22' -name: Orangeworm Attack Group narrative: 'In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with @@ -48,13 +31,13 @@ narrative: 'In May of 2018, the attack group Orangeworm was implicated for insta arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia - - https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.0' +- https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia +- https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/ +tags: + analytics_story: Orangeworm Attack Group + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/phishing_payloads.yml b/stories/phishing_payloads.yml index 2b33128ba2..e8cfcc7768 100644 --- a/stories/phishing_payloads.yml +++ b/stories/phishing_payloads.yml @@ -1,23 +1,9 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2019-04-29' +name: Phishing Payloads +id: 57226b40-94f3-4ce5-b101-a75f67759c27 +version: '1.0' +date: '2019-04-29' description: Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. -detections: - - detection_id: a51bfe1a-94f0-4822-b1e4-16ae10145893 - name: Detect Oulook.exe writing a .zip file - type: splunk - - detection_id: 5d814af1-1041-47b5-a9ac-d754e82e9a26 - name: Suspicious LNK file launching a process - type: splunk -id: 57226b40-94f3-4ce5-b101-a75f67759c27 -maintainers: - - company: Splunk - email: research@splunk.com - name: Splunk Research Team -modification_date: '2019-04-29' -name: Phishing Payloads narrative: 'Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ @@ -55,12 +41,12 @@ narrative: 'Despite its simplicity, phishing remains the most pervasive and dang This Analytic Story focuses on detecting signs that a malicious payload has been injected into your environment. For example, one search detects outlook.exe writing a .zip file. Another looks for suspicious .lnk files launching processes.' -original_authors: - - company: Splunk - email: research@splunk.com - name: Splunk Research Team +author: Splunk Research Team, Splunk +type: ESCU references: - - https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html +tags: + analytics_story: Phishing Payloads + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/mudcarp.yml b/stories/possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml similarity index 69% rename from stories/mudcarp.yml rename to stories/possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml index c709025000..68966255b6 100644 --- a/stories/mudcarp.yml +++ b/stories/possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml @@ -1,32 +1,9 @@ -category: - - Adversary Tactics -channel: ESCU channel -creation_date: '2018-07-24' +name: Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns +id: 988C59C5-0A1C-45B6-A555-0C62276E327E +version: '1.0' +date: '2020-01-22' description: Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. -detections: - - detection_id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 - name: First time seen command line argument - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b - name: Registry Keys Used For Persistence - type: splunk - - detection_id: ee18ed37-0802-4268-9435-b3b91aaa18db - name: Malicious PowerShell Process - Connect To Internet With Hidden Window - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6a4264e7f - name: Unusually Long Command Line - type: splunk - - detection_id: 57edaefa-a73b-45e5-bbae-f39c1473f941 - name: Unusually Long Command Line - MLTK - type: splunk -id: 988C59C5-0A1C-45B6-A555-0C62276E327E -maintainers: - - company: iDefense - email: iDefense.IntelOps@accenture.com - name: iDefense Cyber Espionage Team -modification_date: '2020-01-22' -name: Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns narrative: 'This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon @@ -97,13 +74,13 @@ narrative: 'This story was created as a joint effort between iDefense and Splunk 1. b8ec65dab97cdef3cd256cc4753f0c54\ 1. 04d83cd3813698de28cfbba326d7647c' -original_authors: - - company: iDefense - email: iDefense.IntelOps@accenture.com - name: iDefense Cyber Espionage Team +author: iDefense Cyber Espionage Team, iDefense +type: ESCU references: - - https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/ - - http://blog.amossys.fr/badflick-is-not-so-bad.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/ +- http://blog.amossys.fr/badflick-is-not-so-bad.html +tags: + analytics_story: Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/prohibited_traffic_and_protocol_mismatch.yml b/stories/prohibited_traffic_allowed_or_protocol_mismatch.yml similarity index 53% rename from stories/prohibited_traffic_and_protocol_mismatch.yml rename to stories/prohibited_traffic_allowed_or_protocol_mismatch.yml index 85c8a6a65f..cdc7d63caf 100644 --- a/stories/prohibited_traffic_and_protocol_mismatch.yml +++ b/stories/prohibited_traffic_allowed_or_protocol_mismatch.yml @@ -1,30 +1,10 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2017-04-18' +name: Prohibited Traffic Allowed or Protocol Mismatch +id: 6d13121c-90f3-446d-8ac3-27efbbc65218 +version: '1.0' +date: '2017-09-11' description: Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. -detections: - - detection_id: ea688274-9c06-4473-b951-e4cb7a5d7a45 - name: TOR Traffic - type: splunk - - detection_id: ce5a0962-849f-4720-a678-753fe6674479 - name: Prohibited Network Traffic Allowed - type: splunk - - detection_id: 54dc1265-2f74-4b6d-b30d-49eb506a31b3 - name: Protocol or Port Mismatch - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6v5464g9f - name: Detect hosts connecting to dynamic domain providers - type: splunk -id: 6d13121c-90f3-446d-8ac3-27efbbc65218 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2017-09-11' -name: Prohibited Traffic Allowed or Protocol Mismatch narrative: A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. @@ -33,12 +13,12 @@ narrative: A traditional security best practice is to control the ports, protoco policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/ +tags: + analytics_story: Prohibited Traffic Allowed or Protocol Mismatch + usecase: Security Monitoring + category: + - Best Practices diff --git a/stories/ransomware.yml b/stories/ransomware.yml index 1cc5e35a96..4123369d54 100644 --- a/stories/ransomware.yml +++ b/stories/ransomware.yml @@ -1,73 +1,11 @@ -category: - - Malware -channel: ESCU -creation_date: '2017-07-24' +name: Ransomware +id: cf309d0d-d4aa-4fbb-963d-1e79febd3756 +version: '1.1' +date: '2020-02-04' description: Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. -detections: - - detection_id: ad517544-aff9-4c96-bd99-d6eb43bfbb6a - name: Windows Event Log Cleared - type: splunk - - detection_id: 2827c0fd-e1be-4868-ae25-59d28e0f9d4f - name: Suspicious wevtutil Usage - type: splunk - - detection_id: b6e0ff70-b122-4227-9368-4cf322ab43c3 - name: USN Journal Deletion - type: splunk - - detection_id: b89919ed-ee5f-492c-b139-95dbb162039e - name: Deleting Shadow Copies - type: splunk - - detection_id: fdb0f805-74e4-4539-8c00-618927333aae - name: Spike in File Writes - type: splunk - - detection_id: ce5a0962-849f-4720-a678-753fe6674479 - name: Prohibited Network Traffic Allowed - type: splunk - - detection_id: 7f5fb3e1-4209-4914-90db-0ec21b936378 - name: SMB Traffic Spike - type: splunk - - detection_id: d25773ba-9ad8-48d1-858e-07ad0bbeb828 - name: SMB Traffic Spike - MLTK - type: splunk - - detection_id: a9e5c5db-db11-43ca-86a8-c852d1b2c0ec - name: Common Ransomware Extensions - type: splunk - - detection_id: ada0f478-84a8-4641-a3f1-d82362d6bd71 - name: Common Ransomware Notes - type: splunk - - detection_id: a34aae96-ccf8-4aef-952c-3ea21444444d - name: System Processes Run From Unexpected Locations - type: splunk - - detection_id: d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da - name: Remote Process Instantiation via WMI - type: splunk - - detection_id: ea688274-9c06-4473-b951-e4cb7a5d7a45 - name: TOR Traffic - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b - name: Registry Keys Used For Persistence - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6a4264e7f - name: Unusually Long Command Line - type: splunk - - detection_id: 57edaefa-a73b-45e5-bbae-f39c1473f941 - name: Unusually Long Command Line - MLTK - type: splunk - - detection_id: 1297fb80-f42a-4b4a-9c8b-78c066437cf6 - name: Scheduled tasks used in BadRabbit ransomware - type: splunk - - detection_id: 1297fb80-f42a-4b4a-9c8a-88c066437cf6 - name: Schtasks used for forcing a reboot - type: splunk -id: cf309d0d-d4aa-4fbb-963d-1e79febd3756 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2020-02-04' -name: Ransomware narrative: Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect @@ -77,13 +15,13 @@ narrative: Ransomware is an ever-present risk to the enterprise, wherein an infe functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/ - - https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.1' +- https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/ +- https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html +tags: + analytics_story: Ransomware + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/routers_and_infrastructure.yml b/stories/router_&_infrastructure_security.yml similarity index 64% rename from stories/routers_and_infrastructure.yml rename to stories/router_&_infrastructure_security.yml index b79d1c9ae3..fec9cc09c1 100644 --- a/stories/routers_and_infrastructure.yml +++ b/stories/router_&_infrastructure_security.yml @@ -1,21 +1,10 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2017-06-01' +name: Router & Infrastructure Security +id: 91c676cf-0b23-438d-abee-f6335e177e77 +version: '1.0' +date: '2017-09-12' description: Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. -detections: - - detection_id: 104658f4-afdc-499e-9719-17243rr826f1 - name: Detect New Login Attempts to Routers - type: splunk -id: 91c676cf-0b23-438d-abee-f6335e177e77 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-12' -name: Router & Infrastructure Security narrative: 'Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon @@ -26,13 +15,13 @@ narrative: 'Networking devices, such as routers and switches, are often overlook are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company''s internal infrastructure— effectively increasing the attack surface and accessing private services/data.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html - - https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html +- https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html +tags: + analytics_story: Router & Infrastructure Security + usecase: Security Monitoring + category: + - Best Practices diff --git a/stories/samsam.yml b/stories/samsam_ransomware.yml similarity index 55% rename from stories/samsam.yml rename to stories/samsam_ransomware.yml index 74fbdc2d20..de72c064d6 100644 --- a/stories/samsam.yml +++ b/stories/samsam_ransomware.yml @@ -1,58 +1,11 @@ -category: - - Malware -channel: ESCU -creation_date: '2018-12-13' +name: SamSam Ransomware +id: c4b89506-fbcf-4cb7-bfd6-527e54789604 +version: '1.0' +date: '2018-12-13' description: Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. -detections: - - detection_id: b89919ed-ee5f-492c-b139-95dbb162039e - name: Deleting Shadow Copies - type: splunk - - detection_id: fdb0f805-74e4-4539-8c00-618927333aae - name: Spike in File Writes - type: splunk - - detection_id: a9e5c5db-db11-43ca-86a8-c852d1b2c0ec - name: Common Ransomware Extensions - type: splunk - - detection_id: ada0f478-84a8-4641-a3f1-d82362d6bd71 - name: Common Ransomware Notes - type: splunk - - detection_id: a51bfe1a-94f0-48cc-b4e4-b6ae50145893 - name: Prohibited Software On Endpoint - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-151xb162040e - name: Detect PsExec With accepteula Flag - type: splunk - - detection_id: 272b8407-842d-4b3d-bead-a704584003d3 - name: Remote Desktop Network Traffic - type: splunk - - detection_id: 104658f4-afdc-499e-9719-17243f982681 - name: Detect attackers scanning for vulnerable JBoss servers - type: splunk - - detection_id: c8bff7a4-11ea-4416-a27d-c5bca472913d - name: Detect malicious requests to exploit JBoss servers - type: splunk - - detection_id: a98727cc-286b-4ff2-b898-41df64695923 - name: Remote Desktop Network Bruteforce - type: splunk - - detection_id: 02c6cfc2-ae66-4735-bfc7-6291da834cbf - name: File with Samsam Extension - type: splunk - - detection_id: 69c12d59-d951-431e-ab77-ec426b8d65e6 - name: Samsam Test File Write - type: splunk - - detection_id: 503d17cb-9eab-4cf8-a20e-01d5c6987ae3 - name: Batch File Write to System32 - type: splunk -id: c4b89506-fbcf-4cb7-bfd6-527e54789604 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2018-12-13' -name: SamSam Ransomware narrative: 'The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost @@ -87,14 +40,14 @@ narrative: 'The first version of the SamSam ransomware (a.k.a. Samas or SamsamCr of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/ - - https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/ - - https://thehackernews.com/2018/07/samsam-ransomware-attacks.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/ +- https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/ +- https://thehackernews.com/2018/07/samsam-ransomware-attacks.html +tags: + analytics_story: SamSam Ransomware + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/spectre_meltdown.yml b/stories/spectre_and_meltdown_vulnerabilities.yml similarity index 53% rename from stories/spectre_meltdown.yml rename to stories/spectre_and_meltdown_vulnerabilities.yml index 9acb30f1fa..a139f6f056 100644 --- a/stories/spectre_meltdown.yml +++ b/stories/spectre_and_meltdown_vulnerabilities.yml @@ -1,30 +1,19 @@ -category: - - Vulnerability -channel: ESCU -creation_date: '2018-01-08' +name: Spectre And Meltdown Vulnerabilities +id: 6d3306f6-bb2b-4219-8609-8efad64032f2 +version: '1.0' +date: '2018-01-08' description: Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. -detections: - - detection_id: 354be8e0-32cd-4da0-8c47-796de13b60ea - name: Spectre and Meltdown Vulnerable Systems - type: splunk -id: 6d3306f6-bb2b-4219-8609-8efad64032f2 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-01-08' -name: Spectre And Meltdown Vulnerabilities narrative: Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://meltdownattack.com/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://meltdownattack.com/ +tags: + analytics_story: Spectre And Meltdown Vulnerabilities + usecase: Security Monitoring + category: + - Vulnerability diff --git a/stories/splunk_vulnerabilities.yml b/stories/splunk_enterprise_vulnerability.yml similarity index 72% rename from stories/splunk_vulnerabilities.yml rename to stories/splunk_enterprise_vulnerability.yml index 97e1e46d20..d55921eeb1 100644 --- a/stories/splunk_vulnerabilities.yml +++ b/stories/splunk_enterprise_vulnerability.yml @@ -1,22 +1,11 @@ -category: - - Vulnerability -channel: ESCU -creation_date: '2016-09-13' +name: Splunk Enterprise Vulnerability +id: 4e692b96-de2d-4bd1-9105-37e2368a8db1 +version: '1.0' +date: '2017-09-19' description: Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. -detections: - - detection_id: d199fb99-2312-451a-9daa-e5efa6ed76a7 - name: Open Redirect in Splunk Web - type: splunk -id: 4e692b96-de2d-4bd1-9105-37e2368a8db1 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-19' -name: Splunk Enterprise Vulnerability narrative: 'This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ @@ -42,13 +31,13 @@ narrative: 'This Analytic Story is associated with CVE-2016-4859, an open-redire is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - http://www.splunk.com/view/SP-CAAAPQ6#announce - - https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859 -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- http://www.splunk.com/view/SP-CAAAPQ6#announce +- https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859 +tags: + analytics_story: Splunk Enterprise Vulnerability + usecase: Security Monitoring + category: + - Vulnerability diff --git a/stories/splunk_information_disclosure.yml b/stories/splunk_enterprise_vulnerability_cve_2018_11409.yml similarity index 75% rename from stories/splunk_information_disclosure.yml rename to stories/splunk_enterprise_vulnerability_cve_2018_11409.yml index d6038ffe38..0e6f40222a 100644 --- a/stories/splunk_information_disclosure.yml +++ b/stories/splunk_enterprise_vulnerability_cve_2018_11409.yml @@ -1,21 +1,10 @@ -category: - - Vulnerability -channel: ESCU -creation_date: '2018-06-14' +name: Splunk Enterprise Vulnerability CVE-2018-11409 +id: 1fc34cbc-34e9-43ba-87ab-6811c9e95400 +version: '1.0' +date: '2018-06-14' description: Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. -detections: - - detection_id: f6a26b7b-7e80-4963-a9a8-d836e7534ebd - name: Splunk Enterprise Information Disclosure - type: splunk -id: 1fc34cbc-34e9-43ba-87ab-6811c9e95400 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-06-14' -name: Splunk Enterprise Vulnerability CVE-2018-11409 narrative: 'Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). @@ -36,14 +25,14 @@ narrative: 'Although there have been no reports of it being exploited, Splunk En in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://nvd.nist.gov/vuln/detail/CVE-2018-11409 - - https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings - - https://www.exploit-db.com/exploits/44865/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://nvd.nist.gov/vuln/detail/CVE-2018-11409 +- https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings +- https://www.exploit-db.com/exploits/44865/ +tags: + analytics_story: Splunk Enterprise Vulnerability CVE-2018-11409 + usecase: Security Monitoring + category: + - Vulnerability diff --git a/stories/sql_injection.yml b/stories/sql_injection.yml index 71a21fe09b..1682357c00 100644 --- a/stories/sql_injection.yml +++ b/stories/sql_injection.yml @@ -1,34 +1,23 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2016-09-13' +name: SQL Injection +id: 4f6632f5-449c-4686-80df-57625f59bab3 +version: '1.0' +date: '2017-09-19' description: Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. -detections: - - detection_id: e0aad4cf-0790-423b-8328-7564d0d938f9 - name: SQL Injection with Long URLs - type: splunk -id: 4f6632f5-449c-4686-80df-57625f59bab3 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-19' -name: SQL Injection narrative: 'It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://capec.mitre.org/data/definitions/66.html - - https://www.incapsula.com/web-application-security/sql-injection.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://capec.mitre.org/data/definitions/66.html +- https://www.incapsula.com/web-application-security/sql-injection.html +tags: + analytics_story: SQL Injection + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/suspicious_aws_ec2_activities.yml b/stories/suspicious_aws_ec2_activities.yml new file mode 100644 index 0000000000..3cbc3e2f57 --- /dev/null +++ b/stories/suspicious_aws_ec2_activities.yml @@ -0,0 +1,25 @@ +name: Suspicious AWS EC2 Activities +id: 2e8948a5-5239-406b-b56b-6c50f1268af3 +version: '1.0' +date: '2018-02-09' +description: Use the searches in this Analytic Story to monitor your AWS EC2 instances + for evidence of anomalous activity and suspicious behaviors, such as EC2 instances + that originate from unusual locations or those launched by previously unseen users + (among others). Included investigative searches will help you probe more deeply, + when the information warrants it. +narrative: AWS CloudTrail is an AWS service that helps you enable governance, compliance, + and risk auditing within your AWS account. Actions taken by a user, role, or an + AWS service are recorded as events in CloudTrail. It is crucial for a company to + monitor events and actions taken in the AWS Console, AWS command-line interface, + and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. + This Analytic Story identifies suspicious activities in your AWS EC2 instances and + helps you respond and investigate those activities. +author: Bhavin Patel, Splunk +type: ESCU +references: +- https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +tags: + analytics_story: Suspicious AWS EC2 Activities + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/suspicious_aws_login_activities.yml b/stories/suspicious_aws_login_activities.yml new file mode 100644 index 0000000000..09f456b120 --- /dev/null +++ b/stories/suspicious_aws_login_activities.yml @@ -0,0 +1,21 @@ +name: Suspicious AWS Login Activities +id: 2e8948a5-5239-406b-b56b-6c59f1268af3 +version: '1.0' +date: '2019-05-01' +description: 'Monitor your AWS authentication events using your CloudTrail logs. Searches + within this Analytic Story will help you stay aware of and investigate suspicious + logins. ' +narrative: It is important to monitor and control who has access to your AWS infrastructure. + Detecting suspicious logins to your AWS infrastructure will provide good starting + points for investigations. Abusive behaviors caused by compromised credentials can + lead to direct monetary costs, as you will be billed for any EC2 instances created + by the attacker. +author: Bhavin Patel, Splunk +type: ESCU +references: +- https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html +tags: + analytics_story: Suspicious AWS Login Activities + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/aws_s3.yml b/stories/suspicious_aws_s3_activities.yml similarity index 59% rename from stories/aws_s3.yml rename to stories/suspicious_aws_s3_activities.yml index 493803dcbc..69ffeae043 100644 --- a/stories/aws_s3.yml +++ b/stories/suspicious_aws_s3_activities.yml @@ -1,28 +1,11 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-06-25' +name: Suspicious AWS S3 Activities +id: 2e8948a5-5239-406b-b56b-6c50w3168af3 +version: '2.0' +date: '2018-07-24' description: Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. -detections: - - detection_id: 2a9b80d3-6340-4345-b5ad-290bf3d0dac4 - name: Detect New Open S3 buckets - type: splunk - - detection_id: 2a9b80d3-6340-4345-b5ad-291bq3d0daq4 - name: Detect S3 access from a new IP - type: splunk - - detection_id: ad12w478-84a8-4641-a3w1-e32372q4bd53 - name: Detect Spike in S3 Bucket deletion - type: splunk -id: 2e8948a5-5239-406b-b56b-6c50w3168af3 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-07-24' -name: Suspicious AWS S3 Activities narrative: 'As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ @@ -35,13 +18,13 @@ narrative: 'As cloud computing has exploded, so has the number of creative attac Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. ' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - - https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/ -spec_version: 2 -usecase: Security Monitoring -version: '2.0' +- https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +- https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/ +tags: + analytics_story: Suspicious AWS S3 Activities + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/aws_suspcious_traffic.yml b/stories/suspicious_aws_traffic.yml similarity index 74% rename from stories/aws_suspcious_traffic.yml rename to stories/suspicious_aws_traffic.yml index ccb672683b..1255d6d35e 100644 --- a/stories/aws_suspcious_traffic.yml +++ b/stories/suspicious_aws_traffic.yml @@ -1,21 +1,10 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-05-07' +name: Suspicious AWS Traffic +id: 2e8948a5-5239-406b-b56b-6c50f2168af3 +version: '1.0' +date: '2018-05-07' description: Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). -detections: - - detection_id: ada0f278-84a8-46w1-a3f1-w32372d4bd53 - name: Detect Spike in blocked Outbound Traffic from your AWS - type: splunk -id: 2e8948a5-5239-406b-b56b-6c50f2168af3 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-05-07' -name: Suspicious AWS Traffic narrative: "A virtual private cloud (VPC) is an on-demand managed cloud-computing\ \ service that isolates computing resources for each client. Inside the VPC container,\ \ the environment resembles a physical network. \\\nAmazon's VPC service enables\ @@ -31,12 +20,12 @@ narrative: "A virtual private cloud (VPC) is an on-demand managed cloud-computin \ in and out of your network and to alert you to suspicious activities.\\\nThe searches\ \ in this Analytic Story will monitor your AWS network traffic for evidence of anomalous\ \ activity and suspicious behaviors." -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/ +tags: + analytics_story: Suspicious AWS Traffic + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/suspicious_cmd_line_executions.yml b/stories/suspicious_cmd_line_executions.yml deleted file mode 100644 index fc6f98d9af..0000000000 --- a/stories/suspicious_cmd_line_executions.yml +++ /dev/null @@ -1,54 +0,0 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-10-09' -description: Leveraging the Windows command-line interface (CLI) is one of the most - common attack techniques--one that is also detailed in the MITRE ATT&CK framework. - Use this Analytic Story to help you identify unusual or suspicious use of the CLI - on Windows systems. -detections: - - detection_id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 - name: First time seen command line argument - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6a4264e7f - name: Unusually Long Command Line - type: splunk - - detection_id: 57edaefa-a73b-45e5-bbae-f39c1473f941 - name: Unusually Long Command Line - MLTK - type: splunk - - detection_id: dcfd6b40-42f9-469d-a433-2e53f7486664 - name: Detect Prohibited Applications Spawning cmd.exe - type: splunk - - detection_id: b89919ed-fe5f-492c-b139-95dbb162039e - name: Detect Use of cmd.exe to Launch Script Interpreters - type: splunk - - detection_id: a34aae96-ccf8-4aef-952c-3ea21444444d - name: System Processes Run From Unexpected Locations - type: splunk -id: f4368ddf-d59f-4192-84f6-778ac5a3ffc7 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2020-02-03' -name: Suspicious Command-Line Executions -narrative: The ability to execute arbitrary commands via the Windows CLI is a primary - goal for the adversary. With access to the shell, an attacker can easily run scripts - and interact with the target system. Often, attackers may only have limited access - to the shell or may obtain access in unusual ways. In addition, malware may execute - and interact with the CLI in ways that would be considered unusual and inconsistent - with typical user activity. This provides defenders with opportunities to identify - suspicious use and investigate, as appropriate. This Analytic Story contains various - searches to help identify this suspicious activity, as well as others to aid you - in deeper investigation. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: - - https://attack.mitre.org/wiki/Technique/T1059 - - https://www.microsoft.com/en-us/wdsi/threats/macro-malware - - https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.1' diff --git a/stories/suspicious_command_line_executions.yml b/stories/suspicious_command_line_executions.yml new file mode 100644 index 0000000000..abf90b1828 --- /dev/null +++ b/stories/suspicious_command_line_executions.yml @@ -0,0 +1,28 @@ +name: Suspicious Command-Line Executions +id: f4368ddf-d59f-4192-84f6-778ac5a3ffc7 +version: '2.1' +date: '2020-02-03' +description: Leveraging the Windows command-line interface (CLI) is one of the most + common attack techniques--one that is also detailed in the MITRE ATT&CK framework. + Use this Analytic Story to help you identify unusual or suspicious use of the CLI + on Windows systems. +narrative: The ability to execute arbitrary commands via the Windows CLI is a primary + goal for the adversary. With access to the shell, an attacker can easily run scripts + and interact with the target system. Often, attackers may only have limited access + to the shell or may obtain access in unusual ways. In addition, malware may execute + and interact with the CLI in ways that would be considered unusual and inconsistent + with typical user activity. This provides defenders with opportunities to identify + suspicious use and investigate, as appropriate. This Analytic Story contains various + searches to help identify this suspicious activity, as well as others to aid you + in deeper investigation. +author: Bhavin Patel, Splunk +type: ESCU +references: +- https://attack.mitre.org/wiki/Technique/T1059 +- https://www.microsoft.com/en-us/wdsi/threats/macro-malware +- https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf +tags: + analytics_story: Suspicious Command-Line Executions + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/suspicious_dns_traffic.yml b/stories/suspicious_dns_traffic.yml index ac7d895153..00165c4bf7 100644 --- a/stories/suspicious_dns_traffic.yml +++ b/stories/suspicious_dns_traffic.yml @@ -1,42 +1,10 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2016-09-13' +name: Suspicious DNS Traffic +id: 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 +version: '1.0' +date: '2017-09-18' description: Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. -detections: - - detection_id: 104658f4-afdc-499e-9719-17243f9826f1 - name: Excessive DNS Failures - type: splunk - - detection_id: 74ec6f18-604b-4202-a567-86b2066be3ce - name: Clients Connecting to Multiple DNS Servers - type: splunk - - detection_id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f5 - name: DNS Query Length With High Standard Deviation - type: splunk - - detection_id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f6 - name: DNS Query Requests Resolved by Unauthorized DNS Servers - type: splunk - - detection_id: 05437c07-62f5-452e-afdc-04dd44815bb9 - name: Detect Long DNS TXT Record Response - type: splunk - - detection_id: 104658f4-afdc-499f-9719-17a43f9826f4 - name: Detection of DNS Tunnels - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6v5464g9f - name: Detect hosts connecting to dynamic domain providers - type: splunk - - detection_id: 85fbcfe8-9718-4911-adf6-7000d077a3a9 - name: DNS Query Length Outliers - MLTK - type: splunk -id: 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2017-09-18' -name: Suspicious DNS Traffic narrative: Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One @@ -46,14 +14,14 @@ narrative: Although DNS is one of the fundamental underlying protocols that make involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/ - - http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680 - - https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454 -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/ +- http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680 +- https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454 +tags: + analytics_story: Suspicious DNS Traffic + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/suspicious_emails.yml b/stories/suspicious_emails.yml index d5181c7ce9..a21875c8af 100644 --- a/stories/suspicious_emails.yml +++ b/stories/suspicious_emails.yml @@ -1,30 +1,10 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-03-24' +name: Suspicious Emails +id: 2b1800dd-92f9-47ec-a981-fdf1351e5d55 +version: '1.0' +date: '2020-01-27' description: Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. -detections: - - detection_id: b2ea1f38-3a3e-4b8a-9cf1-82760d86a6b8 - name: Monitor Email For Brand Abuse - type: splunk - - detection_id: 473bd65f-06ca-4dfe-a2b8-ba04ab4a0084 - name: Suspicious Email Attachment Extensions - type: splunk - - detection_id: 56e877a6-1455-4479-ada6-0550dc1e22f8 - name: Email Attachments With Lots Of Spaces - type: splunk - - detection_id: 56e877a6-1455-4479-ad16-0550dc1e33f8 - name: Suspicious Email - UBA Anomaly - type: uba -id: 2b1800dd-92f9-47ec-a981-fdf1351e5d55 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2020-01-27' -name: Suspicious Emails narrative: 'It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk @@ -41,12 +21,12 @@ narrative: 'It is a common practice for attackers of all types to leverage targe attachment or clicking on a malicious URL)?This Analytic Story provides detection searches to identify suspicious emails, as well as contextual and investigative searches to help answer some of these questions.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/ +tags: + analytics_story: Suspicious Emails + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/suspicious_mshta_activities.yml b/stories/suspicious_mshta_activity.yml similarity index 59% rename from stories/suspicious_mshta_activities.yml rename to stories/suspicious_mshta_activity.yml index 6e8a5894db..7a0695e709 100644 --- a/stories/suspicious_mshta_activities.yml +++ b/stories/suspicious_mshta_activity.yml @@ -1,26 +1,9 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2018-08-07' +name: Suspicious MSHTA Activity +id: 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 +version: '1.1' +date: '2020-02-03' description: Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. -detections: - - detection_id: b89919ed-fe5f-492c-b139-95dqb161039e - name: Detect mshta.exe running scripts in command-line arguments - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b - name: Registry Keys Used For Persistence - type: splunk - - detection_id: dcfd6b40-42f9-469d-a433-2e53f7486664 - name: Detect Prohibited Applications Spawning cmd.exe - type: splunk -id: 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2020-02-03' -name: Suspicious MSHTA Activity narrative: 'One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution @@ -35,14 +18,14 @@ narrative: 'One common adversary tactic is to bypass application white-listing s The searches in this story help you detect and investigate suspicious activity that may indicate that an attacker is leveraging mshta.exe to execute malicious code.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://redcanary.com/blog/windows-registry-attacks-threat-detection/ - - https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5 - - https://attack.mitre.org/wiki/Technique/T1170 -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.1' +- https://redcanary.com/blog/windows-registry-attacks-threat-detection/ +- https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5 +- https://attack.mitre.org/wiki/Technique/T1170 +tags: + analytics_story: Suspicious MSHTA Activity + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/suspicious_okta_activities.yml b/stories/suspicious_okta_activities.yml deleted file mode 100644 index fd5ba53fad..0000000000 --- a/stories/suspicious_okta_activities.yml +++ /dev/null @@ -1,55 +0,0 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2020-04-02' -description: Monitor your Okta environment for suspicious activities. Due to the Covid - outbreak, many users are migrating over to leverage cloud services more and more. - Okta is a popular tool to manage multiple users and the web-based applications they need - to stay productive. The searches in this story will help monitor your Okta environment for - suspicious activities and associated user behaviors. -detections: - - detection_id: 371a6545-2618-4032-ad84-93386b8698c5 - name: Okta Failed SSO Attempts - type: splunk - - detection_id: 19cba45f-cad3-4032-8911-0c09e0444552 - name: Multiple Okta Users With Invalid Credentails From The Same IP - type: splunk - - detection_id: 62b70968-a0a5-4724-8ac4-67871e6f544d - name: Okta Account Lockout Events - type: splunk - - detection_id: 7594fa07-9f34-4d01-81cc-d6af6a5db9e8 - name: Okta User Logins From Multiple Cities - type: splunk -id: 9cbd34af-8f39-4476-a423-bacd126c750b -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2020-04-02' -name: Suspicious Okta Activity -narrative: Okta is the leading single sign on (SSO) provider, allowing users to authenticate once - to Okta, and from there access a variety of web-based applications. These applications are - assigned to users and allow administrators to centrally manage which users are allowed to - access which applications. It also provides centralized logging to help understand how the - applications are used and by whom. \ - - While SSO is a major convenience for users, it also provides attackers with an opportunity. - If the attacker can gain access to Okta, they can access a variety of applications. - As such monitoring the environment is important. \ - - With people moving quickly to adopt web-based applications and ways to manage them, many - are still struggling to understand how best to monitor these environments. This analytic - story provides searches to help monitor this environment, and identify events and activity - that warrant further investigation such as credential stuffing or password spraying attacks, - and users logging in from multiple locations when travel is disallowed. -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -references: - - https://attack.mitre.org/wiki/Technique/T1078 - - https://owasp.org/www-community/attacks/Credential_stuffing - - https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work -spec_version: 2 -usecase: Security Monitoring -version: '1.0' diff --git a/stories/suspicious_okta_activity.yml b/stories/suspicious_okta_activity.yml new file mode 100644 index 0000000000..ad8bb93b80 --- /dev/null +++ b/stories/suspicious_okta_activity.yml @@ -0,0 +1,36 @@ +name: Suspicious Okta Activity +id: 9cbd34af-8f39-4476-a423-bacd126c750b +version: '1.0' +date: '2020-04-02' +description: Monitor your Okta environment for suspicious activities. Due to the Covid + outbreak, many users are migrating over to leverage cloud services more and more. + Okta is a popular tool to manage multiple users and the web-based applications they + need to stay productive. The searches in this story will help monitor your Okta + environment for suspicious activities and associated user behaviors. +narrative: 'Okta is the leading single sign on (SSO) provider, allowing users to authenticate + once to Okta, and from there access a variety of web-based applications. These applications + are assigned to users and allow administrators to centrally manage which users are + allowed to access which applications. It also provides centralized logging to help + understand how the applications are used and by whom. \ + + While SSO is a major convenience for users, it also provides attackers with an opportunity. + If the attacker can gain access to Okta, they can access a variety of applications. + As such monitoring the environment is important. \ + + With people moving quickly to adopt web-based applications and ways to manage them, + many are still struggling to understand how best to monitor these environments. + This analytic story provides searches to help monitor this environment, and identify + events and activity that warrant further investigation such as credential stuffing + or password spraying attacks, and users logging in from multiple locations when + travel is disallowed.' +author: Rico Valdez, Splunk +type: ESCU +references: +- https://attack.mitre.org/wiki/Technique/T1078 +- https://owasp.org/www-community/attacks/Credential_stuffing +- https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work +tags: + analytics_story: Suspicious Okta Activity + usecase: Security Monitoring + category: + - Adversary Tactics diff --git a/stories/suspicious_windows_registry_activities.yml b/stories/suspicious_windows_registry_activities.yml index b1d42e9710..31cf8be151 100644 --- a/stories/suspicious_windows_registry_activities.yml +++ b/stories/suspicious_windows_registry_activities.yml @@ -1,41 +1,9 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2018-05-31' +name: Suspicious Windows Registry Activities +id: 2b1800dd-92f9-47dd-a981-fdf1351e5d55 +version: '1.0' +date: '2018-05-31' description: Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. -detections: - - detection_id: c9f4b923-f8af-4155-b697-1354f5dcbc5e - name: Remote Registry Key modifications - type: splunk - - detection_id: 1b989a0e-0129-4446-a695-f193a5b746fc - name: Suspicious Changes to File Associations - type: splunk - - detection_id: bbc644bc-37df-4e1a-9c88-ec9a53e2038c - name: Disabling Remote User Account Control - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01bbb - name: Registry Keys for Creating SHIM Databases - type: splunk - - detection_id: f5f6af30-7ba7-4295-bfe9-07de87c01bbc - name: Monitor Registry Keys for Print Monitors - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6b5264x9f - name: Reg.exe used to hide files/directories via registry keys - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b - name: Registry Keys Used For Persistence - type: splunk - - detection_id: c9f4b923-f8af-4155-b697-1354f5bcbc5e - name: Registry Keys Used For Privilege Escalation - type: splunk -id: 2b1800dd-92f9-47dd-a981-fdf1351e5d55 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-05-31' -name: Suspicious Windows Registry Activities narrative: "Attackers are developing increasingly sophisticated techniques for hijacking\ \ target servers, while evading detection. One such technique that has become progressively\ \ more common is registry modification.\\\n The registry is a key component of the\ @@ -45,13 +13,13 @@ narrative: "Attackers are developing increasingly sophisticated techniques for h \ administrator-level privileges, maintain persistence, and move laterally within\ \ the environment.\\\n The searches in this story are designed to help you detect\ \ behaviors associated with manipulation of the Windows registry." -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://redcanary.com/blog/windows-registry-attacks-threat-detection/ - - https://attack.mitre.org/wiki/Technique/T1112 -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://redcanary.com/blog/windows-registry-attacks-threat-detection/ +- https://attack.mitre.org/wiki/Technique/T1112 +tags: + analytics_story: Suspicious Windows Registry Activities + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/suspicious_wmi.yml b/stories/suspicious_wmi_use.yml similarity index 50% rename from stories/suspicious_wmi.yml rename to stories/suspicious_wmi_use.yml index 74e4da46da..d45a5cbc13 100644 --- a/stories/suspicious_wmi.yml +++ b/stories/suspicious_wmi_use.yml @@ -1,41 +1,12 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-01-13' +name: Suspicious WMI Use +id: c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 +version: '2.0' +date: '2018-10-23' description: Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. -detections: - - detection_id: 272df6de-61f1-4784-877c-1fbc3e2d0838 - name: Remote WMI Command Attempt - type: splunk - - detection_id: d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da - name: Remote Process Instantiation via WMI - type: splunk - - detection_id: 71bfdb13-f200-4c6c-b2c9-a2e07adf437d - name: WMI Permanent Event Subscription - type: splunk - - detection_id: ad05aae6-3b2a-4f73-af97-57bd26cee3b9 - name: WMI Permanent Event Subscription - Sysmon - type: splunk - - detection_id: 38cbd42c-1098-41bb-99cf-9d6d2b296d83 - name: WMI Temporary Event Subscription - type: splunk - - detection_id: 24869767-8579-485d-9a4f-d9ddfd8f0cac - name: Process Execution via WMI - type: splunk - - detection_id: aa73f80d-d728-4077-b226-81ea0c8be589 - name: Script Execution via WMI - type: splunk -id: c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2018-10-23' -name: Suspicious WMI Use narrative: 'WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning @@ -50,13 +21,13 @@ narrative: 'WMI is a Microsoft infrastructure for management data and operations In the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end.' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf - - https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.0' +- https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf +- https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html +tags: + analytics_story: Suspicious WMI Use + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/aws_ec2_modifications.yml b/stories/unusual_aws_ec2_modifications.yml similarity index 68% rename from stories/aws_ec2_modifications.yml rename to stories/unusual_aws_ec2_modifications.yml index 36f409a652..146146c01c 100644 --- a/stories/aws_ec2_modifications.yml +++ b/stories/unusual_aws_ec2_modifications.yml @@ -1,21 +1,10 @@ -category: - - Cloud Security -channel: ESCU -creation_date: '2018-04-09' +name: Unusual AWS EC2 Modifications +id: 73de57ef-0dfc-411f-b1e7-fa24428aeae0 +version: '1.0' +date: '2018-04-09' description: Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. -detections: - - detection_id: 56f91724-cf3f-4666-84e1-e3712fb41e76 - name: EC2 Instance Modified With Previously Unseen User - type: splunk -id: 73de57ef-0dfc-411f-b1e7-fa24428aeae0 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2018-04-09' -name: Unusual AWS EC2 Modifications narrative: "A common attack technique is to infiltrate a cloud instance and make modifications.\ \ The adversary can then secure access to your infrastructure or hide their activities.\ \ So it's important to stay alert to changes that may indicate that your environment\ @@ -25,12 +14,12 @@ narrative: "A common attack technique is to infiltrate a cloud instance and make \ or by known users who modify or create instances in a way that have not been done\ \ before. This story also provides investigative searches that help you go deeper\ \ once you detect suspicious behavior." -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +tags: + analytics_story: Unusual AWS EC2 Modifications + usecase: Security Monitoring + category: + - Cloud Security diff --git a/stories/unusual_processes.yml b/stories/unusual_processes.yml index e845c8d852..17d4aca773 100644 --- a/stories/unusual_processes.yml +++ b/stories/unusual_processes.yml @@ -1,40 +1,11 @@ -category: - - Malware -channel: ESCU -creation_date: '2016-08-09' +name: Unusual Processes +id: f4368e3f-d59f-4192-84f6-748ac5a3ddb6 +version: '2.1' +date: '2020-02-04' description: Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. -detections: - - detection_id: 29ccce64-a10c-4389-a45f-337cb29ba1f7 - name: Uncommon Processes On Endpoint - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6a4264e7f - name: Unusually Long Command Line - type: splunk - - detection_id: 57edaefa-a73b-45e5-bbae-f39c1473f941 - name: Unusually Long Command Line - MLTK - type: splunk - - detection_id: 44fddcb2-8d3b-454c-874e-7c6de5a4f7ac - name: Detect Rare Executables - type: splunk - - detection_id: a34aae96-ccf8-4aef-952c-3ea21444444d - name: System Processes Run From Unexpected Locations - type: splunk - - detection_id: 6c135f8d-5e60-454e-80b7-c56eed739833 - name: RunDLL Loading DLL By Ordinal - type: splunk - - detection_id: a51bfe1a-94f0-48cc-b1e4-16ae10145893 - name: Detect processes used for System Network Configuration Discovery - type: splunk -id: f4368e3f-d59f-4192-84f6-748ac5a3ddb6 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2020-02-04' -name: Unusual Processes narrative: 'Being able to profile a host''s processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ @@ -48,14 +19,14 @@ narrative: 'Being able to profile a host''s processes within your environment ca how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity.' -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html - - https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf - - https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262 -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.1' +- https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html +- https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf +- https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262 +tags: + analytics_story: Unusual Processes + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/non-secure_communications.yml b/stories/use_of_cleartext_protocols.yml similarity index 61% rename from stories/non-secure_communications.yml rename to stories/use_of_cleartext_protocols.yml index 5e35634829..5eaeedac92 100644 --- a/stories/non-secure_communications.yml +++ b/stories/use_of_cleartext_protocols.yml @@ -1,20 +1,9 @@ -category: - - Best Practices -channel: ESCU -creation_date: '2016-09-13' +name: Use of Cleartext Protocols +id: 826e6431-aeef-41b4-9fc0-6d0985d65a21 +version: '1.0' +date: '2017-09-15' description: Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. -detections: - - detection_id: 6923cd64-17a0-453c-b945-81ac2d8c6db9 - name: Protocols passing authentication in cleartext - type: splunk -id: 826e6431-aeef-41b4-9fc0-6d0985d65a21 -maintainers: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2017-09-15' -name: Use of Cleartext Protocols narrative: Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information @@ -22,12 +11,12 @@ narrative: Various legacy protocols operate by default in the clear, without the protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. -original_authors: - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel +author: Bhavin Patel, Splunk +type: ESCU references: - - https://www.monkey.org/~dugsong/dsniff/ -spec_version: 2 -usecase: Security Monitoring -version: '1.0' +- https://www.monkey.org/~dugsong/dsniff/ +tags: + analytics_story: Use of Cleartext Protocols + usecase: Security Monitoring + category: + - Best Practices diff --git a/stories/web_fraud.yml b/stories/web_fraud_detection.yml similarity index 74% rename from stories/web_fraud.yml rename to stories/web_fraud_detection.yml index 46e6421a2c..3d79bd16a0 100644 --- a/stories/web_fraud.yml +++ b/stories/web_fraud_detection.yml @@ -1,26 +1,9 @@ -category: - - Abuse -channel: ESCU -creation_date: '2018-07-12' +name: Web Fraud Detection +id: 31337aaa-bc22-4752-b599-ef112dq1dq7a +version: '1.0' +date: '2018-10-08' description: Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. -detections: - - detection_id: 31337aaa-941d-4ada-81ac-q2a17be5bf0d - name: Web Fraud - Account Harvesting - type: splunk - - detection_id: 31337bbb-bc22-4752-b599-ef192df2dc7a - name: Web Fraud - Anomalous User Clickspeed - type: splunk - - detection_id: 31337a1a-53b9-4e05-96e9-55c934cb71d3 - name: Web Fraud - Password Sharing Across Accounts - type: splunk -id: 31337aaa-bc22-4752-b599-ef112dq1dq7a -maintainers: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger -modification_date: '2018-10-08' -name: Web Fraud Detection narrative: 'The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes @@ -54,13 +37,13 @@ narrative: 'The Federal Bureau of Investigations (FBI) defines Internet fraud as Another search detects incidents wherein a single password is used across multiple accounts, which may indicate that a fraudster has infiltrated your environment and embedded a common password within a script.' -original_authors: - - company: Splunk - email: Mayhem@splunk.com - name: Jim Apger +author: Jim Apger, Splunk +type: ESCU references: - - https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud - - https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718 -spec_version: 2 -usecase: Fraud Detection -version: '1.0' +- https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud +- https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718 +tags: + analytics_story: Web Fraud Detection + usecase: Fraud Detection + category: + - Abuse diff --git a/stories/windows_defense_evasion_tactics.yml b/stories/windows_defense_evasion_tactics.yml new file mode 100644 index 0000000000..6bced15e3c --- /dev/null +++ b/stories/windows_defense_evasion_tactics.yml @@ -0,0 +1,21 @@ +name: Windows Defense Evasion Tactics +id: 56e24a28-5003-4047-b2db-e8f3c4618064 +version: '1.0' +date: '2018-05-31' +description: 'Detect tactics used by malware to evade defenses on Windows endpoints. + A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` + and disabling user-account control, among many others ' +narrative: Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that + adversaries employ in a variety of ways to bypass or defeat defensive security measures. + There are many techniques enumerated by the MITRE ATT&CK framework that are applicable + in this context. This Analytic Story includes searches designed to identify the + use of such techniques on Windows platforms. +author: David Dorsey, Splunk +type: ESCU +references: +- https://attack.mitre.org/wiki/Defense_Evasion +tags: + analytics_story: Windows Defense Evasion Tactics + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/file_extension_abuse.yml b/stories/windows_file_extension_and_association_abuse.yml similarity index 75% rename from stories/file_extension_abuse.yml rename to stories/windows_file_extension_and_association_abuse.yml index 256163145f..4ea47b655b 100644 --- a/stories/file_extension_abuse.yml +++ b/stories/windows_file_extension_and_association_abuse.yml @@ -1,28 +1,11 @@ -category: - - Malware -channel: ESCU -creation_date: '2018-01-26' +name: Windows File Extension and Association Abuse +id: 30552a76-ac78-48e4-b3c0-de4e34e9563d +version: '1.0' +date: '2018-01-26' description: Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. -detections: - - detection_id: b06a555e-dce0-417d-a2eb-28a5d8d66ef7 - name: Execution of File with Multiple Extensions - type: splunk - - detection_id: ab0353e6-a956-420b-b724-a8b4846d5d5a - name: Execution of File With Spaces Before Extension - type: splunk - - detection_id: 1b989a0e-0129-4446-a695-f193a5b746fc - name: Suspicious Changes to File Associations - type: splunk -id: 30552a76-ac78-48e4-b3c0-de4e34e9563d -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2018-01-26' -name: Windows File Extension and Association Abuse narrative: "Attackers use a variety of techniques to entice users to run malicious\ \ code or to persist on an endpoint. One way to accomplish these goals is to leverage\ \ file extensions and the mechanism Windows uses to associate files with specific\ @@ -48,13 +31,13 @@ narrative: "Attackers use a variety of techniques to entice users to run malicio \ the fact that something suspicious has occurred.\\\nRun the searches in this story\ \ to detect and investigate suspicious behavior that may indicate abuse or manipulation\ \ of Windows file extensions and/or associations." -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/ - - https://attack.mitre.org/wiki/Technique/T1042 -spec_version: 2 -usecase: Advanced Threat Detection -version: '1.0' +- https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/ +- https://attack.mitre.org/wiki/Technique/T1042 +tags: + analytics_story: Windows File Extension and Association Abuse + usecase: Advanced Threat Detection + category: + - Malware diff --git a/stories/suspicious_event_log_activity.yml b/stories/windows_log_manipulation.yml similarity index 59% rename from stories/suspicious_event_log_activity.yml rename to stories/windows_log_manipulation.yml index b2d9f85f43..6d219ef284 100644 --- a/stories/suspicious_event_log_activity.yml +++ b/stories/windows_log_manipulation.yml @@ -1,30 +1,10 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-02-17' +name: Windows Log Manipulation +id: b6db2c60-a281-48b4-95f1-2cd99ed56835 +version: '2.0' +date: '2017-09-12' description: Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. -detections: - - detection_id: b89919ed-ee5f-492c-b139-95dbb162039e - name: Deleting Shadow Copies - type: splunk - - detection_id: ad517544-aff9-4c96-bd99-d6eb43bfbb6a - name: Windows Event Log Cleared - type: splunk - - detection_id: 2827c0fd-e1be-4868-ae25-59d28e0f9d4f - name: Suspicious wevtutil Usage - type: splunk - - detection_id: b6e0ff70-b122-4227-9368-4cf322ab43c3 - name: USN Journal Deletion - type: splunk -id: b6db2c60-a281-48b4-95f1-2cd99ed56835 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2017-09-12' -name: Windows Log Manipulation narrative: 'Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still @@ -39,14 +19,14 @@ narrative: 'Because attackers often modify system logs to cover their tracks and Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified).' -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ - - https://zeltser.com/security-incident-log-review-checklist/ - - http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html -spec_version: 2 -usecase: Security Monitoring -version: '2.0' +- https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ +- https://zeltser.com/security-incident-log-review-checklist/ +- http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html +tags: + analytics_story: Windows Log Manipulation + usecase: Security Monitoring + category: + - Adversary Tactics diff --git a/stories/windows_persistence.yml b/stories/windows_persistence.yml deleted file mode 100644 index 6d679379f3..0000000000 --- a/stories/windows_persistence.yml +++ /dev/null @@ -1,74 +0,0 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-04-19' -description: Monitor for activities and techniques associated with maintaining persistence - on a Windows system--a sign that an adversary may have compromised your environment. -detections: - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01bbb - name: Registry Keys for Creating SHIM Databases - type: splunk - - detection_id: 404620de-46d8-48b6-90cc-8a8d7b0876a3 - name: Shim Database Installation With Suspicious Parameters - type: splunk - - detection_id: 6e4c4588-ba2f-42fa-97e6-9f6f548eaa33 - name: Shim Database File Creation - type: splunk - - detection_id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b - name: Registry Keys Used For Persistence - type: splunk - - detection_id: 1297fb80-f42a-4b4a-9c8a-88c066437cf6 - name: Schtasks used for forcing a reboot - type: splunk - - detection_id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d - name: Sc.exe Manipulating Windows Services - type: splunk - - detection_id: 8470d755-0c13-45b3-bd63-387a373c10cf - name: Reg.exe Manipulating Windows Services Registry Keys - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6b5264g9f - name: Hiding Files And Directories With Attrib.exe - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6b5264x9f - name: Reg.exe used to hide files/directories via registry keys - type: splunk - - detection_id: c77162d3-f93c-45cc-80c8-22f6v5264g9f - name: Detect Path Interception By Creation Of program.exe - type: splunk - - detection_id: f5f6af30-7ba7-4295-bfe9-07de87c01bbc - name: Monitor Registry Keys for Print Monitors - type: splunk - - detection_id: c9f4b923-f8af-4155-b697-1354f5dcbc5e - name: Remote Registry Key modifications - type: splunk -id: 30874d4f-20a1-488f-85ec-5d52ef74e3f9 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -modification_date: '2018-05-31' -name: Windows Persistence Techniques -narrative: Maintaining persistence is one of the first steps taken by attackers after - the initial compromise. Attackers leverage various custom and built-in tools to - ensure survivability and persistent access within a compromised enterprise. This - Analytic Story provides searches to help you identify various behaviors used by - attackers to maintain persistent access to a Windows environment. -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey - - company: Splunk - email: bpatel@splunk.com - name: Bhavin Patel -references: - - http://www.fuzzysecurity.com/tutorials/19.html - - https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html - - http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/ - - https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html - - https://www.youtube.com/watch?v=dq2Hv7J9fvk -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.0' diff --git a/stories/windows_persistence_techniques.yml b/stories/windows_persistence_techniques.yml new file mode 100644 index 0000000000..db6b2207d5 --- /dev/null +++ b/stories/windows_persistence_techniques.yml @@ -0,0 +1,24 @@ +name: Windows Persistence Techniques +id: 30874d4f-20a1-488f-85ec-5d52ef74e3f9 +version: '2.0' +date: '2018-05-31' +description: Monitor for activities and techniques associated with maintaining persistence + on a Windows system--a sign that an adversary may have compromised your environment. +narrative: Maintaining persistence is one of the first steps taken by attackers after + the initial compromise. Attackers leverage various custom and built-in tools to + ensure survivability and persistent access within a compromised enterprise. This + Analytic Story provides searches to help you identify various behaviors used by + attackers to maintain persistent access to a Windows environment. +author: Bhavin Patel, Splunk +type: ESCU +references: +- http://www.fuzzysecurity.com/tutorials/19.html +- https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html +- http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/ +- https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html +- https://www.youtube.com/watch?v=dq2Hv7J9fvk +tags: + analytics_story: Windows Persistence Techniques + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/windows_privilege_escalation.yml b/stories/windows_privilege_escalation.yml index 57ba3c1d01..e9c7b61a74 100644 --- a/stories/windows_privilege_escalation.yml +++ b/stories/windows_privilege_escalation.yml @@ -1,30 +1,10 @@ -category: - - Adversary Tactics -channel: ESCU -creation_date: '2017-12-07' +name: Windows Privilege Escalation +id: 644e22d3-598a-429c-a007-16fdb802cae5 +version: '2.0' +date: '2020-02-04' description: Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. -detections: - - detection_id: 13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae - name: Overwriting Accessibility Binaries - type: splunk - - detection_id: c9f4b923-f8af-4155-b697-1354f5bcbc5e - name: Registry Keys Used For Privilege Escalation - type: splunk - - detection_id: 29ccce64-a10c-4389-a45f-337cb29ba1f7 - name: Uncommon Processes On Endpoint - type: splunk - - detection_id: aa0c4aeb-5b18-41c4-8c07-f1442d7599df - name: Child Processes of Spoolsv.exe - type: splunk -id: 644e22d3-598a-429c-a007-16fdb802cae5 -maintainers: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey -modification_date: '2020-02-04' -name: Windows Privilege Escalation narrative: 'Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such @@ -33,12 +13,12 @@ narrative: 'Privilege escalation is a "land-and-expand" technique, wherein an ad control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment.' -original_authors: - - company: Splunk - email: davidd@splunk.com - name: David Dorsey +author: David Dorsey, Splunk +type: ESCU references: - - https://attack.mitre.org/tactics/TA0004/ -spec_version: 2 -usecase: Advanced Threat Detection -version: '2.0' +- https://attack.mitre.org/tactics/TA0004/ +tags: + analytics_story: Windows Privilege Escalation + usecase: Advanced Threat Detection + category: + - Adversary Tactics diff --git a/stories/service_abuse.yml b/stories/windows_service_abuse.yml similarity index 58% rename from stories/service_abuse.yml rename to stories/windows_service_abuse.yml index c3cdb338fa..c924c32e92 100644 --- a/stories/service_abuse.yml +++ b/stories/windows_service_abuse.yml @@ -1,28 +1,11 @@ -category: - - Malware -channel: ESCU -creation_date: '2017-11-02' +name: Windows Service Abuse +id: 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 +version: '3.0' +date: '2017-11-02' description: Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. -detections: - - detection_id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d - name: Sc.exe Manipulating Windows Services - type: splunk - - detection_id: 8470d755-0c13-45b3-bd63-387a373c10cf - name: Reg.exe Manipulating Windows Services Registry Keys - type: splunk - - detection_id: 823136f2-d755-4b6d-ae04-372b486a5808 - name: First Time Seen Running Windows Service - type: splunk -id: 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 -maintainers: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez -modification_date: '2017-11-02' -name: Windows Service Abuse narrative: The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to @@ -32,13 +15,13 @@ narrative: The Windows operating system uses a services architecture to allow fo opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. -original_authors: - - company: Splunk - email: rvaldez@splunk.com - name: Rico Valdez +author: Rico Valdez, Splunk +type: ESCU references: - - https://attack.mitre.org/wiki/Technique/T1050 - - https://attack.mitre.org/wiki/Technique/T1031 -spec_version: 2 -usecase: Advanced Threat Detection -version: '3.0' +- https://attack.mitre.org/wiki/Technique/T1050 +- https://attack.mitre.org/wiki/Technique/T1031 +tags: + analytics_story: Windows Service Abuse + usecase: Advanced Threat Detection + category: + - Malware From e610e87ee04fdbafc099f7b7536a5454899c3f9e Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 30 Apr 2020 10:14:38 +0200 Subject: [PATCH 05/93] WIP --- bin/validate.py | 422 ++++-------------- {deployment => deployments}/deployment.yml | 0 ...baseline.spec.json => baselines.spec.json} | 4 +- ...oyment.spec.json => deployments.spec.json} | 0 spec/detections.spec.json | 11 +- ...ask.spec.json => response_tasks.spec.json} | 2 +- ...response.spec.json => responses.spec.json} | 3 +- spec/stories.spec.json | 4 +- 8 files changed, 92 insertions(+), 354 deletions(-) rename {deployment => deployments}/deployment.yml (100%) rename spec/{baseline.spec.json => baselines.spec.json} (97%) rename spec/{deployment.spec.json => deployments.spec.json} (100%) rename spec/{response_task.spec.json => response_tasks.spec.json} (99%) rename spec/{response.spec.json => responses.spec.json} (98%) diff --git a/bin/validate.py b/bin/validate.py index 194e4d860f..93096761ea 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -13,22 +13,61 @@ import argparse from os import path -def validate_object(REPO_PATH, schema_path, manifest_path, return_objects, verbose, lookups=None, macros=None): - ''' Validate scheme ''' +def validate_schema(REPO_PATH, type, objects): + error = False + schema_file = path.join(path.expanduser(REPO_PATH), 'spec/' + type + '.spec.json') + + try: + schema = json.loads(open(schema_file, 'rb').read()) + except IOError: + print("ERROR: reading schema file {0}".format(schema_file)) + + manifest_files = path.join(path.expanduser(REPO_PATH), type + '/*.yml') + + for manifest_file in glob.glob(manifest_files): + if verbose: + print("processing manifest {0}".format(manifest_file)) + + with open(manifest_file, 'r') as stream: + try: + object = list(yaml.safe_load_all(stream))[0] + except yaml.YAMLError as exc: + print(exc) + print("Error reading {0}".format(manifest_file)) + error = True + continue + + try: + jsonschema.validate(instance=object, schema=schema) + except jsonschema.exceptions.ValidationError as json_ve: + print("ERROR: {0} at:\n\t{1}".format(json.dumps(json_ve.message), manifest_file)) + print("\tAffected Object: {}".format(json.dumps(json_ve.instance))) + error = True + + if type in objects: + objects[type].append(object) + else: + objects[type] = [object] + + return objects, error + + + + +def validate_object(REPO_PATH, schema_path, manifest_path, verbose, lookups=None, macros=None): + ''' Validate scheme ''' + # uuids - baselines_uuids = [] - story_uuids = [] - detection_uuids = [] - investigation_uuids = [] + uuids = [] schema_file = path.join(path.expanduser(REPO_PATH), schema_path) try: schema = json.loads(open(schema_file, 'rb').read()) except IOError: - print("ERROR: reading baseline schema file {0}".format(schema_file)) + print("ERROR: reading schema file {0}".format(schema_file)) objects = {} manifest_files = path.join(path.expanduser(REPO_PATH), manifest_path) @@ -53,361 +92,66 @@ def validate_object(REPO_PATH, schema_path, manifest_path, return_objects, verbo print("\tAffected Object: {}".format(json.dumps(json_ve.instance))) error = True - objects[object['name']] = object + # validate content - if schema_path == 'spec/v2/lookups.spec.json': - error = error or validate_lookups_content(REPO_PATH, "lookups/%s", object, manifest_file) - elif schema_path == 'spec/v2/baselines.spec.json': - error = error or validate_baselines_content(object, macros, lookups, manifest_file, baselines_uuids) - elif schema_path == 'spec/v2/story.spec.json': - error = error or validate_story_content(object, manifest_file, story_uuids) - elif schema_path == 'spec/v2/detections.spec.json': - error = error or validate_detection_content(object, macros, lookups, manifest_file, detection_uuids) - elif schema_path == 'spec/v2/investigations.spec.json': - error = error or validate_investigation_content(object, macros, lookups, manifest_file, investigation_uuids) - - if return_objects: - return error, objects - else: - return error + if schema_path == 'spec/lookups.spec.json': + lookup_errors = validate_lookups_content(REPO_PATH, "lookups/%s", object, manifest_file) + elif schema_path == 'spec/baselines.spec.json' or schema_path == 'spec/stories.spec.json' or schema_path == 'spec/detections.spec.json': + errors, uuids = validate_standard_fields(object, uuids) -def validate_lookups_content(REPO_PATH, lookup_path, lookup, manifest_file): - error = False - if 'filename' in lookup: - lookup_csv_file = path.join(path.expanduser(REPO_PATH), lookup_path % lookup['filename']) - if not path.isfile(lookup_csv_file): - print("ERROR: filename {} does not exist".format(lookup['filename'])) - print(lookup_csv_file) - print("\t{}".format(manifest_file)) - error = True - - return error + #check for duplicate uuids -def validate_baselines_content(baseline, macros, lookups, baselines_manifest_file, baselines_uuids): - errors = [] - error = False - - baselines_errors = validate_single_baseline_content(baseline, baselines_uuids, errors, macros, lookups) - if baselines_errors: - error = True + #list errors for err in baselines_errors: print("{0} at:\n\t {1}".format(err, baselines_manifest_file)) - return error + return error -def validate_single_baseline_content(baseline, baselines_uuids, errors, macros, lookups): - - if baseline['id'] == '': - errors.append('ERROR: Blank ID') - - if baseline['id'] in baselines_uuids: - errors.append('ERROR: Duplicate UUID found: %s' % baseline['id']) - else: - baselines_uuids.append(baseline['id']) - - if baseline['name'].endswith(" "): - errors.append( - "ERROR: Investigation name has trailing spaces: '%s'" % - baseline['name']) - - try: - baseline['description'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: description not ascii") - - if 'how_to_implement' in baseline: - try: - baseline['how_to_implement'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: how_to_implement not ascii") - - if 'eli5' in baseline: - try: - baseline['eli5'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: eli5 not ascii") - - if 'known_false_positives' in baseline: - try: - baseline['known_false_positives'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: known_false_positives not ascii") - - if 'splunk' in baseline['baseline']: - - # do a regex match here instead of key values - if (baseline['baseline']['splunk']['search'].find('tstats') != -1) or \ - (baseline['baseline']['splunk']['search'].find('datamodel') != -1): - - if 'data_models' not in baseline['data_metadata']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' field is not set") - - if not baseline['data_metadata']['data_models']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' is empty") - - # do a regex match here instead of key values - if (baseline['baseline']['splunk']['search'].find('sourcetype') != -1): - if 'data_sourcetypes' not in baseline['data_metadata']: - errors.append("ERROR: The Splunk search specifies a sourcetype but 'data_sourcetypes' \ - field is not set") - - if not baseline['data_metadata']['data_sourcetypes']: - errors.append("ERROR: The Splunk search specifies a sourcetype but \ - 'data_sourcetypes' is empty") - - if 'macros' in baseline['baseline']['splunk']: - for macro in baseline['baseline']['splunk']['macros']: - if macro not in macros: - errors.append("ERROR: The Splunk search specifies a macro \"{}\" \ - but there is no macro manifest for it".format(macro)) - - if 'lookups' in baseline['baseline']['splunk']: - for lookup in baseline['baseline']['splunk']['lookups']: - if lookup not in lookups: - errors.append("ERROR: The Splunk search specifies a lookup \"{}\" \ - but there is no lookup manifest for it".format(lookup)) - - return errors - - -def validate_story_content(story, story_manifest_file, story_uuids): - error = False - - story_errors = validate_single_story_content(story, story_uuids) - if story_errors: - error = True - for err in story_errors: - print("{0} at:\n\t {1}".format(err, story_manifest_file)) - - return error - - -def validate_single_story_content(story, STORY_UUIDS): - ''' Validate that the content of a story manifest is correct''' - errors = [] - - if story['id'] == '': - errors.append('ERROR: Blank ID') - - if story['id'] in STORY_UUIDS: - errors.append('ERROR: Duplicate UUID found: %s' % story['id']) - else: - STORY_UUIDS.append(story['id']) - - try: - story['description'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: description not ascii") - - try: - story['narrative'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: narrative not ascii") - - return errors - - -def validate_detection_content(detection, macros, lookups, manifest_file, detection_uuids): - error = False - - detection_errors = validate_single_detection_content(detection, detection_uuids, macros, lookups) - if detection_errors: - error = True - for err in detection_errors: - print("{0} at:\n\t {1}".format(err, manifest_file)) - - return error - - -def validate_single_detection_content(detection, DETECTION_UUIDS, macros, lookups): +def validate_standard_fields(object, uuids): errors = [] - if detection['id'] == '': + if object['id'] == '': errors.append('ERROR: Blank ID') - if detection['id'] in DETECTION_UUIDS: - errors.append('ERROR: Duplicate UUID found: %s' % detection['id']) + if object['id'] in uuids: + errors.append('ERROR: Duplicate UUID found: %s' % object['id']) else: - DETECTION_UUIDS.append(detection['id']) + uuids.append(object['id']) - if detection['name'].endswith(" "): + if object['name'].endswith(" "): errors.append( - "ERROR: Detection name has trailing spaces: '%s'" % - detection['name']) + "ERROR: name has trailing spaces: '%s'" % + object['name']) try: - detection['description'].encode('ascii') + object['description'].encode('ascii') except UnicodeEncodeError: errors.append("ERROR: description not ascii") - if 'how_to_implement' in detection: + if 'how_to_implement' in object: try: - detection['how_to_implement'].encode('ascii') + object['how_to_implement'].encode('ascii') except UnicodeEncodeError: errors.append("ERROR: how_to_implement not ascii") - if 'eli5' in detection: - try: - detection['eli5'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: eli5 not ascii") - - if 'known_false_positives' in detection: - try: - detection['known_false_positives'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: known_false_positives not ascii") - # modded to pass validation for uba detections - not yet fleshed out - if 'splunk' in detection['detect']: - # do a regex match here instead of key values - # if (detection['detect']['splunk']['correlation_rule']['search'].find('tstats') != -1) or \ - # (detection['detect']['splunk']['correlation_rule']['search'].find('datamodel') != -1): - if (detection['detect']['splunk']['correlation_rule']['search'].find('datamodel') != -1): - if 'data_models' not in detection['data_metadata']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' field is not set") - - if not detection['data_metadata']['data_models']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' is empty") - - # do a regex match here instead of key values - if (detection['detect']['splunk']['correlation_rule']['search'].find('sourcetype') != -1): - if 'data_sourcetypes' not in detection['data_metadata']: - errors.append("ERROR: The Splunk search specifies a sourcetype but 'data_sourcetypes' field is not set") - elif not detection['data_metadata']['data_sourcetypes']: - errors.append("ERROR: The Splunk search specifies a sourcetype but 'data_sourcetypes' is empty") - - if 'macros' in detection['detect']['splunk']['correlation_rule']: - for macro in detection['detect']['splunk']['correlation_rule']['macros']: - if macro not in macros: - errors.append("ERROR: The Splunk search specifies a macro \"{}\" \ - but there is no macro manifest for it".format(macro)) - - if 'lookups' in detection['detect']['splunk']['correlation_rule']: - for lookup in detection['detect']['splunk']['correlation_rule']['lookups']: - if lookup not in lookups: - errors.append("ERROR: The Splunk search specifies a lookup \"{}\" \ - but there is no lookup manifest for it".format(lookup)) - - if 'notable' in detection['detect']['splunk']['correlation_rule']: - if ('drilldown_search' in detection['detect']['splunk']['correlation_rule']['notable']) ^ \ - ('drilldown_name' in detection['detect']['splunk']['correlation_rule']['notable']): - - errors.append("ERROR: Both drilldown_search and drilldown_name must be defined") - - elif 'uba' in detection['detect']: - if (detection['detect']['uba']['correlation_rule']['search'].find('tstats') != -1) or \ - (detection['detect']['splunk']['correlation_rule']['search'].find('datamodel') != -1): - - if 'data_models' not in detection['data_metadata']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' field is not set") - - if not detection['data_metadata']['data_models']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' is empty") - - # do a regex match here instead of key values - if (detection['detect']['uba']['correlation_rule']['search'].find('sourcetype') != -1): - if 'data_sourcetypes' not in detection['data_metadata']: - errors.append("ERROR: The Splunk search specifies a sourcetype but 'data_sourcetypes' \ - field is not set") - - if not detection['data_metadata']['data_sourcetypes']: - errors.append("ERROR: The Splunk search specifies a sourcetype but \ - 'data_sourcetypes' is empty") - - # do a regex match here instead of key values - - return errors + return errors, uuids -def validate_investigation_content(investigation, macros, lookups, manifest_file, investigation_uuids): - error = False - - investigation_errors = validate_single_investigation_content(investigation, investigation_uuids, macros, lookups) - if investigation_errors: - error = True - for err in investigation_errors: - print("{0} at:\n\t {1}".format(err, manifest_file)) - - return error +def validate_search(): + pass -def validate_single_investigation_content(investigation, investigation_uuids, macros, lookups): +def validate_lookups_content(REPO_PATH, lookup_path, lookup, manifest_file): errors = [] - - if investigation['id'] == '': - errors.append('ERROR: Blank ID') - - if investigation['id'] in investigation_uuids: - errors.append('ERROR: Duplicate UUID found: %s' % investigation['id']) - else: - investigation_uuids.append(investigation['id']) - - if investigation['name'].endswith(" "): - errors.append( - "ERROR: Investigation name has trailing spaces: '%s'" % - investigation['name']) - - try: - investigation['description'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: description not ascii") - - if 'how_to_implement' in investigation: - try: - investigation['how_to_implement'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: how_to_implement not ascii") - - if 'eli5' in investigation: - try: - investigation['eli5'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: eli5 not ascii") - - if 'known_false_positives' in investigation: - try: - investigation['known_false_positives'].encode('ascii') - except UnicodeEncodeError: - errors.append("ERROR: known_false_positives not ascii") - - if 'splunk' in investigation['investigate']: - - # do a regex match here instead of key values - if (investigation['investigate']['splunk']['search'].find('tstats') != -1) or \ - (investigation['investigate']['splunk']['search'].find('datamodel') != -1): - - if 'data_models' not in investigation['data_metadata']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' field is not set") - - if not investigation['data_metadata']['data_models']: - errors.append("ERROR: The Splunk search uses a data model but 'data_models' is empty") - - # do a regex match here instead of key values - if (investigation['investigate']['splunk']['search'].find('sourcetype') != -1): - if 'data_sourcetypes' not in investigation['data_metadata']: - errors.append("ERROR: The Splunk search specifies a sourcetype but 'data_sourcetypes' \ - field is not set") - - if not investigation['data_metadata']['data_sourcetypes']: - errors.append("ERROR: The Splunk search specifies a sourcetype but \ - 'data_sourcetypes' is empty") - - if 'macros' in investigation['investigate']['splunk']: - for macro in investigation['investigate']['splunk']['macros']: - if macro not in macros: - errors.append("ERROR: The Splunk search specifies a macro \"{}\" \ - but there is no macro manifest for it".format(macro)) - - if 'lookups' in investigation['investigate']['splunk']: - for lookup in investigation['investigate']['splunk']['lookups']: - if lookup not in lookups: - errors.append("ERROR: The Splunk search specifies a lookup \"{}\" \ - but there is no lookup manifest for it".format(lookup)) + if 'filename' in lookup: + lookup_csv_file = path.join(path.expanduser(REPO_PATH), lookup_path % lookup['filename']) + if not path.isfile(lookup_csv_file): + errors.append("ERROR: filename {} does not exist".format(lookup['filename'])) return errors @@ -424,16 +168,18 @@ if __name__ == "__main__": REPO_PATH = args.path verbose = args.verbose - macros_error, macros = validate_object(REPO_PATH, 'spec/v2/macros.spec.json', 'macros/*.yml', True, verbose) - lookups_error, lookups = validate_object(REPO_PATH, 'spec/v2/lookups.spec.json', 'lookups/*.yml', True, verbose) - story_error = validate_object(REPO_PATH, 'spec/v2/story.spec.json', 'stories/*.yml', False, verbose) - detection_error = validate_object(REPO_PATH, 'spec/v2/detections.spec.json', 'detections/*.yml', False, - verbose, lookups, macros) - investigation_error = validate_object(REPO_PATH, 'spec/v2/investigations.spec.json', 'investigations/*.yml', - False, verbose, lookups, macros) - baseline_error = validate_object(REPO_PATH, 'spec/v2/baselines.spec.json', 'baselines/*.yml', False, verbose, lookups, macros) + validate_objects = ['macros','lookups','stories','detections','response_tasks','responses','deployments'] - if story_error or detection_error or investigation_error or baseline_error or macros_error or lookups_error: + objects = {} + schema_error = False + + for validation_object in validate_objects: + objects, error = validate_schema(REPO_PATH, validation_object, objects) + schema_error = schema_error or error + + print(objects) + + if schema_error: sys.exit("Errors found") else: print("No Errors found") diff --git a/deployment/deployment.yml b/deployments/deployment.yml similarity index 100% rename from deployment/deployment.yml rename to deployments/deployment.yml diff --git a/spec/baseline.spec.json b/spec/baselines.spec.json similarity index 97% rename from spec/baseline.spec.json rename to spec/baselines.spec.json index 6367ae093e..41ab840e31 100644 --- a/spec/baseline.spec.json +++ b/spec/baselines.spec.json @@ -2,7 +2,6 @@ "$id": "http://example.com/example.json", "$schema": "http://json-schema.org/draft-07/schema", "additionalProperties": true, - "default": {}, "description": "schema for baselines", "properties": { "author": { @@ -80,7 +79,6 @@ } ], "minItems": 1, - "properties": null, "required": [], "type": "object", "uniqueItems": true @@ -92,7 +90,7 @@ "examples": [ 1 ], - "type": "integer" + "type": "string" } }, "required": [ diff --git a/spec/deployment.spec.json b/spec/deployments.spec.json similarity index 100% rename from spec/deployment.spec.json rename to spec/deployments.spec.json diff --git a/spec/detections.spec.json b/spec/detections.spec.json index af19e8233f..43269fd8cc 100644 --- a/spec/detections.spec.json +++ b/spec/detections.spec.json @@ -4,7 +4,6 @@ "type": "object", "title": "Detection Schema", "description": "schema for detections", - "default": {}, "additionalProperties": true, "required": [ "name", @@ -13,10 +12,9 @@ "date", "description", "type", - "references", "author", "search", - "knwon_false_positives", + "known_false_positives", "tags" ], "properties": { @@ -40,7 +38,7 @@ }, "version": { "$id": "#/properties/version", - "type": "integer", + "type": "string", "description": "version of detection, e.g. 1 or 2 ...", "default": 0, "examples": [ @@ -87,7 +85,7 @@ "ESCU", "SSE", "RBA" - ] + ], "type": "string" } }, @@ -131,7 +129,7 @@ "`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter`" ] }, - "knwon_false_positives": { + "known_false_positives": { "$id": "#/properties/knwon_false_positives", "type": "string", "description": "known false postives", @@ -153,7 +151,6 @@ ], "additionalProperties": true, "required": [], - "properties": null, "minItems": 1, "uniqueItems": true } diff --git a/spec/response_task.spec.json b/spec/response_tasks.spec.json similarity index 99% rename from spec/response_task.spec.json rename to spec/response_tasks.spec.json index 28b0688e1c..2425848a01 100644 --- a/spec/response_task.spec.json +++ b/spec/response_tasks.spec.json @@ -143,7 +143,7 @@ "examples": [ 3 ], - "type": "integer" + "type": "string" } }, "required": [ diff --git a/spec/response.spec.json b/spec/responses.spec.json similarity index 98% rename from spec/response.spec.json rename to spec/responses.spec.json index 2ff8650157..3eaf1a9b76 100644 --- a/spec/response.spec.json +++ b/spec/responses.spec.json @@ -90,7 +90,6 @@ } ], "minItems": 1, - "properties": null, "required": [], "type": "object", "uniqueItems": true @@ -102,7 +101,7 @@ "examples": [ 1 ], - "type": "integer" + "type": "string" } }, "required": [ diff --git a/spec/stories.spec.json b/spec/stories.spec.json index 410ef8b596..daf7250cc1 100644 --- a/spec/stories.spec.json +++ b/spec/stories.spec.json @@ -78,9 +78,7 @@ "analytics_story": "credential_dumping" } ], - "maxItems": 1, "minItems": 1, - "properties": null, "required": [], "type": "object" }, @@ -91,7 +89,7 @@ "examples": [ 1 ], - "type": "integer" + "type": "string" } }, "required": [ From 7cbc9a9ba64e710ad02fb6dc9dd640a3789d75ea Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 30 Apr 2020 10:34:18 +0200 Subject: [PATCH 06/93] WIP --- ...add_prohibited_processes_to_enterprise_security.yml | 2 +- baselines/baseline_of_api_calls_per_user_arn.yml | 2 +- .../baseline_of_blocked_outbound_traffic_from_aws.yml | 2 +- baselines/baseline_of_command_line_length___mltk.yml | 4 ++-- baselines/baseline_of_dns_query_length___mltk.yml | 2 +- ...excessive_aws_instances_launched_by_user___mltk.yml | 2 +- ...cessive_aws_instances_terminated_by_user___mltk.yml | 2 +- baselines/baseline_of_network_acl_activity_by_arn.yml | 2 +- .../baseline_of_s3_bucket_deletion_activity_by_arn.yml | 2 +- .../baseline_of_security_group_activity_by_arn.yml | 2 +- baselines/baseline_of_smb_traffic___mltk.yml | 4 ++-- baselines/count_of_assets_by_category.yml | 2 +- baselines/count_of_unique_ips_connecting_to_ports.yml | 2 +- .../create_a_list_of_approved_aws_service_accounts.yml | 2 +- baselines/discover_dns_records.yml | 2 +- baselines/dnstwist_domain_names.yml | 4 ++-- ...dentify_systems_creating_remote_desktop_traffic.yml | 2 +- ...entify_systems_receiving_remote_desktop_traffic.yml | 2 +- baselines/identify_systems_using_remote_desktop.yml | 2 +- baselines/monitor_successful_backups.yml | 2 +- baselines/monitor_unsuccessful_backups.yml | 2 +- ...usly_seen_api_call_per_user_roles_in_cloudtrail.yml | 2 +- .../previously_seen_aws_cross_account_activity.yml | 2 +- ...eviously_seen_aws_provisioning_activity_sources.yml | 4 ++-- baselines/previously_seen_aws_regions.yml | 2 +- ...previously_seen_cloud_compute_creations_by_user.yml | 2 +- baselines/previously_seen_cloud_compute_images.yml | 2 +- .../previously_seen_cloud_compute_instance_types.yml | 2 +- baselines/previously_seen_cloud_regions.yml | 2 +- baselines/previously_seen_command_line_arguments.yml | 6 +++--- baselines/previously_seen_ec2_amis.yml | 2 +- baselines/previously_seen_ec2_instance_types.yml | 2 +- baselines/previously_seen_ec2_launches_by_user.yml | 2 +- .../previously_seen_ec2_modifications_by_user.yml | 2 +- baselines/previously_seen_running_windows_services.yml | 2 +- .../previously_seen_s3_bucket_access_by_remote_ip.yml | 2 +- baselines/previously_seen_users_in_cloudtrail.yml | 6 +++--- ...ystems_ready_for_spectre_meltdown_windows_patch.yml | 2 +- .../update_previously_seen_users_in_cloudtrail.yml | 6 +++--- baselines/windows_updates_install_failures.yml | 2 +- baselines/windows_updates_install_successes.yml | 2 +- bin/validate.py | 1 - .../abnormally_high_aws_instances_launched_by_user.yml | 2 +- ...ally_high_aws_instances_launched_by_user___mltk.yml | 2 +- ...bnormally_high_aws_instances_terminated_by_user.yml | 2 +- ...ly_high_aws_instances_terminated_by_user___mltk.yml | 2 +- detections/access_lsass_memory_for_dump_creation.yml | 2 +- .../amazon_eks_kubernetes_cluster_scan_detection.yml | 2 +- .../amazon_eks_kubernetes_pod_scan_detection.yml | 2 +- .../attempt_to_add_certificate_to_untrusted_store.yml | 2 +- ...hell_execution_policy_to_unrestricted_or_bypass.yml | 2 +- detections/attempt_to_stop_security_service.yml | 2 +- ...mpted_credential_dump_from_registry_via_reg_exe.yml | 2 +- ..._cloud_provisioning_from_previously_unseen_city.yml | 2 +- ...oud_provisioning_from_previously_unseen_country.yml | 2 +- ..._provisioning_from_previously_unseen_ip_address.yml | 2 +- ...loud_provisioning_from_previously_unseen_region.yml | 2 +- ...account_activity_from_previously_unseen_account.yml | 2 +- ...access_control_list_created_with_all_open_ports.yml | 2 +- detections/aws_network_access_control_list_deleted.yml | 2 +- detections/batch_file_write_to_system32.yml | 2 +- detections/child_processes_of_spoolsv_exe.yml | 2 +- .../clients_connecting_to_multiple_dns_servers.yml | 6 +++--- ...pute_instance_created_by_previously_unseen_user.yml | 2 +- ...e_instance_created_with_previously_unseen_image.yml | 2 +- ...ce_created_with_previously_unseen_instance_type.yml | 2 +- ...te_instance_started_in_previously_unused_region.yml | 2 +- detections/common_ransomware_extensions.yml | 4 ++-- detections/common_ransomware_notes.yml | 4 ++-- .../create_local_admin_accounts_using_net_exe.yml | 2 +- .../create_or_delete_windows_shares_using_net_exe.yml | 2 +- detections/create_remote_thread_into_lsass.yml | 2 +- detections/creation_of_shadow_copy.yml | 2 +- ...reation_of_shadow_copy_with_wmic_and_powershell.yml | 2 +- ...ntial_dumping_via_copy_command_from_shadow_copy.yml | 2 +- .../credential_dumping_via_symlink_to_shadow_copy.yml | 2 +- detections/deleting_shadow_copies.yml | 6 +++--- ...etect_activity_related_to_pass_the_hash_attacks.yml | 2 +- .../detect_api_activity_from_users_without_mfa.yml | 2 +- ...attackers_scanning_for_vulnerable_jboss_servers.yml | 4 ++-- ...ect_aws_api_activities_from_unapproved_accounts.yml | 2 +- .../detect_aws_console_login_by_user_from_new_city.yml | 2 +- ...tect_aws_console_login_by_user_from_new_country.yml | 2 +- ...etect_aws_console_login_by_user_from_new_region.yml | 2 +- .../detect_credential_dumping_through_LSASS_access.yml | 2 +- ...requests_to_phishing_sites_leveraging_evilginx2.yml | 2 +- ...detect_excessive_account_lockouts_from_endpoint.yml | 2 +- detections/detect_excessive_user_account_lockouts.yml | 2 +- ...ct_hosts_connecting_to_dynamic_domain_providers.yml | 6 +++--- detections/detect_large_outbound_icmp_packets.yml | 2 +- detections/detect_long_dns_txt_record_response.yml | 4 ++-- ...ect_malicious_requests_to_exploit_jboss_servers.yml | 4 ++-- detections/detect_mimikatz_using_loaded_images.yml | 2 +- ...tect_mimikatz_via_powershell_and_eventcode_4703.yml | 2 +- ...a_exe_running_scripts_in_command_line_arguments.yml | 2 +- detections/detect_new_api_calls_from_user_roles.yml | 2 +- detections/detect_new_local_admin_account.yml | 2 +- detections/detect_new_login_attempts_to_routers.yml | 2 +- detections/detect_new_open_s3_buckets.yml | 2 +- detections/detect_new_user_aws_console_login.yml | 2 +- detections/detect_oulook_exe_writing_a__zip_file.yml | 2 +- detections/detect_outbound_smb_traffic.yml | 4 ++-- ...ct_path_interception_by_creation_of_program_exe.yml | 2 +- ...used_for_system_network_configuration_discovery.yml | 2 +- ...detect_prohibited_applications_spawning_cmd_exe.yml | 4 ++-- detections/detect_psexec_with_accepteula_flag.yml | 4 ++-- detections/detect_rare_executables.yml | 4 ++-- detections/detect_s3_access_from_a_new_ip.yml | 2 +- detections/detect_spike_in_aws_api_activity.yml | 2 +- ...spike_in_blocked_outbound_traffic_from_your_aws.yml | 4 ++-- detections/detect_spike_in_network_acl_activity.yml | 2 +- detections/detect_spike_in_s3_bucket_deletion.yml | 2 +- detections/detect_spike_in_security_group_activity.yml | 2 +- .../detect_unauthorized_assets_by_mac_address.yml | 2 +- detections/detect_usb_device_insertion.yml | 2 +- ...ct_use_of_cmd_exe_to_launch_script_interpreters.yml | 4 ++-- .../detect_web_traffic_to_dynamic_domain_providers.yml | 2 +- detections/detection_of_dns_tunnels.yml | 4 ++-- detections/detection_of_tools_built_by_nirsoft.yml | 2 +- detections/disabling_remote_user_account_control.yml | 2 +- detections/dns_query_length_outliers___mltk.yml | 4 ++-- .../dns_query_length_with_high_standard_deviation.yml | 4 ++-- ...y_requests_resolved_by_unauthorized_dns_servers.yml | 6 +++--- detections/dns_record_changed.yml | 2 +- detections/dump_lsass_via_comsvcs_dll.yml | 2 +- ...2_instance_modified_with_previously_unseen_user.yml | 2 +- ...c2_instance_started_in_previously_unseen_region.yml | 2 +- ...ec2_instance_started_with_previously_unseen_ami.yml | 2 +- ...ce_started_with_previously_unseen_instance_type.yml | 2 +- ...c2_instance_started_with_previously_unseen_user.yml | 2 +- detections/email_attachments_with_lots_of_spaces.yml | 2 +- ..._files_written_outside_of_the_outlook_directory.yml | 2 +- ...il_servers_sending_high_volume_traffic_to_hosts.yml | 2 +- detections/excessive_dns_failures.yml | 4 ++-- .../execution_of_file_with_multiple_extensions.yml | 2 +- .../execution_of_file_with_spaces_before_extension.yml | 2 +- ...ded_period_without_successful_netbackup_backups.yml | 2 +- detections/file_with_samsam_extension.yml | 2 +- detections/first_time_seen_command_line_argument.yml | 8 ++++---- detections/first_time_seen_running_windows_service.yml | 4 ++-- detections/gcp_gcr_container_uploaded.yml | 2 +- detections/gcp_kubernetes_cluster_scan_detection.yml | 2 +- .../hiding_files_and_directories_with_attrib_exe.yml | 4 ++-- ...igh_volume_of_network_traffic_from_email_server.yml | 2 +- detections/identify_new_user_accounts.yml | 2 +- detections/large_volume_of_dns_any_queries.yml | 2 +- detections/macos___re_opened_applications.yml | 2 +- ...rocess___connect_to_internet_with_hidden_window.yml | 4 ++-- .../malicious_powershell_process___encoded_command.yml | 2 +- ...us_powershell_process___execution_policy_bypass.yml | 2 +- ...ss___multiple_suspicious_command_line_arguments.yml | 2 +- ..._powershell_process_with_obfuscation_techniques.yml | 2 +- detections/monitor_dns_for_brand_abuse.yml | 2 +- detections/monitor_email_for_brand_abuse.yml | 2 +- .../monitor_registry_keys_for_print_monitors.yml | 4 ++-- detections/monitor_web_traffic_for_brand_abuse.yml | 2 +- ...users_with_invalid_credentails_from_the_same_ip.yml | 2 +- detections/new_container_uploaded_to_aws_ecr.yml | 2 +- detections/no_windows_updates_in_a_time_frame.yml | 2 +- detections/okta_account_lockout_events.yml | 2 +- detections/okta_failed_sso_attempts.yml | 2 +- detections/okta_user_logins_from_multiple_cities.yml | 2 +- detections/open_redirect_in_splunk_web.yml | 2 +- detections/osquery_pack___coldroot_detection.yml | 2 +- detections/overwriting_accessibility_binaries.yml | 2 +- detections/process_execution_via_wmi.yml | 2 +- detections/processes_created_by_netsh.yml | 2 +- detections/processes_launching_netsh.yml | 4 ++-- detections/processes_tapping_keyboard_events.yml | 2 +- detections/prohibited_network_traffic_allowed.yml | 4 ++-- detections/prohibited_software_on_endpoint.yml | 4 ++-- detections/protocol_or_port_mismatch.yml | 4 ++-- .../protocols_passing_authentication_in_cleartext.yml | 2 +- ...exe_manipulating_windows_services_registry_keys.yml | 4 ++-- ...sed_to_hide_files_directories_via_registry_keys.yml | 4 ++-- .../registry_keys_for_creating_shim_databases.yml | 4 ++-- detections/registry_keys_used_for_persistence.yml | 10 +++++----- .../registry_keys_used_for_privilege_escalation.yml | 4 ++-- detections/remote_desktop_network_bruteforce.yml | 2 +- detections/remote_desktop_network_traffic.yml | 2 +- .../remote_desktop_process_running_on_system.yml | 2 +- detections/remote_process_instantiation_via_wmi.yml | 2 +- detections/remote_registry_key_modifications.yml | 4 ++-- detections/remote_wmi_command_attempt.yml | 2 +- detections/rundll_loading_dll_by_ordinal.yml | 2 +- detections/samsam_test_file_write.yml | 2 +- detections/sc_exe_manipulating_windows_services.yml | 10 +++++----- ...duled_task_name_used_by_dragonfly_threat_actors.yml | 2 +- .../scheduled_tasks_used_in_badrabbit_ransomware.yml | 2 +- .../schtasks_scheduling_job_on_remote_system.yml | 2 +- detections/schtasks_used_for_forcing_a_reboot.yml | 2 +- detections/script_execution_via_wmi.yml | 2 +- detections/shim_database_file_creation.yml | 2 +- ...atabase_installation_with_suspicious_parameters.yml | 2 +- detections/short_lived_windows_accounts.yml | 2 +- detections/single_letter_process_on_endpoint.yml | 2 +- detections/smb_traffic_spike.yml | 6 +++--- detections/smb_traffic_spike___mltk.yml | 6 +++--- detections/spectre_and_meltdown_vulnerable_systems.yml | 2 +- detections/spike_in_file_writes.yml | 4 ++-- .../splunk_enterprise_information_disclosure.yml | 2 +- detections/sql_injection_with_long_urls.yml | 2 +- detections/suspicious_changes_to_file_associations.yml | 4 ++-- detections/suspicious_email___uba_anomaly.yml | 2 +- detections/suspicious_email_attachment_extensions.yml | 2 +- detections/suspicious_file_write.yml | 2 +- detections/suspicious_java_classes.yml | 2 +- detections/suspicious_lnk_file_launching_a_process.yml | 2 +- detections/suspicious_reg_exe_process.yml | 4 ++-- detections/suspicious_wevtutil_usage.yml | 4 ++-- .../suspicious_writes_to_system_volume_information.yml | 2 +- .../suspicious_writes_to_windows_recycle_bin.yml | 2 +- .../system_processes_run_from_unexpected_locations.yml | 6 +++--- detections/tor_traffic.yml | 4 ++-- detections/uncommon_processes_on_endpoint.yml | 2 +- detections/unload_sysmon_filter_driver.yml | 2 +- detections/unsigned_image_loaded_by_LSASS.yml | 2 +- detections/unsuccessful_netbackup_backups.yml | 2 +- detections/unusually_long_command_line.yml | 6 +++--- detections/unusually_long_command_line___mltk.yml | 6 +++--- detections/unusually_long_content_type_length.yml | 2 +- detections/usn_journal_deletion.yml | 4 ++-- detections/web_fraud___account_harvesting.yml | 2 +- detections/web_fraud___anomalous_user_clickspeed.yml | 2 +- .../web_fraud___password_sharing_across_accounts.yml | 2 +- .../web_servers_executing_suspicious_processes.yml | 2 +- detections/windows_event_log_cleared.yml | 4 ++-- detections/windows_hosts_file_modification.yml | 2 +- detections/wmi_permanent_event_subscription.yml | 2 +- .../wmi_permanent_event_subscription___sysmon.yml | 2 +- detections/wmi_temporary_event_subscription.yml | 2 +- response_tasks/all_backup_logs_for_host.yml | 2 +- .../amazon_eks_kubernetes_activity_by_src_ip.yml | 2 +- .../aws_investigate_user_activities_by_accesskeyid.yml | 2 +- .../aws_investigate_user_activities_by_arn.yml | 2 +- .../aws_investigate_user_activities_by_source_user.yml | 2 +- response_tasks/aws_network_acl_details_from_id.yml | 2 +- .../aws_network_interface_details_via_resourceid.yml | 2 +- .../aws_s3_bucket_details_via_bucketname.yml | 2 +- response_tasks/dns_hijack_enrichment.yml | 4 ++-- response_tasks/domain_certificate_investigation.yml | 4 ++-- ...essive_account_lockouts_enrichment_and_response.yml | 4 ++-- response_tasks/gcp_kubernetes_activity_by_src_ip.yml | 2 +- response_tasks/get_all_aws_activity_from_city.yml | 2 +- response_tasks/get_all_aws_activity_from_country.yml | 2 +- .../get_all_aws_activity_from_ip_address.yml | 2 +- response_tasks/get_all_aws_activity_from_region.yml | 2 +- .../get_authentication_logs_for_endpoint.yml | 2 +- response_tasks/get_backup_logs_for_endpoint.yml | 2 +- response_tasks/get_certificate_logs_for_a_domain.yml | 2 +- response_tasks/get_dns_server_history_for_a_host.yml | 2 +- response_tasks/get_dns_traffic_ratio.yml | 2 +- .../get_ec2_instance_details_by_instanceid.yml | 2 +- response_tasks/get_ec2_launch_details.yml | 2 +- response_tasks/get_email_info.yml | 2 +- response_tasks/get_emails_from_specific_sender.yml | 2 +- ...occurrence_and_last_occurrence_of_a_mac_address.yml | 2 +- response_tasks/get_history_of_email_sources.yml | 2 +- .../get_logon_rights_modifications_for_endpoint.yml | 2 +- .../get_logon_rights_modifications_for_user.yml | 2 +- response_tasks/get_notable_history.yml | 2 +- response_tasks/get_notable_info.yml | 2 +- ...t_outbound_emails_to_hidden_cobra_threat_actors.yml | 2 +- response_tasks/get_parent_process_info.yml | 2 +- response_tasks/get_process_file_activity.yml | 2 +- response_tasks/get_process_info.yml | 2 +- .../get_process_information_for_port_activity.yml | 2 +- response_tasks/get_process_registry_activity.yml | 2 +- .../get_process_responsible_for_the_dns_traffic.yml | 2 +- response_tasks/get_registry_activities.yml | 2 +- response_tasks/get_risk_modifiers_for_endpoint.yml | 2 +- response_tasks/get_risk_modifiers_for_user.yml | 2 +- response_tasks/get_sysmon_wmi_activity_for_host.yml | 2 +- response_tasks/get_update_logs_for_endpoint.yml | 2 +- .../get_user_information_from_identity_table.yml | 2 +- response_tasks/get_vulnerability_logs_for_endpoint.yml | 2 +- .../get_web_session_information_via_session_id.yml | 2 +- .../investigate_aws_activities_via_region_name.yml | 2 +- .../investigate_aws_ecr_container_listing_activity.yml | 2 +- .../investigate_aws_user_activities_by_user_field.yml | 2 +- .../investigate_cloud_compute_instance_activities.yml | 2 +- ...stigate_failed_logins_for_multiple_destinations.yml | 2 +- .../investigate_network_traffic_from_src_ip.yml | 2 +- response_tasks/investigate_okta_activity_by_app.yml | 2 +- .../investigate_okta_activity_by_ip_address.yml | 2 +- response_tasks/investigate_pass_the_hash_attempts.yml | 2 +- .../investigate_pass_the_ticket_attempts.yml | 2 +- response_tasks/investigate_previous_unseen_user.yml | 2 +- ...igate_successful_remote_desktop_authentications.yml | 2 +- .../investigate_suspicious_strings_in_http_header.yml | 2 +- ...nvestigate_user_activities_in_all_cloud_regions.yml | 2 +- response_tasks/investigate_user_activities_in_okta.yml | 2 +- ...estigate_user_activities_in_single_cloud_region.yml | 2 +- response_tasks/investigate_web_activity_from_host.yml | 2 +- .../investigate_web_activity_from_src_ip.yml | 2 +- response_tasks/investigate_web_posts_from_src.yml | 2 +- response_tasks/malware_hunt_and_contain.yml | 4 ++-- ...picious_email_attachment_investigate_and_delete.yml | 4 ++-- spec/baselines.spec.json | 2 +- spec/deployments.spec.json | 4 ---- spec/detections.spec.json | 2 +- spec/response_tasks.spec.json | 2 +- spec/responses.spec.json | 5 ++--- spec/stories.spec.json | 2 +- stories/account_monitoring_and_controls.yml | 2 +- stories/apache_struts_vulnerability.yml | 2 +- stories/asset_tracking.yml | 2 +- stories/aws_cross_account_activity.yml | 2 +- stories/aws_cryptomining.yml | 2 +- stories/aws_network_acl_activity.yml | 2 +- stories/aws_suspicious_provisioning_activities.yml | 2 +- stories/aws_user_monitoring.yml | 2 +- stories/brand_monitoring.yml | 2 +- stories/cloud_cryptomining.yml | 2 +- stories/coldroot_macos_rat.yml | 2 +- stories/collection_and_staging.yml | 2 +- stories/command_and_control.yml | 2 +- stories/common_phishing_frameworks.yml | 2 +- ...ntainer_implantation_monitoring_&_investigation.yml | 2 +- stories/credential_dumping.yml | 2 +- stories/data_protection.yml | 2 +- stories/dhs_report_ta18_074a.yml | 2 +- stories/disabling_security_tools.yml | 2 +- stories/dns_amplification_attacks.yml | 2 +- stories/dns_hijacking.yml | 2 +- stories/dynamic_dns.yml | 2 +- stories/emotet_malware_(dhs_report_ta18_201a).yml | 2 +- stories/hidden_cobra_malware.yml | 2 +- stories/host_redirection.yml | 2 +- stories/jboss_vulnerability.yml | 2 +- stories/kubernetes_scanning_activity.yml | 2 +- stories/lateral_movement.yml | 2 +- stories/malicious_powershell.yml | 2 +- stories/monitor_backup_solution.yml | 2 +- stories/monitor_for_unauthorized_software.yml | 2 +- stories/monitor_for_updates.yml | 2 +- stories/netsh_abuse.yml | 2 +- stories/orangeworm_attack_group.yml | 2 +- stories/phishing_payloads.yml | 2 +- ...ity_associated_with_mudcarp_espionage_campaigns.yml | 2 +- ...prohibited_traffic_allowed_or_protocol_mismatch.yml | 2 +- stories/ransomware.yml | 2 +- stories/router_&_infrastructure_security.yml | 2 +- stories/samsam_ransomware.yml | 2 +- stories/spectre_and_meltdown_vulnerabilities.yml | 2 +- stories/splunk_enterprise_vulnerability.yml | 2 +- .../splunk_enterprise_vulnerability_cve_2018_11409.yml | 2 +- stories/sql_injection.yml | 2 +- stories/suspicious_aws_ec2_activities.yml | 2 +- stories/suspicious_aws_login_activities.yml | 2 +- stories/suspicious_aws_s3_activities.yml | 2 +- stories/suspicious_aws_traffic.yml | 2 +- stories/suspicious_command_line_executions.yml | 2 +- stories/suspicious_dns_traffic.yml | 2 +- stories/suspicious_emails.yml | 2 +- stories/suspicious_mshta_activity.yml | 2 +- stories/suspicious_okta_activity.yml | 2 +- stories/suspicious_windows_registry_activities.yml | 2 +- stories/suspicious_wmi_use.yml | 2 +- stories/unusual_aws_ec2_modifications.yml | 2 +- stories/unusual_processes.yml | 2 +- stories/use_of_cleartext_protocols.yml | 2 +- stories/web_fraud_detection.yml | 2 +- stories/windows_defense_evasion_tactics.yml | 2 +- .../windows_file_extension_and_association_abuse.yml | 2 +- stories/windows_log_manipulation.yml | 2 +- stories/windows_persistence_techniques.yml | 2 +- stories/windows_privilege_escalation.yml | 2 +- stories/windows_service_abuse.yml | 2 +- 369 files changed, 447 insertions(+), 453 deletions(-) diff --git a/baselines/add_prohibited_processes_to_enterprise_security.yml b/baselines/add_prohibited_processes_to_enterprise_security.yml index 7d56b81d78..7d39ecadae 100644 --- a/baselines/add_prohibited_processes_to_enterprise_security.yml +++ b/baselines/add_prohibited_processes_to_enterprise_security.yml @@ -1,6 +1,6 @@ name: Add Prohibited Processes to Enterprise Security id: 251930a5-1451-4428-bb13-eed5775be0ce -version: '1.0' +version: 1 date: '2017-09-15' description: This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes diff --git a/baselines/baseline_of_api_calls_per_user_arn.yml b/baselines/baseline_of_api_calls_per_user_arn.yml index 73f1346346..50a7149394 100644 --- a/baselines/baseline_of_api_calls_per_user_arn.yml +++ b/baselines/baseline_of_api_calls_per_user_arn.yml @@ -1,6 +1,6 @@ name: Baseline of API Calls per User ARN id: fc0edc96-ff2b-48b0-9f6f-63da3783fd63 -version: '1.0' +version: 1 date: '2018-04-09' description: This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number diff --git a/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml b/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml index 8ab019c3de..9208add20d 100644 --- a/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml +++ b/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml @@ -1,6 +1,6 @@ name: Baseline of blocked outbound traffic from AWS id: fc0edd96-ff2b-48b0-9f1f-63da3782fd63 -version: '1.0' +version: 1 date: '2018-05-07' description: This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by diff --git a/baselines/baseline_of_command_line_length___mltk.yml b/baselines/baseline_of_command_line_length___mltk.yml index 32c0717762..28205e56d9 100644 --- a/baselines/baseline_of_command_line_length___mltk.yml +++ b/baselines/baseline_of_command_line_length___mltk.yml @@ -1,6 +1,6 @@ name: Baseline of Command Line Length - MLTK id: d2a4d85b-fc6a-47a0-82f6-bc1ec2ebc459 -version: '1.0' +version: 1 date: '2019-05-08' description: This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. @@ -31,5 +31,5 @@ tags: - Suspicious MSHTA Activity - Unusual Processes detections: - - Unusually Long Command Line - MLTK - Detect Prohibited Applications Spawning cmd.exe + - Unusually Long Command Line - MLTK diff --git a/baselines/baseline_of_dns_query_length___mltk.yml b/baselines/baseline_of_dns_query_length___mltk.yml index 7dc237389b..2cd47fc291 100644 --- a/baselines/baseline_of_dns_query_length___mltk.yml +++ b/baselines/baseline_of_dns_query_length___mltk.yml @@ -1,6 +1,6 @@ name: Baseline of DNS Query Length - MLTK id: c914844c-0ff5-4efc-8d44-c063443129ba -version: '1.0' +version: 1 date: '2019-05-08' description: This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed diff --git a/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml b/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml index 3c8ac68b0d..e5d126b7e8 100644 --- a/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml +++ b/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml @@ -1,6 +1,6 @@ name: Baseline of Excessive AWS Instances Launched by User - MLTK id: fa5634df-fb05-4b4b-aba0-6115138bb1ba -version: '1.0' +version: 1 date: '2019-11-14' description: This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses diff --git a/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml b/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml index aa37ff0640..094bc80954 100644 --- a/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml +++ b/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml @@ -1,6 +1,6 @@ name: Baseline of Excessive AWS Instances Terminated by User - MLTK id: b28ed6de-e4ba-40f7-ae0a-93a088c774ab -version: '1.0' +version: 1 date: '2019-11-14' description: This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search diff --git a/baselines/baseline_of_network_acl_activity_by_arn.yml b/baselines/baseline_of_network_acl_activity_by_arn.yml index b9bf21a4cc..2e01f2fff2 100644 --- a/baselines/baseline_of_network_acl_activity_by_arn.yml +++ b/baselines/baseline_of_network_acl_activity_by_arn.yml @@ -1,6 +1,6 @@ name: Baseline of Network ACL Activity by ARN id: fc0edd96-ff2b-4810-9f1f-63da3783fd63 -version: '1.0' +version: 1 date: '2018-05-21' description: This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each diff --git a/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml b/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml index 4270200846..d6a8283f9d 100644 --- a/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml +++ b/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml @@ -1,6 +1,6 @@ name: Baseline of S3 Bucket deletion activity by ARN id: fc0edd96-ff2b-48b0-9f1f-63eq3783fd63 -version: '1.0' +version: 1 date: '2018-07-17' description: This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. diff --git a/baselines/baseline_of_security_group_activity_by_arn.yml b/baselines/baseline_of_security_group_activity_by_arn.yml index 673f34c8e4..d3c29ad60a 100644 --- a/baselines/baseline_of_security_group_activity_by_arn.yml +++ b/baselines/baseline_of_security_group_activity_by_arn.yml @@ -1,6 +1,6 @@ name: Baseline of Security Group Activity by ARN id: fc0edd96-ff2b-48b0-9f1f-63da3783fd63 -version: '1.0' +version: 1 date: '2018-04-17' description: This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. diff --git a/baselines/baseline_of_smb_traffic___mltk.yml b/baselines/baseline_of_smb_traffic___mltk.yml index fbd3fef0cd..2dd6e5ad48 100644 --- a/baselines/baseline_of_smb_traffic___mltk.yml +++ b/baselines/baseline_of_smb_traffic___mltk.yml @@ -1,6 +1,6 @@ name: Baseline of SMB Traffic - MLTK id: df98763b-0b08-4281-8ef9-08db7ac572a9 -version: '1.0' +version: 1 date: '2019-05-08' description: This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of @@ -36,5 +36,5 @@ tags: - Netsh Abuse - Ransomware detections: - - SMB Traffic Spike - MLTK - Processes launching netsh + - SMB Traffic Spike - MLTK diff --git a/baselines/count_of_assets_by_category.yml b/baselines/count_of_assets_by_category.yml index 99411b1b50..66fd875219 100644 --- a/baselines/count_of_assets_by_category.yml +++ b/baselines/count_of_assets_by_category.yml @@ -1,6 +1,6 @@ name: Count of assets by category id: dcfd6b40-42f9-469d-a433-2e53f7489ff9 -version: '1.0' +version: 1 date: '2017-09-13' description: This search shows you every asset category you have and the assets that belong to those categories. diff --git a/baselines/count_of_unique_ips_connecting_to_ports.yml b/baselines/count_of_unique_ips_connecting_to_ports.yml index 7610cb45be..6b36cfaeae 100644 --- a/baselines/count_of_unique_ips_connecting_to_ports.yml +++ b/baselines/count_of_unique_ips_connecting_to_ports.yml @@ -1,6 +1,6 @@ name: Count of Unique IPs Connecting to Ports id: 9f3bae5a-9fe3-49df-8c84-5edc51d84b7f -version: '1.0' +version: 1 date: '2017-09-13' description: The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. diff --git a/baselines/create_a_list_of_approved_aws_service_accounts.yml b/baselines/create_a_list_of_approved_aws_service_accounts.yml index e20ec70f9a..8da02c5ee3 100644 --- a/baselines/create_a_list_of_approved_aws_service_accounts.yml +++ b/baselines/create_a_list_of_approved_aws_service_accounts.yml @@ -1,6 +1,6 @@ name: Create a list of approved AWS service accounts id: fc0edc95-ff2b-48b1-5f6f-63ga3789fd43 -version: '2.0' +version: 2 date: '2018-12-03' description: This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values diff --git a/baselines/discover_dns_records.yml b/baselines/discover_dns_records.yml index 2a4315ee8b..0e0e13b35b 100644 --- a/baselines/discover_dns_records.yml +++ b/baselines/discover_dns_records.yml @@ -1,6 +1,6 @@ name: Discover DNS records id: c096f721-8842-42ce-bfc7-74bd8c72b7c3 -version: '1.0' +version: 1 date: '2019-02-14' description: The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` diff --git a/baselines/dnstwist_domain_names.yml b/baselines/dnstwist_domain_names.yml index 54f2a308ae..7955295932 100644 --- a/baselines/dnstwist_domain_names.yml +++ b/baselines/dnstwist_domain_names.yml @@ -1,6 +1,6 @@ name: DNSTwist Domain Names id: 19f7d2ec-6028-4d01-bcdb-bda9a034c17f -version: '2.0' +version: 2 date: '2018-10-08' description: This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked @@ -17,5 +17,5 @@ tags: - Suspicious Emails detections: - Monitor Email For Brand Abuse - - Monitor DNS For Brand Abuse - Monitor Web Traffic For Brand Abuse + - Monitor DNS For Brand Abuse diff --git a/baselines/identify_systems_creating_remote_desktop_traffic.yml b/baselines/identify_systems_creating_remote_desktop_traffic.yml index fbe73f658d..8ab2a53cec 100644 --- a/baselines/identify_systems_creating_remote_desktop_traffic.yml +++ b/baselines/identify_systems_creating_remote_desktop_traffic.yml @@ -1,6 +1,6 @@ name: Identify Systems Creating Remote Desktop Traffic id: 5cdda34f-4caf-4128-a713-0837fc48b67a -version: '1.0' +version: 1 date: '2017-09-15' description: This search counts the numbers of times the system has generated remote desktop traffic. diff --git a/baselines/identify_systems_receiving_remote_desktop_traffic.yml b/baselines/identify_systems_receiving_remote_desktop_traffic.yml index a0eadc74b3..db61f6cb75 100644 --- a/baselines/identify_systems_receiving_remote_desktop_traffic.yml +++ b/baselines/identify_systems_receiving_remote_desktop_traffic.yml @@ -1,6 +1,6 @@ name: Identify Systems Receiving Remote Desktop Traffic id: baaeea15-fe8a-4090-92c2-5b60943bb608 -version: '1.0' +version: 1 date: '2017-09-15' description: This search counts the numbers of times the system has created remote desktop traffic diff --git a/baselines/identify_systems_using_remote_desktop.yml b/baselines/identify_systems_using_remote_desktop.yml index 73e6f774ff..a81c57ea04 100644 --- a/baselines/identify_systems_using_remote_desktop.yml +++ b/baselines/identify_systems_using_remote_desktop.yml @@ -1,6 +1,6 @@ name: Identify Systems Using Remote Desktop id: 063dfe9f-b1d7-4254-a16d-1e2e7eadd6a8 -version: '1.0' +version: 1 date: '2019-04-01' description: This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. diff --git a/baselines/monitor_successful_backups.yml b/baselines/monitor_successful_backups.yml index 4c9bc54ed4..664b0f9e0e 100644 --- a/baselines/monitor_successful_backups.yml +++ b/baselines/monitor_successful_backups.yml @@ -1,6 +1,6 @@ name: Monitor Successful Backups id: b4d0dfb2-2195-4f6e-93a3-48468ed9734e -version: '1.0' +version: 1 date: '2017-09-12' description: This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you diff --git a/baselines/monitor_unsuccessful_backups.yml b/baselines/monitor_unsuccessful_backups.yml index f14fa9aed0..0fdd151ef2 100644 --- a/baselines/monitor_unsuccessful_backups.yml +++ b/baselines/monitor_unsuccessful_backups.yml @@ -1,6 +1,6 @@ name: Monitor Unsuccessful Backups id: b2178fed-592f-492b-b851-74161678aa56 -version: '1.0' +version: 1 date: '2017-09-12' description: This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine diff --git a/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml b/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml index 41a7e93df7..22784a9535 100644 --- a/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml +++ b/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml @@ -1,6 +1,6 @@ name: Previously seen API call per user roles in CloudTrail id: fc0edc95-fq2c-48b0-9f6f-63da3289fd03 -version: '1.0' +version: 1 date: '2018-04-16' description: This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this diff --git a/baselines/previously_seen_aws_cross_account_activity.yml b/baselines/previously_seen_aws_cross_account_activity.yml index 39e0c81ae3..0cf796b7f8 100644 --- a/baselines/previously_seen_aws_cross_account_activity.yml +++ b/baselines/previously_seen_aws_cross_account_activity.yml @@ -1,6 +1,6 @@ name: Previously Seen AWS Cross Account Activity id: 1cc22b09-c867-416e-a511-cb36ac44aee2 -version: '1.0' +version: 1 date: '2018-06-04' description: This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml index c4c5cde8bf..32af3f9484 100644 --- a/baselines/previously_seen_aws_provisioning_activity_sources.yml +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -1,6 +1,6 @@ name: Previously Seen AWS Provisioning Activity Sources id: ac88e6a0-4fba-4dfd-b7b9-8964df7d1aee -version: '1.0' +version: 1 date: '2018-03-16' description: This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning @@ -18,6 +18,6 @@ tags: - AWS Suspicious Provisioning Activities detections: - AWS Cloud Provisioning From Previously Unseen City - - AWS Cloud Provisioning From Previously Unseen Region - AWS Cloud Provisioning From Previously Unseen Country - AWS Cloud Provisioning From Previously Unseen IP Address + - AWS Cloud Provisioning From Previously Unseen Region diff --git a/baselines/previously_seen_aws_regions.yml b/baselines/previously_seen_aws_regions.yml index 22a73df2d0..216d3f2226 100644 --- a/baselines/previously_seen_aws_regions.yml +++ b/baselines/previously_seen_aws_regions.yml @@ -1,6 +1,6 @@ name: Previously Seen AWS Regions id: fc0edc95-ff2b-48b0-9f6f-63da3789fd63 -version: '1.0' +version: 1 date: '2018-01-08' description: This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) diff --git a/baselines/previously_seen_cloud_compute_creations_by_user.yml b/baselines/previously_seen_cloud_compute_creations_by_user.yml index 9d492620b3..abc0c45380 100644 --- a/baselines/previously_seen_cloud_compute_creations_by_user.yml +++ b/baselines/previously_seen_cloud_compute_creations_by_user.yml @@ -1,6 +1,6 @@ name: Previously Seen Cloud Compute Creations By User id: 9fa1c205-4e08-4681-bb1b-d0943e734b85 -version: '1.0' +version: 1 date: '2018-03-15' description: This search builds a table of previously seen users that have launched a cloud compute instance. diff --git a/baselines/previously_seen_cloud_compute_images.yml b/baselines/previously_seen_cloud_compute_images.yml index c871274b48..a0f152bff6 100644 --- a/baselines/previously_seen_cloud_compute_images.yml +++ b/baselines/previously_seen_cloud_compute_images.yml @@ -1,6 +1,6 @@ name: Previously Seen Cloud Compute Images id: 3782ad10-5ce2-46e2-b9c4-1de9ecd3aecc -version: '1.0' +version: 1 date: '2018-03-12' description: This search builds a table of previously seen images used to launch cloud compute instances diff --git a/baselines/previously_seen_cloud_compute_instance_types.yml b/baselines/previously_seen_cloud_compute_instance_types.yml index 4d11210d4d..8cd2e0d610 100644 --- a/baselines/previously_seen_cloud_compute_instance_types.yml +++ b/baselines/previously_seen_cloud_compute_instance_types.yml @@ -1,6 +1,6 @@ name: Previously Seen Cloud Compute Instance Types id: 0ef13d46-164e-4cf5-816e-b3c0df170d00 -version: '1.0' +version: 1 date: '2019-10-03' description: This search builds a table of previously seen cloud compute instance types diff --git a/baselines/previously_seen_cloud_regions.yml b/baselines/previously_seen_cloud_regions.yml index fad9c0bbfe..82fa2c9c9c 100644 --- a/baselines/previously_seen_cloud_regions.yml +++ b/baselines/previously_seen_cloud_regions.yml @@ -1,6 +1,6 @@ name: Previously Seen Cloud Regions id: b5e232db-dec6-4db8-aaa1-dd5474521e40 -version: '1.0' +version: 1 date: '2019-10-02' description: This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time diff --git a/baselines/previously_seen_command_line_arguments.yml b/baselines/previously_seen_command_line_arguments.yml index 30e00acb41..8b15521edb 100644 --- a/baselines/previously_seen_command_line_arguments.yml +++ b/baselines/previously_seen_command_line_arguments.yml @@ -1,6 +1,6 @@ name: Previously seen command line arguments id: fc0edc95-ff2b-48b0-9f6f-63da3789fd23 -version: '2.0' +version: 2 date: '2019-03-01' description: This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we @@ -25,6 +25,6 @@ tags: - Suspicious Command-Line Executions - Suspicious MSHTA Activity detections: - - First time seen command line argument - - Processes launching netsh - Detect Prohibited Applications Spawning cmd.exe + - Processes launching netsh + - First time seen command line argument diff --git a/baselines/previously_seen_ec2_amis.yml b/baselines/previously_seen_ec2_amis.yml index e178d032e4..9898eaf0f3 100644 --- a/baselines/previously_seen_ec2_amis.yml +++ b/baselines/previously_seen_ec2_amis.yml @@ -1,6 +1,6 @@ name: Previously Seen EC2 AMIs id: bb1bd99d-1e93-45f1-9571-cfed42d372b9 -version: '1.0' +version: 1 date: '2018-03-12' description: This search builds a table of previously seen AMIs used to launch EC2 instances diff --git a/baselines/previously_seen_ec2_instance_types.yml b/baselines/previously_seen_ec2_instance_types.yml index 232ef47c5f..7772799582 100644 --- a/baselines/previously_seen_ec2_instance_types.yml +++ b/baselines/previously_seen_ec2_instance_types.yml @@ -1,6 +1,6 @@ name: Previously Seen EC2 Instance Types id: b8f029f2-65a6-4d76-be98-dad1c9d59c45 -version: '1.0' +version: 1 date: '2018-03-08' description: This search builds a table of previously seen EC2 instance types how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or later) diff --git a/baselines/previously_seen_ec2_launches_by_user.yml b/baselines/previously_seen_ec2_launches_by_user.yml index 86e275b619..c78ab03694 100644 --- a/baselines/previously_seen_ec2_launches_by_user.yml +++ b/baselines/previously_seen_ec2_launches_by_user.yml @@ -1,6 +1,6 @@ name: Previously Seen EC2 Launches By User id: 6c767ac0-0906-4355-9a83-927f5ee7bdad -version: '1.0' +version: 1 date: '2018-03-15' description: This search builds a table of previously seen ARNs that have launched a EC2 instance. diff --git a/baselines/previously_seen_ec2_modifications_by_user.yml b/baselines/previously_seen_ec2_modifications_by_user.yml index d7b00395c2..84c8457edc 100644 --- a/baselines/previously_seen_ec2_modifications_by_user.yml +++ b/baselines/previously_seen_ec2_modifications_by_user.yml @@ -1,6 +1,6 @@ name: Previously Seen EC2 Modifications By User id: 4d69091b-d975-4267-85df-888bd41034eb -version: '1.0' +version: 1 date: '2018-04-05' description: This search builds a table of previously seen ARNs that have launched a EC2 instance. diff --git a/baselines/previously_seen_running_windows_services.yml b/baselines/previously_seen_running_windows_services.yml index 5f4daab731..67d8a30669 100644 --- a/baselines/previously_seen_running_windows_services.yml +++ b/baselines/previously_seen_running_windows_services.yml @@ -1,6 +1,6 @@ name: Previously Seen Running Windows Services id: 64ce0ade-cb01-4678-bddd-d31c0b175394 -version: '2.0' +version: 2 date: '2020-01-13' description: This collects the services that have been started across your entire enterprise. diff --git a/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml b/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml index 49b72e8913..100ce354e2 100644 --- a/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml +++ b/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml @@ -1,6 +1,6 @@ name: Previously seen S3 bucket access by remote IP id: fc0edc15-fq2c-48b0-9f6f-63qa1281fd03 -version: '1.0' +version: 1 date: '2018-06-28' description: This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml index eafe11ec93..a28efb9a54 100644 --- a/baselines/previously_seen_users_in_cloudtrail.yml +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -1,6 +1,6 @@ name: Previously seen users in CloudTrail id: fc0edc95-ff2b-48b0-9f6f-63da3789fd03 -version: '1.1' +version: 1 date: '2018-04-30' description: This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country @@ -20,7 +20,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect AWS Console Login by User from New Region - - Detect AWS Console Login by User from New Country - Detect new user AWS Console Login + - Detect AWS Console Login by User from New Region - Detect AWS Console Login by User from New City + - Detect AWS Console Login by User from New Country diff --git a/baselines/systems_ready_for_spectre_meltdown_windows_patch.yml b/baselines/systems_ready_for_spectre_meltdown_windows_patch.yml index 55eb0d8d00..5503ddeb98 100644 --- a/baselines/systems_ready_for_spectre_meltdown_windows_patch.yml +++ b/baselines/systems_ready_for_spectre_meltdown_windows_patch.yml @@ -1,6 +1,6 @@ name: Systems Ready for Spectre-Meltdown Windows Patch id: fc0edc95-ff2b-48b0-9f6f-63da3789fd61 -version: '1.0' +version: 1 date: '2018-01-08' description: Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml index 8b07ed7dd0..75266587b0 100644 --- a/baselines/update_previously_seen_users_in_cloudtrail.yml +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -1,6 +1,6 @@ name: Update previously seen users in CloudTrail id: 06c036e6-d6d7-4daa-bd76-411c3d356031 -version: '1.0' +version: 1 date: '2018-04-30' description: This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country @@ -20,7 +20,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect AWS Console Login by User from New Region - - Detect AWS Console Login by User from New Country - Detect new user AWS Console Login + - Detect AWS Console Login by User from New Region - Detect AWS Console Login by User from New City + - Detect AWS Console Login by User from New Country diff --git a/baselines/windows_updates_install_failures.yml b/baselines/windows_updates_install_failures.yml index 5c9d02a37d..8fa8ad8415 100644 --- a/baselines/windows_updates_install_failures.yml +++ b/baselines/windows_updates_install_failures.yml @@ -1,6 +1,6 @@ name: Windows Updates Install Failures id: 6a4dbd1b-4502-4a11-943a-82b5ae7a42d7 -version: '1.0' +version: 1 date: '2017-09-14' description: This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you diff --git a/baselines/windows_updates_install_successes.yml b/baselines/windows_updates_install_successes.yml index a4c084f794..0b30e84d42 100644 --- a/baselines/windows_updates_install_successes.yml +++ b/baselines/windows_updates_install_successes.yml @@ -1,6 +1,6 @@ name: Windows Updates Install Successes id: 6a80535c-86a6-4b54-894c-4b446d0c701d -version: '1.0' +version: 1 date: '2017-09-14' description: This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow diff --git a/bin/validate.py b/bin/validate.py index 93096761ea..4b9bf045e1 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -177,7 +177,6 @@ if __name__ == "__main__": objects, error = validate_schema(REPO_PATH, validation_object, objects) schema_error = schema_error or error - print(objects) if schema_error: sys.exit("Errors found") diff --git a/detections/abnormally_high_aws_instances_launched_by_user.yml b/detections/abnormally_high_aws_instances_launched_by_user.yml index 4ae5dbc3f3..635eb719d3 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user.yml @@ -1,6 +1,6 @@ name: Abnormally High AWS Instances Launched by User id: 2a9b80d3-6340-4345-b5ad-290bf5d0dac4 -version: '1.0' +version: 1 date: '2018-02-26' description: This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. diff --git a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml index fb7ff60e42..f1513b4a7a 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml @@ -1,6 +1,6 @@ name: Abnormally High AWS Instances Launched by User - MLTK id: dec41ad5-d579-42cb-b4c6-f5dbb778bbe5 -version: '1.0' +version: 1 date: '2019-11-14' description: This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. diff --git a/detections/abnormally_high_aws_instances_terminated_by_user.yml b/detections/abnormally_high_aws_instances_terminated_by_user.yml index 3fa579b83f..83a02b9a46 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user.yml @@ -1,6 +1,6 @@ name: Abnormally High AWS Instances Terminated by User id: ada0f478-84a8-4641-s3f3-d82362dffd75 -version: '1.0' +version: 1 date: '2018-02-26' description: This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window diff --git a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml index edc3f6cea2..d367aa5a6a 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml @@ -1,6 +1,6 @@ name: Abnormally High AWS Instances Terminated by User - MLTK id: 1c02b86a-cd85-473e-a50b-014a9ac8fe3e -version: '1.0' +version: 1 date: '2019-11-14' description: This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. diff --git a/detections/access_lsass_memory_for_dump_creation.yml b/detections/access_lsass_memory_for_dump_creation.yml index b215fed710..8daad06d5c 100644 --- a/detections/access_lsass_memory_for_dump_creation.yml +++ b/detections/access_lsass_memory_for_dump_creation.yml @@ -1,6 +1,6 @@ name: Access LSASS Memory for Dump Creation id: fb4c31b0-13e8-4155-8aa5-24de4b8d6717 -version: '2' +version: 2 date: '2019-12-06' description: Detect memory dumping of the LSASS process. how_to_implement: This search requires Sysmon Logs and a Sysmon configuration, which diff --git a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml index 97cd63b3da..693fd5fba9 100644 --- a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml @@ -1,6 +1,6 @@ name: Amazon EKS Kubernetes cluster scan detection id: 294c4686-63dd-4fe6-93a2-ca807626704a -version: '1.0' +version: 1 date: '2020-04-15' description: This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS diff --git a/detections/amazon_eks_kubernetes_pod_scan_detection.yml b/detections/amazon_eks_kubernetes_pod_scan_detection.yml index b43f24a547..7b01844fa0 100644 --- a/detections/amazon_eks_kubernetes_pod_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_pod_scan_detection.yml @@ -1,6 +1,6 @@ name: Amazon EKS Kubernetes Pod scan detection id: dbfca1dd-b8e5-4ba4-be0e-e565e5d62002 -version: '1.0' +version: 1 date: '2020-04-15' description: This search provides detection information on unauthenticated requests against Kubernetes' Pods API diff --git a/detections/attempt_to_add_certificate_to_untrusted_store.yml b/detections/attempt_to_add_certificate_to_untrusted_store.yml index c68b140756..7d3a299839 100644 --- a/detections/attempt_to_add_certificate_to_untrusted_store.yml +++ b/detections/attempt_to_add_certificate_to_untrusted_store.yml @@ -1,6 +1,6 @@ name: Attempt To Add Certificate To Untrusted Store id: 6bc5243e-ef36-45dc-9b12-f4a6be131159 -version: '4.0' +version: 4 date: '2018-11-15' description: Attempt to add a certificate to the untrusted certificate store how_to_implement: You must be ingesting data that records process activity from your diff --git a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml index c8bc5255db..027189c023 100644 --- a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml +++ b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml @@ -1,6 +1,6 @@ name: Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass id: c2590137-0b08-4985-9ec5-6ae23d92f63d -version: '4.0' +version: 4 date: '2019-12-02' description: Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. diff --git a/detections/attempt_to_stop_security_service.yml b/detections/attempt_to_stop_security_service.yml index 9cc383f3f4..5a7e92b5a0 100644 --- a/detections/attempt_to_stop_security_service.yml +++ b/detections/attempt_to_stop_security_service.yml @@ -1,6 +1,6 @@ name: Attempt To Stop Security Service id: c8e349c6-b97c-486e-8949-bd7bcd1f3910 -version: '2.0' +version: 2 date: '2017-09-15' description: This search looks for attempts to stop security-related services on the endpoint. diff --git a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml index bf63df1c35..ebb92d62a8 100644 --- a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml +++ b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml @@ -1,6 +1,6 @@ name: Attempted Credential Dump From Registry via Reg.exe id: 14038953-e5f2-4daf-acff-5452062baf03 -version: '4.0' +version: 4 date: '2019-12-02' description: Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml index 871e7f27da..8d23d421a1 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml @@ -1,6 +1,6 @@ name: AWS Cloud Provisioning From Previously Unseen City id: 344a1778-0b25-490c-adb1-de8beddf59cd -version: '1.0' +version: 1 date: '2018-03-16' description: 'This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml index 071f97513b..a7496c0c60 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml @@ -1,6 +1,6 @@ name: AWS Cloud Provisioning From Previously Unseen Country id: ceb8d3d8-06cb-49eb-beaf-829526e33ff0 -version: '1.0' +version: 1 date: '2018-03-16' description: 'This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml index 28784215f1..1d9b808d10 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml @@ -1,6 +1,6 @@ name: AWS Cloud Provisioning From Previously Unseen IP Address id: 42e15012-ac14-4801-94f4-f1acbe64880b -version: '1.0' +version: 1 date: '2018-03-16' description: 'This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml index 7bd5963a0f..69511b9777 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml @@ -1,6 +1,6 @@ name: AWS Cloud Provisioning From Previously Unseen Region id: 7971d3df-da82-4648-a6e5-b5637bea5253 -version: '1.0' +version: 1 date: '2018-03-16' description: This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning diff --git a/detections/aws_cross_account_activity_from_previously_unseen_account.yml b/detections/aws_cross_account_activity_from_previously_unseen_account.yml index 10a2bf0c6c..dbd1b491a4 100644 --- a/detections/aws_cross_account_activity_from_previously_unseen_account.yml +++ b/detections/aws_cross_account_activity_from_previously_unseen_account.yml @@ -1,6 +1,6 @@ name: AWS Cross Account Activity From Previously Unseen Account id: 64fbbddf-fabf-4edf-80b3-0cc36ef37727 -version: '2.0' +version: 2 date: '2018-11-02' description: This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. diff --git a/detections/aws_network_access_control_list_created_with_all_open_ports.yml b/detections/aws_network_access_control_list_created_with_all_open_ports.yml index 34631bb25c..b8bf405ece 100644 --- a/detections/aws_network_access_control_list_created_with_all_open_ports.yml +++ b/detections/aws_network_access_control_list_created_with_all_open_ports.yml @@ -1,6 +1,6 @@ name: AWS Network Access Control List Created with All Open Ports id: ada0f478-84a8-4641-a3f1-d82362d6bd75 -version: '1.0' +version: 1 date: '2017-01-10' description: The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. diff --git a/detections/aws_network_access_control_list_deleted.yml b/detections/aws_network_access_control_list_deleted.yml index 9589defa5c..4d2c7e873a 100644 --- a/detections/aws_network_access_control_list_deleted.yml +++ b/detections/aws_network_access_control_list_deleted.yml @@ -1,6 +1,6 @@ name: AWS Network Access Control List Deleted id: ada0f478-84a8-4641-a3f1-d82362d6fd75 -version: '1.0' +version: 1 date: '2017-01-10' description: Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker diff --git a/detections/batch_file_write_to_system32.yml b/detections/batch_file_write_to_system32.yml index cc0a678697..3930ca0474 100644 --- a/detections/batch_file_write_to_system32.yml +++ b/detections/batch_file_write_to_system32.yml @@ -1,6 +1,6 @@ name: Batch File Write to System32 id: 503d17cb-9eab-4cf8-a20e-01d5c6987ae3 -version: '1.0' +version: 1 date: '2018-12-14' description: The search looks for a batch file (.bat) written to the Windows system directory tree. diff --git a/detections/child_processes_of_spoolsv_exe.yml b/detections/child_processes_of_spoolsv_exe.yml index eb6e971288..46c9fe162e 100644 --- a/detections/child_processes_of_spoolsv_exe.yml +++ b/detections/child_processes_of_spoolsv_exe.yml @@ -1,6 +1,6 @@ name: Child Processes of Spoolsv.exe id: aa0c4aeb-5b18-41c4-8c07-f1442d7599df -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. diff --git a/detections/clients_connecting_to_multiple_dns_servers.yml b/detections/clients_connecting_to_multiple_dns_servers.yml index d22499bfee..24849c2e5a 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.yml +++ b/detections/clients_connecting_to_multiple_dns_servers.yml @@ -1,6 +1,6 @@ name: Clients Connecting to Multiple DNS Servers id: 74ec6f18-604b-4202-a567-86b2066be3ce -version: '2.0' +version: 2 date: '2020-01-16' description: This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. @@ -27,10 +27,10 @@ known_false_positives: It's possible that an enterprise has more than five DNS s that are configured in a round-robin rotation. Please customize the search, as appropriate. tags: analytics_story: + - DNS Hijacking + - Command and Control - Host Redirection - Suspicious DNS Traffic - - Command and Control - - DNS Hijacking mitre_attack_id: - T1048 kill_chain_phases: diff --git a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml index d41510dc16..2c482d2064 100644 --- a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml +++ b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml @@ -1,6 +1,6 @@ name: Cloud Compute Instance Created By Previously Unseen User id: 76988f6a-3935-48f6-a9e5-6fca8b3ed843 -version: '1.0' +version: 1 date: '2018-03-12' description: This search looks for cloud compute instances created by users who have not created them before. diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml index 301b5865e2..571e320d81 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml @@ -1,6 +1,6 @@ name: Cloud Compute Instance Created With Previously Unseen Image id: bc24922d-987c-4645-b288-f8c73ec194c4 -version: '1.0' +version: 1 date: '2018-10-12' description: This search looks for cloud compute instances being created with previously unseen image IDs. diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml index b18f021d14..2dfd70c512 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml @@ -1,6 +1,6 @@ name: Cloud Compute Instance Created With Previously Unseen Instance Type id: c6ddbf53-9715-49f3-bb4c-fb2e8a309cda -version: '1.0' +version: 1 date: '2018-03-12' description: Find EC2 instances being created with previously unseen instance types. how_to_implement: You must be ingesting the appropriate cloud-infrastructure logs diff --git a/detections/cloud_compute_instance_started_in_previously_unused_region.yml b/detections/cloud_compute_instance_started_in_previously_unused_region.yml index d281a81ce9..764680aaa3 100644 --- a/detections/cloud_compute_instance_started_in_previously_unused_region.yml +++ b/detections/cloud_compute_instance_started_in_previously_unused_region.yml @@ -1,6 +1,6 @@ name: Cloud Compute Instance Started In Previously Unused Region id: fa4089e2-50e3-40f7-8469-d2cc1564ca59 -version: '1.0' +version: 1 date: '2019-10-02' description: This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file diff --git a/detections/common_ransomware_extensions.yml b/detections/common_ransomware_extensions.yml index 5076023967..1fdd3c7327 100644 --- a/detections/common_ransomware_extensions.yml +++ b/detections/common_ransomware_extensions.yml @@ -1,6 +1,6 @@ name: Common Ransomware Extensions id: a9e5c5db-db11-43ca-86a8-c852d1b2c0ec -version: '3.0' +version: 3 date: '2020-03-16' description: The search looks for file modifications with extensions commonly used by Ransomware @@ -35,8 +35,8 @@ known_false_positives: It is possible for a legitimate file with these extension of files created with these extensions. tags: analytics_story: - - SamSam Ransomware - Ransomware + - SamSam Ransomware kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/common_ransomware_notes.yml b/detections/common_ransomware_notes.yml index 1c6c412e1b..86c21a9512 100644 --- a/detections/common_ransomware_notes.yml +++ b/detections/common_ransomware_notes.yml @@ -1,6 +1,6 @@ name: Common Ransomware Notes id: ada0f478-84a8-4641-a3f1-d82362d6bd71 -version: '3.0' +version: 3 date: '2020-03-16' description: The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. @@ -21,8 +21,8 @@ known_false_positives: It's possible that a legitimate file could be created wit the same name used by ransomware note files. tags: analytics_story: - - SamSam Ransomware - Ransomware + - SamSam Ransomware kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/create_local_admin_accounts_using_net_exe.yml b/detections/create_local_admin_accounts_using_net_exe.yml index c3e38355d4..7ccba36e16 100644 --- a/detections/create_local_admin_accounts_using_net_exe.yml +++ b/detections/create_local_admin_accounts_using_net_exe.yml @@ -1,6 +1,6 @@ name: Create local admin accounts using net.exe id: b89919ed-fe5f-492c-b139-151bb162040e -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for the creation of local administrator accounts using net.exe. diff --git a/detections/create_or_delete_windows_shares_using_net_exe.yml b/detections/create_or_delete_windows_shares_using_net_exe.yml index 4b91efc020..89f0dec103 100644 --- a/detections/create_or_delete_windows_shares_using_net_exe.yml +++ b/detections/create_or_delete_windows_shares_using_net_exe.yml @@ -1,6 +1,6 @@ name: Create or delete windows shares using net.exe id: qw9919ed-fe5f-492c-b139-151bb162140e -version: '4.0' +version: 4 date: '2020-01-20' description: This search looks for the creation or deletion of hidden shares using net.exe. diff --git a/detections/create_remote_thread_into_lsass.yml b/detections/create_remote_thread_into_lsass.yml index 8ab642d9dc..f42dfef20f 100644 --- a/detections/create_remote_thread_into_lsass.yml +++ b/detections/create_remote_thread_into_lsass.yml @@ -1,6 +1,6 @@ name: Create Remote Thread into LSASS id: 67d4dbef-9564-4699-8da8-03a151529edc -version: '1' +version: 1 date: '2019-12-06' description: Detect remote thread creation into LSASS consistent with credential dumping. how_to_implement: This search needs Sysmon Logs with a Sysmon configuration, which diff --git a/detections/creation_of_shadow_copy.yml b/detections/creation_of_shadow_copy.yml index d0c082b6dc..f3275e90e9 100644 --- a/detections/creation_of_shadow_copy.yml +++ b/detections/creation_of_shadow_copy.yml @@ -1,6 +1,6 @@ name: Creation of Shadow Copy id: eb120f5f-b879-4a63-97c1-93352b5df844 -version: '1.0' +version: 1 date: '2019-12-10' description: Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. diff --git a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml index f399159f3a..05a6f965b6 100644 --- a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml +++ b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml @@ -1,6 +1,6 @@ name: Creation of Shadow Copy with wmic and powershell id: 2ed8b538-d284-449a-be1d-82ad1dbd186b -version: '1.0' +version: 1 date: '2019-12-10' description: This search detects the use of wmic and Powershell to create a shadow copy. diff --git a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml index 2f70642e10..32823260a8 100644 --- a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml +++ b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml @@ -1,6 +1,6 @@ name: Credential Dumping via Copy Command from Shadow Copy id: d8c406fe-23d2-45f3-a983-1abe7b83ff3b -version: '1.0' +version: 1 date: '2019-12-10' description: This search detects credential dumping using copy command from a shadow copy. diff --git a/detections/credential_dumping_via_symlink_to_shadow_copy.yml b/detections/credential_dumping_via_symlink_to_shadow_copy.yml index d352b71f72..5b070f555b 100644 --- a/detections/credential_dumping_via_symlink_to_shadow_copy.yml +++ b/detections/credential_dumping_via_symlink_to_shadow_copy.yml @@ -1,6 +1,6 @@ name: Credential Dumping via Symlink to Shadow Copy id: c5eac648-fae0-4263-91a6-773df1f4c903 -version: '1.0' +version: 1 date: '2019-12-10' description: This search detects the creation of a symlink to a shadow copy. how_to_implement: You must be ingesting endpoint data that tracks process activity, diff --git a/detections/deleting_shadow_copies.yml b/detections/deleting_shadow_copies.yml index 5e271880fb..e652ccec14 100644 --- a/detections/deleting_shadow_copies.yml +++ b/detections/deleting_shadow_copies.yml @@ -1,6 +1,6 @@ name: Deleting Shadow Copies id: b89919ed-ee5f-492c-b139-95dbb162039e -version: '2.1' +version: 2 date: '2020-04-17' description: The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This @@ -23,9 +23,9 @@ known_false_positives: vssadmin.exe and wmic.exe are standard applications shipp delete old backup copies, although this is typically rare. tags: analytics_story: - - SamSam Ransomware - - Ransomware - Windows Log Manipulation + - Ransomware + - SamSam Ransomware kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/detect_activity_related_to_pass_the_hash_attacks.yml b/detections/detect_activity_related_to_pass_the_hash_attacks.yml index 4c72180678..d89b4e57d7 100644 --- a/detections/detect_activity_related_to_pass_the_hash_attacks.yml +++ b/detections/detect_activity_related_to_pass_the_hash_attacks.yml @@ -1,6 +1,6 @@ name: Detect Activity Related to Pass the Hash Attacks id: f5939373-8054-40ad-8c64-cec478a22a4b -version: '3.0' +version: 3 date: '2020-01-09' description: This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. diff --git a/detections/detect_api_activity_from_users_without_mfa.yml b/detections/detect_api_activity_from_users_without_mfa.yml index 55b8a9e60a..c29fef5752 100644 --- a/detections/detect_api_activity_from_users_without_mfa.yml +++ b/detections/detect_api_activity_from_users_without_mfa.yml @@ -1,6 +1,6 @@ name: Detect API activity from users without MFA id: 2a9b80d3-6340-4345-w5ad-212bf5d1dac4 -version: '1.0' +version: 1 date: '2018-05-17' description: This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. diff --git a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml index 5d1b4efcc1..f0f6fe7e83 100644 --- a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml +++ b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml @@ -1,6 +1,6 @@ name: Detect attackers scanning for vulnerable JBoss servers id: 104658f4-afdc-499e-9719-17243f982681 -version: '1.0' +version: 1 date: '2017-09-23' description: This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. @@ -19,8 +19,8 @@ known_false_positives: It's possible for legitimate HTTP requests to be made to containing the suspicious paths. tags: analytics_story: - - SamSam Ransomware - JBoss Vulnerability + - SamSam Ransomware mitre_attack_id: - T1082 kill_chain_phases: diff --git a/detections/detect_aws_api_activities_from_unapproved_accounts.yml b/detections/detect_aws_api_activities_from_unapproved_accounts.yml index 1656ef50ae..79024b10ed 100644 --- a/detections/detect_aws_api_activities_from_unapproved_accounts.yml +++ b/detections/detect_aws_api_activities_from_unapproved_accounts.yml @@ -1,6 +1,6 @@ name: Detect AWS API Activities From Unapproved Accounts id: ada0f478-84a8-4641-a3f1-d82362d4bd55 -version: '1.0' +version: 1 date: '2018-03-13' description: This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns diff --git a/detections/detect_aws_console_login_by_user_from_new_city.yml b/detections/detect_aws_console_login_by_user_from_new_city.yml index c10475eb6c..99c6dc88e8 100644 --- a/detections/detect_aws_console_login_by_user_from_new_city.yml +++ b/detections/detect_aws_console_login_by_user_from_new_city.yml @@ -1,6 +1,6 @@ name: Detect AWS Console Login by User from New City id: 121b0b11-f8ac-4ed6-a132-3800ca4fc07a -version: '1.0' +version: 1 date: '2018-04-30' description: This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup diff --git a/detections/detect_aws_console_login_by_user_from_new_country.yml b/detections/detect_aws_console_login_by_user_from_new_country.yml index 50baf1944b..a1d560a146 100644 --- a/detections/detect_aws_console_login_by_user_from_new_country.yml +++ b/detections/detect_aws_console_login_by_user_from_new_country.yml @@ -1,6 +1,6 @@ name: Detect AWS Console Login by User from New Country id: 67bd3def-c41c-4bf6-837b-ae196b4257c6 -version: '1.0' +version: 1 date: '2018-04-30' description: This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup diff --git a/detections/detect_aws_console_login_by_user_from_new_region.yml b/detections/detect_aws_console_login_by_user_from_new_region.yml index a0c39dabc3..9120d4be06 100644 --- a/detections/detect_aws_console_login_by_user_from_new_region.yml +++ b/detections/detect_aws_console_login_by_user_from_new_region.yml @@ -1,6 +1,6 @@ name: Detect AWS Console Login by User from New Region id: 9f31aa8e-e37c-46bc-bce1-8b3be646d026 -version: '1.0' +version: 1 date: '2018-04-30' description: This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup diff --git a/detections/detect_credential_dumping_through_LSASS_access.yml b/detections/detect_credential_dumping_through_LSASS_access.yml index 87bfb3782e..4cc8f7c9fc 100644 --- a/detections/detect_credential_dumping_through_LSASS_access.yml +++ b/detections/detect_credential_dumping_through_LSASS_access.yml @@ -1,6 +1,6 @@ name: Detect Credential Dumping through LSASS access id: 2c365e57-4414-4540-8dc0-73ab10729996 -version: '3' +version: 3 date: '2019-12-03' description: This search looks for reading lsass memory consistent with credential dumping. diff --git a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml index 67d171a40e..5516b0c8f6 100644 --- a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml +++ b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml @@ -1,6 +1,6 @@ name: Detect DNS requests to Phishing Sites leveraging EvilGinx2 id: 24dd17b1-e2fb-4c31-878c-d4f226595bfa -version: '1.0' +version: 1 date: '2019-04-29' description: This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. diff --git a/detections/detect_excessive_account_lockouts_from_endpoint.yml b/detections/detect_excessive_account_lockouts_from_endpoint.yml index 7206159e8a..0c6e69c6ea 100644 --- a/detections/detect_excessive_account_lockouts_from_endpoint.yml +++ b/detections/detect_excessive_account_lockouts_from_endpoint.yml @@ -1,6 +1,6 @@ name: Detect Excessive Account Lockouts From Endpoint id: c026e3dd-7e18-4abb-8f41-929e836efe74 -version: '3.0' +version: 3 date: '2019-04-18' description: This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. diff --git a/detections/detect_excessive_user_account_lockouts.yml b/detections/detect_excessive_user_account_lockouts.yml index e612236bc8..40214661e9 100644 --- a/detections/detect_excessive_user_account_lockouts.yml +++ b/detections/detect_excessive_user_account_lockouts.yml @@ -1,6 +1,6 @@ name: Detect Excessive User Account Lockouts id: 95a7f9a5-6096-437e-a19e-86f42ac609bd -version: '2.0' +version: 2 date: '2019-03-01' description: This search detects user accounts that have been locked out a relatively high number of times in a short period. diff --git a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index ecc59ccd70..f01ec4030b 100644 --- a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -1,6 +1,6 @@ name: Detect hosts connecting to dynamic domain providers id: c77162d3-f93c-45cc-80c8-22f6v5464g9f -version: '2.0' +version: 2 date: '2020-01-16' description: Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate @@ -45,9 +45,9 @@ tags: analytics_story: - Data Protection - DNS Hijacking - - Prohibited Traffic Allowed or Protocol Mismatch - - Command and Control - Dynamic DNS + - Command and Control + - Prohibited Traffic Allowed or Protocol Mismatch - Suspicious DNS Traffic kill_chain_phases: - Command and Control diff --git a/detections/detect_large_outbound_icmp_packets.yml b/detections/detect_large_outbound_icmp_packets.yml index 62ccd7703a..0e5a0e7450 100644 --- a/detections/detect_large_outbound_icmp_packets.yml +++ b/detections/detect_large_outbound_icmp_packets.yml @@ -1,6 +1,6 @@ name: Detect Large Outbound ICMP Packets id: e9c102de-4d43-42a7-b1c8-8062ea297419 -version: '2.0' +version: 2 date: '2018-06-01' description: This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command diff --git a/detections/detect_long_dns_txt_record_response.yml b/detections/detect_long_dns_txt_record_response.yml index b2f8f7667d..a89e8e4f66 100644 --- a/detections/detect_long_dns_txt_record_response.yml +++ b/detections/detect_long_dns_txt_record_response.yml @@ -1,6 +1,6 @@ name: Detect Long DNS TXT Record Response id: 05437c07-62f5-452e-afdc-04dd44815bb9 -version: '1.0' +version: 1 date: '2017-09-18' description: This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission @@ -28,8 +28,8 @@ known_false_positives: It's possible that legitimate TXT record responses can be to help mitigate false positives. tags: analytics_story: - - Suspicious DNS Traffic - Command and Control + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml index 1589b6e486..b1d4e18ec5 100644 --- a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml +++ b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml @@ -1,6 +1,6 @@ name: Detect malicious requests to exploit JBoss servers id: c8bff7a4-11ea-4416-a27d-c5bca472913d -version: '1.0' +version: 1 date: '2017-09-23' description: This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as @@ -20,8 +20,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: No known false positives for this detection. tags: analytics_story: - - SamSam Ransomware - JBoss Vulnerability + - SamSam Ransomware kill_chain_phases: - Delivery cis20: diff --git a/detections/detect_mimikatz_using_loaded_images.yml b/detections/detect_mimikatz_using_loaded_images.yml index a6e22c923c..d597116c93 100644 --- a/detections/detect_mimikatz_using_loaded_images.yml +++ b/detections/detect_mimikatz_using_loaded_images.yml @@ -1,6 +1,6 @@ name: Detect Mimikatz Using Loaded Images id: 29e307ba-40af-4ab2-91b2-3c6b392bbba0 -version: '1' +version: 1 date: '2019-12-03' description: This search looks for reading loaded Images unique to credential dumping with Mimikatz. diff --git a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml index 3d3afded3e..eb436f58b8 100644 --- a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml +++ b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml @@ -1,6 +1,6 @@ name: Detect Mimikatz Via PowerShell And EventCode 4703 id: 98917be2-bfc8-475a-8618-a9bb06575188 -version: '2.0' +version: 2 date: '2019-02-27' description: This search looks for PowerShell requesting privileges consistent with credential dumping. diff --git a/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml index 4fb9e2c4c3..37acfd5d3f 100644 --- a/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml +++ b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml @@ -1,6 +1,6 @@ name: Detect mshta.exe running scripts in command-line arguments id: b89919ed-fe5f-492c-b139-95dqb161039e -version: '2.0' +version: 2 date: '2018-12-03' description: This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time diff --git a/detections/detect_new_api_calls_from_user_roles.yml b/detections/detect_new_api_calls_from_user_roles.yml index 931ba516ee..d354664be2 100644 --- a/detections/detect_new_api_calls_from_user_roles.yml +++ b/detections/detect_new_api_calls_from_user_roles.yml @@ -1,6 +1,6 @@ name: Detect new API calls from user roles id: 22773e84-bac0-4595-b086-20d3f335b4f1 -version: '1.0' +version: 1 date: '2018-04-16' description: This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. diff --git a/detections/detect_new_local_admin_account.yml b/detections/detect_new_local_admin_account.yml index 58d8779525..57c659a7d2 100644 --- a/detections/detect_new_local_admin_account.yml +++ b/detections/detect_new_local_admin_account.yml @@ -1,6 +1,6 @@ name: Detect New Local Admin account id: b25f6f62-0712-43c1-b203-083231ffd97d -version: '1.0' +version: 1 date: '2019-02-28' description: This search looks for newly created accounts that have been elevated to local administrators. diff --git a/detections/detect_new_login_attempts_to_routers.yml b/detections/detect_new_login_attempts_to_routers.yml index 3f1cc7f6d6..67b12e4a37 100644 --- a/detections/detect_new_login_attempts_to_routers.yml +++ b/detections/detect_new_login_attempts_to_routers.yml @@ -1,6 +1,6 @@ name: Detect New Login Attempts to Routers id: 104658f4-afdc-499e-9719-17243rr826f1 -version: '1.0' +version: 1 date: '2017-09-12' description: The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that diff --git a/detections/detect_new_open_s3_buckets.yml b/detections/detect_new_open_s3_buckets.yml index 839a9bd2ae..dbedcdc575 100644 --- a/detections/detect_new_open_s3_buckets.yml +++ b/detections/detect_new_open_s3_buckets.yml @@ -1,6 +1,6 @@ name: Detect New Open S3 buckets id: 2a9b80d3-6340-4345-b5ad-290bf3d0dac4 -version: '1.0' +version: 1 date: '2018-07-25' description: This search looks for CloudTrail events where a user has created an open/public S3 bucket. diff --git a/detections/detect_new_user_aws_console_login.yml b/detections/detect_new_user_aws_console_login.yml index 3c98c23f58..3b97b0920d 100644 --- a/detections/detect_new_user_aws_console_login.yml +++ b/detections/detect_new_user_aws_console_login.yml @@ -1,6 +1,6 @@ name: Detect new user AWS Console Login id: ada0f478-84a8-4641-a3f3-d82362dffd75 -version: '1.0' +version: 1 date: '2018-04-30' description: This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup diff --git a/detections/detect_oulook_exe_writing_a__zip_file.yml b/detections/detect_oulook_exe_writing_a__zip_file.yml index 0a5920394d..3ceea54ef3 100644 --- a/detections/detect_oulook_exe_writing_a__zip_file.yml +++ b/detections/detect_oulook_exe_writing_a__zip_file.yml @@ -1,6 +1,6 @@ name: Detect Oulook.exe writing a .zip file id: a51bfe1a-94f0-4822-b1e4-16ae10145893 -version: '2.0' +version: 2 date: '2020-03-16' description: This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. diff --git a/detections/detect_outbound_smb_traffic.yml b/detections/detect_outbound_smb_traffic.yml index eca2d96d78..05282b3f07 100644 --- a/detections/detect_outbound_smb_traffic.yml +++ b/detections/detect_outbound_smb_traffic.yml @@ -1,6 +1,6 @@ name: Detect Outbound SMB Traffic id: 7f5fb3e1-4209-414-90db-0ec21b936378 -version: '2.0' +version: 2 date: '2020-01-22' description: This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. @@ -35,8 +35,8 @@ known_false_positives: It is likely that the outbound Server Message Block (SMB) of all SMB versions and related protocols at the network boundary. tags: analytics_story: - - Hidden Cobra Malware - DHS Report TA18-074A + - Hidden Cobra Malware mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/detect_path_interception_by_creation_of_program_exe.yml b/detections/detect_path_interception_by_creation_of_program_exe.yml index 2fda445b41..f9eb93a5a3 100644 --- a/detections/detect_path_interception_by_creation_of_program_exe.yml +++ b/detections/detect_path_interception_by_creation_of_program_exe.yml @@ -1,6 +1,6 @@ name: Detect Path Interception By Creation Of program.exe id: c77162d3-f93c-45cc-80c8-22f6v5264g9f -version: '2.0' +version: 2 date: '2018-11-15' description: 'The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path diff --git a/detections/detect_processes_used_for_system_network_configuration_discovery.yml b/detections/detect_processes_used_for_system_network_configuration_discovery.yml index c0139f808f..26b88a6301 100644 --- a/detections/detect_processes_used_for_system_network_configuration_discovery.yml +++ b/detections/detect_processes_used_for_system_network_configuration_discovery.yml @@ -1,6 +1,6 @@ name: Detect processes used for System Network Configuration Discovery id: a51bfe1a-94f0-48cc-b1e4-16ae10145893 -version: '1.0' +version: 1 date: '2018-11-20' description: This search looks for fast execution of processes used for system network configuration discovery on the endpoint. diff --git a/detections/detect_prohibited_applications_spawning_cmd_exe.yml b/detections/detect_prohibited_applications_spawning_cmd_exe.yml index ba65349c48..137e07b6f6 100644 --- a/detections/detect_prohibited_applications_spawning_cmd_exe.yml +++ b/detections/detect_prohibited_applications_spawning_cmd_exe.yml @@ -1,6 +1,6 @@ name: Detect Prohibited Applications Spawning cmd.exe id: dcfd6b40-42f9-469d-a433-2e53f7486664 -version: '3.0' +version: 3 date: '2020-02-03' description: This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. @@ -22,8 +22,8 @@ known_false_positives: There are circumstances where an application may legitima the lookup file, as appropriate. tags: analytics_story: - - Suspicious MSHTA Activity - Suspicious Command-Line Executions + - Suspicious MSHTA Activity mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detect_psexec_with_accepteula_flag.yml b/detections/detect_psexec_with_accepteula_flag.yml index 03182f21a1..a104bf113e 100644 --- a/detections/detect_psexec_with_accepteula_flag.yml +++ b/detections/detect_psexec_with_accepteula_flag.yml @@ -1,6 +1,6 @@ name: Detect PsExec With accepteula Flag id: b89919ed-fe5f-492c-b139-151xb162040e -version: '2.0' +version: 2 date: '2019-02-26' description: This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you @@ -29,8 +29,8 @@ known_false_positives: Administrators can leverage PsExec for accessing remote s event on a machine tags: analytics_story: - - SamSam Ransomware - DHS Report TA18-074A + - SamSam Ransomware mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detect_rare_executables.yml b/detections/detect_rare_executables.yml index 727a831b34..080ef20c20 100644 --- a/detections/detect_rare_executables.yml +++ b/detections/detect_rare_executables.yml @@ -1,6 +1,6 @@ name: Detect Rare Executables id: 44fddcb2-8d3b-454c-874e-7c6de5a4f7ac -version: '5.0' +version: 5 date: '2020-03-16' description: This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. @@ -28,8 +28,8 @@ known_false_positives: Some legitimate processes may be only rarely executed in to filter them out of your search results. tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - Unusual Processes + - Emotet Malware (DHS Report TA18-201A) kill_chain_phases: - Installation - Command and Control diff --git a/detections/detect_s3_access_from_a_new_ip.yml b/detections/detect_s3_access_from_a_new_ip.yml index c0915c0160..739b4a74c4 100644 --- a/detections/detect_s3_access_from_a_new_ip.yml +++ b/detections/detect_s3_access_from_a_new_ip.yml @@ -1,6 +1,6 @@ name: Detect S3 access from a new IP id: 2a9b80d3-6340-4345-b5ad-291bq3d0daq4 -version: '1.0' +version: 1 date: '2018-06-28' description: This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. diff --git a/detections/detect_spike_in_aws_api_activity.yml b/detections/detect_spike_in_aws_api_activity.yml index 6d0c2fc590..b28ab4cbde 100644 --- a/detections/detect_spike_in_aws_api_activity.yml +++ b/detections/detect_spike_in_aws_api_activity.yml @@ -1,6 +1,6 @@ name: Detect Spike in AWS API Activity id: ada0f478-84a8-4641-a3f1-d32362d4bd55 -version: '1.0' +version: 1 date: '2018-04-09' description: This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml index a7fd705ef8..a312f25483 100644 --- a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -1,6 +1,6 @@ name: Detect Spike in blocked Outbound Traffic from your AWS id: ada0f278-84a8-46w1-a3f1-w32372d4bd53 -version: '1.0' +version: 1 date: '2018-05-07' description: This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file @@ -41,9 +41,9 @@ known_false_positives: The false-positive rate may vary based on the values of`d of blocked outbound connections. tags: analytics_story: - - Command and Control - Suspicious AWS Traffic - AWS Network ACL Activity + - Command and Control kill_chain_phases: - Actions on Objectives - Command and Control diff --git a/detections/detect_spike_in_network_acl_activity.yml b/detections/detect_spike_in_network_acl_activity.yml index 36059a85bc..487798abb8 100644 --- a/detections/detect_spike_in_network_acl_activity.yml +++ b/detections/detect_spike_in_network_acl_activity.yml @@ -1,6 +1,6 @@ name: Detect Spike in Network ACL Activity id: ada0f478-84a8-4641-a1f1-e32372d4bd53 -version: '1.0' +version: 1 date: '2018-05-21' description: This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. diff --git a/detections/detect_spike_in_s3_bucket_deletion.yml b/detections/detect_spike_in_s3_bucket_deletion.yml index bde12a46fc..4d679f1365 100644 --- a/detections/detect_spike_in_s3_bucket_deletion.yml +++ b/detections/detect_spike_in_s3_bucket_deletion.yml @@ -1,6 +1,6 @@ name: Detect Spike in S3 Bucket deletion id: ad12w478-84a8-4641-a3w1-e32372q4bd53 -version: '1.0' +version: 1 date: '2018-11-27' description: This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file diff --git a/detections/detect_spike_in_security_group_activity.yml b/detections/detect_spike_in_security_group_activity.yml index 9216bc5c49..7c4921e15e 100644 --- a/detections/detect_spike_in_security_group_activity.yml +++ b/detections/detect_spike_in_security_group_activity.yml @@ -1,6 +1,6 @@ name: Detect Spike in Security Group Activity id: ada0f478-84a8-4641-a3f1-e32372d4bd53 -version: '1.0' +version: 1 date: '2018-04-18' description: This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file diff --git a/detections/detect_unauthorized_assets_by_mac_address.yml b/detections/detect_unauthorized_assets_by_mac_address.yml index 865d4ee51a..2a014870a1 100644 --- a/detections/detect_unauthorized_assets_by_mac_address.yml +++ b/detections/detect_unauthorized_assets_by_mac_address.yml @@ -1,6 +1,6 @@ name: Detect Unauthorized Assets by MAC address id: dcfd6b40-42f9-469d-a433-2e53f7489ff4 -version: '1.0' +version: 1 date: '2017-09-13' description: By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the diff --git a/detections/detect_usb_device_insertion.yml b/detections/detect_usb_device_insertion.yml index 931147fc76..4b148f2a96 100644 --- a/detections/detect_usb_device_insertion.yml +++ b/detections/detect_usb_device_insertion.yml @@ -1,6 +1,6 @@ name: Detect USB device insertion id: 104658f4-afdc-499f-9719-17a43f9826f5 -version: '1.0' +version: 1 date: '2017-11-27' description: The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID diff --git a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml index f48160d13a..09fb80ca2f 100644 --- a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml @@ -1,6 +1,6 @@ name: Detect Use of cmd.exe to Launch Script Interpreters id: b89919ed-fe5f-492c-b139-95dbb162039e -version: '3.0' +version: 3 date: '2020-03-02' description: This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first @@ -21,8 +21,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: Some legitimate applications may exhibit this behavior. tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - Suspicious Command-Line Executions + - Emotet Malware (DHS Report TA18-201A) mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detect_web_traffic_to_dynamic_domain_providers.yml b/detections/detect_web_traffic_to_dynamic_domain_providers.yml index c06b246800..dbc1b75af5 100644 --- a/detections/detect_web_traffic_to_dynamic_domain_providers.yml +++ b/detections/detect_web_traffic_to_dynamic_domain_providers.yml @@ -1,6 +1,6 @@ name: Detect web traffic to dynamic domain providers id: 134da869-e264-4a8f-8d7e-fcd01c18f301 -version: '1.0' +version: 1 date: '2018-09-06' description: This search looks for web connections to dynamic DNS providers. how_to_implement: 'This search requires you to be ingesting web-traffic logs. You diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml index 99ef09ed65..b23bd81f2f 100644 --- a/detections/detection_of_dns_tunnels.yml +++ b/detections/detection_of_dns_tunnels.yml @@ -1,6 +1,6 @@ name: Detection of DNS Tunnels id: 104658f4-afdc-499f-9719-17a43f9826f4 -version: '1.0' +version: 1 date: '2017-09-18' description: This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential @@ -39,9 +39,9 @@ known_false_positives: It's possible that normal DNS traffic will exhibit this b can also be modified to better suit your environment. tags: analytics_story: - - Suspicious DNS Traffic - Data Protection - Command and Control + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/detection_of_tools_built_by_nirsoft.yml b/detections/detection_of_tools_built_by_nirsoft.yml index c14600d46d..b137167b68 100644 --- a/detections/detection_of_tools_built_by_nirsoft.yml +++ b/detections/detection_of_tools_built_by_nirsoft.yml @@ -1,6 +1,6 @@ name: Detection of tools built by NirSoft id: 1297fb80-f42a-4q4a-9c8b-78c061417cf6 -version: '2.0' +version: 2 date: '2018-12-03' description: This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml index b3bbbbe3e4..d1c2db2277 100644 --- a/detections/disabling_remote_user_account_control.yml +++ b/detections/disabling_remote_user_account_control.yml @@ -1,6 +1,6 @@ name: Disabling Remote User Account Control id: bbc644bc-37df-4e1a-9c88-ec9a53e2038c -version: '3.0' +version: 3 date: '2020-03-02' description: The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). diff --git a/detections/dns_query_length_outliers___mltk.yml b/detections/dns_query_length_outliers___mltk.yml index a3082433b8..a877746d66 100644 --- a/detections/dns_query_length_outliers___mltk.yml +++ b/detections/dns_query_length_outliers___mltk.yml @@ -1,6 +1,6 @@ name: DNS Query Length Outliers - MLTK id: 85fbcfe8-9718-4911-adf6-7000d077a3a9 -version: '2.0' +version: 2 date: '2020-01-22' description: This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. @@ -48,8 +48,8 @@ known_false_positives: If you are seeing more results than desired, you may cons tags: analytics_story: - Hidden Cobra Malware - - Suspicious DNS Traffic - Command and Control + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/dns_query_length_with_high_standard_deviation.yml b/detections/dns_query_length_with_high_standard_deviation.yml index 3c76c72037..28675f08d9 100644 --- a/detections/dns_query_length_with_high_standard_deviation.yml +++ b/detections/dns_query_length_with_high_standard_deviation.yml @@ -1,6 +1,6 @@ name: DNS Query Length With High Standard Deviation id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f5 -version: '1.0' +version: 1 date: '2020-01-22' description: This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the @@ -19,8 +19,8 @@ known_false_positives: It's possible there can be long domain names that are leg tags: analytics_story: - Hidden Cobra Malware - - Suspicious DNS Traffic - Command and Control + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml index 813739def1..eface92f00 100644 --- a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml +++ b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml @@ -1,6 +1,6 @@ name: DNS Query Requests Resolved by Unauthorized DNS Servers id: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f6 -version: '2.0' +version: 2 date: '2020-01-17' description: This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and @@ -18,10 +18,10 @@ known_false_positives: Legitimate DNS activity can be detected in this search. I verify and update the list of authorized DNS servers as appropriate. tags: analytics_story: + - DNS Hijacking + - Command and Control - Host Redirection - Suspicious DNS Traffic - - Command and Control - - DNS Hijacking kill_chain_phases: - Command and Control cis20: diff --git a/detections/dns_record_changed.yml b/detections/dns_record_changed.yml index 0bdc39357c..37c0a05b6d 100644 --- a/detections/dns_record_changed.yml +++ b/detections/dns_record_changed.yml @@ -1,6 +1,6 @@ name: DNS record changed id: 44d3a43e-dcd5-49f7-8356-5209bb369065 -version: '2.0' +version: 2 date: '2020-01-16' description: The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the diff --git a/detections/dump_lsass_via_comsvcs_dll.yml b/detections/dump_lsass_via_comsvcs_dll.yml index 46fde885b2..b325a8df91 100644 --- a/detections/dump_lsass_via_comsvcs_dll.yml +++ b/detections/dump_lsass_via_comsvcs_dll.yml @@ -1,6 +1,6 @@ name: Dump LSASS via comsvcs DLL id: 8943b567-f14d-4ee8-a0bb-2121d4ce3184 -version: '1.0' +version: 1 date: '2020-02-21' description: Detect the usage of comsvcs.dll for dumping the lsass process. how_to_implement: You must be ingesting endpoint data that tracks process activity, diff --git a/detections/ec2_instance_modified_with_previously_unseen_user.yml b/detections/ec2_instance_modified_with_previously_unseen_user.yml index e8537447c4..be4f5c1a80 100644 --- a/detections/ec2_instance_modified_with_previously_unseen_user.yml +++ b/detections/ec2_instance_modified_with_previously_unseen_user.yml @@ -1,6 +1,6 @@ name: EC2 Instance Modified With Previously Unseen User id: 56f91724-cf3f-4666-84e1-e3712fb41e76 -version: '2.0' +version: 2 date: '2018-04-09' description: This search looks for EC2 instances being modified by users who have not previously modified them. diff --git a/detections/ec2_instance_started_in_previously_unseen_region.yml b/detections/ec2_instance_started_in_previously_unseen_region.yml index 6054c44ec9..82b954dbfe 100644 --- a/detections/ec2_instance_started_in_previously_unseen_region.yml +++ b/detections/ec2_instance_started_in_previously_unseen_region.yml @@ -1,6 +1,6 @@ name: EC2 Instance Started In Previously Unseen Region id: ada0f478-84a8-4641-a3f3-d82362d6fd75 -version: '1.0' +version: 1 date: '2018-02-23' description: This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file diff --git a/detections/ec2_instance_started_with_previously_unseen_ami.yml b/detections/ec2_instance_started_with_previously_unseen_ami.yml index e0edccaca3..dbfa4abcb9 100644 --- a/detections/ec2_instance_started_with_previously_unseen_ami.yml +++ b/detections/ec2_instance_started_with_previously_unseen_ami.yml @@ -1,6 +1,6 @@ name: EC2 Instance Started With Previously Unseen AMI id: 347ec301-601b-48b9-81aa-9ddf9c829dd3 -version: '1.0' +version: 1 date: '2018-03-12' description: This search looks for EC2 instances being created with previously unseen AMIs. diff --git a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml index a6bb0438df..de7a45b9b5 100644 --- a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml +++ b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml @@ -1,6 +1,6 @@ name: EC2 Instance Started With Previously Unseen Instance Type id: 65541c80-03c7-4e05-83c8-1dcd57a2e1ad -version: '2.0' +version: 2 date: '2020-02-07' description: This search looks for EC2 instances being created with previously unseen instance types. diff --git a/detections/ec2_instance_started_with_previously_unseen_user.yml b/detections/ec2_instance_started_with_previously_unseen_user.yml index 0ce6335ab7..72cd4108f5 100644 --- a/detections/ec2_instance_started_with_previously_unseen_user.yml +++ b/detections/ec2_instance_started_with_previously_unseen_user.yml @@ -1,6 +1,6 @@ name: EC2 Instance Started With Previously Unseen User id: 22773e84-bac0-4595-b086-20d3f735b4f1 -version: '1.0' +version: 1 date: '2018-03-12' description: This search looks for EC2 instances being created by users who have not created them before. diff --git a/detections/email_attachments_with_lots_of_spaces.yml b/detections/email_attachments_with_lots_of_spaces.yml index 4952803813..b9d87e12bd 100644 --- a/detections/email_attachments_with_lots_of_spaces.yml +++ b/detections/email_attachments_with_lots_of_spaces.yml @@ -1,6 +1,6 @@ name: Email Attachments With Lots Of Spaces id: 56e877a6-1455-4479-ada6-0550dc1e22f8 -version: '2.0' +version: 2 date: '2017-09-19' description: Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many diff --git a/detections/email_files_written_outside_of_the_outlook_directory.yml b/detections/email_files_written_outside_of_the_outlook_directory.yml index 0ac0e64a37..9bdee8d4a8 100644 --- a/detections/email_files_written_outside_of_the_outlook_directory.yml +++ b/detections/email_files_written_outside_of_the_outlook_directory.yml @@ -1,6 +1,6 @@ name: Email files written outside of the Outlook directory id: ee18ed37-0802-4268-9435-b3b91aaa18xx -version: '2.0' +version: 2 date: '2020-03-23' description: The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. diff --git a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml index a3d2e7265e..c00784f397 100644 --- a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml +++ b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml @@ -1,6 +1,6 @@ name: Email servers sending high volume traffic to hosts id: 7f5fb3e1-4209-4914-90db-0ec21b556378 -version: '1.0' +version: 1 date: '2017-12-20' description: This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using diff --git a/detections/excessive_dns_failures.yml b/detections/excessive_dns_failures.yml index 4e44ad8091..6ffb3e3246 100644 --- a/detections/excessive_dns_failures.yml +++ b/detections/excessive_dns_failures.yml @@ -1,6 +1,6 @@ name: Excessive DNS Failures id: 104658f4-afdc-499e-9719-17243f9826f1 -version: '1.0' +version: 1 date: '2017-09-18' description: This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. @@ -21,8 +21,8 @@ known_false_positives: It is possible legitimate traffic can trigger this rule. to better suit your environment. tags: analytics_story: - - Suspicious DNS Traffic - Command and Control + - Suspicious DNS Traffic mitre_attack_id: - T1048 - T1043 diff --git a/detections/execution_of_file_with_multiple_extensions.yml b/detections/execution_of_file_with_multiple_extensions.yml index 7d443538bc..a8332a36d1 100644 --- a/detections/execution_of_file_with_multiple_extensions.yml +++ b/detections/execution_of_file_with_multiple_extensions.yml @@ -1,6 +1,6 @@ name: Execution of File with Multiple Extensions id: b06a555e-dce0-417d-a2eb-28a5d8d66ef7 -version: '1.0' +version: 1 date: '2018-11-02' description: This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension diff --git a/detections/execution_of_file_with_spaces_before_extension.yml b/detections/execution_of_file_with_spaces_before_extension.yml index 709fd5dc42..0153688e85 100644 --- a/detections/execution_of_file_with_spaces_before_extension.yml +++ b/detections/execution_of_file_with_spaces_before_extension.yml @@ -1,6 +1,6 @@ name: Execution of File With Spaces Before Extension id: ab0353e6-a956-420b-b724-a8b4846d5d5a -version: '1.0' +version: 1 date: '2018-01-26' description: This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the diff --git a/detections/extended_period_without_successful_netbackup_backups.yml b/detections/extended_period_without_successful_netbackup_backups.yml index 22cc222818..cd903bb151 100644 --- a/detections/extended_period_without_successful_netbackup_backups.yml +++ b/detections/extended_period_without_successful_netbackup_backups.yml @@ -1,6 +1,6 @@ name: Extended Period Without Successful Netbackup Backups id: a34aae96-ccf8-4aef-952c-3ea214444440 -version: '1.0' +version: 1 date: '2017-09-12' description: This search returns a list of hosts that have not successfully completed a backup in over a week. diff --git a/detections/file_with_samsam_extension.yml b/detections/file_with_samsam_extension.yml index 3c26e311db..a6849be68d 100644 --- a/detections/file_with_samsam_extension.yml +++ b/detections/file_with_samsam_extension.yml @@ -1,6 +1,6 @@ name: File with Samsam Extension id: 02c6cfc2-ae66-4735-bfc7-6291da834cbf -version: '1.0' +version: 1 date: '2018-12-14' description: The search looks for file writes with extensions consistent with a SamSam ransomware attack. diff --git a/detections/first_time_seen_command_line_argument.yml b/detections/first_time_seen_command_line_argument.yml index 9437359955..d0d6384f46 100644 --- a/detections/first_time_seen_command_line_argument.yml +++ b/detections/first_time_seen_command_line_argument.yml @@ -1,6 +1,6 @@ name: First time seen command line argument id: 9be56c82-b1cc-4318-87eb-q138afaaqa39 -version: '4.1' +version: 4 date: '2020-03-02' description: This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. @@ -34,11 +34,11 @@ known_false_positives: Legitimate programs can also use command-line arguments t macro to exclude legitimate parent_process_name tags: analytics_story: - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Suspicious Command-Line Executions - - Orangeworm Attack Group - - Hidden Cobra Malware - DHS Report TA18-074A + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Hidden Cobra Malware + - Orangeworm Attack Group mitre_attack_id: - T1064 - T1059 diff --git a/detections/first_time_seen_running_windows_service.yml b/detections/first_time_seen_running_windows_service.yml index 72209927c0..ff7e30ad70 100644 --- a/detections/first_time_seen_running_windows_service.yml +++ b/detections/first_time_seen_running_windows_service.yml @@ -1,6 +1,6 @@ name: First Time Seen Running Windows Service id: 823136f2-d755-4b6d-ae04-372b486a5808 -version: '2.0' +version: 2 date: '2020-01-13' description: This search looks for the first time a Windows service is seen running in your environment. @@ -27,8 +27,8 @@ known_false_positives: A previously unseen service is not necessarily malicious. that the service is legitimate and that was installed by a legitimate process. tags: analytics_story: - - Windows Service Abuse - Orangeworm Attack Group + - Windows Service Abuse mitre_attack_id: - T1050 kill_chain_phases: diff --git a/detections/gcp_gcr_container_uploaded.yml b/detections/gcp_gcr_container_uploaded.yml index 710c0e2d67..6191290f09 100644 --- a/detections/gcp_gcr_container_uploaded.yml +++ b/detections/gcp_gcr_container_uploaded.yml @@ -1,6 +1,6 @@ name: GCP GCR container uploaded id: 4f00ca88-e766-4605-ac65-ae51c9fd185b -version: '1.0' +version: 1 date: '2020-02-20' description: This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination diff --git a/detections/gcp_kubernetes_cluster_scan_detection.yml b/detections/gcp_kubernetes_cluster_scan_detection.yml index 62c8b2df8a..65393f0bc9 100644 --- a/detections/gcp_kubernetes_cluster_scan_detection.yml +++ b/detections/gcp_kubernetes_cluster_scan_detection.yml @@ -1,6 +1,6 @@ name: GCP Kubernetes cluster scan detection id: db5957ec-0144-4c56-b512-9dccbe7a2d26 -version: '1.0' +version: 1 date: '2020-04-15' description: This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster diff --git a/detections/hiding_files_and_directories_with_attrib_exe.yml b/detections/hiding_files_and_directories_with_attrib_exe.yml index e3d30981d1..50c23b7109 100644 --- a/detections/hiding_files_and_directories_with_attrib_exe.yml +++ b/detections/hiding_files_and_directories_with_attrib_exe.yml @@ -1,6 +1,6 @@ name: Hiding Files And Directories With Attrib.exe id: c77162d3-f93c-45cc-80c8-22f6b5264g9f -version: '3.0' +version: 3 date: '2020-03-16' description: Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The @@ -23,8 +23,8 @@ known_false_positives: 'Some applications and users may legitimately use attrib. to interact with the files. ' tags: analytics_story: - - Windows Persistence Techniques - Windows Defense Evasion Tactics + - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml index 194a8e223c..b230f25a95 100644 --- a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml +++ b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml @@ -1,6 +1,6 @@ name: Hosts receiving high volume of network traffic from email server id: 7f5fb3e1-4209-4914-90db-0ec21b556368 -version: '1.0' +version: 1 date: '2017-12-20' description: This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using diff --git a/detections/identify_new_user_accounts.yml b/detections/identify_new_user_accounts.yml index cb851c0a46..a1a8129766 100644 --- a/detections/identify_new_user_accounts.yml +++ b/detections/identify_new_user_accounts.yml @@ -1,6 +1,6 @@ name: Identify New User Accounts id: 475b9e27-17e4-46e2-b7e2-648221be3b89 -version: '1.0' +version: 1 date: '2017-09-12' description: This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the diff --git a/detections/large_volume_of_dns_any_queries.yml b/detections/large_volume_of_dns_any_queries.yml index 4c1e28bbdb..18086da03b 100644 --- a/detections/large_volume_of_dns_any_queries.yml +++ b/detections/large_volume_of_dns_any_queries.yml @@ -1,6 +1,6 @@ name: Large Volume of DNS ANY Queries id: 8fa891f7-a533-4b3c-af85-5aa2e7c1f1eb -version: '1.0' +version: 1 date: '2017-09-20' description: The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. diff --git a/detections/macos___re_opened_applications.yml b/detections/macos___re_opened_applications.yml index 81839d0088..9a72f5d028 100644 --- a/detections/macos___re_opened_applications.yml +++ b/detections/macos___re_opened_applications.yml @@ -1,6 +1,6 @@ name: MacOS - Re-opened Applications id: 40bb64f9-f619-4e3d-8732-328d40377c4b -version: '1.0' +version: 1 date: '2020-02-07' description: This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. diff --git a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml index a0fd706068..d278b482bf 100644 --- a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml +++ b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml @@ -1,6 +1,6 @@ name: Malicious PowerShell Process - Connect To Internet With Hidden Window id: ee18ed37-0802-4268-9435-b3b91aaa18db -version: '3.0' +version: 3 date: '2018-12-03' description: This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the @@ -26,8 +26,8 @@ known_false_positives: Legitimate process can have this combination of command-l options, but it's not common. tags: analytics_story: - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Malicious PowerShell + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns mitre_attack_id: - T1086 - T1064 diff --git a/detections/malicious_powershell_process___encoded_command.yml b/detections/malicious_powershell_process___encoded_command.yml index 38923dd4ac..30088bf15f 100644 --- a/detections/malicious_powershell_process___encoded_command.yml +++ b/detections/malicious_powershell_process___encoded_command.yml @@ -1,6 +1,6 @@ name: Malicious PowerShell Process - Encoded Command id: c4db14d9-7909-48b4-a054-aa14d89dbb19 -version: '3.0' +version: 3 date: '2018-12-03' description: This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates diff --git a/detections/malicious_powershell_process___execution_policy_bypass.yml b/detections/malicious_powershell_process___execution_policy_bypass.yml index 92a258438e..9ecf87886b 100644 --- a/detections/malicious_powershell_process___execution_policy_bypass.yml +++ b/detections/malicious_powershell_process___execution_policy_bypass.yml @@ -1,6 +1,6 @@ name: Malicious PowerShell Process - Execution Policy Bypass id: 9be56c82-b1cc-4318-87eb-d138afaaca39 -version: '3.0' +version: 3 date: '2018-12-03' description: This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed diff --git a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml index becbf54219..f790d95dbb 100644 --- a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml +++ b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml @@ -1,6 +1,6 @@ name: Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments id: 2cdb91d2-542c-497f-b252-be495e71f38c -version: '3.0' +version: 3 date: '2018-12-03' description: This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the diff --git a/detections/malicious_powershell_process_with_obfuscation_techniques.yml b/detections/malicious_powershell_process_with_obfuscation_techniques.yml index 3bce4a70e9..73e2542ecd 100644 --- a/detections/malicious_powershell_process_with_obfuscation_techniques.yml +++ b/detections/malicious_powershell_process_with_obfuscation_techniques.yml @@ -1,6 +1,6 @@ name: Malicious PowerShell Process With Obfuscation Techniques id: cde75cf6-3c7a-4dd6-af01-27cdb4511fd4 -version: '2.0' +version: 2 date: '2020-01-17' description: This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. diff --git a/detections/monitor_dns_for_brand_abuse.yml b/detections/monitor_dns_for_brand_abuse.yml index 825e1fcfd5..1bf4278b23 100644 --- a/detections/monitor_dns_for_brand_abuse.yml +++ b/detections/monitor_dns_for_brand_abuse.yml @@ -1,6 +1,6 @@ name: Monitor DNS For Brand Abuse id: 24dd17b1-e2fb-4c31-878c-d4f746595bfa -version: '1.0' +version: 1 date: '2017-09-23' description: This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml index 3213a12b6f..e88497e456 100644 --- a/detections/monitor_email_for_brand_abuse.yml +++ b/detections/monitor_email_for_brand_abuse.yml @@ -1,6 +1,6 @@ name: Monitor Email For Brand Abuse id: b2ea1f38-3a3e-4b8a-9cf1-82760d86a6b8 -version: '2.0' +version: 2 date: '2018-01-05' description: This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. diff --git a/detections/monitor_registry_keys_for_print_monitors.yml b/detections/monitor_registry_keys_for_print_monitors.yml index 3cb8cf4713..0bf408a744 100644 --- a/detections/monitor_registry_keys_for_print_monitors.yml +++ b/detections/monitor_registry_keys_for_print_monitors.yml @@ -1,6 +1,6 @@ name: Monitor Registry Keys for Print Monitors id: f5f6af30-7ba7-4295-bfe9-07de87c01bbc -version: '1.0' +version: 1 date: '2018-11-02' description: This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this @@ -25,8 +25,8 @@ known_false_positives: You will encounter noise from legitimate print-monitor re entries. tags: analytics_story: - - Windows Persistence Techniques - Suspicious Windows Registry Activities + - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/monitor_web_traffic_for_brand_abuse.yml b/detections/monitor_web_traffic_for_brand_abuse.yml index c99524e943..98b80017a2 100644 --- a/detections/monitor_web_traffic_for_brand_abuse.yml +++ b/detections/monitor_web_traffic_for_brand_abuse.yml @@ -1,6 +1,6 @@ name: Monitor Web Traffic For Brand Abuse id: 134da869-e264-4a8f-8d7e-fcd0ec88f301 -version: '1.0' +version: 1 date: '2017-09-23' description: This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. diff --git a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml index ae03106743..878f25baa4 100644 --- a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml +++ b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml @@ -1,6 +1,6 @@ name: Multiple Okta Users With Invalid Credentails From The Same IP id: 19cba45f-cad3-4032-8911-0c09e0444552 -version: '1' +version: 1 date: '2020-04-01' description: This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. diff --git a/detections/new_container_uploaded_to_aws_ecr.yml b/detections/new_container_uploaded_to_aws_ecr.yml index 1878723676..a1bb251a57 100644 --- a/detections/new_container_uploaded_to_aws_ecr.yml +++ b/detections/new_container_uploaded_to_aws_ecr.yml @@ -1,6 +1,6 @@ name: New container uploaded to AWS ECR id: f0f70b40-f7ad-489d-9905-23d149da8099 -version: '1.0' +version: 1 date: '2020-02-20' description: This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time diff --git a/detections/no_windows_updates_in_a_time_frame.yml b/detections/no_windows_updates_in_a_time_frame.yml index ed527a2635..419ab2328d 100644 --- a/detections/no_windows_updates_in_a_time_frame.yml +++ b/detections/no_windows_updates_in_a_time_frame.yml @@ -1,6 +1,6 @@ name: No Windows Updates in a time frame id: 1a77c08c-2f56-409c-a2d3-7d64617edd4f -version: '1.0' +version: 1 date: '2017-09-15' description: This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are diff --git a/detections/okta_account_lockout_events.yml b/detections/okta_account_lockout_events.yml index 4aaaa36b48..c62059dbd0 100644 --- a/detections/okta_account_lockout_events.yml +++ b/detections/okta_account_lockout_events.yml @@ -1,6 +1,6 @@ name: Okta Account Lockout Events id: 62b70968-a0a5-4724-8ac4-67871e6f544d -version: '1' +version: 1 date: '2020-04-01' description: Detect Okta user lockout events how_to_implement: This search is specific to Okta and requires Okta logs are being diff --git a/detections/okta_failed_sso_attempts.yml b/detections/okta_failed_sso_attempts.yml index 10b34eba5b..147c69b8a1 100644 --- a/detections/okta_failed_sso_attempts.yml +++ b/detections/okta_failed_sso_attempts.yml @@ -1,6 +1,6 @@ name: Okta Failed SSO Attempts id: 371a6545-2618-4032-ad84-93386b8698c5 -version: '1' +version: 1 date: '2020-04-01' description: Detect failed Okta SSO events how_to_implement: This search is specific to Okta and requires Okta logs are being diff --git a/detections/okta_user_logins_from_multiple_cities.yml b/detections/okta_user_logins_from_multiple_cities.yml index c8f6435c46..7c851a268e 100644 --- a/detections/okta_user_logins_from_multiple_cities.yml +++ b/detections/okta_user_logins_from_multiple_cities.yml @@ -1,6 +1,6 @@ name: Okta User Logins From Multiple Cities id: 7594fa07-9f34-4d01-81cc-d6af6a5db9e8 -version: '1' +version: 1 date: '2020-04-01' description: This search detects logins from the same user from different states in a 24 hour period. diff --git a/detections/open_redirect_in_splunk_web.yml b/detections/open_redirect_in_splunk_web.yml index 599c767148..e96aa87570 100644 --- a/detections/open_redirect_in_splunk_web.yml +++ b/detections/open_redirect_in_splunk_web.yml @@ -1,6 +1,6 @@ name: Open Redirect in Splunk Web id: d199fb99-2312-451a-9daa-e5efa6ed76a7 -version: '1.0' +version: 1 date: '2017-09-19' description: This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. diff --git a/detections/osquery_pack___coldroot_detection.yml b/detections/osquery_pack___coldroot_detection.yml index be9fd0716c..7ec31dfbc1 100644 --- a/detections/osquery_pack___coldroot_detection.yml +++ b/detections/osquery_pack___coldroot_detection.yml @@ -1,6 +1,6 @@ name: Osquery pack - ColdRoot detection id: a6fffe5e-05c3-4c04-badc-887607fbb8dc -version: '1.0' +version: 1 date: '2019-01-29' description: This search looks for ColdRoot events from the osx-attacks osquery pack. how_to_implement: In order to properly run this search, Splunk needs to ingest data diff --git a/detections/overwriting_accessibility_binaries.yml b/detections/overwriting_accessibility_binaries.yml index 2d12793ef6..aa6074a88a 100644 --- a/detections/overwriting_accessibility_binaries.yml +++ b/detections/overwriting_accessibility_binaries.yml @@ -1,6 +1,6 @@ name: Overwriting Accessibility Binaries id: 13c2f6c3-10c5-4deb-9ba1-7c4460ebe4ae -version: '3.0' +version: 3 date: '2020-03-16' description: Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace diff --git a/detections/process_execution_via_wmi.yml b/detections/process_execution_via_wmi.yml index 4c264aaadf..b3d9139b71 100644 --- a/detections/process_execution_via_wmi.yml +++ b/detections/process_execution_via_wmi.yml @@ -1,6 +1,6 @@ name: Process Execution via WMI id: 24869767-8579-485d-9a4f-d9ddfd8f0cac -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for processes launched via WMI. how_to_implement: You must be ingesting endpoint data that tracks process activity, diff --git a/detections/processes_created_by_netsh.yml b/detections/processes_created_by_netsh.yml index be3b8a9857..5c90a372b5 100644 --- a/detections/processes_created_by_netsh.yml +++ b/detections/processes_created_by_netsh.yml @@ -1,6 +1,6 @@ name: Processes created by netsh id: b89919ed-fe5f-492c-b139-95dbb162041e -version: '3.0' +version: 3 date: '2020-03-02' description: This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting diff --git a/detections/processes_launching_netsh.yml b/detections/processes_launching_netsh.yml index b20a3bfa25..80e063f0cf 100644 --- a/detections/processes_launching_netsh.yml +++ b/detections/processes_launching_netsh.yml @@ -1,6 +1,6 @@ name: Processes launching netsh id: b89919ed-fe5f-492c-b139-95dbb162040e -version: '2.0' +version: 2 date: '2018-11-02' description: This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify @@ -22,9 +22,9 @@ known_false_positives: Some VPN applications are known to launch netsh.exe. Outs commands. tags: analytics_story: + - DHS Report TA18-074A - Disabling Security Tools - Netsh Abuse - - DHS Report TA18-074A mitre_attack_id: - T1059 - T1089 diff --git a/detections/processes_tapping_keyboard_events.yml b/detections/processes_tapping_keyboard_events.yml index 96432d68a3..686bbee409 100644 --- a/detections/processes_tapping_keyboard_events.yml +++ b/detections/processes_tapping_keyboard_events.yml @@ -1,6 +1,6 @@ name: Processes Tapping Keyboard Events id: 2a371608-331d-4034-ae2c-21dda8f1d0ec -version: '1.0' +version: 1 date: '2019-01-25' description: This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This diff --git a/detections/prohibited_network_traffic_allowed.yml b/detections/prohibited_network_traffic_allowed.yml index d043f0ff7b..9b1a5edbd9 100644 --- a/detections/prohibited_network_traffic_allowed.yml +++ b/detections/prohibited_network_traffic_allowed.yml @@ -1,6 +1,6 @@ name: Prohibited Network Traffic Allowed id: ce5a0962-849f-4720-a678-753fe6674479 -version: '1.0' +version: 1 date: '2017-09-11' description: This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that @@ -23,9 +23,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: + - Prohibited Traffic Allowed or Protocol Mismatch - Ransomware - Command and Control - - Prohibited Traffic Allowed or Protocol Mismatch mitre_attack_id: - T1043 - T1048 diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index b3e27f4b51..2002c4937e 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -1,6 +1,6 @@ name: Prohibited Software On Endpoint id: a51bfe1a-94f0-48cc-b4e4-b6ae50145893 -version: '2.0' +version: 2 date: '2019-10-11' description: This search looks for applications on the endpoint that you have marked as prohibited. @@ -24,9 +24,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: + - Monitor for Unauthorized Software - Emotet Malware (DHS Report TA18-201A) - SamSam Ransomware - - Monitor for Unauthorized Software kill_chain_phases: - Installation - Command and Control diff --git a/detections/protocol_or_port_mismatch.yml b/detections/protocol_or_port_mismatch.yml index 4d3a774bba..5bf6fd7ad7 100644 --- a/detections/protocol_or_port_mismatch.yml +++ b/detections/protocol_or_port_mismatch.yml @@ -1,6 +1,6 @@ name: Protocol or Port Mismatch id: 54dc1265-2f74-4b6d-b30d-49eb506a31b3 -version: '1.0' +version: 1 date: '2017-09-11' description: This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search @@ -26,8 +26,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Command and Control - Prohibited Traffic Allowed or Protocol Mismatch + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/protocols_passing_authentication_in_cleartext.yml b/detections/protocols_passing_authentication_in_cleartext.yml index 50f6105b31..03ba0c6645 100644 --- a/detections/protocols_passing_authentication_in_cleartext.yml +++ b/detections/protocols_passing_authentication_in_cleartext.yml @@ -1,6 +1,6 @@ name: Protocols passing authentication in cleartext id: 6923cd64-17a0-453c-b945-81ac2d8c6db9 -version: '1.0' +version: 1 date: '2017-09-15' description: This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous diff --git a/detections/reg_exe_manipulating_windows_services_registry_keys.yml b/detections/reg_exe_manipulating_windows_services_registry_keys.yml index 764fd94737..3d05263345 100644 --- a/detections/reg_exe_manipulating_windows_services_registry_keys.yml +++ b/detections/reg_exe_manipulating_windows_services_registry_keys.yml @@ -1,6 +1,6 @@ name: Reg.exe Manipulating Windows Services Registry Keys id: 8470d755-0c13-45b3-bd63-387a373c10cf -version: '2.0' +version: 2 date: '2019-03-01' description: The search looks for reg.exe modifying registry keys that define Windows services and their configurations. @@ -25,8 +25,8 @@ known_false_positives: It is unusual for a service to be created or modified by It is important to validate and investigate, as appropriate. tags: analytics_story: - - Windows Persistence Techniques - Windows Service Abuse + - Windows Persistence Techniques mitre_attack_id: - T1050 - T1031 diff --git a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml index cf922b058f..d0540cdeef 100644 --- a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml +++ b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml @@ -1,6 +1,6 @@ name: Reg.exe used to hide files/directories via registry keys id: c77162d3-f93c-45cc-80c8-22f6b5264x9f -version: '2.0' +version: 2 date: '2019-02-27' description: The search looks for command-line arguments used to hide a file or directory using the reg add command. @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as known_false_positives: None at the moment tags: analytics_story: - - Windows Persistence Techniques - Suspicious Windows Registry Activities - Windows Defense Evasion Tactics + - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/registry_keys_for_creating_shim_databases.yml b/detections/registry_keys_for_creating_shim_databases.yml index 39247b2350..af55867a39 100644 --- a/detections/registry_keys_for_creating_shim_databases.yml +++ b/detections/registry_keys_for_creating_shim_databases.yml @@ -1,6 +1,6 @@ name: Registry Keys for Creating SHIM Databases id: f5f6af30-7aa7-4295-bfe9-07fe87c01bbb -version: '1.0' +version: 1 date: '2017-09-15' description: This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. @@ -21,8 +21,8 @@ known_false_positives: There are many legitimate applications that leverage shim for compatibility purposes for legacy applications tags: analytics_story: - - Windows Persistence Techniques - Suspicious Windows Registry Activities + - Windows Persistence Techniques mitre_attack_id: - T1138 kill_chain_phases: diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml index f45c2e3109..8a738c1098 100644 --- a/detections/registry_keys_used_for_persistence.yml +++ b/detections/registry_keys_used_for_persistence.yml @@ -1,6 +1,6 @@ name: Registry Keys Used For Persistence id: f5f6af30-7aa7-4295-bfe9-07fe87c01a4b -version: '3.0' +version: 3 date: '2017-10-10' description: The search looks for modifications to registry keys that can be used to launch an application or service at system startup. @@ -27,13 +27,13 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Suspicious MSHTA Activity - - Windows Persistence Techniques - Emotet Malware (DHS Report TA18-201A) + - DHS Report TA18-074A + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Ransomware - Suspicious Windows Registry Activities - - DHS Report TA18-074A + - Windows Persistence Techniques + - Suspicious MSHTA Activity mitre_attack_id: - T1103 - T1131 diff --git a/detections/registry_keys_used_for_privilege_escalation.yml b/detections/registry_keys_used_for_privilege_escalation.yml index f7fd7711a4..0768da5c72 100644 --- a/detections/registry_keys_used_for_privilege_escalation.yml +++ b/detections/registry_keys_used_for_privilege_escalation.yml @@ -1,6 +1,6 @@ name: Registry Keys Used For Privilege Escalation id: c9f4b923-f8af-4155-b697-1354f5bcbc5e -version: '2.0' +version: 2 date: '2020-03-02' description: This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are @@ -26,8 +26,8 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Windows Privilege Escalation - Suspicious Windows Registry Activities + - Windows Privilege Escalation mitre_attack_id: - T1015 kill_chain_phases: diff --git a/detections/remote_desktop_network_bruteforce.yml b/detections/remote_desktop_network_bruteforce.yml index 0d65a51af3..5fd6f25f2b 100644 --- a/detections/remote_desktop_network_bruteforce.yml +++ b/detections/remote_desktop_network_bruteforce.yml @@ -1,6 +1,6 @@ name: Remote Desktop Network Bruteforce id: a98727cc-286b-4ff2-b898-41df64695923 -version: '1.0' +version: 1 date: '2018-12-14' description: This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the diff --git a/detections/remote_desktop_network_traffic.yml b/detections/remote_desktop_network_traffic.yml index 6e3c768340..f8293627e6 100644 --- a/detections/remote_desktop_network_traffic.yml +++ b/detections/remote_desktop_network_traffic.yml @@ -1,6 +1,6 @@ name: Remote Desktop Network Traffic id: 272b8407-842d-4b3d-bead-a704584003d3 -version: '2.0' +version: 2 date: '2020-01-10' description: This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it diff --git a/detections/remote_desktop_process_running_on_system.yml b/detections/remote_desktop_process_running_on_system.yml index 32c10efafc..b15a5c0b23 100644 --- a/detections/remote_desktop_process_running_on_system.yml +++ b/detections/remote_desktop_process_running_on_system.yml @@ -1,6 +1,6 @@ name: Remote Desktop Process Running On System id: f5939373-8054-40ad-8c64-cec478a22a4a -version: '4.0' +version: 4 date: '2020-01-13' description: This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out diff --git a/detections/remote_process_instantiation_via_wmi.yml b/detections/remote_process_instantiation_via_wmi.yml index 5db7928183..6d43c391a9 100644 --- a/detections/remote_process_instantiation_via_wmi.yml +++ b/detections/remote_process_instantiation_via_wmi.yml @@ -1,6 +1,6 @@ name: Remote Process Instantiation via WMI id: d25d2c3d-d9d8-40ec-8fdf-e86fe155a3da -version: '3.0' +version: 3 date: '2019-02-27' description: This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml index 6324d4f27f..30f8e23b52 100644 --- a/detections/remote_registry_key_modifications.yml +++ b/detections/remote_registry_key_modifications.yml @@ -1,6 +1,6 @@ name: Remote Registry Key modifications id: c9f4b923-f8af-4155-b697-1354f5dcbc5e -version: '3.0' +version: 3 date: '2020-03-02' description: This search monitors for remote modifications to registry keys. how_to_implement: To successfully implement this search, you must populate the `Endpoint` @@ -20,9 +20,9 @@ known_false_positives: This technique may be legitimately used by administrators modify remote registries, so it's important to filter these events out. tags: analytics_story: - - Windows Persistence Techniques - Suspicious Windows Registry Activities - Windows Defense Evasion Tactics + - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/remote_wmi_command_attempt.yml b/detections/remote_wmi_command_attempt.yml index fca71cb36a..13e593995e 100644 --- a/detections/remote_wmi_command_attempt.yml +++ b/detections/remote_wmi_command_attempt.yml @@ -1,6 +1,6 @@ name: Remote WMI Command Attempt id: 272df6de-61f1-4784-877c-1fbc3e2d0838 -version: '2.0' +version: 2 date: '2018-12-03' description: This search looks for wmic.exe being launched with parameters to operate on remote systems. diff --git a/detections/rundll_loading_dll_by_ordinal.yml b/detections/rundll_loading_dll_by_ordinal.yml index e6c189182f..0efb2e9a0f 100644 --- a/detections/rundll_loading_dll_by_ordinal.yml +++ b/detections/rundll_loading_dll_by_ordinal.yml @@ -1,6 +1,6 @@ name: RunDLL Loading DLL By Ordinal id: 6c135f8d-5e60-454e-80b7-c56eed739833 -version: '2.0' +version: 2 date: '2019-02-27' description: This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions diff --git a/detections/samsam_test_file_write.yml b/detections/samsam_test_file_write.yml index 2a817341bd..c3cf7d9bd4 100644 --- a/detections/samsam_test_file_write.yml +++ b/detections/samsam_test_file_write.yml @@ -1,6 +1,6 @@ name: Samsam Test File Write id: 69c12d59-d951-431e-ab77-ec426b8d65e6 -version: '1.0' +version: 1 date: '2018-12-14' description: The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. diff --git a/detections/sc_exe_manipulating_windows_services.yml b/detections/sc_exe_manipulating_windows_services.yml index 8cf1ff4f41..cd2e7fd2b2 100644 --- a/detections/sc_exe_manipulating_windows_services.yml +++ b/detections/sc_exe_manipulating_windows_services.yml @@ -1,6 +1,6 @@ name: Sc.exe Manipulating Windows Services id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d -version: '2.0' +version: 2 date: '2019-02-27' description: This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. @@ -23,11 +23,11 @@ known_false_positives: Using sc.exe to manipulate Windows services is uncommon. and investigate as appropriate. tags: analytics_story: - - Disabling Security Tools - - Windows Persistence Techniques - - Windows Service Abuse - - Orangeworm Attack Group - DHS Report TA18-074A + - Windows Service Abuse + - Windows Persistence Techniques + - Orangeworm Attack Group + - Disabling Security Tools mitre_attack_id: - T1050 - T1031 diff --git a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml index 16334aef8d..f8d80214f3 100644 --- a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml +++ b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml @@ -1,6 +1,6 @@ name: Scheduled Task Name Used by Dragonfly Threat Actors id: d5af132c-7c17-439c-9d31-13d55340f36c -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created diff --git a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml index 4ab29390e3..2393833e77 100644 --- a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml +++ b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml @@ -1,6 +1,6 @@ name: Scheduled tasks used in BadRabbit ransomware id: 1297fb80-f42a-4b4a-9c8b-78c066437cf6 -version: '2.0' +version: 2 date: '2019-02-28' description: This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware diff --git a/detections/schtasks_scheduling_job_on_remote_system.yml b/detections/schtasks_scheduling_job_on_remote_system.yml index e6f986d726..4f770dab9b 100644 --- a/detections/schtasks_scheduling_job_on_remote_system.yml +++ b/detections/schtasks_scheduling_job_on_remote_system.yml @@ -1,6 +1,6 @@ name: Schtasks scheduling job on remote system id: 1297fb80-f42a-4b4a-9c8a-88c066237cf6 -version: '3.0' +version: 3 date: '2020-01-10' description: This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. diff --git a/detections/schtasks_used_for_forcing_a_reboot.yml b/detections/schtasks_used_for_forcing_a_reboot.yml index 2be59ce165..a090db2feb 100644 --- a/detections/schtasks_used_for_forcing_a_reboot.yml +++ b/detections/schtasks_used_for_forcing_a_reboot.yml @@ -1,6 +1,6 @@ name: Schtasks used for forcing a reboot id: 1297fb80-f42a-4b4a-9c8a-88c066437cf6 -version: '2.0' +version: 2 date: '2019-02-27' description: This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. diff --git a/detections/script_execution_via_wmi.yml b/detections/script_execution_via_wmi.yml index 17a0a4d172..347ad207d1 100644 --- a/detections/script_execution_via_wmi.yml +++ b/detections/script_execution_via_wmi.yml @@ -1,6 +1,6 @@ name: Script Execution via WMI id: aa73f80d-d728-4077-b226-81ea0c8be589 -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for scripts launched via WMI. how_to_implement: You must be ingesting endpoint data that tracks process activity, diff --git a/detections/shim_database_file_creation.yml b/detections/shim_database_file_creation.yml index 7375bf9713..4e0e5e8f70 100644 --- a/detections/shim_database_file_creation.yml +++ b/detections/shim_database_file_creation.yml @@ -1,6 +1,6 @@ name: Shim Database File Creation id: 6e4c4588-ba2f-42fa-97e6-9f6f548eaa33 -version: '2.0' +version: 2 date: '2018-11-02' description: This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According diff --git a/detections/shim_database_installation_with_suspicious_parameters.yml b/detections/shim_database_installation_with_suspicious_parameters.yml index 0384566636..2d28e9bd67 100644 --- a/detections/shim_database_installation_with_suspicious_parameters.yml +++ b/detections/shim_database_installation_with_suspicious_parameters.yml @@ -1,6 +1,6 @@ name: Shim Database Installation With Suspicious Parameters id: 404620de-46d8-48b6-90cc-8a8d7b0876a3 -version: '2.0' +version: 2 date: '2019-03-01' description: This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database diff --git a/detections/short_lived_windows_accounts.yml b/detections/short_lived_windows_accounts.yml index b450ad1338..563c959bc8 100644 --- a/detections/short_lived_windows_accounts.yml +++ b/detections/short_lived_windows_accounts.yml @@ -1,6 +1,6 @@ name: Short Lived Windows Accounts id: b25f6f62-0782-43c1-b403-083231ffd97d -version: '1.0' +version: 1 date: '2018-01-05' description: This search detects accounts that were created and deleted in a short time period. diff --git a/detections/single_letter_process_on_endpoint.yml b/detections/single_letter_process_on_endpoint.yml index 9848d4ae3e..bb28c4a3b6 100644 --- a/detections/single_letter_process_on_endpoint.yml +++ b/detections/single_letter_process_on_endpoint.yml @@ -1,6 +1,6 @@ name: Single Letter Process On Endpoint id: a4214f0b-e01c-41bc-8cc4-d2b71e3056b4 -version: '2.0' +version: 2 date: '2019-04-01' description: This search looks for process names that consist only of a single letter. how_to_implement: You must be ingesting data that records process activity from your diff --git a/detections/smb_traffic_spike.yml b/detections/smb_traffic_spike.yml index 49d36a9f3d..651efee702 100644 --- a/detections/smb_traffic_spike.yml +++ b/detections/smb_traffic_spike.yml @@ -1,6 +1,6 @@ name: SMB Traffic Spike id: 7f5fb3e1-4209-4914-90db-0ec21b936378 -version: '2.0' +version: 2 date: '2020-01-22' description: This search looks for spikes in the number of Server Message Block (SMB) traffic connections. @@ -21,10 +21,10 @@ known_false_positives: A file server may experience high-demand loads that could this analytic to trigger. tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - - Ransomware - DHS Report TA18-074A - Hidden Cobra Malware + - Emotet Malware (DHS Report TA18-201A) + - Ransomware mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/smb_traffic_spike___mltk.yml b/detections/smb_traffic_spike___mltk.yml index b88a4b6650..f8e6216f61 100644 --- a/detections/smb_traffic_spike___mltk.yml +++ b/detections/smb_traffic_spike___mltk.yml @@ -1,6 +1,6 @@ name: SMB Traffic Spike - MLTK id: d25773ba-9ad8-48d1-858e-07ad0bbeb828 -version: '2.0' +version: 2 date: '2020-01-22' description: This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. @@ -42,10 +42,10 @@ known_false_positives: If you are seeing more results than desired, you may cons the `smb_traffic_spike_mltk_filter` macro to filter out false positive results tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - - Ransomware - DHS Report TA18-074A - Hidden Cobra Malware + - Emotet Malware (DHS Report TA18-201A) + - Ransomware mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/spectre_and_meltdown_vulnerable_systems.yml b/detections/spectre_and_meltdown_vulnerable_systems.yml index eef397f8c9..248f55d80d 100644 --- a/detections/spectre_and_meltdown_vulnerable_systems.yml +++ b/detections/spectre_and_meltdown_vulnerable_systems.yml @@ -1,6 +1,6 @@ name: Spectre and Meltdown Vulnerable Systems id: 354be8e0-32cd-4da0-8c47-796de13b60ea -version: '1.0' +version: 1 date: '2017-01-07' description: The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. diff --git a/detections/spike_in_file_writes.yml b/detections/spike_in_file_writes.yml index c05d115b27..ace85df4db 100644 --- a/detections/spike_in_file_writes.yml +++ b/detections/spike_in_file_writes.yml @@ -1,6 +1,6 @@ name: Spike in File Writes id: fdb0f805-74e4-4539-8c00-618927333aae -version: '3.0' +version: 3 date: '2020-03-16' description: The search looks for a sharp increase in the number of files written to a particular host @@ -24,8 +24,8 @@ known_false_positives: It is important to understand that if you happen to insta expect to see a large increase of file modifications. tags: analytics_story: - - SamSam Ransomware - Ransomware + - SamSam Ransomware kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/splunk_enterprise_information_disclosure.yml b/detections/splunk_enterprise_information_disclosure.yml index 20ec94b66d..9f109cee53 100644 --- a/detections/splunk_enterprise_information_disclosure.yml +++ b/detections/splunk_enterprise_information_disclosure.yml @@ -1,6 +1,6 @@ name: Splunk Enterprise Information Disclosure id: f6a26b7b-7e80-4963-a9a8-d836e7534ebd -version: '1.0' +version: 1 date: '2018-06-14' description: This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. diff --git a/detections/sql_injection_with_long_urls.yml b/detections/sql_injection_with_long_urls.yml index 8c8a2a72f0..f1569f0097 100644 --- a/detections/sql_injection_with_long_urls.yml +++ b/detections/sql_injection_with_long_urls.yml @@ -1,6 +1,6 @@ name: SQL Injection with Long URLs id: e0aad4cf-0790-423b-8328-7564d0d938f9 -version: '1.0' +version: 1 date: '2017-09-19' description: This search looks for long URLs that have several SQL commands visible within them. diff --git a/detections/suspicious_changes_to_file_associations.yml b/detections/suspicious_changes_to_file_associations.yml index 92ecf1328b..bf0095340e 100644 --- a/detections/suspicious_changes_to_file_associations.yml +++ b/detections/suspicious_changes_to_file_associations.yml @@ -1,6 +1,6 @@ name: Suspicious Changes to File Associations id: 1b989a0e-0129-4446-a695-f193a5b746fc -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine @@ -26,8 +26,8 @@ known_false_positives: There may be other processes in your environment that use finding false positives, you can modify the search to add those processes as exceptions. tags: analytics_story: - - Windows File Extension and Association Abuse - Suspicious Windows Registry Activities + - Windows File Extension and Association Abuse mitre_attack_id: - T1042 kill_chain_phases: diff --git a/detections/suspicious_email___uba_anomaly.yml b/detections/suspicious_email___uba_anomaly.yml index b5ceff52f0..72cd6c1634 100644 --- a/detections/suspicious_email___uba_anomaly.yml +++ b/detections/suspicious_email___uba_anomaly.yml @@ -1,6 +1,6 @@ name: Suspicious Email - UBA Anomaly id: 56e877a6-1455-4479-ad16-0550dc1e33f8 -version: '2.0' +version: 2 date: '2019-07-21' description: This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by diff --git a/detections/suspicious_email_attachment_extensions.yml b/detections/suspicious_email_attachment_extensions.yml index 33213762cf..d7cb847959 100644 --- a/detections/suspicious_email_attachment_extensions.yml +++ b/detections/suspicious_email_attachment_extensions.yml @@ -1,6 +1,6 @@ name: Suspicious Email Attachment Extensions id: 473bd65f-06ca-4dfe-a2b8-ba04ab4a0084 -version: '2.0' +version: 2 date: '2020-01-27' description: This search looks for emails that have attachments with suspicious file extensions. diff --git a/detections/suspicious_file_write.yml b/detections/suspicious_file_write.yml index 23f6d303d0..8944c272a2 100644 --- a/detections/suspicious_file_write.yml +++ b/detections/suspicious_file_write.yml @@ -1,6 +1,6 @@ name: Suspicious File Write id: 57f76b8a-32f0-42ed-b358-d9fa3ca7bac8 -version: '3.0' +version: 3 date: '2019-04-25' description: The search looks for files created with names that have been linked to malicious activity. diff --git a/detections/suspicious_java_classes.yml b/detections/suspicious_java_classes.yml index 5c62d8bb70..80aa3b4715 100644 --- a/detections/suspicious_java_classes.yml +++ b/detections/suspicious_java_classes.yml @@ -1,6 +1,6 @@ name: Suspicious Java Classes id: if1fea6da-3c86-4c1d-b255-fc3b2781a491 -version: '1.0' +version: 1 date: '2018-12-06' description: This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. diff --git a/detections/suspicious_lnk_file_launching_a_process.yml b/detections/suspicious_lnk_file_launching_a_process.yml index 413f44bee9..c6a523cca9 100644 --- a/detections/suspicious_lnk_file_launching_a_process.yml +++ b/detections/suspicious_lnk_file_launching_a_process.yml @@ -1,6 +1,6 @@ name: Suspicious LNK file launching a process id: 5d814af1-1041-47b5-a9ac-d754e82e9a26 -version: '2.0' +version: 2 date: '2020-03-16' description: This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. diff --git a/detections/suspicious_reg_exe_process.yml b/detections/suspicious_reg_exe_process.yml index 3c745fd333..1d3b977833 100644 --- a/detections/suspicious_reg_exe_process.yml +++ b/detections/suspicious_reg_exe_process.yml @@ -1,6 +1,6 @@ name: Suspicious Reg.exe Process id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually @@ -29,9 +29,9 @@ known_false_positives: It's possible for system administrators to write scripts to filter them out. tags: analytics_story: - - Disabling Security Tools - DHS Report TA18-074A - Windows Defense Evasion Tactics + - Disabling Security Tools mitre_attack_id: - T1112 - T1089 diff --git a/detections/suspicious_wevtutil_usage.yml b/detections/suspicious_wevtutil_usage.yml index a574dbacc6..adbe4355d5 100644 --- a/detections/suspicious_wevtutil_usage.yml +++ b/detections/suspicious_wevtutil_usage.yml @@ -1,6 +1,6 @@ name: Suspicious wevtutil Usage id: 2827c0fd-e1be-4868-ae25-59d28e0f9d4f -version: '2.0' +version: 2 date: '2019-02-28' description: The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, @@ -23,8 +23,8 @@ known_false_positives: The wevtutil.exe application is a legitimate Windows even log utility. Administrators may use it to manage Windows event logs. tags: analytics_story: - - Ransomware - Windows Log Manipulation + - Ransomware mitre_attack_id: - T1070 kill_chain_phases: diff --git a/detections/suspicious_writes_to_system_volume_information.yml b/detections/suspicious_writes_to_system_volume_information.yml index de3d750cb0..8b1d079194 100644 --- a/detections/suspicious_writes_to_system_volume_information.yml +++ b/detections/suspicious_writes_to_system_volume_information.yml @@ -1,6 +1,6 @@ name: Suspicious writes to System Volume Information id: cd6297cd-2bdd-4aa1-84aa-5d2f84228fac -version: '1.0' +version: 1 date: '2018-01-08' description: This search detects writes to the 'System Volume Information' folder by something other than the System process. diff --git a/detections/suspicious_writes_to_windows_recycle_bin.yml b/detections/suspicious_writes_to_windows_recycle_bin.yml index 901200f1cc..60c79ec695 100644 --- a/detections/suspicious_writes_to_windows_recycle_bin.yml +++ b/detections/suspicious_writes_to_windows_recycle_bin.yml @@ -1,6 +1,6 @@ name: Suspicious writes to windows Recycle Bin id: b5541828-8ffd-4070-9d95-b3da4de924cb -version: '3.0' +version: 3 date: '2020-02-03' description: This search detects writes to the recycle bin by a process other than explorer.exe. diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index afe453b685..8dd2c04abd 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -1,6 +1,6 @@ name: System Processes Run From Unexpected Locations id: a34aae96-ccf8-4aef-952c-3ea21444444d -version: '5.0' +version: 5 date: '2020-02-04' description: This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a @@ -20,9 +20,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Ransomware - - Unusual Processes - Suspicious Command-Line Executions + - Unusual Processes + - Ransomware mitre_attack_id: - T1036 kill_chain_phases: diff --git a/detections/tor_traffic.yml b/detections/tor_traffic.yml index 724473cce9..563e0deec7 100644 --- a/detections/tor_traffic.yml +++ b/detections/tor_traffic.yml @@ -1,6 +1,6 @@ name: TOR Traffic id: ea688274-9c06-4473-b951-e4cb7a5d7a45 -version: '1.0' +version: 1 date: '2017-09-11' description: This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious @@ -20,9 +20,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None at this time tags: analytics_story: + - Prohibited Traffic Allowed or Protocol Mismatch - Ransomware - Command and Control - - Prohibited Traffic Allowed or Protocol Mismatch mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/uncommon_processes_on_endpoint.yml b/detections/uncommon_processes_on_endpoint.yml index 14725aa441..6c56717012 100644 --- a/detections/uncommon_processes_on_endpoint.yml +++ b/detections/uncommon_processes_on_endpoint.yml @@ -1,6 +1,6 @@ name: Uncommon Processes On Endpoint id: 29ccce64-a10c-4389-a45f-337cb29ba1f7 -version: '3.0' +version: 3 date: '2020-03-16' description: This search looks for applications on the endpoint that you have marked as uncommon. diff --git a/detections/unload_sysmon_filter_driver.yml b/detections/unload_sysmon_filter_driver.yml index 947efd3943..be4283c047 100644 --- a/detections/unload_sysmon_filter_driver.yml +++ b/detections/unload_sysmon_filter_driver.yml @@ -1,6 +1,6 @@ name: Unload Sysmon Filter Driver id: c77162d3-f93c-45cc-80c8-22f665664g9f -version: '2.0' +version: 2 date: '2020-01-13' description: Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop diff --git a/detections/unsigned_image_loaded_by_LSASS.yml b/detections/unsigned_image_loaded_by_LSASS.yml index 282f189dc9..a016c7667b 100644 --- a/detections/unsigned_image_loaded_by_LSASS.yml +++ b/detections/unsigned_image_loaded_by_LSASS.yml @@ -1,6 +1,6 @@ name: Unsigned Image Loaded by LSASS id: 56ef054c-76ef-45f9-af4a-a634695dcd65 -version: '1' +version: 1 date: '2019-12-06' description: This search detects loading of unsigned images by LSASS. how_to_implement: This search needs Sysmon Logs with a sysmon configuration, which diff --git a/detections/unsuccessful_netbackup_backups.yml b/detections/unsuccessful_netbackup_backups.yml index a4bb87d0aa..3f69a62870 100644 --- a/detections/unsuccessful_netbackup_backups.yml +++ b/detections/unsuccessful_netbackup_backups.yml @@ -1,6 +1,6 @@ name: Unsuccessful Netbackup backups id: a34aae96-ccf8-4aaa-952c-3ea21444444f -version: '1.0' +version: 1 date: '2017-09-12' description: This search gives you the hosts where a backup was attempted and then failed. diff --git a/detections/unusually_long_command_line.yml b/detections/unusually_long_command_line.yml index a080766ae9..ca69595779 100644 --- a/detections/unusually_long_command_line.yml +++ b/detections/unusually_long_command_line.yml @@ -1,6 +1,6 @@ name: Unusually Long Command Line id: c77162d3-f93c-45cc-80c8-22f6a4264e7f -version: '4.0' +version: 4 date: '2020-03-16' description: Command lines that are extremely long may be indicative of malicious activity on your hosts. @@ -22,10 +22,10 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Some legitimate applications start with long command lines. tags: analytics_story: + - Suspicious Command-Line Executions + - Unusual Processes - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Ransomware - - Unusual Processes - - Suspicious Command-Line Executions kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml index 7c3788f126..e39ba8c8fa 100644 --- a/detections/unusually_long_command_line___mltk.yml +++ b/detections/unusually_long_command_line___mltk.yml @@ -1,6 +1,6 @@ name: Unusually Long Command Line - MLTK id: 57edaefa-a73b-45e5-bbae-f39c1473f941 -version: '1.0' +version: 1 date: '2019-05-08' description: Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) @@ -35,10 +35,10 @@ known_false_positives: Some legitimate applications use long command lines for i build the associated model. tags: analytics_story: + - Suspicious Command-Line Executions + - Unusual Processes - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Ransomware - - Unusual Processes - - Suspicious Command-Line Executions kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/unusually_long_content_type_length.yml b/detections/unusually_long_content_type_length.yml index 277fb1ce1a..6fea27b238 100644 --- a/detections/unusually_long_content_type_length.yml +++ b/detections/unusually_long_content_type_length.yml @@ -1,6 +1,6 @@ name: Unusually Long Content-Type Length id: 57a0a2bf-353f-40c1-84dc-29293f3c35b7 -version: '1.0' +version: 1 date: '2017-10-13' description: This search looks for unusually long strings in the Content-Type http header that the client sends the server. diff --git a/detections/usn_journal_deletion.yml b/detections/usn_journal_deletion.yml index dcb45a6c81..bfd108430c 100644 --- a/detections/usn_journal_deletion.yml +++ b/detections/usn_journal_deletion.yml @@ -1,6 +1,6 @@ name: USN Journal Deletion id: b6e0ff70-b122-4227-9368-4cf322ab43c3 -version: '2.0' +version: 2 date: '2018-12-03' description: The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update @@ -23,8 +23,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: None identified tags: analytics_story: - - Ransomware - Windows Log Manipulation + - Ransomware mitre_attack_id: - T1070 kill_chain_phases: diff --git a/detections/web_fraud___account_harvesting.yml b/detections/web_fraud___account_harvesting.yml index f8b3e7c7a3..4d16df532e 100644 --- a/detections/web_fraud___account_harvesting.yml +++ b/detections/web_fraud___account_harvesting.yml @@ -1,6 +1,6 @@ name: Web Fraud - Account Harvesting id: 31337aaa-941d-4ada-81ac-q2a17be5bf0d -version: '1.0' +version: 1 date: '2018-10-08' description: This search is used to identify the creation of multiple user accounts using the same email domain name. diff --git a/detections/web_fraud___anomalous_user_clickspeed.yml b/detections/web_fraud___anomalous_user_clickspeed.yml index 2273a0e28b..56df1c0b6f 100644 --- a/detections/web_fraud___anomalous_user_clickspeed.yml +++ b/detections/web_fraud___anomalous_user_clickspeed.yml @@ -1,6 +1,6 @@ name: Web Fraud - Anomalous User Clickspeed id: 31337bbb-bc22-4752-b599-ef192df2dc7a -version: '1.0' +version: 1 date: '2018-10-08' description: This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect diff --git a/detections/web_fraud___password_sharing_across_accounts.yml b/detections/web_fraud___password_sharing_across_accounts.yml index 85139358ff..8166186b34 100644 --- a/detections/web_fraud___password_sharing_across_accounts.yml +++ b/detections/web_fraud___password_sharing_across_accounts.yml @@ -1,6 +1,6 @@ name: Web Fraud - Password Sharing Across Accounts id: 31337a1a-53b9-4e05-96e9-55c934cb71d3 -version: '1.0' +version: 1 date: '2018-10-08' description: This search is used to identify user accounts that share a common password. how_to_implement: We need to start with a dataset that allows us to see the values diff --git a/detections/web_servers_executing_suspicious_processes.yml b/detections/web_servers_executing_suspicious_processes.yml index a0c4be6264..033e37712b 100644 --- a/detections/web_servers_executing_suspicious_processes.yml +++ b/detections/web_servers_executing_suspicious_processes.yml @@ -1,6 +1,6 @@ name: Web Servers Executing Suspicious Processes id: ec3b7601-689a-4463-94e0-c9f45638efb9 -version: '1.0' +version: 1 date: '2019-04-01' description: This search looks for suspicious processes on all systems labeled as web servers. diff --git a/detections/windows_event_log_cleared.yml b/detections/windows_event_log_cleared.yml index f3b3769543..77b17d889f 100644 --- a/detections/windows_event_log_cleared.yml +++ b/detections/windows_event_log_cleared.yml @@ -1,6 +1,6 @@ name: Windows Event Log Cleared id: ad517544-aff9-4c96-bd99-d6eb43bfbb6a -version: '3.0' +version: 3 date: '2019-02-27' description: This search looks for Windows events that indicate one of the Windows event logs has been purged. @@ -17,8 +17,8 @@ known_false_positives: It is possible that these logs may be legitimately cleare by Administrators. tags: analytics_story: - - Ransomware - Windows Log Manipulation + - Ransomware mitre_attack_id: - T1070 kill_chain_phases: diff --git a/detections/windows_hosts_file_modification.yml b/detections/windows_hosts_file_modification.yml index 25f9da5816..fc1e86c0af 100644 --- a/detections/windows_hosts_file_modification.yml +++ b/detections/windows_hosts_file_modification.yml @@ -1,6 +1,6 @@ name: Windows hosts file modification id: 06a6fc63-a72d-41dc-8736-7e3dd9612116 -version: '1.0' +version: 1 date: '2018-11-02' description: The search looks for modifications to the hosts file on all Windows endpoints across your environment. diff --git a/detections/wmi_permanent_event_subscription.yml b/detections/wmi_permanent_event_subscription.yml index fb1e8904a9..f2483110b6 100644 --- a/detections/wmi_permanent_event_subscription.yml +++ b/detections/wmi_permanent_event_subscription.yml @@ -1,6 +1,6 @@ name: WMI Permanent Event Subscription id: 71bfdb13-f200-4c6c-b2c9-a2e07adf437d -version: '1.0' +version: 1 date: '2018-10-23' description: This search looks for the creation of WMI permanent event subscriptions. how_to_implement: To successfully implement this search, you must be ingesting the diff --git a/detections/wmi_permanent_event_subscription___sysmon.yml b/detections/wmi_permanent_event_subscription___sysmon.yml index 0ae4c2027b..d5b710e9d8 100644 --- a/detections/wmi_permanent_event_subscription___sysmon.yml +++ b/detections/wmi_permanent_event_subscription___sysmon.yml @@ -1,6 +1,6 @@ name: WMI Permanent Event Subscription - Sysmon id: ad05aae6-3b2a-4f73-af97-57bd26cee3b9 -version: '1.0' +version: 1 date: '2018-10-23' description: This search looks for the creation of WMI permanent event subscriptions. how_to_implement: To successfully implement this search, you must be collecting Sysmon diff --git a/detections/wmi_temporary_event_subscription.yml b/detections/wmi_temporary_event_subscription.yml index 75849c9be5..b86da7f152 100644 --- a/detections/wmi_temporary_event_subscription.yml +++ b/detections/wmi_temporary_event_subscription.yml @@ -1,6 +1,6 @@ name: WMI Temporary Event Subscription id: 38cbd42c-1098-41bb-99cf-9d6d2b296d83 -version: '1.0' +version: 1 date: '2018-10-23' description: This search looks for the creation of WMI temporary event subscriptions. how_to_implement: To successfully implement this search, you must be ingesting the diff --git a/response_tasks/all_backup_logs_for_host.yml b/response_tasks/all_backup_logs_for_host.yml index baa68a138a..0437fd5701 100644 --- a/response_tasks/all_backup_logs_for_host.yml +++ b/response_tasks/all_backup_logs_for_host.yml @@ -1,6 +1,6 @@ name: All backup logs for host id: bc91a8cf-aaaa-4bb2-8140-e756cc06fd72 -version: '1.0' +version: 1 date: '2017-09-12' description: Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. diff --git a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml index 0a2ca269b2..01e6d9dece 100644 --- a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml +++ b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml @@ -1,6 +1,6 @@ name: Amazon EKS Kubernetes activity by src_ip id: a636cca4-7434-4a15-a278-c70734938e39 -version: '1.0' +version: 1 date: '2020-04-13' description: This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster diff --git a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml index def4a36fda..f634fc6df6 100644 --- a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml +++ b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml @@ -1,6 +1,6 @@ name: AWS Investigate User Activities By AccessKeyId id: 703b65a4-a0ae-4171-965d-45507506c64f -version: '1.0' +version: 1 date: '2018-06-08' description: This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. diff --git a/response_tasks/aws_investigate_user_activities_by_arn.yml b/response_tasks/aws_investigate_user_activities_by_arn.yml index c438136f91..caa7a74ae2 100644 --- a/response_tasks/aws_investigate_user_activities_by_arn.yml +++ b/response_tasks/aws_investigate_user_activities_by_arn.yml @@ -1,6 +1,6 @@ name: AWS Investigate User Activities By ARN id: bc91a8cd-35e7-4bb2-6140-e756cc46fd71 -version: '2.0' +version: 2 date: '2019-04-30' description: This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of diff --git a/response_tasks/aws_investigate_user_activities_by_source_user.yml b/response_tasks/aws_investigate_user_activities_by_source_user.yml index 5bee3726e3..b138d68f30 100644 --- a/response_tasks/aws_investigate_user_activities_by_source_user.yml +++ b/response_tasks/aws_investigate_user_activities_by_source_user.yml @@ -1,6 +1,6 @@ name: AWS Investigate User Activities By Source User id: b0d2e6a8-75fa-4b1b-9486-3d32acadf891 -version: '1.0' +version: 1 date: '2018-06-08' description: This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. diff --git a/response_tasks/aws_network_acl_details_from_id.yml b/response_tasks/aws_network_acl_details_from_id.yml index a1b99183f6..22a52853d6 100644 --- a/response_tasks/aws_network_acl_details_from_id.yml +++ b/response_tasks/aws_network_acl_details_from_id.yml @@ -1,6 +1,6 @@ name: AWS Network ACL Details from ID id: f3fb4d1b-5f33-4b01-b541-c7ah9534c242 -version: '1.0' +version: 1 date: '2017-01-22' description: This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID diff --git a/response_tasks/aws_network_interface_details_via_resourceid.yml b/response_tasks/aws_network_interface_details_via_resourceid.yml index 777e3169f4..aec37847a5 100644 --- a/response_tasks/aws_network_interface_details_via_resourceid.yml +++ b/response_tasks/aws_network_interface_details_via_resourceid.yml @@ -1,6 +1,6 @@ name: AWS Network Interface details via resourceId id: f3fb4d1c-5f33-4b01-b541-c3ah9534c241 -version: '1.0' +version: 1 date: '2018-05-07' description: This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will diff --git a/response_tasks/aws_s3_bucket_details_via_bucketname.yml b/response_tasks/aws_s3_bucket_details_via_bucketname.yml index 2f9e4b4243..be0bf69abf 100644 --- a/response_tasks/aws_s3_bucket_details_via_bucketname.yml +++ b/response_tasks/aws_s3_bucket_details_via_bucketname.yml @@ -1,6 +1,6 @@ name: AWS S3 Bucket details via bucketName id: f3fb2q1c-5f33-4b01-b541-c2ah9534c242 -version: '1.0' +version: 1 date: '2018-06-26' description: This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket diff --git a/response_tasks/dns_hijack_enrichment.yml b/response_tasks/dns_hijack_enrichment.yml index a7ad943a26..98419a7c15 100644 --- a/response_tasks/dns_hijack_enrichment.yml +++ b/response_tasks/dns_hijack_enrichment.yml @@ -1,6 +1,6 @@ name: DNS Hijack Enrichment id: c096f721-8842-42ce-bfc7-74bd9a72c712 -version: '1.0' +version: 1 date: '2019-02-14' description: 'This Playbook is part of the Splunk Analytic Story called DNS Hijacking. It is made to be run when the Detection Search within that story called "DNS Record @@ -30,4 +30,4 @@ author: Bhavin Patel, Splunk playbook: name: dns_hijack_enrichment url_json: https://github.com/phantomcyber/playbooks/blob/4.6/dns_hijack_enrichment.json - url_py: https://github.com/phantomcyber/playbooks/blob/4.6/dns_hijack_enrichment.py + url_python: https://github.com/phantomcyber/playbooks/blob/4.6/dns_hijack_enrichment.py diff --git a/response_tasks/domain_certificate_investigation.yml b/response_tasks/domain_certificate_investigation.yml index 8957391034..e5c0e3905f 100644 --- a/response_tasks/domain_certificate_investigation.yml +++ b/response_tasks/domain_certificate_investigation.yml @@ -1,6 +1,6 @@ name: Domain Certificate Investigation id: c096f721-8842-42ce-2fc7-742d8272b712 -version: '1.0' +version: 1 date: '2019-04-29' description: Investigate domain names and URLs of a potentially malicious website. These domain names and URLs could come from anywhere, but this Playbook was designed @@ -20,4 +20,4 @@ author: Philip Royer, Splunk playbook: name: lets_encrypt_domain_investigate url_json: https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json - url_py: https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py + url_python: https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py diff --git a/response_tasks/excessive_account_lockouts_enrichment_and_response.yml b/response_tasks/excessive_account_lockouts_enrichment_and_response.yml index 6c998e1e9a..c471e420cd 100644 --- a/response_tasks/excessive_account_lockouts_enrichment_and_response.yml +++ b/response_tasks/excessive_account_lockouts_enrichment_and_response.yml @@ -1,6 +1,6 @@ name: Excessive Account Lockouts Enrichment And Response id: ab62b5c1-95d4-4e71-8fd7-53a55db33da4 -version: '2.0' +version: 2 date: '2019-02-14' description: This Playbook is part of the Splunk Analytic Story called Account Monitoring and Controls. It is made to be run when the Detection Search within that story called @@ -17,4 +17,4 @@ author: Bhavin Patel, Splunk playbook: name: excessive_account_lockouts_enrichment_and_response url_json: https://github.com/phantomcyber/playbooks/blob/4.6/excessive_account_lockouts_enrichment_and_response.json - url_py: https://github.com/phantomcyber/playbooks/blob/4.6/excessive_account_lockouts_enrichment_and_response.py + url_python: https://github.com/phantomcyber/playbooks/blob/4.6/excessive_account_lockouts_enrichment_and_response.py diff --git a/response_tasks/gcp_kubernetes_activity_by_src_ip.yml b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml index a3e109e80b..a2b8d0f4a1 100644 --- a/response_tasks/gcp_kubernetes_activity_by_src_ip.yml +++ b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml @@ -1,6 +1,6 @@ name: GCP Kubernetes activity by src_ip id: c00e7626-92cc-4e06-9a51-b6db0a50bd1f -version: '1.0' +version: 1 date: '2020-04-13' description: This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes diff --git a/response_tasks/get_all_aws_activity_from_city.yml b/response_tasks/get_all_aws_activity_from_city.yml index b407996b86..ee8c514915 100644 --- a/response_tasks/get_all_aws_activity_from_city.yml +++ b/response_tasks/get_all_aws_activity_from_city.yml @@ -1,6 +1,6 @@ name: Get All AWS Activity From City id: 0abeeb40-1255-4b68-91d1-7a7eb410c4b8 -version: '1.0' +version: 1 date: '2018-03-19' description: This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source diff --git a/response_tasks/get_all_aws_activity_from_country.yml b/response_tasks/get_all_aws_activity_from_country.yml index 66dce86c53..9bcf654f1e 100644 --- a/response_tasks/get_all_aws_activity_from_country.yml +++ b/response_tasks/get_all_aws_activity_from_country.yml @@ -1,6 +1,6 @@ name: Get All AWS Activity From Country id: e763cdb9-00da-41e0-9bda-444debc9501a -version: '1.0' +version: 1 date: '2018-03-19' description: This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the diff --git a/response_tasks/get_all_aws_activity_from_ip_address.yml b/response_tasks/get_all_aws_activity_from_ip_address.yml index c3b78c5e51..82b3f593c9 100644 --- a/response_tasks/get_all_aws_activity_from_ip_address.yml +++ b/response_tasks/get_all_aws_activity_from_ip_address.yml @@ -1,6 +1,6 @@ name: Get All AWS Activity From IP Address id: 446ec87a-85c6-40d4-b060-bea4498281d6 -version: '1.0' +version: 1 date: '2018-03-19' description: This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP diff --git a/response_tasks/get_all_aws_activity_from_region.yml b/response_tasks/get_all_aws_activity_from_region.yml index a9d74e75a7..1db6e7e6c2 100644 --- a/response_tasks/get_all_aws_activity_from_region.yml +++ b/response_tasks/get_all_aws_activity_from_region.yml @@ -1,6 +1,6 @@ name: Get All AWS Activity From Region id: 5b794bef-1743-4f6f-804a-43915a2702ff -version: '1.0' +version: 1 date: '2018-03-19' description: This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the diff --git a/response_tasks/get_authentication_logs_for_endpoint.yml b/response_tasks/get_authentication_logs_for_endpoint.yml index 8dfeb3fa32..ad5861aa26 100644 --- a/response_tasks/get_authentication_logs_for_endpoint.yml +++ b/response_tasks/get_authentication_logs_for_endpoint.yml @@ -1,6 +1,6 @@ name: Get Authentication Logs For Endpoint id: bc91a8cf-35e7-4bb2-8140-e756cc06fd76 -version: '1.0' +version: 1 date: '2017-11-01' description: This search returns all users that have attempted to access a particular endpoint. diff --git a/response_tasks/get_backup_logs_for_endpoint.yml b/response_tasks/get_backup_logs_for_endpoint.yml index 75b280dc0f..96638e2beb 100644 --- a/response_tasks/get_backup_logs_for_endpoint.yml +++ b/response_tasks/get_backup_logs_for_endpoint.yml @@ -1,6 +1,6 @@ name: Get Backup Logs For Endpoint id: fdcfb369-1725-4c24-824a-22972d7f0d44 -version: '1.0' +version: 1 date: '2017-09-14' description: This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. diff --git a/response_tasks/get_certificate_logs_for_a_domain.yml b/response_tasks/get_certificate_logs_for_a_domain.yml index 822e0b0ae3..b4a9420088 100644 --- a/response_tasks/get_certificate_logs_for_a_domain.yml +++ b/response_tasks/get_certificate_logs_for_a_domain.yml @@ -1,6 +1,6 @@ name: Get Certificate logs for a domain id: bc91a8cf-35e7-4bb2-2240-e756cc06fd73 -version: '2.0' +version: 2 date: '2019-04-29' description: This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" diff --git a/response_tasks/get_dns_server_history_for_a_host.yml b/response_tasks/get_dns_server_history_for_a_host.yml index 2062e634a2..7ac551a567 100644 --- a/response_tasks/get_dns_server_history_for_a_host.yml +++ b/response_tasks/get_dns_server_history_for_a_host.yml @@ -1,6 +1,6 @@ name: Get DNS Server History for a host id: bc91a8cf-35e7-4bb2-8140-e756cc06fd72 -version: '1.0' +version: 1 date: '2017-11-09' description: While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data diff --git a/response_tasks/get_dns_traffic_ratio.yml b/response_tasks/get_dns_traffic_ratio.yml index 87078796ca..8c3f05a4bf 100644 --- a/response_tasks/get_dns_traffic_ratio.yml +++ b/response_tasks/get_dns_traffic_ratio.yml @@ -1,6 +1,6 @@ name: Get DNS traffic ratio id: bc91a8cf-35e7-4bb2-8140-e756cc06fd73 -version: '1.0' +version: 1 date: '2017-11-09' description: 'This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this diff --git a/response_tasks/get_ec2_instance_details_by_instanceid.yml b/response_tasks/get_ec2_instance_details_by_instanceid.yml index 4d54493250..ad4f420767 100644 --- a/response_tasks/get_ec2_instance_details_by_instanceid.yml +++ b/response_tasks/get_ec2_instance_details_by_instanceid.yml @@ -1,6 +1,6 @@ name: Get EC2 Instance Details by instanceId id: f3db4d1b-5f33-4b01-c541-c7ah9514c242 -version: '1.0' +version: 1 date: '2018-02-12' description: This search queries AWS description logs and returns all the information about a specific instance via the instanceId field diff --git a/response_tasks/get_ec2_launch_details.yml b/response_tasks/get_ec2_launch_details.yml index bfdced961a..7681171576 100644 --- a/response_tasks/get_ec2_launch_details.yml +++ b/response_tasks/get_ec2_launch_details.yml @@ -1,6 +1,6 @@ name: Get EC2 Launch Details id: 0e40fe83-3edb-4d86-8206-8fed36529ca6 -version: '1.0' +version: 1 date: '2018-03-12' description: This search returns some of the launch details for a EC2 instance. how_to_implement: In order to implement this search, you must install the AWS App diff --git a/response_tasks/get_email_info.yml b/response_tasks/get_email_info.yml index aff77d9278..de81c4b03c 100644 --- a/response_tasks/get_email_info.yml +++ b/response_tasks/get_email_info.yml @@ -1,6 +1,6 @@ name: Get Email Info id: bc91a8cf-35e7-4bb2-8140-e756cc06fd75 -version: '1.0' +version: 1 date: '2017-11-09' description: This search returns all the information Splunk might have collected a specific email message over the last 2 hours. diff --git a/response_tasks/get_emails_from_specific_sender.yml b/response_tasks/get_emails_from_specific_sender.yml index 80cfc6a695..318a75d760 100644 --- a/response_tasks/get_emails_from_specific_sender.yml +++ b/response_tasks/get_emails_from_specific_sender.yml @@ -1,6 +1,6 @@ name: Get Emails From Specific Sender id: 5df39b3f-447d-4869-b673-8f45ad4616fe -version: '1.0' +version: 1 date: '2017-11-09' description: This search returns all the emails from a specific sender over the last 24 and next hours. diff --git a/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml index ba126b7dad..ac496cc266 100644 --- a/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml +++ b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml @@ -1,6 +1,6 @@ name: Get First Occurrence and Last Occurrence of a MAC Address id: bc91a8cf-35e7-4bb2-8140-e756cc06fd33 -version: '1.0' +version: 1 date: '2017-09-13' description: This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine diff --git a/response_tasks/get_history_of_email_sources.yml b/response_tasks/get_history_of_email_sources.yml index 725c13cd52..1a4ed12369 100644 --- a/response_tasks/get_history_of_email_sources.yml +++ b/response_tasks/get_history_of_email_sources.yml @@ -1,6 +1,6 @@ name: Get History Of Email Sources id: ddc7af28-c34d-4392-af93-7f29a4e8806c -version: '1.0' +version: 1 date: '2019-02-21' description: This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each diff --git a/response_tasks/get_logon_rights_modifications_for_endpoint.yml b/response_tasks/get_logon_rights_modifications_for_endpoint.yml index 7ea9d9de8a..8fac127169 100644 --- a/response_tasks/get_logon_rights_modifications_for_endpoint.yml +++ b/response_tasks/get_logon_rights_modifications_for_endpoint.yml @@ -1,6 +1,6 @@ name: Get Logon Rights Modifications For Endpoint id: 03bffe94-ec7a-4cbe-b677-6af40d1c4505 -version: '2.0' +version: 2 date: '2017-09-12' description: This search allows you to retrieve any modifications to logon rights associated with a specific host. diff --git a/response_tasks/get_logon_rights_modifications_for_user.yml b/response_tasks/get_logon_rights_modifications_for_user.yml index 57dd2eeaca..88c2b6612a 100644 --- a/response_tasks/get_logon_rights_modifications_for_user.yml +++ b/response_tasks/get_logon_rights_modifications_for_user.yml @@ -1,6 +1,6 @@ name: Get Logon Rights Modifications For User id: 552bc86c-f72c-4d44-b3f2-06ede13af7bb -version: '2.0' +version: 2 date: '2019-02-27' description: This search allows you to retrieve any modifications to logon rights for a specific user account. diff --git a/response_tasks/get_notable_history.yml b/response_tasks/get_notable_history.yml index 04968ccd83..722af7abed 100644 --- a/response_tasks/get_notable_history.yml +++ b/response_tasks/get_notable_history.yml @@ -1,6 +1,6 @@ name: Get Notable History id: 3d6c3213-5fff-4a1e-b57d-b24c262171e7 -version: '2.0' +version: 2 date: '2017-09-20' description: This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents diff --git a/response_tasks/get_notable_info.yml b/response_tasks/get_notable_info.yml index 5fe0d39f0e..fc44212fe8 100644 --- a/response_tasks/get_notable_info.yml +++ b/response_tasks/get_notable_info.yml @@ -1,6 +1,6 @@ name: Get Notable Info id: f3fb4d1b-5f33-4b01-b541-c7af9534c242 -version: '1.0' +version: 1 date: '2017-09-20' description: This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which diff --git a/response_tasks/get_outbound_emails_to_hidden_cobra_threat_actors.yml b/response_tasks/get_outbound_emails_to_hidden_cobra_threat_actors.yml index 1a2a00b1b1..42078e684d 100644 --- a/response_tasks/get_outbound_emails_to_hidden_cobra_threat_actors.yml +++ b/response_tasks/get_outbound_emails_to_hidden_cobra_threat_actors.yml @@ -1,6 +1,6 @@ name: Get Outbound Emails to Hidden Cobra Threat Actors id: 5df39b3f-347d-4869-b673-8r45ad4616fe -version: '1.0' +version: 1 date: '2018-06-14' description: 'This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, diff --git a/response_tasks/get_parent_process_info.yml b/response_tasks/get_parent_process_info.yml index c9e287f9c9..4a83624bb6 100644 --- a/response_tasks/get_parent_process_info.yml +++ b/response_tasks/get_parent_process_info.yml @@ -1,6 +1,6 @@ name: Get Parent Process Info id: fecf2918-670d-4f1c-872b-3d7317a41bf9 -version: '2.0' +version: 2 date: '2019-02-28' description: This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. diff --git a/response_tasks/get_process_file_activity.yml b/response_tasks/get_process_file_activity.yml index 9c9cfe7952..99c395e87c 100644 --- a/response_tasks/get_process_file_activity.yml +++ b/response_tasks/get_process_file_activity.yml @@ -1,6 +1,6 @@ name: Get Process File Activity id: 6a9ad4d9-6ef2-4b85-953f-a37ab256acd5 -version: '2.0' +version: 2 date: '2019-11-06' description: This search returns the file activity for a specific process on a specific endpoint diff --git a/response_tasks/get_process_info.yml b/response_tasks/get_process_info.yml index 355d953b7e..271c5b4642 100644 --- a/response_tasks/get_process_info.yml +++ b/response_tasks/get_process_info.yml @@ -1,6 +1,6 @@ name: Get Process Info id: bc91a8cf-35e7-4bb2-8140-e756cc06fd71 -version: '2.0' +version: 2 date: '2019-04-01' description: This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process diff --git a/response_tasks/get_process_information_for_port_activity.yml b/response_tasks/get_process_information_for_port_activity.yml index bb55876f40..d1d39c7357 100644 --- a/response_tasks/get_process_information_for_port_activity.yml +++ b/response_tasks/get_process_information_for_port_activity.yml @@ -1,6 +1,6 @@ name: Get Process Information For Port Activity id: 9925d08f-561e-4faa-8912-e3888a842341 -version: '2.0' +version: 2 date: '2019-04-01' description: This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. diff --git a/response_tasks/get_process_registry_activity.yml b/response_tasks/get_process_registry_activity.yml index 2655682cc3..cba445e477 100644 --- a/response_tasks/get_process_registry_activity.yml +++ b/response_tasks/get_process_registry_activity.yml @@ -1,6 +1,6 @@ name: Get Process Registry Activity id: d8362a34-b78a-4364-9733-59b505f5b8d5 -version: '2.0' +version: 2 date: '2019-11-06' description: This search returns the registry activity for a specific process on a specific endpoint diff --git a/response_tasks/get_process_responsible_for_the_dns_traffic.yml b/response_tasks/get_process_responsible_for_the_dns_traffic.yml index 1de953a101..78a0353925 100644 --- a/response_tasks/get_process_responsible_for_the_dns_traffic.yml +++ b/response_tasks/get_process_responsible_for_the_dns_traffic.yml @@ -1,6 +1,6 @@ name: Get Process Responsible For The DNS Traffic id: 910e6512-edc9-4f93-ba24-5b786f47a672 -version: '2.0' +version: 2 date: '2019-04-01' description: While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and diff --git a/response_tasks/get_registry_activities.yml b/response_tasks/get_registry_activities.yml index a49cdb6504..ea5c57a116 100644 --- a/response_tasks/get_registry_activities.yml +++ b/response_tasks/get_registry_activities.yml @@ -1,6 +1,6 @@ name: Get Registry Activities id: fecf2918-670d-4f1c-872b-3d7317a41xf9 -version: '2.0' +version: 2 date: '2019-03-01' description: This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. diff --git a/response_tasks/get_risk_modifiers_for_endpoint.yml b/response_tasks/get_risk_modifiers_for_endpoint.yml index 5de22cad42..5c36c8c55a 100644 --- a/response_tasks/get_risk_modifiers_for_endpoint.yml +++ b/response_tasks/get_risk_modifiers_for_endpoint.yml @@ -1,6 +1,6 @@ name: Get Risk Modifiers For Endpoint id: fdcfb369-1725-4c24-824a-22972d7f0d65 -version: '1.0' +version: 1 date: '2017-10-19' description: 'For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the diff --git a/response_tasks/get_risk_modifiers_for_user.yml b/response_tasks/get_risk_modifiers_for_user.yml index 78ca702357..e7b13eb2ea 100644 --- a/response_tasks/get_risk_modifiers_for_user.yml +++ b/response_tasks/get_risk_modifiers_for_user.yml @@ -1,6 +1,6 @@ name: Get Risk Modifiers For User id: fdcfb369-1725-4c24-824a-22972d7f0d55 -version: '1.0' +version: 1 date: '2017-10-19' description: 'For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the diff --git a/response_tasks/get_sysmon_wmi_activity_for_host.yml b/response_tasks/get_sysmon_wmi_activity_for_host.yml index 4e8fa68613..d220bb0277 100644 --- a/response_tasks/get_sysmon_wmi_activity_for_host.yml +++ b/response_tasks/get_sysmon_wmi_activity_for_host.yml @@ -1,6 +1,6 @@ name: Get Sysmon WMI Activity for Host id: 155e0571-7db6-42f2-aa62-9a3a4cf35c94 -version: '1.0' +version: 1 date: '2018-10-23' description: This search queries Sysmon WMI events for the host of interest. how_to_implement: To successfully implement this search, you must be collecting Sysmon diff --git a/response_tasks/get_update_logs_for_endpoint.yml b/response_tasks/get_update_logs_for_endpoint.yml index e7d01d053b..ca5608cf9d 100644 --- a/response_tasks/get_update_logs_for_endpoint.yml +++ b/response_tasks/get_update_logs_for_endpoint.yml @@ -1,6 +1,6 @@ name: Get Update Logs For Endpoint id: d98675ed-da43-4a7e-96a7-eeca3232ba8e -version: '1.0' +version: 1 date: '2017-08-24' description: This search will tell you give you the update logs for a specific endpoint for the last week. diff --git a/response_tasks/get_user_information_from_identity_table.yml b/response_tasks/get_user_information_from_identity_table.yml index 42b8dc91a0..f411283077 100644 --- a/response_tasks/get_user_information_from_identity_table.yml +++ b/response_tasks/get_user_information_from_identity_table.yml @@ -1,6 +1,6 @@ name: Get User Information from Identity Table id: bc91a8cf-35e7-4bb2-8140-e756cc06fd74 -version: '1.0' +version: 1 date: '2017-09-20' description: Gather more information about the user identified in the Notable Event. how_to_implement: To successfully implement this search you must have populated the diff --git a/response_tasks/get_vulnerability_logs_for_endpoint.yml b/response_tasks/get_vulnerability_logs_for_endpoint.yml index e364d66ff7..f6ff538252 100644 --- a/response_tasks/get_vulnerability_logs_for_endpoint.yml +++ b/response_tasks/get_vulnerability_logs_for_endpoint.yml @@ -1,6 +1,6 @@ name: Get Vulnerability Logs For Endpoint id: df7a7f50-30f2-4cde-8448-69d2d5f9b3c5 -version: '1.0' +version: 1 date: '2017-09-10' description: This search will show you any vulnerabilities noted for a specific endpoint for the last week. diff --git a/response_tasks/get_web_session_information_via_session_id.yml b/response_tasks/get_web_session_information_via_session_id.yml index b4d36131c7..1828cc124a 100644 --- a/response_tasks/get_web_session_information_via_session_id.yml +++ b/response_tasks/get_web_session_information_via_session_id.yml @@ -1,6 +1,6 @@ name: Get Web Session Information via session_id id: bc91a8cf-35e7-4bb2-1120-e756cc06fd89 -version: '1.0' +version: 1 date: '2018-10-08' description: This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID diff --git a/response_tasks/investigate_aws_activities_via_region_name.yml b/response_tasks/investigate_aws_activities_via_region_name.yml index c40cfe8db4..859e5c9de3 100644 --- a/response_tasks/investigate_aws_activities_via_region_name.yml +++ b/response_tasks/investigate_aws_activities_via_region_name.yml @@ -1,6 +1,6 @@ name: Investigate AWS activities via region name id: bc91a8cd-35e7-4bb2-6140-e756cc46fd11 -version: '1.0' +version: 1 date: '2018-02-09' description: This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters diff --git a/response_tasks/investigate_aws_ecr_container_listing_activity.yml b/response_tasks/investigate_aws_ecr_container_listing_activity.yml index 2a543520ef..85009637fc 100644 --- a/response_tasks/investigate_aws_ecr_container_listing_activity.yml +++ b/response_tasks/investigate_aws_ecr_container_listing_activity.yml @@ -1,6 +1,6 @@ name: Investigate AWS ECR container listing activity id: 6027623f-7d10-4847-af3b-8d7e87970451 -version: '1.0' +version: 1 date: '2020-02-20' description: This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, diff --git a/response_tasks/investigate_aws_user_activities_by_user_field.yml b/response_tasks/investigate_aws_user_activities_by_user_field.yml index dfe55b22fd..82e1f14b4a 100644 --- a/response_tasks/investigate_aws_user_activities_by_user_field.yml +++ b/response_tasks/investigate_aws_user_activities_by_user_field.yml @@ -1,6 +1,6 @@ name: Investigate AWS User Activities by user field id: bc91a8cd-35e7-4bb2-6140-e756cc46fd76 -version: '1.0' +version: 1 date: '2018-03-12' description: This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the diff --git a/response_tasks/investigate_cloud_compute_instance_activities.yml b/response_tasks/investigate_cloud_compute_instance_activities.yml index 1e393c68b1..93743435f3 100644 --- a/response_tasks/investigate_cloud_compute_instance_activities.yml +++ b/response_tasks/investigate_cloud_compute_instance_activities.yml @@ -1,6 +1,6 @@ name: Investigate Cloud Compute Instance Activities id: 33a95cf2-900c-4636-8fca-5c5f71474720 -version: '1.0' +version: 1 date: '2018-03-12' description: This search returns a logs of events that operated on the compute instance. how_to_implement: You must be ingesting the approrpiate cloud infrastructure logs diff --git a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml index 2ec144b15d..251dc84b84 100644 --- a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml +++ b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml @@ -1,6 +1,6 @@ name: Investigate Failed Logins for Multiple Destinations id: 097e8030-8662-4254-a735-bf0bdda696e3 -version: '1.0' +version: 1 date: '2019-12-10' description: This search returns failed logins to multiple destinations by user. how_to_implement: To successfully implement this search you need to be ingesting authentication diff --git a/response_tasks/investigate_network_traffic_from_src_ip.yml b/response_tasks/investigate_network_traffic_from_src_ip.yml index 7d691a147a..7eeebca9c3 100644 --- a/response_tasks/investigate_network_traffic_from_src_ip.yml +++ b/response_tasks/investigate_network_traffic_from_src_ip.yml @@ -1,6 +1,6 @@ name: Investigate Network Traffic From src_ip id: 9df9ca9c-a02b-4f48-9eba-0bac55179050 -version: '1.0' +version: 1 date: '2018-06-15' description: This search allows you to find all the network traffic from a specific IP address. diff --git a/response_tasks/investigate_okta_activity_by_app.yml b/response_tasks/investigate_okta_activity_by_app.yml index ae581cd6ac..2597df23ee 100644 --- a/response_tasks/investigate_okta_activity_by_app.yml +++ b/response_tasks/investigate_okta_activity_by_app.yml @@ -1,6 +1,6 @@ name: Investigate Okta Activity by app id: 420eb1b8-2992-45d1-80cf-0b1b2759524d -version: '1.0' +version: 1 date: '2020-04-02' description: This search returns all okta events associated with a specific app how_to_implement: You must be ingesting Okta logs diff --git a/response_tasks/investigate_okta_activity_by_ip_address.yml b/response_tasks/investigate_okta_activity_by_ip_address.yml index 2b83f270d4..24158fc3af 100644 --- a/response_tasks/investigate_okta_activity_by_ip_address.yml +++ b/response_tasks/investigate_okta_activity_by_ip_address.yml @@ -1,6 +1,6 @@ name: Investigate Okta Activity by IP Address id: 56aae066-d619-477c-93e3-3fb83b2d23c3 -version: '1.0' +version: 1 date: '2020-04-02' description: This search returns all okta events from a specific IP address. how_to_implement: You must be ingesting Okta logs diff --git a/response_tasks/investigate_pass_the_hash_attempts.yml b/response_tasks/investigate_pass_the_hash_attempts.yml index fe76888d64..b22e2e2ca6 100644 --- a/response_tasks/investigate_pass_the_hash_attempts.yml +++ b/response_tasks/investigate_pass_the_hash_attempts.yml @@ -1,6 +1,6 @@ name: Investigate Pass the Hash Attempts id: ed3fff45-cba6-4990-983f-6fac72bee659 -version: '1.0' +version: 1 date: '2019-12-10' description: This search hunts for dumped NTLM hashes used for pass the hash. how_to_implement: To successfully implement this search you need be ingesting windows diff --git a/response_tasks/investigate_pass_the_ticket_attempts.yml b/response_tasks/investigate_pass_the_ticket_attempts.yml index 3e405a2716..fc7b48a427 100644 --- a/response_tasks/investigate_pass_the_ticket_attempts.yml +++ b/response_tasks/investigate_pass_the_ticket_attempts.yml @@ -1,6 +1,6 @@ name: Investigate Pass the Ticket Attempts id: 990007ad-d798-4b29-ab2f-f0034144c937 -version: '1.0' +version: 1 date: '2019-12-10' description: This search hunts for dumped kerberos ticket from LSASS memory. how_to_implement: To successfully implement this search you need to be ingesting windows diff --git a/response_tasks/investigate_previous_unseen_user.yml b/response_tasks/investigate_previous_unseen_user.yml index 83f25dfcff..3b906920f8 100644 --- a/response_tasks/investigate_previous_unseen_user.yml +++ b/response_tasks/investigate_previous_unseen_user.yml @@ -1,6 +1,6 @@ name: Investigate Previous Unseen User id: 5de385bf-4f1e-404e-9b67-92d162ff8938ad -version: '1.0' +version: 1 date: '2019-12-10' description: This search returns previous unseen user, which didn't log in for 30 days. diff --git a/response_tasks/investigate_successful_remote_desktop_authentications.yml b/response_tasks/investigate_successful_remote_desktop_authentications.yml index 8b2b2aae9f..8d761d71d4 100644 --- a/response_tasks/investigate_successful_remote_desktop_authentications.yml +++ b/response_tasks/investigate_successful_remote_desktop_authentications.yml @@ -1,6 +1,6 @@ name: Investigate Successful Remote Desktop Authentications id: b6618e8e-be04-40a0-a0b9-f0bd4b6c81bc -version: '1.0' +version: 1 date: '2018-12-14' description: 'This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force diff --git a/response_tasks/investigate_suspicious_strings_in_http_header.yml b/response_tasks/investigate_suspicious_strings_in_http_header.yml index eb9fc3a122..af4d1a4a0d 100644 --- a/response_tasks/investigate_suspicious_strings_in_http_header.yml +++ b/response_tasks/investigate_suspicious_strings_in_http_header.yml @@ -1,6 +1,6 @@ name: Investigate Suspicious Strings in HTTP Header id: bc91a8cf-35e7-4bb2-8140-e756cc06fd89 -version: '1.0' +version: 1 date: '2017-10-20' description: This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and diff --git a/response_tasks/investigate_user_activities_in_all_cloud_regions.yml b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml index 96d65a134a..8e016413f7 100644 --- a/response_tasks/investigate_user_activities_in_all_cloud_regions.yml +++ b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml @@ -1,6 +1,6 @@ name: Investigate User Activities In All Cloud Regions id: 2ef6310f-8e79-42af-b20b-b4eeaba9608a -version: '2.0' +version: 2 date: '2019-04-30' description: This search lists all the logged cloud infrastructure activities by a specific cloud user diff --git a/response_tasks/investigate_user_activities_in_okta.yml b/response_tasks/investigate_user_activities_in_okta.yml index 3460b60952..a31571d31e 100644 --- a/response_tasks/investigate_user_activities_in_okta.yml +++ b/response_tasks/investigate_user_activities_in_okta.yml @@ -1,6 +1,6 @@ name: Investigate User Activities In Okta id: 24ff145d-4d16-420a-b047-480f2a51c403 -version: '1.0' +version: 1 date: '2020-04-02' description: This search returns all okta events by a specific user how_to_implement: You must be ingesting Okta logs diff --git a/response_tasks/investigate_user_activities_in_single_cloud_region.yml b/response_tasks/investigate_user_activities_in_single_cloud_region.yml index 1c97891f28..6153826ae6 100644 --- a/response_tasks/investigate_user_activities_in_single_cloud_region.yml +++ b/response_tasks/investigate_user_activities_in_single_cloud_region.yml @@ -1,6 +1,6 @@ name: Investigate User Activities In Single Cloud Region id: 3dc3a8e7-394b-44ae-8262-4ef8e90b723d -version: '2.0' +version: 2 date: '2019-04-30' description: This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region diff --git a/response_tasks/investigate_web_activity_from_host.yml b/response_tasks/investigate_web_activity_from_host.yml index b4e77d6552..033161bee5 100644 --- a/response_tasks/investigate_web_activity_from_host.yml +++ b/response_tasks/investigate_web_activity_from_host.yml @@ -1,6 +1,6 @@ name: Investigate Web Activity From Host id: bc91a8cf-35e7-4bb2-8140-e756cc06fd22 -version: '1.0' +version: 1 date: '2017-11-09' description: This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize diff --git a/response_tasks/investigate_web_activity_from_src_ip.yml b/response_tasks/investigate_web_activity_from_src_ip.yml index f0b82ce1bc..5ff7313e90 100644 --- a/response_tasks/investigate_web_activity_from_src_ip.yml +++ b/response_tasks/investigate_web_activity_from_src_ip.yml @@ -1,6 +1,6 @@ name: Investigate Web Activity From src_ip id: 2f5b960b-71df-49c0-affc-74992ce60e45 -version: '1.0' +version: 1 date: '2018-06-15' description: This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or diff --git a/response_tasks/investigate_web_posts_from_src.yml b/response_tasks/investigate_web_posts_from_src.yml index fa01e69edd..3a10c2872b 100644 --- a/response_tasks/investigate_web_posts_from_src.yml +++ b/response_tasks/investigate_web_posts_from_src.yml @@ -1,6 +1,6 @@ name: Investigate Web POSTs From src id: f5c39fac-205c-4e07-9004-8fd61ea3431a -version: '1.0' +version: 1 date: '2018-12-06' description: 'This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination diff --git a/response_tasks/malware_hunt_and_contain.yml b/response_tasks/malware_hunt_and_contain.yml index c4be6d85eb..b16e82a2a1 100644 --- a/response_tasks/malware_hunt_and_contain.yml +++ b/response_tasks/malware_hunt_and_contain.yml @@ -1,10 +1,10 @@ name: Malware Hunt and Contain id: 1d7b437a-5114-4b94-a585-04c3362ba08f -version: '1.0' +version: 1 date: '2020-04-29' description: Use the previous identified findings and hunt for the indicators of the malicious file. author: Patrick Bareiss, Splunk playbook: name: malware_hunt_and_contain url_json: https://github.com/phantomcyber/playbooks/blob/4.6/malware_hunt_and_contain.json - url_py: https://github.com/phantomcyber/playbooks/blob/4.6/malware_hunt_and_contain.py + url_python: https://github.com/phantomcyber/playbooks/blob/4.6/malware_hunt_and_contain.py diff --git a/response_tasks/suspicious_email_attachment_investigate_and_delete.yml b/response_tasks/suspicious_email_attachment_investigate_and_delete.yml index 702c55bfa9..d786d34ee0 100644 --- a/response_tasks/suspicious_email_attachment_investigate_and_delete.yml +++ b/response_tasks/suspicious_email_attachment_investigate_and_delete.yml @@ -1,6 +1,6 @@ name: Suspicious Email Attachment Investigate and Delete id: 3096f721-8842-42ce-2fc7-742d8372b712 -version: '1.0' +version: 1 date: '2019-06-03' description: Investigate an email with a suspicious file attachment detected by Splunk Enterprise Security. Detonate the file attachment in a sandbox, gather network behavior @@ -14,4 +14,4 @@ author: Philip Royer, Splunk playbook: name: suspicious_email_attachment_investigate_and_delete url_json: https://github.com/phantomcyber/playbooks/blob/4.6/suspicious_email_attachment_investigate_and_delete.json - url_py: https://github.com/phantomcyber/playbooks/blob/4.6/suspicious_email_attachment_investigate_and_delete.py + url_python: https://github.com/phantomcyber/playbooks/blob/4.6/suspicious_email_attachment_investigate_and_delete.py diff --git a/spec/baselines.spec.json b/spec/baselines.spec.json index 41ab840e31..33c677bfa4 100644 --- a/spec/baselines.spec.json +++ b/spec/baselines.spec.json @@ -90,7 +90,7 @@ "examples": [ 1 ], - "type": "string" + "type": "integer" } }, "required": [ diff --git a/spec/deployments.spec.json b/spec/deployments.spec.json index 2576677bc5..4d39ef8d8b 100644 --- a/spec/deployments.spec.json +++ b/spec/deployments.spec.json @@ -139,9 +139,6 @@ "type": "object" } }, - "required": [ - "index" - ], "type": "object" }, "date": { @@ -249,7 +246,6 @@ } ], "minItems": 1, - "properties": null, "required": [], "type": "object", "uniqueItems": true diff --git a/spec/detections.spec.json b/spec/detections.spec.json index 43269fd8cc..56dd2242a1 100644 --- a/spec/detections.spec.json +++ b/spec/detections.spec.json @@ -38,7 +38,7 @@ }, "version": { "$id": "#/properties/version", - "type": "string", + "type": "integer", "description": "version of detection, e.g. 1 or 2 ...", "default": 0, "examples": [ diff --git a/spec/response_tasks.spec.json b/spec/response_tasks.spec.json index 2425848a01..28b0688e1c 100644 --- a/spec/response_tasks.spec.json +++ b/spec/response_tasks.spec.json @@ -143,7 +143,7 @@ "examples": [ 3 ], - "type": "string" + "type": "integer" } }, "required": [ diff --git a/spec/responses.spec.json b/spec/responses.spec.json index 3eaf1a9b76..8779c28b81 100644 --- a/spec/responses.spec.json +++ b/spec/responses.spec.json @@ -75,9 +75,8 @@ ] } ], - "properties": null, "required": [], - "type": "object" + "type": "array" }, "tags": { "$id": "#/properties/tags", @@ -101,7 +100,7 @@ "examples": [ 1 ], - "type": "string" + "type": "integer" } }, "required": [ diff --git a/spec/stories.spec.json b/spec/stories.spec.json index daf7250cc1..983433b9a3 100644 --- a/spec/stories.spec.json +++ b/spec/stories.spec.json @@ -89,7 +89,7 @@ "examples": [ 1 ], - "type": "string" + "type": "integer" } }, "required": [ diff --git a/stories/account_monitoring_and_controls.yml b/stories/account_monitoring_and_controls.yml index 10622b4f42..f03fe46e46 100644 --- a/stories/account_monitoring_and_controls.yml +++ b/stories/account_monitoring_and_controls.yml @@ -1,6 +1,6 @@ name: Account Monitoring and Controls id: 8892a655-6205-55f7-abba-06460e38c8ae -version: '1.0' +version: 1 date: '2017-09-06' description: A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for diff --git a/stories/apache_struts_vulnerability.yml b/stories/apache_struts_vulnerability.yml index 4020cbb2f2..e58c7ab44c 100644 --- a/stories/apache_struts_vulnerability.yml +++ b/stories/apache_struts_vulnerability.yml @@ -1,6 +1,6 @@ name: Apache Struts Vulnerability id: 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e -version: '1.0' +version: 1 date: '2018-12-06' description: Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent diff --git a/stories/asset_tracking.yml b/stories/asset_tracking.yml index 28df768a2d..18b27b7073 100644 --- a/stories/asset_tracking.yml +++ b/stories/asset_tracking.yml @@ -1,6 +1,6 @@ name: Asset Tracking id: 91c676cf-0b23-438d-abee-f6335e1fce77 -version: '1.0' +version: 1 date: '2017-09-13' description: Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of diff --git a/stories/aws_cross_account_activity.yml b/stories/aws_cross_account_activity.yml index 151ef37118..8eec2711c4 100644 --- a/stories/aws_cross_account_activity.yml +++ b/stories/aws_cross_account_activity.yml @@ -1,6 +1,6 @@ name: AWS Cross Account Activity id: 2f2f610a-d64d-48c2-b57c-967a2b49ab5a -version: '1.0' +version: 1 date: '2018-06-04' description: Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles diff --git a/stories/aws_cryptomining.yml b/stories/aws_cryptomining.yml index 49fac68c79..555dc39d40 100644 --- a/stories/aws_cryptomining.yml +++ b/stories/aws_cryptomining.yml @@ -1,6 +1,6 @@ name: AWS Cryptomining id: ced74200-8465-4bc3-bd2c-9a782eec6750 -version: '1.0' +version: 1 date: '2018-03-08' description: Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally diff --git a/stories/aws_network_acl_activity.yml b/stories/aws_network_acl_activity.yml index 3fa8826eaf..642741a086 100644 --- a/stories/aws_network_acl_activity.yml +++ b/stories/aws_network_acl_activity.yml @@ -1,6 +1,6 @@ name: AWS Network ACL Activity id: 2e8948a5-5239-406b-b56b-6c50ff268af4 -version: '2.0' +version: 2 date: '2018-05-21' description: Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. diff --git a/stories/aws_suspicious_provisioning_activities.yml b/stories/aws_suspicious_provisioning_activities.yml index 2385b0fccc..06d443a817 100644 --- a/stories/aws_suspicious_provisioning_activities.yml +++ b/stories/aws_suspicious_provisioning_activities.yml @@ -1,6 +1,6 @@ name: AWS Suspicious Provisioning Activities id: 3338b567-3804-4261-9889-cf0ca4753c7f -version: '1.0' +version: 1 date: '2018-03-16' description: Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities diff --git a/stories/aws_user_monitoring.yml b/stories/aws_user_monitoring.yml index 0cdc936454..af43bd792e 100644 --- a/stories/aws_user_monitoring.yml +++ b/stories/aws_user_monitoring.yml @@ -1,6 +1,6 @@ name: AWS User Monitoring id: 2e8948a5-5239-406b-b56b-6c50f1269af3 -version: '1.0' +version: 1 date: '2018-03-12' description: Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack diff --git a/stories/brand_monitoring.yml b/stories/brand_monitoring.yml index d7cec56686..dd27bee03f 100644 --- a/stories/brand_monitoring.yml +++ b/stories/brand_monitoring.yml @@ -1,6 +1,6 @@ name: Brand Monitoring id: 91c676cf-0b23-438d-abee-f6335e1fce78 -version: '1.0' +version: 1 date: '2017-12-19' description: Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. diff --git a/stories/cloud_cryptomining.yml b/stories/cloud_cryptomining.yml index a678ebe75a..4341815a17 100644 --- a/stories/cloud_cryptomining.yml +++ b/stories/cloud_cryptomining.yml @@ -1,6 +1,6 @@ name: Cloud Cryptomining id: 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a -version: '1.0' +version: 1 date: '2019-10-02' description: Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally diff --git a/stories/coldroot_macos_rat.yml b/stories/coldroot_macos_rat.yml index 87e3132b30..a9ca577bd2 100644 --- a/stories/coldroot_macos_rat.yml +++ b/stories/coldroot_macos_rat.yml @@ -1,6 +1,6 @@ name: ColdRoot MacOS RAT id: bd91a2bc-d20b-4f44-a982-1bea98e86390 -version: '1.0' +version: 1 date: '2019-01-09' description: Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example diff --git a/stories/collection_and_staging.yml b/stories/collection_and_staging.yml index 7f913b2bbb..81ba716e0f 100644 --- a/stories/collection_and_staging.yml +++ b/stories/collection_and_staging.yml @@ -1,6 +1,6 @@ name: Collection and Staging id: 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a -version: '1.1' +version: 1 date: '2020-02-03' description: 'Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific diff --git a/stories/command_and_control.yml b/stories/command_and_control.yml index df86d114f1..88b1ff4876 100644 --- a/stories/command_and_control.yml +++ b/stories/command_and_control.yml @@ -1,6 +1,6 @@ name: Command and Control id: 943773c6-c4de-4f38-89a8-0b92f98804d8 -version: '1.0' +version: 1 date: '2018-06-01' description: Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed diff --git a/stories/common_phishing_frameworks.yml b/stories/common_phishing_frameworks.yml index a0357a1435..4f6f64bd4b 100644 --- a/stories/common_phishing_frameworks.yml +++ b/stories/common_phishing_frameworks.yml @@ -1,6 +1,6 @@ name: Common Phishing Frameworks id: 9a64ab44-9214-4639-8163-7eaa2621bd61 -version: '1.0' +version: 1 date: '2019-04-29' description: 'Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on diff --git a/stories/container_implantation_monitoring_&_investigation.yml b/stories/container_implantation_monitoring_&_investigation.yml index e24ac1ff58..df19f74acf 100644 --- a/stories/container_implantation_monitoring_&_investigation.yml +++ b/stories/container_implantation_monitoring_&_investigation.yml @@ -1,6 +1,6 @@ name: Container Implantation Monitoring & Investigation id: aa0e28b1-0521-4b6f-9d2a-7b87e34af246 -version: '1.0' +version: 1 date: '2020-02-20' description: Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. diff --git a/stories/credential_dumping.yml b/stories/credential_dumping.yml index a2dd2ab329..5f20c92524 100644 --- a/stories/credential_dumping.yml +++ b/stories/credential_dumping.yml @@ -1,6 +1,6 @@ name: Credential Dumping id: 854d78bf-d0e2-4f4e-b05c-640905f86d7a -version: '3.0' +version: 3 date: '2020-02-04' description: Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The diff --git a/stories/data_protection.yml b/stories/data_protection.yml index dc387a45fc..36e5f876af 100644 --- a/stories/data_protection.yml +++ b/stories/data_protection.yml @@ -1,6 +1,6 @@ name: Data Protection id: 91c676cf-0b23-438d-abee-f6335e1fce33 -version: '1.0' +version: 1 date: '2017-09-14' description: Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate diff --git a/stories/dhs_report_ta18_074a.yml b/stories/dhs_report_ta18_074a.yml index f7b17d326d..2104110345 100644 --- a/stories/dhs_report_ta18_074a.yml +++ b/stories/dhs_report_ta18_074a.yml @@ -1,6 +1,6 @@ name: DHS Report TA18-074A id: 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef -version: '2.0' +version: 2 date: '2020-01-22' description: Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises diff --git a/stories/disabling_security_tools.yml b/stories/disabling_security_tools.yml index 00d5a808f5..12cf57def9 100644 --- a/stories/disabling_security_tools.yml +++ b/stories/disabling_security_tools.yml @@ -1,6 +1,6 @@ name: Disabling Security Tools id: fcc27099-46a0-46b0-a271-5c7dab56b6f1 -version: '2.0' +version: 2 date: '2020-02-04' description: Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes diff --git a/stories/dns_amplification_attacks.yml b/stories/dns_amplification_attacks.yml index f18885164d..d273831862 100644 --- a/stories/dns_amplification_attacks.yml +++ b/stories/dns_amplification_attacks.yml @@ -1,6 +1,6 @@ name: DNS Amplification Attacks id: e8afd39e-3294-11e6-b39d-a45e60c6700 -version: '1.0' +version: 1 date: '2016-09-13' description: DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers diff --git a/stories/dns_hijacking.yml b/stories/dns_hijacking.yml index 9f2a6fb131..0ff67cdfda 100644 --- a/stories/dns_hijacking.yml +++ b/stories/dns_hijacking.yml @@ -1,6 +1,6 @@ name: DNS Hijacking id: 8169f17b-ef68-4b59-aa28-586907301221 -version: '1.0' +version: 1 date: '2020-02-04' description: Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. diff --git a/stories/dynamic_dns.yml b/stories/dynamic_dns.yml index 806bf27626..3ebcea30c9 100644 --- a/stories/dynamic_dns.yml +++ b/stories/dynamic_dns.yml @@ -1,6 +1,6 @@ name: Dynamic DNS id: 8169f17b-ef68-4b59-aae8-586907301221 -version: '2.0' +version: 2 date: '2018-09-06' description: Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them diff --git a/stories/emotet_malware_(dhs_report_ta18_201a).yml b/stories/emotet_malware_(dhs_report_ta18_201a).yml index ce7fe40866..d3d50ad719 100644 --- a/stories/emotet_malware_(dhs_report_ta18_201a).yml +++ b/stories/emotet_malware_(dhs_report_ta18_201a).yml @@ -1,6 +1,6 @@ name: Emotet Malware (DHS Report TA18-201A) id: bb9f5ed2-916e-4364-bb6d-91c310efcf52 -version: '1.0' +version: 1 date: '2020-01-27' description: Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch diff --git a/stories/hidden_cobra_malware.yml b/stories/hidden_cobra_malware.yml index 9039a985ac..5fc84b1ac7 100644 --- a/stories/hidden_cobra_malware.yml +++ b/stories/hidden_cobra_malware.yml @@ -1,6 +1,6 @@ name: Hidden Cobra Malware id: baf7580b-d4b4-4774-8173-7d198e9da335 -version: '2.0' +version: 2 date: '2020-01-22' description: Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North diff --git a/stories/host_redirection.yml b/stories/host_redirection.yml index 6774315e9d..346b913191 100644 --- a/stories/host_redirection.yml +++ b/stories/host_redirection.yml @@ -1,6 +1,6 @@ name: Host Redirection id: 2e8948a5-5239-406b-b56b-6c50fe268af4 -version: '1.0' +version: 1 date: '2017-09-14' description: Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's diff --git a/stories/jboss_vulnerability.yml b/stories/jboss_vulnerability.yml index 5a6d274939..fe822e0c1d 100644 --- a/stories/jboss_vulnerability.yml +++ b/stories/jboss_vulnerability.yml @@ -1,6 +1,6 @@ name: JBoss Vulnerability id: 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd -version: '1.0' +version: 1 date: '2017-09-14' description: In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches diff --git a/stories/kubernetes_scanning_activity.yml b/stories/kubernetes_scanning_activity.yml index 8c7ae44194..be38a9c8a1 100644 --- a/stories/kubernetes_scanning_activity.yml +++ b/stories/kubernetes_scanning_activity.yml @@ -1,6 +1,6 @@ name: Kubernetes Scanning Activity id: a9ef59cf-e981-4e66-9eef-bb049f695c09 -version: '1.0' +version: 1 date: '2020-04-15' description: This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, diff --git a/stories/lateral_movement.yml b/stories/lateral_movement.yml index 9e535d8d09..ac9b5e0ebc 100644 --- a/stories/lateral_movement.yml +++ b/stories/lateral_movement.yml @@ -1,6 +1,6 @@ name: Lateral Movement id: 399d65dc-1f08-499b-a259-aad9051f38ad -version: '2.0' +version: 2 date: '2020-02-04' description: Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose diff --git a/stories/malicious_powershell.yml b/stories/malicious_powershell.yml index 5cb44f90d2..e32686a527 100644 --- a/stories/malicious_powershell.yml +++ b/stories/malicious_powershell.yml @@ -1,6 +1,6 @@ name: Malicious PowerShell id: 2c8ff66e-0b57-42af-8ad7-912438a403fc -version: '4.0' +version: 4 date: '2017-08-23' description: Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their diff --git a/stories/monitor_backup_solution.yml b/stories/monitor_backup_solution.yml index 0c5e1d1d97..c581fc63fe 100644 --- a/stories/monitor_backup_solution.yml +++ b/stories/monitor_backup_solution.yml @@ -1,6 +1,6 @@ name: Monitor Backup Solution id: abe807c7-1eb6-4304-ac32-6e7aacdb891d -version: '1.0' +version: 1 date: '2017-09-12' description: Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical diff --git a/stories/monitor_for_unauthorized_software.yml b/stories/monitor_for_unauthorized_software.yml index 65e1d358c7..fd33be58d2 100644 --- a/stories/monitor_for_unauthorized_software.yml +++ b/stories/monitor_for_unauthorized_software.yml @@ -1,6 +1,6 @@ name: Monitor for Unauthorized Software id: 8892a655-6205-43f7-abba-06460e38c8ae -version: '1.0' +version: 1 date: '2017-09-15' description: 'Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. ' diff --git a/stories/monitor_for_updates.yml b/stories/monitor_for_updates.yml index 0de634dd83..6394705018 100644 --- a/stories/monitor_for_updates.yml +++ b/stories/monitor_for_updates.yml @@ -1,6 +1,6 @@ name: Monitor for Updates id: 9ef8d677-7b52-4213-a038-99cfc7acc2d8 -version: '1.0' +version: 1 date: '2017-09-15' description: Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be diff --git a/stories/netsh_abuse.yml b/stories/netsh_abuse.yml index 78a84d2c65..f294b5483c 100644 --- a/stories/netsh_abuse.yml +++ b/stories/netsh_abuse.yml @@ -1,6 +1,6 @@ name: Netsh Abuse id: 2b1800dd-92f9-47ec-a981-fdf1351e5f65 -version: '1.0' +version: 1 date: '2017-01-05' description: Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection diff --git a/stories/orangeworm_attack_group.yml b/stories/orangeworm_attack_group.yml index 1cb4fe7f66..a72bf7c573 100644 --- a/stories/orangeworm_attack_group.yml +++ b/stories/orangeworm_attack_group.yml @@ -1,6 +1,6 @@ name: Orangeworm Attack Group id: bb9f5ed2-916e-4364-bb6d-97c370efcf52 -version: '2.0' +version: 2 date: '2020-01-22' description: Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. diff --git a/stories/phishing_payloads.yml b/stories/phishing_payloads.yml index e8cfcc7768..62fa65e2a4 100644 --- a/stories/phishing_payloads.yml +++ b/stories/phishing_payloads.yml @@ -1,6 +1,6 @@ name: Phishing Payloads id: 57226b40-94f3-4ce5-b101-a75f67759c27 -version: '1.0' +version: 1 date: '2019-04-29' description: Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. diff --git a/stories/possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml b/stories/possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml index 68966255b6..943ec649c4 100644 --- a/stories/possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml +++ b/stories/possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns.yml @@ -1,6 +1,6 @@ name: Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns id: 988C59C5-0A1C-45B6-A555-0C62276E327E -version: '1.0' +version: 1 date: '2020-01-22' description: Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. diff --git a/stories/prohibited_traffic_allowed_or_protocol_mismatch.yml b/stories/prohibited_traffic_allowed_or_protocol_mismatch.yml index cdc7d63caf..4e41c6b110 100644 --- a/stories/prohibited_traffic_allowed_or_protocol_mismatch.yml +++ b/stories/prohibited_traffic_allowed_or_protocol_mismatch.yml @@ -1,6 +1,6 @@ name: Prohibited Traffic Allowed or Protocol Mismatch id: 6d13121c-90f3-446d-8ac3-27efbbc65218 -version: '1.0' +version: 1 date: '2017-09-11' description: Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors diff --git a/stories/ransomware.yml b/stories/ransomware.yml index 4123369d54..9293bd2276 100644 --- a/stories/ransomware.yml +++ b/stories/ransomware.yml @@ -1,6 +1,6 @@ name: Ransomware id: cf309d0d-d4aa-4fbb-963d-1e79febd3756 -version: '1.1' +version: 1 date: '2020-02-04' description: Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, diff --git a/stories/router_&_infrastructure_security.yml b/stories/router_&_infrastructure_security.yml index fec9cc09c1..486671f861 100644 --- a/stories/router_&_infrastructure_security.yml +++ b/stories/router_&_infrastructure_security.yml @@ -1,6 +1,6 @@ name: Router & Infrastructure Security id: 91c676cf-0b23-438d-abee-f6335e177e77 -version: '1.0' +version: 1 date: '2017-09-12' description: Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing diff --git a/stories/samsam_ransomware.yml b/stories/samsam_ransomware.yml index de72c064d6..b6c5fa9754 100644 --- a/stories/samsam_ransomware.yml +++ b/stories/samsam_ransomware.yml @@ -1,6 +1,6 @@ name: SamSam Ransomware id: c4b89506-fbcf-4cb7-bfd6-527e54789604 -version: '1.0' +version: 1 date: '2018-12-13' description: Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated diff --git a/stories/spectre_and_meltdown_vulnerabilities.yml b/stories/spectre_and_meltdown_vulnerabilities.yml index a139f6f056..eb7b3c0bda 100644 --- a/stories/spectre_and_meltdown_vulnerabilities.yml +++ b/stories/spectre_and_meltdown_vulnerabilities.yml @@ -1,6 +1,6 @@ name: Spectre And Meltdown Vulnerabilities id: 6d3306f6-bb2b-4219-8609-8efad64032f2 -version: '1.0' +version: 1 date: '2018-01-08' description: Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. diff --git a/stories/splunk_enterprise_vulnerability.yml b/stories/splunk_enterprise_vulnerability.yml index d55921eeb1..65e9efc461 100644 --- a/stories/splunk_enterprise_vulnerability.yml +++ b/stories/splunk_enterprise_vulnerability.yml @@ -1,6 +1,6 @@ name: Splunk Enterprise Vulnerability id: 4e692b96-de2d-4bd1-9105-37e2368a8db1 -version: '1.0' +version: 1 date: '2017-09-19' description: Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some diff --git a/stories/splunk_enterprise_vulnerability_cve_2018_11409.yml b/stories/splunk_enterprise_vulnerability_cve_2018_11409.yml index 0e6f40222a..b86d68483a 100644 --- a/stories/splunk_enterprise_vulnerability_cve_2018_11409.yml +++ b/stories/splunk_enterprise_vulnerability_cve_2018_11409.yml @@ -1,6 +1,6 @@ name: Splunk Enterprise Vulnerability CVE-2018-11409 id: 1fc34cbc-34e9-43ba-87ab-6811c9e95400 -version: '1.0' +version: 1 date: '2018-06-14' description: Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help diff --git a/stories/sql_injection.yml b/stories/sql_injection.yml index 1682357c00..d146c538a1 100644 --- a/stories/sql_injection.yml +++ b/stories/sql_injection.yml @@ -1,6 +1,6 @@ name: SQL Injection id: 4f6632f5-449c-4686-80df-57625f59bab3 -version: '1.0' +version: 1 date: '2017-09-19' description: Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain diff --git a/stories/suspicious_aws_ec2_activities.yml b/stories/suspicious_aws_ec2_activities.yml index 3cbc3e2f57..d94a36ca18 100644 --- a/stories/suspicious_aws_ec2_activities.yml +++ b/stories/suspicious_aws_ec2_activities.yml @@ -1,6 +1,6 @@ name: Suspicious AWS EC2 Activities id: 2e8948a5-5239-406b-b56b-6c50f1268af3 -version: '1.0' +version: 1 date: '2018-02-09' description: Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances diff --git a/stories/suspicious_aws_login_activities.yml b/stories/suspicious_aws_login_activities.yml index 09f456b120..e04a2e5459 100644 --- a/stories/suspicious_aws_login_activities.yml +++ b/stories/suspicious_aws_login_activities.yml @@ -1,6 +1,6 @@ name: Suspicious AWS Login Activities id: 2e8948a5-5239-406b-b56b-6c59f1268af3 -version: '1.0' +version: 1 date: '2019-05-01' description: 'Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious diff --git a/stories/suspicious_aws_s3_activities.yml b/stories/suspicious_aws_s3_activities.yml index 69ffeae043..362f0b2d25 100644 --- a/stories/suspicious_aws_s3_activities.yml +++ b/stories/suspicious_aws_s3_activities.yml @@ -1,6 +1,6 @@ name: Suspicious AWS S3 Activities id: 2e8948a5-5239-406b-b56b-6c50w3168af3 -version: '2.0' +version: 2 date: '2018-07-24' description: Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open diff --git a/stories/suspicious_aws_traffic.yml b/stories/suspicious_aws_traffic.yml index 1255d6d35e..c241058937 100644 --- a/stories/suspicious_aws_traffic.yml +++ b/stories/suspicious_aws_traffic.yml @@ -1,6 +1,6 @@ name: Suspicious AWS Traffic id: 2e8948a5-5239-406b-b56b-6c50f2168af3 -version: '1.0' +version: 1 date: '2018-05-07' description: Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound diff --git a/stories/suspicious_command_line_executions.yml b/stories/suspicious_command_line_executions.yml index abf90b1828..9c9febd2e3 100644 --- a/stories/suspicious_command_line_executions.yml +++ b/stories/suspicious_command_line_executions.yml @@ -1,6 +1,6 @@ name: Suspicious Command-Line Executions id: f4368ddf-d59f-4192-84f6-778ac5a3ffc7 -version: '2.1' +version: 2 date: '2020-02-03' description: Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. diff --git a/stories/suspicious_dns_traffic.yml b/stories/suspicious_dns_traffic.yml index 00165c4bf7..a0925d45f2 100644 --- a/stories/suspicious_dns_traffic.yml +++ b/stories/suspicious_dns_traffic.yml @@ -1,6 +1,6 @@ name: Suspicious DNS Traffic id: 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 -version: '1.0' +version: 1 date: '2017-09-18' description: Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol diff --git a/stories/suspicious_emails.yml b/stories/suspicious_emails.yml index a21875c8af..17efc4676f 100644 --- a/stories/suspicious_emails.yml +++ b/stories/suspicious_emails.yml @@ -1,6 +1,6 @@ name: Suspicious Emails id: 2b1800dd-92f9-47ec-a981-fdf1351e5d55 -version: '1.0' +version: 1 date: '2020-01-27' description: Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails diff --git a/stories/suspicious_mshta_activity.yml b/stories/suspicious_mshta_activity.yml index 7a0695e709..6c1a98a5a5 100644 --- a/stories/suspicious_mshta_activity.yml +++ b/stories/suspicious_mshta_activity.yml @@ -1,6 +1,6 @@ name: Suspicious MSHTA Activity id: 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 -version: '1.1' +version: 1 date: '2020-02-03' description: Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. diff --git a/stories/suspicious_okta_activity.yml b/stories/suspicious_okta_activity.yml index ad8bb93b80..2d8b9d820c 100644 --- a/stories/suspicious_okta_activity.yml +++ b/stories/suspicious_okta_activity.yml @@ -1,6 +1,6 @@ name: Suspicious Okta Activity id: 9cbd34af-8f39-4476-a423-bacd126c750b -version: '1.0' +version: 1 date: '2020-04-02' description: Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. diff --git a/stories/suspicious_windows_registry_activities.yml b/stories/suspicious_windows_registry_activities.yml index 31cf8be151..f079fd1f25 100644 --- a/stories/suspicious_windows_registry_activities.yml +++ b/stories/suspicious_windows_registry_activities.yml @@ -1,6 +1,6 @@ name: Suspicious Windows Registry Activities id: 2b1800dd-92f9-47dd-a981-fdf1351e5d55 -version: '1.0' +version: 1 date: '2018-05-31' description: Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. diff --git a/stories/suspicious_wmi_use.yml b/stories/suspicious_wmi_use.yml index d45a5cbc13..b46d55757e 100644 --- a/stories/suspicious_wmi_use.yml +++ b/stories/suspicious_wmi_use.yml @@ -1,6 +1,6 @@ name: Suspicious WMI Use id: c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 -version: '2.0' +version: 2 date: '2018-10-23' description: Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating diff --git a/stories/unusual_aws_ec2_modifications.yml b/stories/unusual_aws_ec2_modifications.yml index 146146c01c..03f4c1edac 100644 --- a/stories/unusual_aws_ec2_modifications.yml +++ b/stories/unusual_aws_ec2_modifications.yml @@ -1,6 +1,6 @@ name: Unusual AWS EC2 Modifications id: 73de57ef-0dfc-411f-b1e7-fa24428aeae0 -version: '1.0' +version: 1 date: '2018-04-09' description: Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users diff --git a/stories/unusual_processes.yml b/stories/unusual_processes.yml index 17d4aca773..173d644caa 100644 --- a/stories/unusual_processes.yml +++ b/stories/unusual_processes.yml @@ -1,6 +1,6 @@ name: Unusual Processes id: f4368e3f-d59f-4192-84f6-748ac5a3ddb6 -version: '2.1' +version: 2 date: '2020-02-04' description: Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, diff --git a/stories/use_of_cleartext_protocols.yml b/stories/use_of_cleartext_protocols.yml index 5eaeedac92..279d6984c9 100644 --- a/stories/use_of_cleartext_protocols.yml +++ b/stories/use_of_cleartext_protocols.yml @@ -1,6 +1,6 @@ name: Use of Cleartext Protocols id: 826e6431-aeef-41b4-9fc0-6d0985d65a21 -version: '1.0' +version: 1 date: '2017-09-15' description: Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. diff --git a/stories/web_fraud_detection.yml b/stories/web_fraud_detection.yml index 3d79bd16a0..d02f1f1ff6 100644 --- a/stories/web_fraud_detection.yml +++ b/stories/web_fraud_detection.yml @@ -1,6 +1,6 @@ name: Web Fraud Detection id: 31337aaa-bc22-4752-b599-ef112dq1dq7a -version: '1.0' +version: 1 date: '2018-10-08' description: Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. diff --git a/stories/windows_defense_evasion_tactics.yml b/stories/windows_defense_evasion_tactics.yml index 6bced15e3c..2958e60dc1 100644 --- a/stories/windows_defense_evasion_tactics.yml +++ b/stories/windows_defense_evasion_tactics.yml @@ -1,6 +1,6 @@ name: Windows Defense Evasion Tactics id: 56e24a28-5003-4047-b2db-e8f3c4618064 -version: '1.0' +version: 1 date: '2018-05-31' description: 'Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` diff --git a/stories/windows_file_extension_and_association_abuse.yml b/stories/windows_file_extension_and_association_abuse.yml index 4ea47b655b..84c7e88da1 100644 --- a/stories/windows_file_extension_and_association_abuse.yml +++ b/stories/windows_file_extension_and_association_abuse.yml @@ -1,6 +1,6 @@ name: Windows File Extension and Association Abuse id: 30552a76-ac78-48e4-b3c0-de4e34e9563d -version: '1.0' +version: 1 date: '2018-01-26' description: Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting diff --git a/stories/windows_log_manipulation.yml b/stories/windows_log_manipulation.yml index 6d219ef284..18fdf81a66 100644 --- a/stories/windows_log_manipulation.yml +++ b/stories/windows_log_manipulation.yml @@ -1,6 +1,6 @@ name: Windows Log Manipulation id: b6db2c60-a281-48b4-95f1-2cd99ed56835 -version: '2.0' +version: 2 date: '2017-09-12' description: Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an diff --git a/stories/windows_persistence_techniques.yml b/stories/windows_persistence_techniques.yml index db6b2207d5..c05d4d7b4a 100644 --- a/stories/windows_persistence_techniques.yml +++ b/stories/windows_persistence_techniques.yml @@ -1,6 +1,6 @@ name: Windows Persistence Techniques id: 30874d4f-20a1-488f-85ec-5d52ef74e3f9 -version: '2.0' +version: 2 date: '2018-05-31' description: Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. diff --git a/stories/windows_privilege_escalation.yml b/stories/windows_privilege_escalation.yml index e9c7b61a74..470196052b 100644 --- a/stories/windows_privilege_escalation.yml +++ b/stories/windows_privilege_escalation.yml @@ -1,6 +1,6 @@ name: Windows Privilege Escalation id: 644e22d3-598a-429c-a007-16fdb802cae5 -version: '2.0' +version: 2 date: '2020-02-04' description: Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, diff --git a/stories/windows_service_abuse.yml b/stories/windows_service_abuse.yml index c924c32e92..f30090c6b2 100644 --- a/stories/windows_service_abuse.yml +++ b/stories/windows_service_abuse.yml @@ -1,6 +1,6 @@ name: Windows Service Abuse id: 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 -version: '3.0' +version: 3 date: '2017-11-02' description: Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic From 42172669523ec13722a038d046bad6bcab3c0a74 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 30 Apr 2020 12:53:55 +0200 Subject: [PATCH 07/93] WIP --- bin/validate.py | 117 ++++++++---------- ...credential_dump_from_registry_via_reg.yml} | 2 +- ...exe.yml => child_processes_of_spoolsv.yml} | 2 +- ...create_local_admin_accounts_using_net.yml} | 2 +- ...te_or_delete_windows_shares_using_net.yml} | 2 +- ...ing_scripts_in_command_line_arguments.yml} | 2 +- ...l => detect_oulook_writing_a_zip_file.yml} | 2 +- ...h_interception_by_creation_of_program.yml} | 2 +- ..._prohibited_applications_spawning_cmd.yml} | 2 +- ..._of_cmd_to_launch_script_interpreters.yml} | 2 +- ...ing_files_and_directories_with_attrib.yml} | 2 +- ...manipulating_windows_services_with_sc.yml} | 2 +- ...lating_windows_services_registry_keys.yml} | 2 +- ...iles_or_directories_via_registry_keys.yml} | 2 +- ...process.yml => suspicious_reg_process.yml} | 2 +- ...azon_eks_kubernetes_activity_by_src_ip.yml | 2 +- .../gcp_kubernetes_activity_by_src_ip.yml | 2 +- ...web_session_information_via_session_id.yml | 2 +- ...nvestigate_network_traffic_from_src_ip.yml | 2 +- .../investigate_web_activity_from_src_ip.yml | 2 +- ...antation_monitoring_and_investigation.yml} | 2 +- ...port_ta18_201a).yml => emotet_malware.yml} | 2 +- ...=> router_and_infrastructure_security.yml} | 2 +- 23 files changed, 77 insertions(+), 84 deletions(-) rename detections/{attempted_credential_dump_from_registry_via_reg_exe.yml => attempted_credential_dump_from_registry_via_reg.yml} (96%) rename detections/{child_processes_of_spoolsv_exe.yml => child_processes_of_spoolsv.yml} (97%) rename detections/{create_local_admin_accounts_using_net_exe.yml => create_local_admin_accounts_using_net.yml} (96%) rename detections/{create_or_delete_windows_shares_using_net_exe.yml => create_or_delete_windows_shares_using_net.yml} (96%) rename detections/{detect_mshta_exe_running_scripts_in_command_line_arguments.yml => detect_mshta_running_scripts_in_command_line_arguments.yml} (95%) rename detections/{detect_oulook_exe_writing_a__zip_file.yml => detect_oulook_writing_a_zip_file.yml} (98%) rename detections/{detect_path_interception_by_creation_of_program_exe.yml => detect_path_interception_by_creation_of_program.yml} (96%) rename detections/{detect_prohibited_applications_spawning_cmd_exe.yml => detect_prohibited_applications_spawning_cmd.yml} (96%) rename detections/{detect_use_of_cmd_exe_to_launch_script_interpreters.yml => detect_use_of_cmd_to_launch_script_interpreters.yml} (96%) rename detections/{hiding_files_and_directories_with_attrib_exe.yml => hiding_files_and_directories_with_attrib.yml} (96%) rename detections/{sc_exe_manipulating_windows_services.yml => manipulating_windows_services_with_sc.yml} (97%) rename detections/{reg_exe_manipulating_windows_services_registry_keys.yml => reg_manipulating_windows_services_registry_keys.yml} (96%) rename detections/{reg_exe_used_to_hide_files_directories_via_registry_keys.yml => reg_used_to_hide_files_or_directories_via_registry_keys.yml} (95%) rename detections/{suspicious_reg_exe_process.yml => suspicious_reg_process.yml} (98%) rename stories/{container_implantation_monitoring_&_investigation.yml => container_implantation_monitoring_and_investigation.yml} (95%) rename stories/{emotet_malware_(dhs_report_ta18_201a).yml => emotet_malware.yml} (97%) rename stories/{router_&_infrastructure_security.yml => router_and_infrastructure_security.yml} (97%) diff --git a/bin/validate.py b/bin/validate.py index 4b9bf045e1..6bd732d387 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -10,12 +10,15 @@ import jsonschema import yaml import sys import argparse +import datetime +import string from os import path def validate_schema(REPO_PATH, type, objects): error = False + errors = [] schema_file = path.join(path.expanduser(REPO_PATH), 'spec/' + type + '.spec.json') @@ -42,73 +45,39 @@ def validate_schema(REPO_PATH, type, objects): try: jsonschema.validate(instance=object, schema=schema) except jsonschema.exceptions.ValidationError as json_ve: - print("ERROR: {0} at:\n\t{1}".format(json.dumps(json_ve.message), manifest_file)) - print("\tAffected Object: {}".format(json.dumps(json_ve.instance))) + errors.append("ERROR: {0} at:\n\t{1}".format(json.dumps(json_ve.message), manifest_file)) error = True if type in objects: objects[type].append(object) else: - objects[type] = [object] + arr = [] + arr.append(object) + objects[type] = arr - return objects, error + return objects, error, errors - - -def validate_object(REPO_PATH, schema_path, manifest_path, verbose, lookups=None, macros=None): - ''' Validate scheme ''' +def validate_objects(REPO_PATH, objects): # uuids uuids = [] + errors = [] - schema_file = path.join(path.expanduser(REPO_PATH), schema_path) + for lookup in objects['lookups']: + lookup_errors = validate_lookups_content(REPO_PATH, "lookups/%s", lookup) - try: - schema = json.loads(open(schema_file, 'rb').read()) - except IOError: - print("ERROR: reading schema file {0}".format(schema_file)) + objects_array = objects['stories'] + objects['detections'] + objects['baselines'] + objects['response_tasks'] + objects['responses'] + for object in objects_array: + validation_errors, uuids = validate_standard_fields(object, uuids) + errors = errors + validation_errors - objects = {} - manifest_files = path.join(path.expanduser(REPO_PATH), manifest_path) + for object in objects['detections']: + errors = errors + validate_detection_search(object) - for manifest_file in glob.glob(manifest_files): - if verbose: - print("processing manifest {0}".format(manifest_file)) + errors = lookup_errors + errors - with open(manifest_file, 'r') as stream: - try: - object = list(yaml.safe_load_all(stream))[0] - except yaml.YAMLError as exc: - print(exc) - print("Error reading {0}".format(manifest_file)) - error = True - continue - - try: - jsonschema.validate(instance=object, schema=schema) - except jsonschema.exceptions.ValidationError as json_ve: - print("ERROR: {0} at:\n\t{1}".format(json.dumps(json_ve.message), manifest_file)) - print("\tAffected Object: {}".format(json.dumps(json_ve.instance))) - error = True - - - - # validate content - if schema_path == 'spec/lookups.spec.json': - lookup_errors = validate_lookups_content(REPO_PATH, "lookups/%s", object, manifest_file) - elif schema_path == 'spec/baselines.spec.json' or schema_path == 'spec/stories.spec.json' or schema_path == 'spec/detections.spec.json': - errors, uuids = validate_standard_fields(object, uuids) - - - #check for duplicate uuids - - - #list errors - for err in baselines_errors: - print("{0} at:\n\t {1}".format(err, baselines_manifest_file)) - - return error + return errors def validate_standard_fields(object, uuids): @@ -116,10 +85,10 @@ def validate_standard_fields(object, uuids): errors = [] if object['id'] == '': - errors.append('ERROR: Blank ID') + errors.append('ERROR: Blank ID for object: %s' % object['name']) if object['id'] in uuids: - errors.append('ERROR: Duplicate UUID found: %s' % object['id']) + errors.append('ERROR: Duplicate UUID found for object: %s' % object['name']) else: uuids.append(object['id']) @@ -128,25 +97,40 @@ def validate_standard_fields(object, uuids): "ERROR: name has trailing spaces: '%s'" % object['name']) + invalidChars = set(string.punctuation.replace("-", "")) + if any(char in invalidChars for char in object['name']): + errors.append('ERROR: No special characters allowed in name for object: %s' % object['name']) + try: object['description'].encode('ascii') except UnicodeEncodeError: - errors.append("ERROR: description not ascii") + errors.append("ERROR: description not ascii for object: %s" % object['name']) if 'how_to_implement' in object: try: object['how_to_implement'].encode('ascii') except UnicodeEncodeError: - errors.append("ERROR: how_to_implement not ascii") + errors.append('ERROR: how_to_implement not ascii for object: %s' % object['name']) + + try: + datetime.datetime.strptime(object['date'], '%Y-%m-%d') + except ValueError: + errors.append("ERROR: Incorrect date format, should be YYYY-MM-DD for object: %s" % object['name']) return errors, uuids -def validate_search(): - pass +def validate_detection_search(object): + errors = [] + + if 'search' in object: + if not str(object['name'].replace('-','_').lower()) in object['search']: + errors.append("ERROR: Missing filter for detection: " + object['name']) + + return errors -def validate_lookups_content(REPO_PATH, lookup_path, lookup, manifest_file): +def validate_lookups_content(REPO_PATH, lookup_path, lookup): errors = [] if 'filename' in lookup: lookup_csv_file = path.join(path.expanduser(REPO_PATH), lookup_path % lookup['filename']) @@ -168,17 +152,26 @@ if __name__ == "__main__": REPO_PATH = args.path verbose = args.verbose - validate_objects = ['macros','lookups','stories','detections','response_tasks','responses','deployments'] + validation_objects = ['macros','lookups','stories','detections','baselines','response_tasks','responses','deployments'] objects = {} schema_error = False + schema_errors = [] - for validation_object in validate_objects: - objects, error = validate_schema(REPO_PATH, validation_object, objects) + for validation_object in validation_objects: + objects, error, errors = validate_schema(REPO_PATH, validation_object, objects) schema_error = schema_error or error + if len(errors) > 0: + schema_errors = schema_errors + errors + validation_errors = validate_objects(REPO_PATH, objects) - if schema_error: + schema_errors = schema_errors + validation_errors + + for schema_error in schema_errors: + print(schema_error) + + if schema_error or len(schema_errors) > 0: sys.exit("Errors found") else: print("No Errors found") diff --git a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml b/detections/attempted_credential_dump_from_registry_via_reg.yml similarity index 96% rename from detections/attempted_credential_dump_from_registry_via_reg_exe.yml rename to detections/attempted_credential_dump_from_registry_via_reg.yml index ebb92d62a8..a662ac96be 100644 --- a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml +++ b/detections/attempted_credential_dump_from_registry_via_reg.yml @@ -1,4 +1,4 @@ -name: Attempted Credential Dump From Registry via Reg.exe +name: Attempted Credential Dump From Registry via Reg id: 14038953-e5f2-4daf-acff-5452062baf03 version: 4 date: '2019-12-02' diff --git a/detections/child_processes_of_spoolsv_exe.yml b/detections/child_processes_of_spoolsv.yml similarity index 97% rename from detections/child_processes_of_spoolsv_exe.yml rename to detections/child_processes_of_spoolsv.yml index 46c9fe162e..ea5b148c83 100644 --- a/detections/child_processes_of_spoolsv_exe.yml +++ b/detections/child_processes_of_spoolsv.yml @@ -1,4 +1,4 @@ -name: Child Processes of Spoolsv.exe +name: Child Processes of Spoolsv id: aa0c4aeb-5b18-41c4-8c07-f1442d7599df version: 3 date: '2020-03-16' diff --git a/detections/create_local_admin_accounts_using_net_exe.yml b/detections/create_local_admin_accounts_using_net.yml similarity index 96% rename from detections/create_local_admin_accounts_using_net_exe.yml rename to detections/create_local_admin_accounts_using_net.yml index 7ccba36e16..c60b3b0d87 100644 --- a/detections/create_local_admin_accounts_using_net_exe.yml +++ b/detections/create_local_admin_accounts_using_net.yml @@ -1,4 +1,4 @@ -name: Create local admin accounts using net.exe +name: Create local admin accounts using net id: b89919ed-fe5f-492c-b139-151bb162040e version: 3 date: '2020-03-16' diff --git a/detections/create_or_delete_windows_shares_using_net_exe.yml b/detections/create_or_delete_windows_shares_using_net.yml similarity index 96% rename from detections/create_or_delete_windows_shares_using_net_exe.yml rename to detections/create_or_delete_windows_shares_using_net.yml index 89f0dec103..7afcb4f9d1 100644 --- a/detections/create_or_delete_windows_shares_using_net_exe.yml +++ b/detections/create_or_delete_windows_shares_using_net.yml @@ -1,4 +1,4 @@ -name: Create or delete windows shares using net.exe +name: Create or delete windows shares using net id: qw9919ed-fe5f-492c-b139-151bb162140e version: 4 date: '2020-01-20' diff --git a/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml b/detections/detect_mshta_running_scripts_in_command_line_arguments.yml similarity index 95% rename from detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml rename to detections/detect_mshta_running_scripts_in_command_line_arguments.yml index 37acfd5d3f..dfff52792a 100644 --- a/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml +++ b/detections/detect_mshta_running_scripts_in_command_line_arguments.yml @@ -1,4 +1,4 @@ -name: Detect mshta.exe running scripts in command-line arguments +name: Detect mshta running scripts in command-line arguments id: b89919ed-fe5f-492c-b139-95dqb161039e version: 2 date: '2018-12-03' diff --git a/detections/detect_oulook_exe_writing_a__zip_file.yml b/detections/detect_oulook_writing_a_zip_file.yml similarity index 98% rename from detections/detect_oulook_exe_writing_a__zip_file.yml rename to detections/detect_oulook_writing_a_zip_file.yml index 3ceea54ef3..2bee25132a 100644 --- a/detections/detect_oulook_exe_writing_a__zip_file.yml +++ b/detections/detect_oulook_writing_a_zip_file.yml @@ -1,4 +1,4 @@ -name: Detect Oulook.exe writing a .zip file +name: Detect Oulook writing a zip file id: a51bfe1a-94f0-4822-b1e4-16ae10145893 version: 2 date: '2020-03-16' diff --git a/detections/detect_path_interception_by_creation_of_program_exe.yml b/detections/detect_path_interception_by_creation_of_program.yml similarity index 96% rename from detections/detect_path_interception_by_creation_of_program_exe.yml rename to detections/detect_path_interception_by_creation_of_program.yml index f9eb93a5a3..4c17363954 100644 --- a/detections/detect_path_interception_by_creation_of_program_exe.yml +++ b/detections/detect_path_interception_by_creation_of_program.yml @@ -1,4 +1,4 @@ -name: Detect Path Interception By Creation Of program.exe +name: Detect Path Interception By Creation Of program id: c77162d3-f93c-45cc-80c8-22f6v5264g9f version: 2 date: '2018-11-15' diff --git a/detections/detect_prohibited_applications_spawning_cmd_exe.yml b/detections/detect_prohibited_applications_spawning_cmd.yml similarity index 96% rename from detections/detect_prohibited_applications_spawning_cmd_exe.yml rename to detections/detect_prohibited_applications_spawning_cmd.yml index 137e07b6f6..0bc5b3158f 100644 --- a/detections/detect_prohibited_applications_spawning_cmd_exe.yml +++ b/detections/detect_prohibited_applications_spawning_cmd.yml @@ -1,4 +1,4 @@ -name: Detect Prohibited Applications Spawning cmd.exe +name: Detect Prohibited Applications Spawning cmd id: dcfd6b40-42f9-469d-a433-2e53f7486664 version: 3 date: '2020-02-03' diff --git a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_to_launch_script_interpreters.yml similarity index 96% rename from detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml rename to detections/detect_use_of_cmd_to_launch_script_interpreters.yml index 09fb80ca2f..c4c2ade900 100644 --- a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_to_launch_script_interpreters.yml @@ -1,4 +1,4 @@ -name: Detect Use of cmd.exe to Launch Script Interpreters +name: Detect Use of cmd to Launch Script Interpreters id: b89919ed-fe5f-492c-b139-95dbb162039e version: 3 date: '2020-03-02' diff --git a/detections/hiding_files_and_directories_with_attrib_exe.yml b/detections/hiding_files_and_directories_with_attrib.yml similarity index 96% rename from detections/hiding_files_and_directories_with_attrib_exe.yml rename to detections/hiding_files_and_directories_with_attrib.yml index 50c23b7109..a3636c8bd0 100644 --- a/detections/hiding_files_and_directories_with_attrib_exe.yml +++ b/detections/hiding_files_and_directories_with_attrib.yml @@ -1,4 +1,4 @@ -name: Hiding Files And Directories With Attrib.exe +name: Hiding Files And Directories With Attrib id: c77162d3-f93c-45cc-80c8-22f6b5264g9f version: 3 date: '2020-03-16' diff --git a/detections/sc_exe_manipulating_windows_services.yml b/detections/manipulating_windows_services_with_sc.yml similarity index 97% rename from detections/sc_exe_manipulating_windows_services.yml rename to detections/manipulating_windows_services_with_sc.yml index cd2e7fd2b2..b46348d23a 100644 --- a/detections/sc_exe_manipulating_windows_services.yml +++ b/detections/manipulating_windows_services_with_sc.yml @@ -1,4 +1,4 @@ -name: Sc.exe Manipulating Windows Services +name: Manipulating Windows Services eith sc id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d version: 2 date: '2019-02-27' diff --git a/detections/reg_exe_manipulating_windows_services_registry_keys.yml b/detections/reg_manipulating_windows_services_registry_keys.yml similarity index 96% rename from detections/reg_exe_manipulating_windows_services_registry_keys.yml rename to detections/reg_manipulating_windows_services_registry_keys.yml index 3d05263345..cd03cb4e17 100644 --- a/detections/reg_exe_manipulating_windows_services_registry_keys.yml +++ b/detections/reg_manipulating_windows_services_registry_keys.yml @@ -1,4 +1,4 @@ -name: Reg.exe Manipulating Windows Services Registry Keys +name: Reg Manipulating Windows Services Registry Keys id: 8470d755-0c13-45b3-bd63-387a373c10cf version: 2 date: '2019-03-01' diff --git a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml b/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml similarity index 95% rename from detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml rename to detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml index d0540cdeef..7fc992d139 100644 --- a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml +++ b/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml @@ -1,4 +1,4 @@ -name: Reg.exe used to hide files/directories via registry keys +name: Reg used to hide files or directories via registry keys id: c77162d3-f93c-45cc-80c8-22f6b5264x9f version: 2 date: '2019-02-27' diff --git a/detections/suspicious_reg_exe_process.yml b/detections/suspicious_reg_process.yml similarity index 98% rename from detections/suspicious_reg_exe_process.yml rename to detections/suspicious_reg_process.yml index 1d3b977833..9d231429d0 100644 --- a/detections/suspicious_reg_exe_process.yml +++ b/detections/suspicious_reg_process.yml @@ -1,4 +1,4 @@ -name: Suspicious Reg.exe Process +name: Suspicious Reg Process id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 version: 3 date: '2020-03-16' diff --git a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml index 01e6d9dece..f43e42d0e9 100644 --- a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml +++ b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml @@ -1,4 +1,4 @@ -name: Amazon EKS Kubernetes activity by src_ip +name: Amazon EKS Kubernetes activity by src ip id: a636cca4-7434-4a15-a278-c70734938e39 version: 1 date: '2020-04-13' diff --git a/response_tasks/gcp_kubernetes_activity_by_src_ip.yml b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml index a2b8d0f4a1..c0b890a4f6 100644 --- a/response_tasks/gcp_kubernetes_activity_by_src_ip.yml +++ b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml @@ -1,4 +1,4 @@ -name: GCP Kubernetes activity by src_ip +name: GCP Kubernetes activity by src ip id: c00e7626-92cc-4e06-9a51-b6db0a50bd1f version: 1 date: '2020-04-13' diff --git a/response_tasks/get_web_session_information_via_session_id.yml b/response_tasks/get_web_session_information_via_session_id.yml index 1828cc124a..c561f6dc29 100644 --- a/response_tasks/get_web_session_information_via_session_id.yml +++ b/response_tasks/get_web_session_information_via_session_id.yml @@ -1,4 +1,4 @@ -name: Get Web Session Information via session_id +name: Get Web Session Information via session id id: bc91a8cf-35e7-4bb2-1120-e756cc06fd89 version: 1 date: '2018-10-08' diff --git a/response_tasks/investigate_network_traffic_from_src_ip.yml b/response_tasks/investigate_network_traffic_from_src_ip.yml index 7eeebca9c3..87bcc2731c 100644 --- a/response_tasks/investigate_network_traffic_from_src_ip.yml +++ b/response_tasks/investigate_network_traffic_from_src_ip.yml @@ -1,4 +1,4 @@ -name: Investigate Network Traffic From src_ip +name: Investigate Network Traffic From src ip id: 9df9ca9c-a02b-4f48-9eba-0bac55179050 version: 1 date: '2018-06-15' diff --git a/response_tasks/investigate_web_activity_from_src_ip.yml b/response_tasks/investigate_web_activity_from_src_ip.yml index 5ff7313e90..c151ae28c3 100644 --- a/response_tasks/investigate_web_activity_from_src_ip.yml +++ b/response_tasks/investigate_web_activity_from_src_ip.yml @@ -1,4 +1,4 @@ -name: Investigate Web Activity From src_ip +name: Investigate Web Activity From src ip id: 2f5b960b-71df-49c0-affc-74992ce60e45 version: 1 date: '2018-06-15' diff --git a/stories/container_implantation_monitoring_&_investigation.yml b/stories/container_implantation_monitoring_and_investigation.yml similarity index 95% rename from stories/container_implantation_monitoring_&_investigation.yml rename to stories/container_implantation_monitoring_and_investigation.yml index df19f74acf..4b2d8ce07f 100644 --- a/stories/container_implantation_monitoring_&_investigation.yml +++ b/stories/container_implantation_monitoring_and_investigation.yml @@ -1,4 +1,4 @@ -name: Container Implantation Monitoring & Investigation +name: Container Implantation Monitoring and Investigation id: aa0e28b1-0521-4b6f-9d2a-7b87e34af246 version: 1 date: '2020-02-20' diff --git a/stories/emotet_malware_(dhs_report_ta18_201a).yml b/stories/emotet_malware.yml similarity index 97% rename from stories/emotet_malware_(dhs_report_ta18_201a).yml rename to stories/emotet_malware.yml index d3d50ad719..17a8af6d1b 100644 --- a/stories/emotet_malware_(dhs_report_ta18_201a).yml +++ b/stories/emotet_malware.yml @@ -1,4 +1,4 @@ -name: Emotet Malware (DHS Report TA18-201A) +name: Emotet Malware id: bb9f5ed2-916e-4364-bb6d-91c310efcf52 version: 1 date: '2020-01-27' diff --git a/stories/router_&_infrastructure_security.yml b/stories/router_and_infrastructure_security.yml similarity index 97% rename from stories/router_&_infrastructure_security.yml rename to stories/router_and_infrastructure_security.yml index 486671f861..ed86080e89 100644 --- a/stories/router_&_infrastructure_security.yml +++ b/stories/router_and_infrastructure_security.yml @@ -1,4 +1,4 @@ -name: Router & Infrastructure Security +name: Router and Infrastructure Security id: 91c676cf-0b23-438d-abee-f6335e177e77 version: 1 date: '2017-09-12' From 442a575e1d02b2c846d81cce0d4b7f5e9e8f8d2e Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 30 Apr 2020 15:51:16 +0200 Subject: [PATCH 08/93] WIP validate script --- baselines/baseline_of_api_calls_per_user_arn.yml | 4 ++-- ...of_excessive_aws_instances_launched_by_user___mltk.yml | 4 ++-- ..._excessive_aws_instances_terminated_by_user___mltk.yml | 4 ++-- baselines/baseline_of_network_acl_activity_by_arn.yml | 4 ++-- .../baseline_of_s3_bucket_deletion_activity_by_arn.yml | 4 ++-- baselines/baseline_of_security_group_activity_by_arn.yml | 4 ++-- .../create_a_list_of_approved_aws_service_accounts.yml | 4 ++-- ...viously_seen_api_call_per_user_roles_in_cloudtrail.yml | 4 ++-- baselines/previously_seen_aws_cross_account_activity.yml | 4 ++-- .../previously_seen_aws_provisioning_activity_sources.yml | 4 ++-- baselines/previously_seen_aws_regions.yml | 4 ++-- baselines/previously_seen_ec2_amis.yml | 4 ++-- baselines/previously_seen_ec2_instance_types.yml | 4 ++-- baselines/previously_seen_ec2_launches_by_user.yml | 4 ++-- baselines/previously_seen_ec2_modifications_by_user.yml | 4 ++-- baselines/previously_seen_users_in_cloudtrail.yml | 4 ++-- baselines/update_previously_seen_users_in_cloudtrail.yml | 4 ++-- bin/validate.py | 8 +++++--- .../abnormally_high_aws_instances_launched_by_user.yml | 4 ++-- ...ormally_high_aws_instances_launched_by_user___mltk.yml | 4 ++-- .../abnormally_high_aws_instances_terminated_by_user.yml | 4 ++-- ...mally_high_aws_instances_terminated_by_user___mltk.yml | 4 ++-- .../amazon_eks_kubernetes_cluster_scan_detection.yml | 2 +- detections/amazon_eks_kubernetes_pod_scan_detection.yml | 2 +- .../attempt_to_add_certificate_to_untrusted_store.yml | 3 ++- detections/attempt_to_stop_security_service.yml | 2 +- ...aws_cloud_provisioning_from_previously_unseen_city.yml | 6 +++--- ..._cloud_provisioning_from_previously_unseen_country.yml | 6 +++--- ...oud_provisioning_from_previously_unseen_ip_address.yml | 6 +++--- ...s_cloud_provisioning_from_previously_unseen_region.yml | 6 +++--- ...ss_account_activity_from_previously_unseen_account.yml | 4 ++-- ...rk_access_control_list_created_with_all_open_ports.yml | 4 ++-- detections/aws_network_access_control_list_deleted.yml | 4 ++-- detections/batch_file_write_to_system32.yml | 2 +- ...compute_instance_created_by_previously_unseen_user.yml | 2 +- detections/deleting_shadow_copies.yml | 3 ++- detections/detect_api_activity_from_users_without_mfa.yml | 4 ++-- ...ct_attackers_scanning_for_vulnerable_jboss_servers.yml | 2 +- ...detect_aws_api_activities_from_unapproved_accounts.yml | 3 ++- .../detect_aws_console_login_by_user_from_new_city.yml | 2 +- .../detect_aws_console_login_by_user_from_new_country.yml | 2 +- .../detect_aws_console_login_by_user_from_new_region.yml | 2 +- ...ns_requests_to_phishing_sites_leveraging_evilginx2.yml | 2 +- .../detect_excessive_account_lockouts_from_endpoint.yml | 2 +- detections/detect_excessive_user_account_lockouts.yml | 2 +- ...etect_hosts_connecting_to_dynamic_domain_providers.yml | 3 ++- detections/detect_large_outbound_icmp_packets.yml | 2 +- detections/detect_long_dns_txt_record_response.yml | 2 +- ...detect_malicious_requests_to_exploit_jboss_servers.yml | 2 +- .../detect_mimikatz_via_powershell_and_eventcode_4703.yml | 2 +- ...ct_mshta_running_scripts_in_command_line_arguments.yml | 2 +- detections/detect_new_api_calls_from_user_roles.yml | 6 +++--- detections/detect_new_local_admin_account.yml | 2 +- detections/detect_new_login_attempts_to_routers.yml | 2 +- detections/detect_new_open_s3_buckets.yml | 4 ++-- detections/detect_new_user_aws_console_login.yml | 4 ++-- .../detect_path_interception_by_creation_of_program.yml | 2 +- ...es_used_for_system_network_configuration_discovery.yml | 2 +- .../detect_prohibited_applications_spawning_cmd.yml | 2 +- detections/detect_psexec_with_accepteula_flag.yml | 2 +- detections/detect_s3_access_from_a_new_ip.yml | 2 +- detections/detect_spike_in_aws_api_activity.yml | 4 ++-- ...ct_spike_in_blocked_outbound_traffic_from_your_aws.yml | 1 + detections/detect_spike_in_network_acl_activity.yml | 4 ++-- detections/detect_spike_in_s3_bucket_deletion.yml | 3 ++- detections/detect_spike_in_security_group_activity.yml | 4 ++-- detections/detect_unauthorized_assets_by_mac_address.yml | 2 +- detections/detect_usb_device_insertion.yml | 2 +- .../detect_use_of_cmd_to_launch_script_interpreters.yml | 3 ++- .../detect_web_traffic_to_dynamic_domain_providers.yml | 3 ++- detections/detection_of_dns_tunnels.yml | 2 +- detections/detection_of_tools_built_by_nirsoft.yml | 2 +- detections/disabling_remote_user_account_control.yml | 2 +- .../ec2_instance_modified_with_previously_unseen_user.yml | 4 ++-- .../ec2_instance_started_in_previously_unseen_region.yml | 4 ++-- .../ec2_instance_started_with_previously_unseen_ami.yml | 4 ++-- ...tance_started_with_previously_unseen_instance_type.yml | 4 ++-- .../ec2_instance_started_with_previously_unseen_user.yml | 4 ++-- detections/email_attachments_with_lots_of_spaces.yml | 2 +- ...email_servers_sending_high_volume_traffic_to_hosts.yml | 2 +- detections/excessive_dns_failures.yml | 2 +- detections/execution_of_file_with_multiple_extensions.yml | 2 +- .../execution_of_file_with_spaces_before_extension.yml | 2 +- ...tended_period_without_successful_netbackup_backups.yml | 2 +- detections/file_with_samsam_extension.yml | 2 +- detections/first_time_seen_running_windows_service.yml | 2 +- detections/gcp_kubernetes_cluster_scan_detection.yml | 2 +- ...g_high_volume_of_network_traffic_from_email_server.yml | 2 +- detections/identify_new_user_accounts.yml | 2 +- detections/large_volume_of_dns_any_queries.yml | 2 +- detections/macos___re_opened_applications.yml | 3 ++- ...l_process___connect_to_internet_with_hidden_window.yml | 2 +- .../malicious_powershell_process___encoded_command.yml | 2 +- ...cious_powershell_process___execution_policy_bypass.yml | 2 +- ...ocess___multiple_suspicious_command_line_arguments.yml | 3 ++- detections/manipulating_windows_services_with_sc.yml | 4 ++-- detections/monitor_dns_for_brand_abuse.yml | 2 +- detections/monitor_email_for_brand_abuse.yml | 2 +- detections/monitor_registry_keys_for_print_monitors.yml | 2 +- detections/monitor_web_traffic_for_brand_abuse.yml | 2 +- detections/no_windows_updates_in_a_time_frame.yml | 2 +- detections/open_redirect_in_splunk_web.yml | 2 +- detections/osquery_pack___coldroot_detection.yml | 2 +- detections/overwriting_accessibility_binaries.yml | 2 +- detections/processes_created_by_netsh.yml | 3 ++- detections/processes_launching_netsh.yml | 3 ++- detections/processes_tapping_keyboard_events.yml | 2 +- detections/prohibited_network_traffic_allowed.yml | 2 +- detections/prohibited_software_on_endpoint.yml | 2 +- detections/protocol_or_port_mismatch.yml | 2 +- .../protocols_passing_authentication_in_cleartext.yml | 2 +- .../reg_manipulating_windows_services_registry_keys.yml | 2 +- ...sed_to_hide_files_or_directories_via_registry_keys.yml | 2 +- detections/registry_keys_for_creating_shim_databases.yml | 2 +- detections/registry_keys_used_for_persistence.yml | 2 +- .../registry_keys_used_for_privilege_escalation.yml | 2 +- detections/remote_desktop_network_bruteforce.yml | 2 +- detections/remote_process_instantiation_via_wmi.yml | 2 +- detections/remote_registry_key_modifications.yml | 2 +- detections/remote_wmi_command_attempt.yml | 2 +- detections/rundll_loading_dll_by_ordinal.yml | 3 ++- detections/samsam_test_file_write.yml | 2 +- .../scheduled_tasks_used_in_badrabbit_ransomware.yml | 2 +- detections/schtasks_used_for_forcing_a_reboot.yml | 2 +- detections/shim_database_file_creation.yml | 2 +- ...m_database_installation_with_suspicious_parameters.yml | 3 ++- detections/short_lived_windows_accounts.yml | 2 +- detections/single_letter_process_on_endpoint.yml | 3 ++- detections/spectre_and_meltdown_vulnerable_systems.yml | 3 ++- detections/splunk_enterprise_information_disclosure.yml | 2 +- detections/sql_injection_with_long_urls.yml | 2 +- detections/suspicious_email___uba_anomaly.yml | 3 ++- detections/suspicious_file_write.yml | 2 +- detections/suspicious_java_classes.yml | 1 + detections/suspicious_wevtutil_usage.yml | 3 ++- .../suspicious_writes_to_system_volume_information.yml | 2 +- detections/suspicious_writes_to_windows_recycle_bin.yml | 2 +- .../system_processes_run_from_unexpected_locations.yml | 2 +- detections/tor_traffic.yml | 3 ++- detections/unsuccessful_netbackup_backups.yml | 1 + detections/unusually_long_command_line___mltk.yml | 2 +- detections/unusually_long_content_type_length.yml | 4 ++-- detections/usn_journal_deletion.yml | 2 +- detections/web_fraud___account_harvesting.yml | 4 ++-- detections/web_fraud___anomalous_user_clickspeed.yml | 3 ++- .../web_fraud___password_sharing_across_accounts.yml | 3 ++- detections/web_servers_executing_suspicious_processes.yml | 2 +- detections/windows_event_log_cleared.yml | 2 +- detections/windows_hosts_file_modification.yml | 2 +- detections/wmi_permanent_event_subscription.yml | 2 +- detections/wmi_permanent_event_subscription___sysmon.yml | 2 +- detections/wmi_temporary_event_subscription.yml | 2 +- macros/cloudtrail.yml | 3 +++ .../aws_investigate_user_activities_by_accesskeyid.yml | 2 +- response_tasks/aws_investigate_user_activities_by_arn.yml | 2 +- .../aws_investigate_user_activities_by_source_user.yml | 2 +- response_tasks/get_all_aws_activity_from_city.yml | 2 +- response_tasks/get_all_aws_activity_from_country.yml | 2 +- response_tasks/get_all_aws_activity_from_ip_address.yml | 2 +- response_tasks/get_all_aws_activity_from_region.yml | 2 +- response_tasks/get_ec2_launch_details.yml | 2 +- .../investigate_aws_activities_via_region_name.yml | 2 +- .../investigate_aws_user_activities_by_user_field.yml | 2 +- spec/baselines.spec.json | 2 +- 164 files changed, 238 insertions(+), 210 deletions(-) create mode 100644 macros/cloudtrail.yml diff --git a/baselines/baseline_of_api_calls_per_user_arn.yml b/baselines/baseline_of_api_calls_per_user_arn.yml index 50a7149394..70a7a6e837 100644 --- a/baselines/baseline_of_api_calls_per_user_arn.yml +++ b/baselines/baseline_of_api_calls_per_user_arn.yml @@ -10,11 +10,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn +search: '`cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, - avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count + avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count' tags: analytics_story: - AWS User Monitoring diff --git a/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml b/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml index e5d126b7e8..d5bdab4b81 100644 --- a/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml +++ b/baselines/baseline_of_excessive_aws_instances_launched_by_user___mltk.yml @@ -22,9 +22,9 @@ how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or lat More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.' author: Jason Brewer, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` +search: '`cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | - fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 + fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1' tags: analytics_story: - Cloud Cryptomining diff --git a/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml b/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml index 094bc80954..d342dddd11 100644 --- a/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml +++ b/baselines/baseline_of_excessive_aws_instances_terminated_by_user___mltk.yml @@ -23,9 +23,9 @@ how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or lat More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`.' author: Jason Brewer, Splunk -search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` +search: '`cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user - | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 + | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1' tags: analytics_story: - Suspicious AWS EC2 Activities diff --git a/baselines/baseline_of_network_acl_activity_by_arn.yml b/baselines/baseline_of_network_acl_activity_by_arn.yml index 2e01f2fff2..8d815ed92a 100644 --- a/baselines/baseline_of_network_acl_activity_by_arn.yml +++ b/baselines/baseline_of_network_acl_activity_by_arn.yml @@ -10,12 +10,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail `network_acl_events` | spath output=arn path=userIdentity.arn +search: '`cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats - count + count' tags: analytics_story: - AWS Network ACL Activity diff --git a/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml b/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml index d6a8283f9d..1b0075050d 100644 --- a/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml +++ b/baselines/baseline_of_s3_bucket_deletion_activity_by_arn.yml @@ -10,11 +10,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventName=DeleteBucket | spath output=arn path=userIdentity.arn +search: '`cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, - avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count + avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count' tags: analytics_story: - Suspicious AWS S3 Activities diff --git a/baselines/baseline_of_security_group_activity_by_arn.yml b/baselines/baseline_of_security_group_activity_by_arn.yml index d3c29ad60a..1c0b705c71 100644 --- a/baselines/baseline_of_security_group_activity_by_arn.yml +++ b/baselines/baseline_of_security_group_activity_by_arn.yml @@ -10,12 +10,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail `security_group_api_calls` | spath output=arn path=userIdentity.arn +search: '`cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats - count + count' tags: analytics_story: - AWS User Monitoring diff --git a/baselines/create_a_list_of_approved_aws_service_accounts.yml b/baselines/create_a_list_of_approved_aws_service_accounts.yml index 8da02c5ee3..ed92b277d3 100644 --- a/baselines/create_a_list_of_approved_aws_service_accounts.yml +++ b/baselines/create_a_list_of_approved_aws_service_accounts.yml @@ -11,9 +11,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail errorCode=success | rename userName as identity +search: '`cloudtrail` errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count - by identity | table identity | outputlookup aws_service_accounts | stats count + by identity | table identity | outputlookup aws_service_accounts | stats count' tags: analytics_story: - AWS User Monitoring diff --git a/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml b/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml index 22784a9535..ac87b6efbc 100644 --- a/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml +++ b/baselines/previously_seen_api_call_per_user_roles_in_cloudtrail.yml @@ -12,9 +12,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole +search: '`cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName - | outputlookup previously_seen_api_calls_from_user_roles | stats count + | outputlookup previously_seen_api_calls_from_user_roles | stats count' tags: analytics_story: - AWS User Monitoring diff --git a/baselines/previously_seen_aws_cross_account_activity.yml b/baselines/previously_seen_aws_cross_account_activity.yml index 0cf796b7f8..af146aff93 100644 --- a/baselines/previously_seen_aws_cross_account_activity.yml +++ b/baselines/previously_seen_aws_cross_account_activity.yml @@ -10,12 +10,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId +search: '`cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats - count + count' tags: analytics_story: - AWS Cross Account Activity diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml index 32af3f9484..0ebb6bc4a8 100644 --- a/baselines/previously_seen_aws_provisioning_activity_sources.yml +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -9,10 +9,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv - | stats count + | stats count' tags: analytics_story: - AWS Suspicious Provisioning Activities diff --git a/baselines/previously_seen_aws_regions.yml b/baselines/previously_seen_aws_regions.yml index 216d3f2226..7e6e55e3a2 100644 --- a/baselines/previously_seen_aws_regions.yml +++ b/baselines/previously_seen_aws_regions.yml @@ -10,9 +10,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest +search: '`cloudtrail` StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv - | stats count + | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_ec2_amis.yml b/baselines/previously_seen_ec2_amis.yml index 9898eaf0f3..7f46af7532 100644 --- a/baselines/previously_seen_ec2_amis.yml +++ b/baselines/previously_seen_ec2_amis.yml @@ -8,10 +8,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename +search: '`cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv - | stats count + | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_ec2_instance_types.yml b/baselines/previously_seen_ec2_instance_types.yml index 7772799582..6859d3c5b3 100644 --- a/baselines/previously_seen_ec2_instance_types.yml +++ b/baselines/previously_seen_ec2_instance_types.yml @@ -7,10 +7,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename +search: '`cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup - previously_seen_ec2_instance_types.csv | stats count + previously_seen_ec2_instance_types.csv | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_ec2_launches_by_user.yml b/baselines/previously_seen_ec2_launches_by_user.yml index c78ab03694..5d2cdf3efd 100644 --- a/baselines/previously_seen_ec2_launches_by_user.yml +++ b/baselines/previously_seen_ec2_launches_by_user.yml @@ -8,9 +8,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename +search: '`cloudtrail` eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime - by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count + by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_ec2_modifications_by_user.yml b/baselines/previously_seen_ec2_modifications_by_user.yml index 84c8457edc..83ea4ca580 100644 --- a/baselines/previously_seen_ec2_modifications_by_user.yml +++ b/baselines/previously_seen_ec2_modifications_by_user.yml @@ -8,10 +8,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail `ec2_modification_api_calls` errorCode=success | +search: '`cloudtrail` `ec2_modification_api_calls` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats - count + count' tags: analytics_story: - Unusual AWS EC2 Modifications diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml index a28efb9a54..091ef3fa9a 100644 --- a/baselines/previously_seen_users_in_cloudtrail.yml +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -11,11 +11,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. author: Jason Brewer, Splunk -search: sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn +search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv - | stats count + | stats count' tags: analytics_story: - Suspicious AWS Login Activities diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml index 75266587b0..ac4399e7e6 100644 --- a/baselines/update_previously_seen_users_in_cloudtrail.yml +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -10,12 +10,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. author: Jason Brewer, Splunk -search: sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn +search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region - Country | outputlookup previously_seen_users_console_logins.csv + Country | outputlookup previously_seen_users_console_logins.csv' tags: analytics_story: - Suspicious AWS Login Activities diff --git a/bin/validate.py b/bin/validate.py index 6bd732d387..a8ef495b06 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -123,9 +123,11 @@ def validate_standard_fields(object, uuids): def validate_detection_search(object): errors = [] - if 'search' in object: - if not str(object['name'].replace('-','_').lower()) in object['search']: - errors.append("ERROR: Missing filter for detection: " + object['name']) + if not '_filter' in object['search']: + errors.append("ERROR: Missing filter for detection: " + object['name']) + + if any(x in object['search'] for x in ['eventtype=', 'sourcetype=', 'source=', 'index=']): + errors.append("ERROR: Use source macro instead of eventtype, sourcetype, source or index in detection: " + object['name']) return errors diff --git a/detections/abnormally_high_aws_instances_launched_by_user.yml b/detections/abnormally_high_aws_instances_launched_by_user.yml index 635eb719d3..bb944fdaeb 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user.yml @@ -10,14 +10,14 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | bucket +search: '`cloudtrail` eventName=RunInstances errorCode=success | bucket span=10m _time | stats count AS instances_launched by _time userName | eventstats avg(instances_launched) as total_launched_avg, stdev(instances_launched) as total_launched_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_launched > total_launched_avg+(total_launched_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m") | eval num_standard_deviations_away = round(abs(instances_launched - total_launched_avg) / total_launched_stdev, 2) | table _time, userName, instances_launched, num_standard_deviations_away, - total_launched_avg, total_launched_stdev + total_launched_avg, total_launched_stdev | `abnormally_high_aws_instances_launched_by_user_filter`' known_false_positives: Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a diff --git a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml index f1513b4a7a..1904cf3d98 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml @@ -10,10 +10,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Jason Brewer, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` +search: '`cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as - isOutlier | where isOutlier=1 + isOutlier | where isOutlier=1' known_false_positives: Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a diff --git a/detections/abnormally_high_aws_instances_terminated_by_user.yml b/detections/abnormally_high_aws_instances_terminated_by_user.yml index 83a02b9a46..72bcf4c47a 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user.yml @@ -10,7 +10,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success | +search: '`cloudtrail` eventName=TerminateInstances errorCode=success | bucket span=10m _time | stats count AS instances_terminated by _time userName | eventstats avg(instances_terminated) as total_terminations_avg, stdev(instances_terminated) as total_terminations_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_terminated @@ -18,7 +18,7 @@ search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success isOutlier=1 AND _time >= relative_time(now(), "-10m@m")| eval num_standard_deviations_away = round(abs(instances_terminated - total_terminations_avg) / total_terminations_stdev, 2) |table _time, userName, instances_terminated, num_standard_deviations_away, total_terminations_avg, - total_terminations_stdev + total_terminations_stdev | `abnormally_high_aws_instances_terminated_by_user_filter`' known_false_positives: Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted diff --git a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml index d367aa5a6a..61c2f9f259 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml @@ -10,10 +10,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Jason Brewer, Splunk -search: sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` +search: '`cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" - as isOutlier | where isOutlier=1 + as isOutlier | where isOutlier=1' known_false_positives: Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a diff --git a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml index 693fd5fba9..77fd43238e 100644 --- a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml @@ -15,7 +15,7 @@ search: sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" u max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - |`kubernetes_aws_scan_fingerprint_detection` + | `amazon_eks_kubernetes_cluster_scan_detection_filter` known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. tags: diff --git a/detections/amazon_eks_kubernetes_pod_scan_detection.yml b/detections/amazon_eks_kubernetes_pod_scan_detection.yml index 7b01844fa0..22d32937cf 100644 --- a/detections/amazon_eks_kubernetes_pod_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_pod_scan_detection.yml @@ -16,7 +16,7 @@ search: sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" v sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_detection` + | `security_content_ctime(firstTime)` | `amazon_eks_kubernetes_pod_scan_detection_filter` known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. tags: diff --git a/detections/attempt_to_add_certificate_to_untrusted_store.yml b/detections/attempt_to_add_certificate_to_untrusted_store.yml index 7d3a299839..9819bbd8d6 100644 --- a/detections/attempt_to_add_certificate_to_untrusted_store.yml +++ b/detections/attempt_to_add_certificate_to_untrusted_store.yml @@ -14,7 +14,8 @@ author: Rico Valdez, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process - Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' + Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + | `attempt_to_add_certificate_to_untrusted_store_filter`' known_false_positives: There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. diff --git a/detections/attempt_to_stop_security_service.yml b/detections/attempt_to_stop_security_service.yml index 5a7e92b5a0..313c00599b 100644 --- a/detections/attempt_to_stop_security_service.yml +++ b/detections/attempt_to_stop_security_service.yml @@ -23,7 +23,7 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as stop *" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |lookup security_services_lookup service as process OUTPUTNEW category, description - | search category=security' + | search category=security | `attempt_to_stop_security_service_filter`' known_false_positives: None identified. Attempts to disable security-related services should be identified and understood. tags: diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml index 8d23d421a1..aadf01938f 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml @@ -13,8 +13,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search City=* [search sourcetype=aws:cloudtrail (eventName=Run* +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search City=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) @@ -23,7 +23,7 @@ search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iploca as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, - errorCode + errorCode | `aws_cloud_provisioning_from_previously_unseen_city_filter`' known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching within, plus what is\ diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml index a7496c0c60..c6e02cc7c4 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml @@ -13,8 +13,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search Country=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) @@ -23,7 +23,7 @@ search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iploca as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCountry=1 | table Country] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, - user, src_ip, Country, eventName, errorCode + user, src_ip, Country, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_country_filter`' known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching over plus what is stored\ diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml index 1d9b808d10..5b061a16c6 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml @@ -13,8 +13,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search Country=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) @@ -23,7 +23,7 @@ search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iploca as firstTime max(lastTime) as lastTime by sourceIPAddress | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | table sourceIPAddress] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table - _time, user, src_ip, eventName, errorCode + _time, user, src_ip, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_ip_address_filter`' known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching within, plus what is\ diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml index 69511b9777..eb4c410c9f 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml @@ -13,8 +13,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Region=* [search sourcetype=aws:cloudtrail (eventName=Run* +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search Region=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) @@ -23,7 +23,7 @@ search: sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iploca as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newRegion=1 | table Region] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, - src_ip, Region, eventName, errorCode + src_ip, Region, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_region_filter`' known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching within, plus what is\ diff --git a/detections/aws_cross_account_activity_from_previously_unseen_account.yml b/detections/aws_cross_account_activity_from_previously_unseen_account.yml index dbd1b491a4..de8bd5afc5 100644 --- a/detections/aws_cross_account_activity_from_previously_unseen_account.yml +++ b/detections/aws_cross_account_activity_from_previously_unseen_account.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId +search: '`cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity | multireport @@ -28,7 +28,7 @@ search: sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requesting as lastTime values(sharedEventID) as sharedEventID, values(requestingARN) as src_user, values(responseElements.assumedRoleUser.arn) as dest_user by _time, requestingAccountId, requestedAccountId, accessKeyId] | table _time, firstTime, lastTime, src_user, requestingAccountId, - dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID + dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID | `aws_cross_account_activity_from_previously_unseen_account_filter`' known_false_positives: Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. diff --git a/detections/aws_network_access_control_list_created_with_all_open_ports.yml b/detections/aws_network_access_control_list_created_with_all_open_ports.yml index b8bf405ece..76a47e39f9 100644 --- a/detections/aws_network_access_control_list_created_with_all_open_ports.yml +++ b/detections/aws_network_access_control_list_created_with_all_open_ports.yml @@ -10,11 +10,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventName=CreateNetworkAclEntry | mvexpand requestParameters +search: '`cloudtrail` eventName=CreateNetworkAclEntry | mvexpand requestParameters | mvexpand responseElements | search requestParameters.portRange.from=1024 requestParameters.portRange.to=65535 requestParameters.ruleAction=allow | rename userIdentity.arn as arn | rename requestParameters.networkAclId as networkAclId | table _time aws_account_id src userName arn networkAclId requestParameters.* - responseElements.* + responseElements.* | `aws_network_access_control_list_created_with_all_open_ports_filter`' known_false_positives: It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. diff --git a/detections/aws_network_access_control_list_deleted.yml b/detections/aws_network_access_control_list_deleted.yml index 4d2c7e873a..ca086d633c 100644 --- a/detections/aws_network_access_control_list_deleted.yml +++ b/detections/aws_network_access_control_list_deleted.yml @@ -13,10 +13,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventName=DeleteNetworkAcl|rename userIdentity.arn +search: '`cloudtrail` eventName=DeleteNetworkAcl|rename userIdentity.arn as arn | stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) values(errorCode) values(userAgent) values(userIdentity.*) by src userName arn eventName - | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `aws_network_access_control_list_deleted_filter`' known_false_positives: It's possible that a user has legitimately deleted a network ACL. tags: diff --git a/detections/batch_file_write_to_system32.yml b/detections/batch_file_write_to_system32.yml index 3930ca0474..d79d0cfd24 100644 --- a/detections/batch_file_write_to_system32.yml +++ b/detections/batch_file_write_to_system32.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Filesystem.user) as user from datamodel=Endpoint.Filesystem by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_path=*system32* - AND file_extension=.bat' + AND file_extension=.bat | `batch_file_write_to_system32_filter`' known_false_positives: It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the diff --git a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml index 2c482d2064..588d8bde65 100644 --- a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml +++ b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` earliest(_time) as firstTime, | multireport [| table src_user, firstTime, lastTime | outputlookup previously_seen_cloud_compute_creations_by_user | where fact=fiction][| eval new_user=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_creations_by_user_search_window_begin_offset`), 1, 0) | where new_user=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] - | table src_user, dest, firstTime, lastTime' + | table src_user, dest, firstTime, lastTime | `cloud_compute_instance_created_by_previously_unseen_user_filter`' known_false_positives: It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. diff --git a/detections/deleting_shadow_copies.yml b/detections/deleting_shadow_copies.yml index e652ccec14..cf59b4e42f 100644 --- a/detections/deleting_shadow_copies.yml +++ b/detections/deleting_shadow_copies.yml @@ -17,7 +17,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=vssadmin.exe OR Processes.process_name=wmic.exe) by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | search process=*delete* AND process=*shadow*' + `security_content_ctime(lastTime)` | search process=*delete* AND process=*shadow* + | `deleting_shadow_copies_filter`' known_false_positives: vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. diff --git a/detections/detect_api_activity_from_users_without_mfa.yml b/detections/detect_api_activity_from_users_without_mfa.yml index c29fef5752..4fba07bde4 100644 --- a/detections/detect_api_activity_from_users_without_mfa.yml +++ b/detections/detect_api_activity_from_users_without_mfa.yml @@ -34,11 +34,11 @@ how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or lat type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail userIdentity.sessionContext.attributes.mfaAuthenticated=false +search: '`cloudtrail` userIdentity.sessionContext.attributes.mfaAuthenticated=false | search NOT [| inputlookup aws_service_accounts | fields identity | rename identity as user]| stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by userIdentity.arn userIdentity.type user | `security_content_ctime(firstTime)` | - `security_content_ctime(lastTime)` + `security_content_ctime(lastTime)` | `detect_api_activity_from_users_without_mfa_filter`' known_false_positives: Many service accounts configured within an AWS infrastructure do not have multi factor authentication enabled. Please ignore the service accounts, if triggered and instead add them to the aws_service_accounts.csv file to fine tune diff --git a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml index f0f6fe7e83..7cef1dd564 100644 --- a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml +++ b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml @@ -14,7 +14,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") AND (Web.url="*/web-console/ServerInfo.jsp*" OR Web.url="*web-console*" OR Web.url="*jmx-console*" OR Web.url = "*invoker*") by Web.http_method, Web.url, Web.src, Web.dest | `drop_dm_object_name("Web")` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_attackers_scanning_for_vulnerable_jboss_servers_filter`' known_false_positives: It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. tags: diff --git a/detections/detect_aws_api_activities_from_unapproved_accounts.yml b/detections/detect_aws_api_activities_from_unapproved_accounts.yml index 79024b10ed..7ff455fbd1 100644 --- a/detections/detect_aws_api_activities_from_unapproved_accounts.yml +++ b/detections/detect_aws_api_activities_from_unapproved_accounts.yml @@ -34,11 +34,12 @@ how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or lat type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail errorCode=success | rename userName as identity +search: '`cloudtrail` errorCode=success | rename userName as identity | search NOT [| inputlookup identity_lookup_expanded | fields identity] | search NOT [| inputlookup aws_service_accounts | fields identity] | rename identity as user | stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `detect_aws_api_activities_from_unapproved_accounts_filter`' known_false_positives: It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` file. If the user is a legitimate service account, update the `aws_service_accounts.csv` diff --git a/detections/detect_aws_console_login_by_user_from_new_city.yml b/detections/detect_aws_console_login_by_user_from_new_city.yml index 99c6dc88e8..fcd4ea90f1 100644 --- a/detections/detect_aws_console_login_by_user_from_new_city.yml +++ b/detections/detect_aws_console_login_by_user_from_new_city.yml @@ -23,7 +23,7 @@ search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firs "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New City" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `security_content_ctime(earliestseen)` | table user City userStatus firstTime lastTime - earliestseen' + earliestseen | `detect_aws_console_login_by_user_from_new_city_filter`' known_false_positives: When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. diff --git a/detections/detect_aws_console_login_by_user_from_new_country.yml b/detections/detect_aws_console_login_by_user_from_new_country.yml index a1d560a146..925c53ce84 100644 --- a/detections/detect_aws_console_login_by_user_from_new_country.yml +++ b/detections/detect_aws_console_login_by_user_from_new_country.yml @@ -23,7 +23,7 @@ search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firs >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Country" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`security_content_ctime(earliestseen)` | table - user Country userStatus firstTime lastTime earliestseen' + user Country userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_country_filter`' known_false_positives: When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. diff --git a/detections/detect_aws_console_login_by_user_from_new_region.yml b/detections/detect_aws_console_login_by_user_from_new_region.yml index 9120d4be06..2cb3865643 100644 --- a/detections/detect_aws_console_login_by_user_from_new_region.yml +++ b/detections/detect_aws_console_login_by_user_from_new_region.yml @@ -23,7 +23,7 @@ search: '| inputlookup previously_seen_users_console_logins.csv | stats min(firs relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Region" AND UserData="Old User" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `security_content_ctime(earliestseen)` | table - user Region userStatus firstTime lastTime earliestseen' + user Region userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_region_filter`' known_false_positives: When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. diff --git a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml index 5516b0c8f6..d4daa00380 100644 --- a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml +++ b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml @@ -29,7 +29,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime | search NOT [ inputlookup legit_domains.csv | fields domain]| join domain type=outer [| tstats count `security_content_summariesonly` values(Web.url) as url from datamodel=Web.Web by Web.dest Web.site | rename "Web.*" as * | rex field=site ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" - | table dest domain url] | table count src dest query answer domain url' + | table dest domain url] | table count src dest query answer domain url | `detect_dns_requests_to_phishing_sites_leveraging_evilginx2_filter`' known_false_positives: If a known good domain is not listed in the legit_domains.csv file, then the search could give you false postives. Please update that lookup file to filter out DNS requests to legitimate domains. diff --git a/detections/detect_excessive_account_lockouts_from_endpoint.yml b/detections/detect_excessive_account_lockouts_from_endpoint.yml index 0c6e69c6ea..1c5d489fc5 100644 --- a/detections/detect_excessive_account_lockouts_from_endpoint.yml +++ b/detections/detect_excessive_account_lockouts_from_endpoint.yml @@ -24,7 +24,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.dest All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | search count > 5' + | `security_content_ctime(lastTime)` | search count > 5 | `detect_excessive_account_lockouts_from_endpoint_filter`' known_false_positives: It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts. tags: diff --git a/detections/detect_excessive_user_account_lockouts.yml b/detections/detect_excessive_user_account_lockouts.yml index 40214661e9..08863cca46 100644 --- a/detections/detect_excessive_user_account_lockouts.yml +++ b/detections/detect_excessive_user_account_lockouts.yml @@ -15,7 +15,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.user All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | search count > 5' + | `security_content_ctime(lastTime)` | search count > 5 | `detect_excessive_user_account_lockouts_filter`' known_false_positives: It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. tags: diff --git a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index f01ec4030b..a46833e297 100644 --- a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -37,7 +37,8 @@ type: ESCU author: Bhavin Patel, Splunk search: '| tstats `security_content_summariesonly` count values(DNS.answer) as answer min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query - | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)` | `dynamic_dns_providers`' + | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)` | `dynamic_dns_providers` + | `detect_hosts_connecting_to_dynamic_domain_providers_filter`' known_false_positives: Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified. diff --git a/detections/detect_large_outbound_icmp_packets.yml b/detections/detect_large_outbound_icmp_packets.yml index 0e5a0e7450..6215fdd423 100644 --- a/detections/detect_large_outbound_icmp_packets.yml +++ b/detections/detect_large_outbound_icmp_packets.yml @@ -24,7 +24,7 @@ search: '| tstats `security_content_summariesonly` count earliest(_time) as firs !=internal (All_Traffic.protocol=icmp OR All_Traffic.transport=icmp) All_Traffic.bytes > 1000 by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) - | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' + | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `detect_large_outbound_icmp_packets_filter`' known_false_positives: ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are diff --git a/detections/detect_long_dns_txt_record_response.yml b/detections/detect_long_dns_txt_record_response.yml index a89e8e4f66..66ffc5f840 100644 --- a/detections/detect_long_dns_txt_record_response.yml +++ b/detections/detect_long_dns_txt_record_response.yml @@ -22,7 +22,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime IP", answer as "DNS Answer" anslen as "Answer Length" record_type as "DNS Record Type" firstTime as "First Time" lastTime as "Last Time" count as Count | table "Source IP" "Destination IP" "DNS Answer" "DNS Record Type" "Answer Length" Count "First - Time" "Last Time"' + Time" "Last Time" | `detect_long_dns_txt_record_response_filter`' known_false_positives: It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. diff --git a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml index b1d4e18ec5..d19d9094ee 100644 --- a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml +++ b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime by Web.http_method, Web.url,Web.url_length Web.src, Web.dest | search Web.url="*jmx-console/HtmlAdaptor?action=invokeOpByName&name=jboss.admin*import*" AND Web.url_length > 200 | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table src, dest_ip, http_method, url, firstTime, - lastTime' + lastTime | `detect_malicious_requests_to_exploit_jboss_servers_filter`' known_false_positives: No known false positives for this detection. tags: analytics_story: diff --git a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml index eb436f58b8..0de4cd8e0d 100644 --- a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml +++ b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml @@ -19,7 +19,7 @@ search: eventtype=wineventlog_security signature_id=4703 Process_Name=*powershel | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs as "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` + `security_content_ctime(lastTime)` | `detect_mimikatz_via_powershell_and_eventcode_4703_filter` known_false_positives: The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you diff --git a/detections/detect_mshta_running_scripts_in_command_line_arguments.yml b/detections/detect_mshta_running_scripts_in_command_line_arguments.yml index dfff52792a..68d435d62d 100644 --- a/detections/detect_mshta_running_scripts_in_command_line_arguments.yml +++ b/detections/detect_mshta_running_scripts_in_command_line_arguments.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=mshta.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| - search (process=*vbscript* OR process=*javascript*)' + search (process=*vbscript* OR process=*javascript*) | `detect_mshta_running_scripts_in_command_line_arguments_filter`' known_false_positives: Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. tags: diff --git a/detections/detect_new_api_calls_from_user_roles.yml b/detections/detect_new_api_calls_from_user_roles.yml index d354664be2..09c32fd0d7 100644 --- a/detections/detect_new_api_calls_from_user_roles.yml +++ b/detections/detect_new_api_calls_from_user_roles.yml @@ -12,8 +12,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole - [search sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole +search: '`cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole + [search `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | inputlookup append=t previously_seen_api_calls_from_user_roles | stats min(earliest) as earliest, max(latest) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles| @@ -21,7 +21,7 @@ search: sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIde where newApiCallfromUserRole=1 | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | table eventName userName] |rename userName as user| stats values(eventName) earliest(_time) as earliest latest(_time) as latest by user | `security_content_ctime(earliest)` - | `security_content_ctime(latest)` + | `security_content_ctime(latest)` | `detect_new_api_calls_from_user_roles_filter`' known_false_positives: It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. diff --git a/detections/detect_new_local_admin_account.yml b/detections/detect_new_local_admin_account.yml index 57c659a7d2..b537b182f7 100644 --- a/detections/detect_new_local_admin_account.yml +++ b/detections/detect_new_local_admin_account.yml @@ -35,7 +35,7 @@ author: David Dorsey, Splunk search: eventtype = wineventlog_security signature_id=4720 OR (signature_id=4732 Group_Name= Administrators) | transaction Security_ID connected=false maxspan=180m | search signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID - Group_Name src_user Message + Group_Name src_user Message | `detect_new_local_admin_account_filter` known_false_positives: The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not diff --git a/detections/detect_new_login_attempts_to_routers.yml b/detections/detect_new_login_attempts_to_routers.yml index 67b12e4a37..04a58e49ba 100644 --- a/detections/detect_new_login_attempts_to_routers.yml +++ b/detections/detect_new_login_attempts_to_routers.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count earliest(_time) as earl latest(_time) as latest from datamodel=Authentication where Authentication.dest_category=router by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= relative_time(now(), "-30d@d"), 1, 0) | where isOutlier=1| `security_content_ctime(earliest)`| `security_content_ctime(latest)` - | `drop_dm_object_name("Authentication")`' + | `drop_dm_object_name("Authentication")` | `detect_new_login_attempts_to_routers_filter`' known_false_positives: Legitimate router connections may appear as new connections tags: analytics_story: diff --git a/detections/detect_new_open_s3_buckets.yml b/detections/detect_new_open_s3_buckets.yml index dbedcdc575..7ef7905d9b 100644 --- a/detections/detect_new_open_s3_buckets.yml +++ b/detections/detect_new_open_s3_buckets.yml @@ -10,12 +10,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail AllUsers eventName=PutBucketAcl | spath output=userIdentityArn +search: '`cloudtrail` AllUsers eventName=PutBucketAcl | spath output=userIdentityArn path=userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | spath output=aclControlList path=requestParameters.AccessControlPolicy.AccessControlList | spath input=aclControlList output=grantee path=Grant{} | mvexpand grantee | spath input=grantee | search Grantee.URI=*AllUsers | rename userIdentityArn as user| table - _time, src,awsRegion Permission, Grantee.URI, bucketName, user + _time, src,awsRegion Permission, Grantee.URI, bucketName, user | `detect_new_open_s3_buckets_filter`' known_false_positives: While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" diff --git a/detections/detect_new_user_aws_console_login.yml b/detections/detect_new_user_aws_console_login.yml index 3b97b0920d..29224abaed 100644 --- a/detections/detect_new_user_aws_console_login.yml +++ b/detections/detect_new_user_aws_console_login.yml @@ -15,13 +15,13 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late often you run the detection searches) to refresh the baselines. type: ESCU author: Bhavin Patel, Splunk -search: 'sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn +search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | stats earliest(_time) as firstTime latest(_time) as lastTime by user | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user | eval userStatus=if(firstTime >= relative_time(now(), "-70m@m"), "First Time Logging into AWS Console","Previously Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| - where userStatus ="First Time Logging into AWS Console" ' + where userStatus ="First Time Logging into AWS Console" | `detect_new_user_aws_console_login_filter`' known_false_positives: When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. diff --git a/detections/detect_path_interception_by_creation_of_program.yml b/detections/detect_path_interception_by_creation_of_program.yml index 4c17363954..759e116157 100644 --- a/detections/detect_path_interception_by_creation_of_program.yml +++ b/detections/detect_path_interception_by_creation_of_program.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where Filesystem.file_path="C:\\program.exe" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` - | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`' + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `detect_path_interception_by_creation_of_program_filter`' known_false_positives: 'It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user.' tags: diff --git a/detections/detect_processes_used_for_system_network_configuration_discovery.yml b/detections/detect_processes_used_for_system_network_configuration_discovery.yml index 26b88a6301..9275fb11c5 100644 --- a/detections/detect_processes_used_for_system_network_configuration_discovery.yml +++ b/detections/detect_processes_used_for_system_network_configuration_discovery.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces Processes.user _time | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` | transaction dest connected=false maxpause=5m |where eventcount>=5 | table firstTime - lastTime dest user process_name process parent_process eventcount' + lastTime dest user process_name process parent_process eventcount | `detect_processes_used_for_system_network_configuration_discovery_filter`' known_false_positives: It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. diff --git a/detections/detect_prohibited_applications_spawning_cmd.yml b/detections/detect_prohibited_applications_spawning_cmd.yml index 0bc5b3158f..d266162e4b 100644 --- a/detections/detect_prohibited_applications_spawning_cmd.yml +++ b/detections/detect_prohibited_applications_spawning_cmd.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`]' + `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`] | `detect_prohibited_applications_spawning_cmd_filter`' known_false_positives: There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. diff --git a/detections/detect_psexec_with_accepteula_flag.yml b/detections/detect_psexec_with_accepteula_flag.yml index a104bf113e..010a0024bd 100644 --- a/detections/detect_psexec_with_accepteula_flag.yml +++ b/detections/detect_psexec_with_accepteula_flag.yml @@ -22,7 +22,7 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = PsExec.exe Processes.process = "*accepteula*" by Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| - `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' + `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_psexec_with_accepteula_flag_filter`' known_false_positives: Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this diff --git a/detections/detect_s3_access_from_a_new_ip.yml b/detections/detect_s3_access_from_a_new_ip.yml index 739b4a74c4..d9cc514509 100644 --- a/detections/detect_s3_access_from_a_new_ip.yml +++ b/detections/detect_s3_access_from_a_new_ip.yml @@ -20,7 +20,7 @@ search: sourcetype=aws:s3:accesslogs http_status=200 [search sourcetype=aws:s3: >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | table bucket_name remote_ip]| iplocation remote_ip |rename remote_ip as src_ip | table _time bucket_name src_ip City Country operation - request_uri + request_uri | `detect_s3_access_from_a_new_ip_filter` known_false_positives: S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour diff --git a/detections/detect_spike_in_aws_api_activity.yml b/detections/detect_spike_in_aws_api_activity.yml index b28ab4cbde..f58dc47a91 100644 --- a/detections/detect_spike_in_aws_api_activity.yml +++ b/detections/detect_spike_in_aws_api_activity.yml @@ -34,7 +34,7 @@ how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or lat type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventType=AwsApiCall [search sourcetype=aws:cloudtrail +search: '`cloudtrail` eventType=AwsApiCall [search `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls @@ -47,7 +47,7 @@ search: sourcetype=aws:cloudtrail eventType=AwsApiCall [search sourcetype=aws:cl AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) - as uniqueApisCalled by user + as uniqueApisCalled by user | `detect_spike_in_aws_api_activity_filter`' known_false_positives: '' tags: analytics_story: diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml index a312f25483..9df3868671 100644 --- a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -35,6 +35,7 @@ search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | table src_ip] | stats values(dest_ip) as "Blocked Destination IPs", values(interface_id) as "resourceId" count as numberOfBlockedConnections, dc(dest_ip) as uniqueDestConnections by src_ip + | `detect_spike_in_blocked_outbound_traffic_from_your_aws_filter` known_false_positives: The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number diff --git a/detections/detect_spike_in_network_acl_activity.yml b/detections/detect_spike_in_network_acl_activity.yml index 487798abb8..f878514d68 100644 --- a/detections/detect_spike_in_network_acl_activity.yml +++ b/detections/detect_spike_in_network_acl_activity.yml @@ -17,7 +17,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail `network_acl_events` [search sourcetype=aws:cloudtrail +search: '`cloudtrail` `network_acl_events` [search `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup network_acl_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls @@ -30,7 +30,7 @@ search: sourcetype=aws:cloudtrail `network_acl_events` [search sourcetype=aws:cl AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) - as uniqueApisCalled by user + as uniqueApisCalled by user | `detect_spike_in_network_acl_activity_filter`' known_false_positives: The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. tags: diff --git a/detections/detect_spike_in_s3_bucket_deletion.yml b/detections/detect_spike_in_s3_bucket_deletion.yml index 4d679f1365..62e679eff3 100644 --- a/detections/detect_spike_in_s3_bucket_deletion.yml +++ b/detections/detect_spike_in_s3_bucket_deletion.yml @@ -17,7 +17,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail eventName=DeleteBucket [search sourcetype=aws:cloudtrail +search: '`cloudtrail` eventName=DeleteBucket [search `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup s3_deletion_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls @@ -31,6 +31,7 @@ search: sourcetype=aws:cloudtrail eventName=DeleteBucket [search sourcetype=aws: userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | stats values(bucketName) as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user + | `detect_spike_in_s3_bucket_deletion_filter`' known_false_positives: Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. tags: diff --git a/detections/detect_spike_in_security_group_activity.yml b/detections/detect_spike_in_security_group_activity.yml index 7c4921e15e..d449dc6f22 100644 --- a/detections/detect_spike_in_security_group_activity.yml +++ b/detections/detect_spike_in_security_group_activity.yml @@ -18,7 +18,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail `security_group_api_calls` [search sourcetype=aws:cloudtrail +search: '`cloudtrail` `security_group_api_calls` [search `cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup security_group_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval @@ -31,7 +31,7 @@ search: sourcetype=aws:cloudtrail `security_group_api_calls` [search sourcetype= AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) - as uniqueApisCalled by user + as uniqueApisCalled by user | `detect_spike_in_security_group_activity_filter`' known_false_positives: Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. tags: diff --git a/detections/detect_unauthorized_assets_by_mac_address.yml b/detections/detect_unauthorized_assets_by_mac_address.yml index 2a014870a1..f190d3877e 100644 --- a/detections/detect_unauthorized_assets_by_mac_address.yml +++ b/detections/detect_unauthorized_assets_by_mac_address.yml @@ -20,7 +20,7 @@ search: '| tstats `security_content_summariesonly` count from datamodel=Network_ where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST by All_Sessions.src_ip All_Sessions.src_mac | dedup All_Sessions.src_mac| `drop_dm_object_name("Network_Sessions")`|`drop_dm_object_name("All_Sessions")` | search NOT [| inputlookup asset_lookup_by_str |rename mac as src_mac | fields - + src_mac]' + + src_mac] | `detect_unauthorized_assets_by_mac_address_filter`' known_false_positives: This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the diff --git a/detections/detect_usb_device_insertion.yml b/detections/detect_usb_device_insertion.yml index 4b148f2a96..6b3d32ffa2 100644 --- a/detections/detect_usb_device_insertion.yml +++ b/detections/detect_usb_device_insertion.yml @@ -21,7 +21,7 @@ search: '| tstats `security_content_summariesonly` count earliest(_time) AS earl latest(_time) AS latest from datamodel=Change_Analysis where (nodename = All_Changes) All_Changes.result="Removable Storage device" (All_Changes.result_id=4663 OR All_Changes.result_id=4656) (All_Changes.src_priority=high) by All_Changes.dest | `drop_dm_object_name("All_Changes")`| - `security_content_ctime(earliest)`| `security_content_ctime(latest)` ' + `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `detect_usb_device_insertion_filter`' known_false_positives: Legitimate USB activity will also be detected. Please verify and investigate as appropriate. tags: diff --git a/detections/detect_use_of_cmd_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_to_launch_script_interpreters.yml index c4c2ade900..e56fd49dbd 100644 --- a/detections/detect_use_of_cmd_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_to_launch_script_interpreters.yml @@ -17,7 +17,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name="cmd.exe" (Processes.process_name=cscript.exe OR Processes.process_name =wscript.exe) by Processes.parent_process Processes.process_name - Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' + Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + | `detect_use_of_cmd_to_launch_script_interpreters_filter`' known_false_positives: Some legitimate applications may exhibit this behavior. tags: analytics_story: diff --git a/detections/detect_web_traffic_to_dynamic_domain_providers.yml b/detections/detect_web_traffic_to_dynamic_domain_providers.yml index dbc1b75af5..736a7ff11d 100644 --- a/detections/detect_web_traffic_to_dynamic_domain_providers.yml +++ b/detections/detect_web_traffic_to_dynamic_domain_providers.yml @@ -25,7 +25,8 @@ references: [] author: Bhavin Patel, Splunk search: '| tstats `security_content_summariesonly` count values(Web.url) as url min(_time) as firstTime from datamodel=Web where Web.status=200 by Web.src Web.dest Web.status - | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `dynamic_dns_web_traffic`' + | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `dynamic_dns_web_traffic` + | `detect_web_traffic_to_dynamic_domain_providers_filter`' known_false_positives: It is possible that list of dynamic DNS providers is outdated and/or that the URL being requested is legitimate. tags: diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml index b23bd81f2f..db2afbc202 100644 --- a/detections/detection_of_dns_tunnels.yml +++ b/detections/detection_of_dns_tunnels.yml @@ -33,7 +33,7 @@ search: '| tstats `security_content_summariesonly` dc("DNS.query") as count fro OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.answer" | rename "DNS.src" as src "DNS.answer" as message | eval message=if(message=="unknown","", message) | eval length=len(message) | stats sum(length) as length by src ] | stats - sum(length) as length by src | where length > 10000' + sum(length) as length by src | where length > 10000 | `detection_of_dns_tunnels_filter`' known_false_positives: It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. diff --git a/detections/detection_of_tools_built_by_nirsoft.yml b/detections/detection_of_tools_built_by_nirsoft.yml index b137167b68..086935f03c 100644 --- a/detections/detection_of_tools_built_by_nirsoft.yml +++ b/detections/detection_of_tools_built_by_nirsoft.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) values(Proce as process max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process="* /stext *" OR Processes.process="* /scomma *" ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - |`security_content_ctime(lastTime)`' + |`security_content_ctime(lastTime)` | `detection_of_tools_built_by_nirsoft_filter`' known_false_positives: While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. tags: diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml index d1c2db2277..b5952ff44e 100644 --- a/detections/disabling_remote_user_account_control.yml +++ b/detections/disabling_remote_user_account_control.yml @@ -16,7 +16,7 @@ author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="*Windows\\CurrentVersion\\Policies\\System\\LocalAccountTokenFilterPolicy" by Registry.dest, Registry.registry_key_name Registry.user Registry.registry_path - Registry.action | `drop_dm_object_name(Registry)`' + Registry.action | `drop_dm_object_name(Registry)` | `disabling_remote_user_account_control_filter`' known_false_positives: This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. tags: diff --git a/detections/ec2_instance_modified_with_previously_unseen_user.yml b/detections/ec2_instance_modified_with_previously_unseen_user.yml index be4f5c1a80..43f2fbe0cd 100644 --- a/detections/ec2_instance_modified_with_previously_unseen_user.yml +++ b/detections/ec2_instance_modified_with_previously_unseen_user.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail `ec2_modification_api_calls` [search sourcetype=aws:cloudtrail +search: '`cloudtrail` `ec2_modification_api_calls` [search `cloudtrail` `ec2_modification_api_calls` errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) @@ -20,7 +20,7 @@ search: sourcetype=aws:cloudtrail `ec2_modification_api_calls` [search sourcetyp | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId - | spath output=user userIdentity.arn | table _time, user, dest + | spath output=user userIdentity.arn | table _time, user, dest | `ec2_instance_modified_with_previously_unseen_user_filter`' known_false_positives: It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. diff --git a/detections/ec2_instance_started_in_previously_unseen_region.yml b/detections/ec2_instance_started_in_previously_unseen_region.yml index 82b954dbfe..50ba795c21 100644 --- a/detections/ec2_instance_started_in_previously_unseen_region.yml +++ b/detections/ec2_instance_started_in_previously_unseen_region.yml @@ -12,13 +12,13 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudtrail earliest=-1h StartInstances | stats earliest(_time) +search: '`cloudtrail` earliest=-1h StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | inputlookup append=t previously_seen_aws_regions.csv | stats min(earliest) as earliest max(latest) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | eval regionStatus=if(earliest >= relative_time(now(),"-1d@d"), "Instance Started in a New Region","Previously Seen Region") | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | where regionStatus="Instance Started in a New - Region" + Region" | `ec2_instance_started_in_previously_unseen_region_filter`' known_false_positives: It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. tags: diff --git a/detections/ec2_instance_started_with_previously_unseen_ami.yml b/detections/ec2_instance_started_with_previously_unseen_ami.yml index dbfa4abcb9..8553cfcd53 100644 --- a/detections/ec2_instance_started_with_previously_unseen_ami.yml +++ b/detections/ec2_instance_started_with_previously_unseen_ami.yml @@ -11,7 +11,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail +search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by requestParameters.instancesSet.items{}.imageId | rename requestParameters.instancesSet.items{}.imageId as amiID | inputlookup append=t previously_seen_ec2_amis.csv | stats min(firstTime) @@ -21,7 +21,7 @@ search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws: | table requestParameters.instancesSet.items{}.imageId] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as arn, requestParameters.instancesSet.items{}.imageId as amiID | table firstTime, - lastTime, arn, amiID, dest, instanceType + lastTime, arn, amiID, dest, instanceType | `ec2_instance_started_with_previously_unseen_ami_filter`' known_false_positives: After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. diff --git a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml index de7a45b9b5..68d8464232 100644 --- a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml +++ b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml @@ -11,7 +11,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail +search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | fillnull value="m1.small" requestParameters.instanceType | stats earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType | rename requestParameters.instanceType as instanceType | inputlookup append=t previously_seen_ec2_instance_types.csv @@ -21,7 +21,7 @@ search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws: | where newType=1 | rename instanceType as requestParameters.instanceType | table requestParameters.instanceType] | spath output=user userIdentity.arn | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest | table - _time, user, dest, instanceType + _time, user, dest, instanceType | `ec2_instance_started_with_previously_unseen_instance_type_filter`' known_false_positives: It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. diff --git a/detections/ec2_instance_started_with_previously_unseen_user.yml b/detections/ec2_instance_started_with_previously_unseen_user.yml index 72cd4108f5..faaf81ff45 100644 --- a/detections/ec2_instance_started_with_previously_unseen_user.yml +++ b/detections/ec2_instance_started_with_previously_unseen_user.yml @@ -11,7 +11,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail +search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) @@ -20,7 +20,7 @@ search: sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws: | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn - as user | table _time, user, dest, instanceType + as user | table _time, user, dest, instanceType | `ec2_instance_started_with_previously_unseen_user_filter`' known_false_positives: It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. diff --git a/detections/email_attachments_with_lots_of_spaces.yml b/detections/email_attachments_with_lots_of_spaces.yml index b9d87e12bd..23662d40af 100644 --- a/detections/email_attachments_with_lots_of_spaces.yml +++ b/detections/email_attachments_with_lots_of_spaces.yml @@ -25,7 +25,7 @@ search: '| tstats `security_content_summariesonly` count values(All_Email.recipi where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | eval space_ratio = (mvcount(split(file_name," "))-1)/len(file_name) | search space_ratio - >= 0.1 | rex field=recipient_address "(?.*)@"' + >= 0.1 | rex field=recipient_address "(?.*)@" | `email_attachments_with_lots_of_spaces_filter`' known_false_positives: None at this time tags: analytics_story: diff --git a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml index c00784f397..cb38ddd234 100644 --- a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml +++ b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml @@ -28,7 +28,7 @@ search: '| tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as = round(abs(bytes_out - avg_bytes_out) / stdev_bytes_out, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_out - per_source_avg_bytes_out) / per_source_stdev_bytes_out, 2) | table dest_ip, _time, bytes_out, avg_bytes_out, per_source_avg_bytes_out, num_standard_deviations_away_from_server_average, - num_standard_deviations_away_from_client_average' + num_standard_deviations_away_from_client_average | `email_servers_sending_high_volume_traffic_to_hosts_filter`' known_false_positives: The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. diff --git a/detections/excessive_dns_failures.yml b/detections/excessive_dns_failures.yml index 6ffb3e3246..d32c4eb1e5 100644 --- a/detections/excessive_dns_failures.yml +++ b/detections/excessive_dns_failures.yml @@ -15,7 +15,7 @@ search: '| tstats `security_content_summariesonly` count values("DNS.query") as by "DNS.src","DNS.query"| `drop_dm_object_name("DNS")`| lookup cim_corporate_web_domain_lookup domain as query OUTPUT domain| where isnull(domain)| lookup update=true alexa_lookup_by_str domain as query OUTPUT rank| where isnull(rank)| stats sum(count) as count mode(queries) - as queries by src| `get_asset(src)`| where count>50' + as queries by src| `get_asset(src)`| where count>50 | `excessive_dns_failures_filter`' known_false_positives: It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. diff --git a/detections/execution_of_file_with_multiple_extensions.yml b/detections/execution_of_file_with_multiple_extensions.yml index a8332a36d1..ac65c2f205 100644 --- a/detections/execution_of_file_with_multiple_extensions.yml +++ b/detections/execution_of_file_with_multiple_extensions.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe by Processes.dest Processes.user Processes.process Processes.parent_process | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)`' + | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `execution_of_file_with_multiple_extensions_filter`' known_false_positives: None identified. tags: analytics_story: diff --git a/detections/execution_of_file_with_spaces_before_extension.yml b/detections/execution_of_file_with_spaces_before_extension.yml index 0153688e85..73b0257d79 100644 --- a/detections/execution_of_file_with_spaces_before_extension.yml +++ b/detections/execution_of_file_with_spaces_before_extension.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as process_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "* .*" by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `drop_dm_object_name(Processes)`' + | `drop_dm_object_name(Processes)` | `execution_of_file_with_spaces_before_extension_filter`' known_false_positives: None identified. tags: analytics_story: diff --git a/detections/extended_period_without_successful_netbackup_backups.yml b/detections/extended_period_without_successful_netbackup_backups.yml index cd903bb151..9375b50d86 100644 --- a/detections/extended_period_without_successful_netbackup_backups.yml +++ b/detections/extended_period_without_successful_netbackup_backups.yml @@ -16,7 +16,7 @@ author: David Dorsey, Splunk search: sourcetype="netbackup_logs" MESSAGE="Disk/Partition backup completed successfully." | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), - "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest + "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest | `extended_period_without_successful_netbackup_backups_filter` known_false_positives: None identified tags: analytics_story: diff --git a/detections/file_with_samsam_extension.yml b/detections/file_with_samsam_extension.yml index a6849be68d..dd18fcd67e 100644 --- a/detections/file_with_samsam_extension.yml +++ b/detections/file_with_samsam_extension.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_extension=.stubbin OR file_extension=.berkshire OR file_extension=.satoshi OR file_extension=.sophos - OR file_extension=.keyxml' + OR file_extension=.keyxml | `file_with_samsam_extension_filter`' known_false_positives: Because these extensions are not typically used in normal operations, you should investigate all results. tags: diff --git a/detections/first_time_seen_running_windows_service.yml b/detections/first_time_seen_running_windows_service.yml index ff7e30ad70..77d9f1199b 100644 --- a/detections/first_time_seen_running_windows_service.yml +++ b/detections/first_time_seen_running_windows_service.yml @@ -22,7 +22,7 @@ search: eventtype=wineventlog_system signature_id=7036 | rename param1 as servic >= relative_time(now(),"-60m@m"), "First time seen Windows service","Previously seen Windows service") | where serviceStatus="First time seen Windows service"| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table - service_name]| table _time dest service_name + service_name]| table _time dest service_name | `first_time_seen_running_windows_service_filter` known_false_positives: A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. tags: diff --git a/detections/gcp_kubernetes_cluster_scan_detection.yml b/detections/gcp_kubernetes_cluster_scan_detection.yml index 65393f0bc9..c2f75b5b1b 100644 --- a/detections/gcp_kubernetes_cluster_scan_detection.yml +++ b/detections/gcp_kubernetes_cluster_scan_detection.yml @@ -19,7 +19,7 @@ search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | - `kubernetes_gcp_scan_fingerprint_detection` + `kubernetes_gcp_scan_fingerprint_detection` | `gcp_kubernetes_cluster_scan_detection_filter` known_false_positives: Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. tags: diff --git a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml index b230f25a95..9156d529a7 100644 --- a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml +++ b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml @@ -28,7 +28,7 @@ search: '| tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as = round(abs(bytes_in - avg_bytes_in) / stdev_bytes_in, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_in - per_source_avg_bytes_in) / per_source_stdev_bytes_in, 2) | table src_ip, _time, bytes_in, avg_bytes_in, per_source_avg_bytes_in, num_standard_deviations_away_from_server_average, - num_standard_deviations_away_from_client_average' + num_standard_deviations_away_from_client_average | `hosts_receiving_high_volume_of_network_traffic_from_email_server_filter`' known_false_positives: The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. diff --git a/detections/identify_new_user_accounts.yml b/detections/identify_new_user_accounts.yml index a1a8129766..e339ff536e 100644 --- a/detections/identify_new_user_accounts.yml +++ b/detections/identify_new_user_accounts.yml @@ -14,7 +14,7 @@ author: Bhavin Patel, Splunk search: '| from datamodel Identity_Management.All_Identities | eval empStatus=case((now()-startDate)<604800, "Accounts created in last week") | search empStatus="Accounts created in last week"| `security_content_ctime(endDate)` | `security_content_ctime(startDate)`| table identity - empStatus endDate startDate' + empStatus endDate startDate | `identify_new_user_accounts_filter`' known_false_positives: If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. diff --git a/detections/large_volume_of_dns_any_queries.yml b/detections/large_volume_of_dns_any_queries.yml index 18086da03b..62f27ff0fb 100644 --- a/detections/large_volume_of_dns_any_queries.yml +++ b/detections/large_volume_of_dns_any_queries.yml @@ -11,7 +11,7 @@ references: [] author: Bhavin Patel, Splunk search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" "DNS.record_type"="ANY" by "DNS.dest" - | `drop_dm_object_name("DNS")` | where count>200' + | `drop_dm_object_name("DNS")` | where count>200 | `large_volume_of_dns_any_queries_filter`' known_false_positives: Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. diff --git a/detections/macos___re_opened_applications.yml b/detections/macos___re_opened_applications.yml index 9a72f5d028..bce35562ea 100644 --- a/detections/macos___re_opened_applications.yml +++ b/detections/macos___re_opened_applications.yml @@ -16,7 +16,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process="*com.apple.loginwindow*" by Processes.user Processes.process_name Processes.parent_process_name Processes.dest - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `macos___re_opened_applications_filter`' known_false_positives: At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed diff --git a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml index d278b482bf..0e4aee69c1 100644 --- a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml +++ b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml @@ -21,7 +21,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process="*-Exec*" process="*-WindowStyle*" process="*hidden*" process="*New-Object*" - process="*System.Net.WebClient*"' + process="*System.Net.WebClient*" | `malicious_powershell_process___connect_to_internet_with_hidden_window_filter`' known_false_positives: Legitimate process can have this combination of command-line options, but it's not common. tags: diff --git a/detections/malicious_powershell_process___encoded_command.yml b/detections/malicious_powershell_process___encoded_command.yml index 30088bf15f..cc9700e81e 100644 --- a/detections/malicious_powershell_process___encoded_command.yml +++ b/detections/malicious_powershell_process___encoded_command.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | search process=*-EncodedCommand* OR process=*-enc*' + | search process=*-EncodedCommand* OR process=*-enc* | `malicious_powershell_process___encoded_command_filter`' known_false_positives: System administrators may use this option, but it's not common. tags: analytics_story: diff --git a/detections/malicious_powershell_process___execution_policy_bypass.yml b/detections/malicious_powershell_process___execution_policy_bypass.yml index 9ecf87886b..6bb93419e9 100644 --- a/detections/malicious_powershell_process___execution_policy_bypass.yml +++ b/detections/malicious_powershell_process___execution_policy_bypass.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` values(Processes.process_id) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe AND (Processes.process="* -ex*" OR Processes.process="* bypass *") by Processes.process_id, Processes.user, Processes.dest | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `malicious_powershell_process___execution_policy_bypass_filter`' known_false_positives: There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. diff --git a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml index f790d95dbb..50113f4a7d 100644 --- a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml +++ b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml @@ -21,7 +21,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| - search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI*' + search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI* + | `malicious_powershell_process___multiple_suspicious_command_line_arguments_filter`' known_false_positives: Legitimate process can have this combination of command-line options, but it's not common. tags: diff --git a/detections/manipulating_windows_services_with_sc.yml b/detections/manipulating_windows_services_with_sc.yml index b46348d23a..86f05223e7 100644 --- a/detections/manipulating_windows_services_with_sc.yml +++ b/detections/manipulating_windows_services_with_sc.yml @@ -1,4 +1,4 @@ -name: Manipulating Windows Services eith sc +name: Manipulating Windows Services with sc id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d version: 2 date: '2019-02-27' @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as where Processes.process_name = sc.exe (Processes.process="* create *" OR Processes.process="* config *") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)`' + | `security_content_ctime(lastTime)` | `manipulating_windows_services_with_sc_filter`' known_false_positives: Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. diff --git a/detections/monitor_dns_for_brand_abuse.yml b/detections/monitor_dns_for_brand_abuse.yml index 1bf4278b23..625290c6bc 100644 --- a/detections/monitor_dns_for_brand_abuse.yml +++ b/detections/monitor_dns_for_brand_abuse.yml @@ -16,7 +16,7 @@ references: [] author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` values(DNS.answer) as IPs min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` - | `security_content_ctime(firstTime)`| `brand_abuse_dns`' + | `security_content_ctime(firstTime)`| `brand_abuse_dns` | `monitor_dns_for_brand_abuse_filter`' known_false_positives: None at this time tags: analytics_story: diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml index e88497e456..32141899bf 100644 --- a/detections/monitor_email_for_brand_abuse.yml +++ b/detections/monitor_email_for_brand_abuse.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` values(All_Email.recipient) a | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval temp=split(src_user, "@") | eval email_domain=mvindex(temp, 1) | lookup update=true brandMonitoring_lookup domain as email_domain OUTPUT domain_abuse | search domain_abuse=true - | table message_id, src_user, email_domain, recipients, firstTime, lastTime' + | table message_id, src_user, email_domain, recipients, firstTime, lastTime | `monitor_email_for_brand_abuse_filter`' known_false_positives: None at this time tags: analytics_story: diff --git a/detections/monitor_registry_keys_for_print_monitors.yml b/detections/monitor_registry_keys_for_print_monitors.yml index 0bf408a744..0ce1a37e62 100644 --- a/detections/monitor_registry_keys_for_print_monitors.yml +++ b/detections/monitor_registry_keys_for_print_monitors.yml @@ -20,7 +20,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime FROM datamodel=Endpoint.Registry where Registry.action=modified AND Registry.registry_path="*CurrentControlSet\\Control\\Print\\Monitors*" by Registry.dest, Registry.registry_key_name Registry.status Registry.user Registry.registry_path - Registry.action | `drop_dm_object_name(Registry)`' + Registry.action | `drop_dm_object_name(Registry)` | `monitor_registry_keys_for_print_monitors_filter`' known_false_positives: You will encounter noise from legitimate print-monitor registry entries. tags: diff --git a/detections/monitor_web_traffic_for_brand_abuse.yml b/detections/monitor_web_traffic_for_brand_abuse.yml index 98b80017a2..31399c7e0f 100644 --- a/detections/monitor_web_traffic_for_brand_abuse.yml +++ b/detections/monitor_web_traffic_for_brand_abuse.yml @@ -13,7 +13,7 @@ references: [] author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` values(Web.url) as urls min(_time) as firstTime from datamodel=Web by Web.src | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` - | `brand_abuse_web`' + | `brand_abuse_web` | `monitor_web_traffic_for_brand_abuse_filter`' known_false_positives: None at this time tags: analytics_story: diff --git a/detections/no_windows_updates_in_a_time_frame.yml b/detections/no_windows_updates_in_a_time_frame.yml index 419ab2328d..fe2f9470b5 100644 --- a/detections/no_windows_updates_in_a_time_frame.yml +++ b/detections/no_windows_updates_in_a_time_frame.yml @@ -22,7 +22,7 @@ search: '| tstats `security_content_summariesonly` max(_time) as lastTime from d as "Update Status" | rename Updates.vendor_product as Product | eval isOutlier=if(lastTime <= relative_time(now(), "-60d@d"), 1, 0) | `security_content_ctime(lastTime)` | search isOutlier=1 | rename lastTime as "Last Update Time", | table Host, "Update - Status", Product, "Last Update Time"' + Status", Product, "Last Update Time" | `no_windows_updates_in_a_time_frame_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/open_redirect_in_splunk_web.yml b/detections/open_redirect_in_splunk_web.yml index e96aa87570..d2a9a94009 100644 --- a/detections/open_redirect_in_splunk_web.yml +++ b/detections/open_redirect_in_splunk_web.yml @@ -8,7 +8,7 @@ how_to_implement: No extra steps needed to implement this search. type: ESCU references: [] author: Bhavin Patel, Splunk -search: index=_internal sourcetype=splunk_web_access return_to="/%09/*" +search: index=_internal sourcetype=splunk_web_access return_to="/%09/*" | `open_redirect_in_splunk_web_filter` known_false_positives: None identified tags: analytics_story: diff --git a/detections/osquery_pack___coldroot_detection.yml b/detections/osquery_pack___coldroot_detection.yml index 7ec31dfbc1..253f906356 100644 --- a/detections/osquery_pack___coldroot_detection.yml +++ b/detections/osquery_pack___coldroot_detection.yml @@ -13,7 +13,7 @@ references: [] author: Rico Valdez, Splunk search: '| from datamodel Alerts.Alerts | search app=osquery:results (name=pack_osx-attacks_OSX_ColdRoot_RAT_Launchd OR name=pack_osx-attacks_OSX_ColdRoot_RAT_Files) | rename columns.path as path | - bucket _time span=30s | stats count(path) by _time, host, user, path' + bucket _time span=30s | stats count(path) by _time, host, user, path | `osquery_pack___coldroot_detection_filter`' known_false_positives: There are no known false positives. tags: analytics_story: diff --git a/detections/overwriting_accessibility_binaries.yml b/detections/overwriting_accessibility_binaries.yml index aa6074a88a..4c226c3d63 100644 --- a/detections/overwriting_accessibility_binaries.yml +++ b/detections/overwriting_accessibility_binaries.yml @@ -20,7 +20,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) by Filesystem.file_name Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)`' + | `security_content_ctime(firstTime)` | `overwriting_accessibility_binaries_filter`' known_false_positives: Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. tags: diff --git a/detections/processes_created_by_netsh.yml b/detections/processes_created_by_netsh.yml index 5c90a372b5..b49e8bc17a 100644 --- a/detections/processes_created_by_netsh.yml +++ b/detections/processes_created_by_netsh.yml @@ -19,7 +19,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process="*C:\\Windows\\System32\\netsh.exe*" by Processes.user Processes.dest Processes.parent_process Processes.parent_process_name Processes.process_name - | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `processes_created_by_netsh_filter`' known_false_positives: It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. diff --git a/detections/processes_launching_netsh.yml b/detections/processes_launching_netsh.yml index 80e063f0cf..f24b7100cd 100644 --- a/detections/processes_launching_netsh.yml +++ b/detections/processes_launching_netsh.yml @@ -16,7 +16,8 @@ author: Bhavin Patel, Splunk search: '| tstats `security_content_summariesonly` count values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=netsh.exe by Processes.parent_process Processes.process_name - Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`' + Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + | `processes_launching_netsh_filter`' known_false_positives: Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. diff --git a/detections/processes_tapping_keyboard_events.yml b/detections/processes_tapping_keyboard_events.yml index 686bbee409..388c1362df 100644 --- a/detections/processes_tapping_keyboard_events.yml +++ b/detections/processes_tapping_keyboard_events.yml @@ -16,7 +16,7 @@ references: [] author: Jose Hernandez, Splunk search: '| from datamodel Alerts.Alerts | search app=osquery:results name=pack_osx-attacks_Keyboard_Event_Taps | rename columns.cmdline as cmd, columns.name as process_name, columns.pid as process_id| - dedup host,process_name | table host,process_name, cmd, process_id' + dedup host,process_name | table host,process_name, cmd, process_id | `processes_tapping_keyboard_events_filter`' known_false_positives: There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) diff --git a/detections/prohibited_network_traffic_allowed.yml b/detections/prohibited_network_traffic_allowed.yml index 9b1a5edbd9..c16f37b8cb 100644 --- a/detections/prohibited_network_traffic_allowed.yml +++ b/detections/prohibited_network_traffic_allowed.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action | lookup update=true interesting_ports_lookup dest_port as All_Traffic.dest_port OUTPUT app is_prohibited note transport | search is_prohibited=true | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' + | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `prohibited_network_traffic_allowed_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index 2002c4937e..8ec7f0ced0 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -20,7 +20,7 @@ author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` - | `prohibited_softwares`' + | `prohibited_softwares` | `prohibited_software_on_endpoint_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/protocol_or_port_mismatch.yml b/detections/protocol_or_port_mismatch.yml index 5bf6fd7ad7..729457940d 100644 --- a/detections/protocol_or_port_mismatch.yml +++ b/detections/protocol_or_port_mismatch.yml @@ -22,7 +22,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime NOT (All_Traffic.dest_port=443 OR All_Traffic.dest_port=8443)) OR (All_Traffic.app=smtp NOT All_Traffic.dest_port=25) by All_Traffic.src_ip, All_Traffic.dest_ip, All_Traffic.app, All_Traffic.dest_port |`security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | `drop_dm_object_name("All_Traffic")`' + | `drop_dm_object_name("All_Traffic")` | `protocol_or_port_mismatch_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/protocols_passing_authentication_in_cleartext.yml b/detections/protocols_passing_authentication_in_cleartext.yml index 03ba0c6645..1d709c2c05 100644 --- a/detections/protocols_passing_authentication_in_cleartext.yml +++ b/detections/protocols_passing_authentication_in_cleartext.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime (All_Traffic.dest_port="23" OR All_Traffic.dest_port="143" OR All_Traffic.dest_port="110" OR (All_Traffic.dest_port="21" AND All_Traffic.user != "anonymous")) groupby All_Traffic.user All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' + | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `protocols_passing_authentication_in_cleartext_filter`' known_false_positives: Some networks may use kerberized FTP or telnet servers, however, this is rare. tags: diff --git a/detections/reg_manipulating_windows_services_registry_keys.yml b/detections/reg_manipulating_windows_services_registry_keys.yml index cd03cb4e17..2d5a1bb0f1 100644 --- a/detections/reg_manipulating_windows_services_registry_keys.yml +++ b/detections/reg_manipulating_windows_services_registry_keys.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table - process_id dest registry_path]' + process_id dest registry_path] | `reg_manipulating_windows_services_registry_keys_filter`' known_false_positives: It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. diff --git a/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml b/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml index 7fc992d139..502e90c0b2 100644 --- a/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml +++ b/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as where Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)"' + |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)" | `reg_used_to_hide_files_or_directories_via_registry_keys_filter`' known_false_positives: None at the moment tags: analytics_story: diff --git a/detections/registry_keys_for_creating_shim_databases.yml b/detections/registry_keys_for_creating_shim_databases.yml index af55867a39..7a9cd19d90 100644 --- a/detections/registry_keys_for_creating_shim_databases.yml +++ b/detections/registry_keys_for_creating_shim_databases.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\Custom*" OR All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\InstalledSDB*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, - All_Changes.object_path | `drop_dm_object_name("All_Changes")`' + All_Changes.object_path | `drop_dm_object_name("All_Changes")` | `registry_keys_for_creating_shim_databases_filter`' known_false_positives: There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications tags: diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml index 8a738c1098..73c8e905a7 100644 --- a/detections/registry_keys_used_for_persistence.yml +++ b/detections/registry_keys_used_for_persistence.yml @@ -22,7 +22,7 @@ search: '| tstats `security_content_summariesonly` count values(Registry.registr OR Registry.registry_path=*\\CurrentControlSet\\Control\\Lsa\\* OR Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*" OR Registry.registry_path=HKLM\\SOFTWARE\\Microsoft\\Netsh\\*) by Registry.dest , Registry.status, Registry.user | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)`' + | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `registry_keys_used_for_persistence_filter`' known_false_positives: There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. tags: diff --git a/detections/registry_keys_used_for_privilege_escalation.yml b/detections/registry_keys_used_for_privilege_escalation.yml index 0768da5c72..ce8e067c36 100644 --- a/detections/registry_keys_used_for_privilege_escalation.yml +++ b/detections/registry_keys_used_for_privilege_escalation.yml @@ -21,7 +21,7 @@ search: '| tstats `security_content_summariesonly` count values(Registry.registr as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*") AND (Registry.registry_key_name=GlobalFlag OR Registry.registry_key_name=Debugger) by Registry.dest Registry.user | `security_content_ctime(lastTime)` | - `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)`' + `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `registry_keys_used_for_privilege_escalation_filter`' known_false_positives: There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. tags: diff --git a/detections/remote_desktop_network_bruteforce.yml b/detections/remote_desktop_network_bruteforce.yml index 5fd6f25f2b..c336a1026f 100644 --- a/detections/remote_desktop_network_bruteforce.yml +++ b/detections/remote_desktop_network_bruteforce.yml @@ -15,7 +15,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime All_Traffic.dest All_Traffic.dest_port | eventstats stdev(count) AS stdev avg(count) AS avg p50(count) AS p50 | where count>(avg + stdev*2) | rename All_Traffic.src AS src All_Traffic.dest AS dest | table firstTime lastTime src dest count avg p50 - stdev' + stdev | `remote_desktop_network_bruteforce_filter`' known_false_positives: RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. tags: diff --git a/detections/remote_process_instantiation_via_wmi.yml b/detections/remote_process_instantiation_via_wmi.yml index 6d43c391a9..656de383fe 100644 --- a/detections/remote_process_instantiation_via_wmi.yml +++ b/detections/remote_process_instantiation_via_wmi.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as where Processes.process_name = wmic.exe Processes.process="*/node*" Processes.process="*process*" Processes.process="*call*" Processes.process="*create*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`' + | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `remote_process_instantiation_via_wmi_filter`' known_false_positives: The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml index 30f8e23b52..8c159e9d87 100644 --- a/detections/remote_registry_key_modifications.yml +++ b/detections/remote_registry_key_modifications.yml @@ -15,7 +15,7 @@ search: '| tstats `security_content_summariesonly` count values(Registry.registr as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="\\\\*" by Registry.dest , Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - | `drop_dm_object_name(Registry)`' + | `drop_dm_object_name(Registry)` | `remote_registry_key_modifications_filter`' known_false_positives: This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. tags: diff --git a/detections/remote_wmi_command_attempt.yml b/detections/remote_wmi_command_attempt.yml index 13e593995e..8978d2afa7 100644 --- a/detections/remote_wmi_command_attempt.yml +++ b/detections/remote_wmi_command_attempt.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=wmic.exe AND Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)`' + `security_content_ctime(lastTime)` | `remote_wmi_command_attempt_filter`' known_false_positives: Administrators may use this legitimately to gather info from remote systems. tags: diff --git a/detections/rundll_loading_dll_by_ordinal.yml b/detections/rundll_loading_dll_by_ordinal.yml index 0efb2e9a0f..b904b94d46 100644 --- a/detections/rundll_loading_dll_by_ordinal.yml +++ b/detections/rundll_loading_dll_by_ordinal.yml @@ -20,7 +20,8 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = rundll32.exe Processes.process="*AppData*" Processes.process="*,#2" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `rundll_loading_dll_by_ordinal_filter`' known_false_positives: While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process tags: diff --git a/detections/samsam_test_file_write.yml b/detections/samsam_test_file_write.yml index c3cf7d9bd4..4e5ff40187 100644 --- a/detections/samsam_test_file_write.yml +++ b/detections/samsam_test_file_write.yml @@ -15,7 +15,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name from datamodel=Endpoint.Filesystem where Filesystem.file_path=*\\windows\\system32\\test.txt by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)`' + | `security_content_ctime(firstTime)` | `samsam_test_file_write_filter`' known_false_positives: No false positives have been identified. tags: analytics_story: diff --git a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml index 2393833e77..bd136246c4 100644 --- a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml +++ b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime where Processes.process_name=schtasks.exe (Processes.process= "*create*" OR Processes.process= "*delete*") by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` - | search (process=*rhaegal* OR process=*drogon* OR *viserion_*)' + | search (process=*rhaegal* OR process=*drogon* OR *viserion_*) | `scheduled_tasks_used_in_badrabbit_ransomware_filter`' known_false_positives: No known false positives tags: analytics_story: diff --git a/detections/schtasks_used_for_forcing_a_reboot.yml b/detections/schtasks_used_for_forcing_a_reboot.yml index a090db2feb..55735edce7 100644 --- a/detections/schtasks_used_for_forcing_a_reboot.yml +++ b/detections/schtasks_used_for_forcing_a_reboot.yml @@ -15,7 +15,7 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as where Processes.process_name = schtasks.exe Processes.process="*shutdown*" Processes.process="*/r*" Processes.process="*/f*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)`' + | `security_content_ctime(lastTime)` | `schtasks_used_for_forcing_a_reboot_filter`' known_false_positives: Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. tags: diff --git a/detections/shim_database_file_creation.yml b/detections/shim_database_file_creation.yml index 4e0e5e8f70..6287bd2831 100644 --- a/detections/shim_database_file_creation.yml +++ b/detections/shim_database_file_creation.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count values(Filesystem.actio values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\AppPatch\Custom* by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - |`drop_dm_object_name(Filesystem)`' + |`drop_dm_object_name(Filesystem)` | `shim_database_file_creation_filter`' known_false_positives: Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. diff --git a/detections/shim_database_installation_with_suspicious_parameters.yml b/detections/shim_database_installation_with_suspicious_parameters.yml index 2d28e9bd67..fa19888635 100644 --- a/detections/shim_database_installation_with_suspicious_parameters.yml +++ b/detections/shim_database_installation_with_suspicious_parameters.yml @@ -19,7 +19,8 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sdbinst.exe Processes.process="*-p*" Processes.process="*-q*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user - | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `shim_database_installation_with_suspicious_parameters_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/short_lived_windows_accounts.yml b/detections/short_lived_windows_accounts.yml index 563c959bc8..ba8ed384fe 100644 --- a/detections/short_lived_windows_accounts.yml +++ b/detections/short_lived_windows_accounts.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` values(All_Changes.result_id) All_Changes.user All_Changes.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` | search result_id = 4720 result_id=4726 | transaction user connected=false maxspan=240m | table firstTime lastTime count - user dest result_id' + user dest result_id | `short_lived_windows_accounts_filter`' known_false_positives: It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. tags: diff --git a/detections/single_letter_process_on_endpoint.yml b/detections/single_letter_process_on_endpoint.yml index bb28c4a3b6..a4d1c3eb98 100644 --- a/detections/single_letter_process_on_endpoint.yml +++ b/detections/single_letter_process_on_endpoint.yml @@ -16,7 +16,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime Processes.process, Processes.process_name | `drop_dm_object_name(Processes)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | eval process_name_length = len(process_name), endExe = if(substr(process_name, -4) == ".exe", 1, 0) | search process_name_length=5 - AND endExe=1 | table count, firstTime, lastTime, dest, user, process, process_name' + AND endExe=1 | table count, firstTime, lastTime, dest, user, process, process_name + | `single_letter_process_on_endpoint_filter`' known_false_positives: Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. tags: diff --git a/detections/spectre_and_meltdown_vulnerable_systems.yml b/detections/spectre_and_meltdown_vulnerable_systems.yml index 248f55d80d..2a87753bea 100644 --- a/detections/spectre_and_meltdown_vulnerable_systems.yml +++ b/detections/spectre_and_meltdown_vulnerable_systems.yml @@ -12,7 +12,8 @@ author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Vulnerabilities where Vulnerabilities.cve ="CVE-2017-5753" OR Vulnerabilities.cve ="CVE-2017-5715" OR Vulnerabilities.cve ="CVE-2017-5754" - by Vulnerabilities.dest| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + by Vulnerabilities.dest| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `spectre_and_meltdown_vulnerable_systems_filter`' known_false_positives: It is possible that your vulnerability scanner is not detecting that the patches have been applied. tags: diff --git a/detections/splunk_enterprise_information_disclosure.yml b/detections/splunk_enterprise_information_disclosure.yml index 9f109cee53..980528d5c0 100644 --- a/detections/splunk_enterprise_information_disclosure.yml +++ b/detections/splunk_enterprise_information_disclosure.yml @@ -14,7 +14,7 @@ search: index=_internal sourcetype=splunkd_ui_access server-info | search client uri_path="*raw/services/server/info/server-info" | rename clientip as src_ip, splunk_server as dest | stats earliest(_time) as firstTime, latest(_time) as lastTime, values(uri) as uri, values(useragent) as http_user_agent, values(user) as user by src_ip, dest - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `splunk_enterprise_information_disclosure_filter` known_false_positives: Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. tags: diff --git a/detections/sql_injection_with_long_urls.yml b/detections/sql_injection_with_long_urls.yml index f1569f0097..6e0805fc1f 100644 --- a/detections/sql_injection_with_long_urls.yml +++ b/detections/sql_injection_with_long_urls.yml @@ -24,7 +24,7 @@ search: '| tstats `security_content_summariesonly` count from datamodel=Web wher + mvcount(split(url, "left%20join")) + mvcount(split(url, "right%20join")) + mvcount(split(url, "full%20join")) + mvcount(split(url, "select")) + mvcount(split(url, "distinct")) + mvcount(split(url, "select%20top")) + mvcount(split(url, "union")) + mvcount(split(url, - "xp_cmdshell")) - 24 | where num_sql_cmds > 3' + "xp_cmdshell")) - 24 | where num_sql_cmds > 3 | `sql_injection_with_long_urls_filter`' known_false_positives: It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. diff --git a/detections/suspicious_email___uba_anomaly.yml b/detections/suspicious_email___uba_anomaly.yml index 72cd6c1634..8695278a92 100644 --- a/detections/suspicious_email___uba_anomaly.yml +++ b/detections/suspicious_email___uba_anomaly.yml @@ -16,7 +16,8 @@ search: '|tstats `security_content_summariesonly` count min(_time) as firstTime = "SuspiciousEmailDetectionModel" by All_UEBA_Events.description All_UEBA_Events.severity All_UEBA_Events.user All_UEBA_Events.uba_event_type All_UEBA_Events.link All_UEBA_Events.signature All_UEBA_Events.url All_UEBA_Events.UEBA_Anomalies.uba_model | `drop_dm_object_name(All_UEBA_Events)` - | `drop_dm_object_name(UEBA_Anomalies)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' + | `drop_dm_object_name(UEBA_Anomalies)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `suspicious_email___uba_anomaly_filter`' known_false_positives: This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate diff --git a/detections/suspicious_file_write.yml b/detections/suspicious_file_write.yml index 8944c272a2..45801a2d63 100644 --- a/detections/suspicious_file_write.yml +++ b/detections/suspicious_file_write.yml @@ -20,7 +20,7 @@ search: '| tstats `security_content_summariesonly` count values(Filesystem.actio as action values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Filesystem)` - | `suspicious_writes`' + | `suspicious_writes` | `suspicious_file_write_filter`' known_false_positives: It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and diff --git a/detections/suspicious_java_classes.yml b/detections/suspicious_java_classes.yml index 80aa3b4715..27c122d944 100644 --- a/detections/suspicious_java_classes.yml +++ b/detections/suspicious_java_classes.yml @@ -15,6 +15,7 @@ search: sourcetype="stream:http" http_method=POST http_content_length>1 | regex | rename src_ip as src | stats count earliest(_time) as firstTime, latest(_time) as lastTime, values(url) as uri, values(status) as status, values(http_user_agent) as http_user_agent by src, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | `suspicious_java_classes_filter` known_false_positives: There are no known false positives. tags: analytics_story: diff --git a/detections/suspicious_wevtutil_usage.yml b/detections/suspicious_wevtutil_usage.yml index adbe4355d5..3b2d3d9c3e 100644 --- a/detections/suspicious_wevtutil_usage.yml +++ b/detections/suspicious_wevtutil_usage.yml @@ -18,7 +18,8 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as where Processes.process_name = wevtutil.exe Processes.process="*cl*" (Processes.process="*System*" OR Processes.process="*Security*" OR Processes.process="*Setup*" OR Processes.process="*Application*") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| - `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`' + `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` + | `suspicious_wevtutil_usage_filter`' known_false_positives: The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. tags: diff --git a/detections/suspicious_writes_to_system_volume_information.yml b/detections/suspicious_writes_to_system_volume_information.yml index 8b1d079194..1ca613c4b9 100644 --- a/detections/suspicious_writes_to_system_volume_information.yml +++ b/detections/suspicious_writes_to_system_volume_information.yml @@ -13,7 +13,7 @@ author: Rico Valdez, Splunk search: (sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational OR tag=process) EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` + `security_content_ctime(lastTime)` | `suspicious_writes_to_system_volume_information_filter` known_false_positives: It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. diff --git a/detections/suspicious_writes_to_windows_recycle_bin.yml b/detections/suspicious_writes_to_windows_recycle_bin.yml index 60c79ec695..d69bbf93d8 100644 --- a/detections/suspicious_writes_to_windows_recycle_bin.yml +++ b/detections/suspicious_writes_to_windows_recycle_bin.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name != "explorer.exe" by Processes.process_id Processes.dest| `drop_dm_object_name("Processes")` - | table process_id dest]' + | table process_id dest] | `suspicious_writes_to_windows_recycle_bin_filter`' known_false_positives: Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index 8dd2c04abd..69d3f95bf3 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime Processes.process_path !="C:\\Windows\\SysWOW64*" by Processes.user Processes.dest Processes.process_name Processes.process_id Processes.process_path Processes.parent_process_name Processes.process_hash| `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)`| `is_windows_system_file`' + `security_content_ctime(lastTime)`| `is_windows_system_file` | `system_processes_run_from_unexpected_locations_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/tor_traffic.yml b/detections/tor_traffic.yml index 563e0deec7..aa181c7289 100644 --- a/detections/tor_traffic.yml +++ b/detections/tor_traffic.yml @@ -16,7 +16,8 @@ author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.app=tor AND All_Traffic.action=allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")`' + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` + | `tor_traffic_filter`' known_false_positives: None at this time tags: analytics_story: diff --git a/detections/unsuccessful_netbackup_backups.yml b/detections/unsuccessful_netbackup_backups.yml index 3f69a62870..92545cd594 100644 --- a/detections/unsuccessful_netbackup_backups.yml +++ b/detections/unsuccessful_netbackup_backups.yml @@ -14,6 +14,7 @@ author: David Dorsey, Splunk search: sourcetype="netbackup_logs" | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature + | `unsuccessful_netbackup_backups_filter` known_false_positives: None identified tags: analytics_story: diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml index e39ba8c8fa..d602211e30 100644 --- a/detections/unusually_long_command_line___mltk.yml +++ b/detections/unusually_long_command_line___mltk.yml @@ -24,7 +24,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime `security_content_ctime(lastTime)`| eval processlen=len(process) | search user!=unknown | apply cmdline_pdfmodel threshold=0.01 | rename "IsOutlier(processlen)" as isOutlier | search isOutlier > 0 | table firstTime lastTime user dest process_name process - processlen count' + processlen count | `unusually_long_command_line___mltk_filter`' known_false_positives: Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. diff --git a/detections/unusually_long_content_type_length.yml b/detections/unusually_long_content_type_length.yml index 6fea27b238..1f5a2b964e 100644 --- a/detections/unusually_long_content_type_length.yml +++ b/detections/unusually_long_content_type_length.yml @@ -10,9 +10,9 @@ how_to_implement: This particular search leverages data extracted from Stream:HT type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=stream:http | eval cs_content_type_length = len(cs_content_type) +search: '`stream_http` | eval cs_content_type_length = len(cs_content_type) | where cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length - cs_content_type url + cs_content_type url | `unusually_long_content_type_length_filter`' known_false_positives: Very few legitimate Content-Type fields will have a length greater than 100 characters. tags: diff --git a/detections/usn_journal_deletion.yml b/detections/usn_journal_deletion.yml index bfd108430c..04995bc56a 100644 --- a/detections/usn_journal_deletion.yml +++ b/detections/usn_journal_deletion.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fsutil.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | search process="*deletejournal*" AND process="*usn*"' + | search process="*deletejournal*" AND process="*usn*" | `usn_journal_deletion_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/web_fraud___account_harvesting.yml b/detections/web_fraud___account_harvesting.yml index 4d16df532e..ab233c1660 100644 --- a/detections/web_fraud___account_harvesting.yml +++ b/detections/web_fraud___account_harvesting.yml @@ -17,11 +17,11 @@ references: - https://splunkbase.splunk.com/app/2734/ - https://splunkbase.splunk.com/app/1809/ author: Jim Apger, Splunk -search: sourcetype=stream:http http_content_type=text* uri="/magento2/customer/account/loginPost/" +search: '`stream_http` http_content_type=text* uri="/magento2/customer/account/loginPost/" | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> - 25 + 25 | `web_fraud___account_harvesting_filter`' known_false_positives: As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamolous behavior. This search will need to be customized to diff --git a/detections/web_fraud___anomalous_user_clickspeed.yml b/detections/web_fraud___anomalous_user_clickspeed.yml index 56df1c0b6f..d367912689 100644 --- a/detections/web_fraud___anomalous_user_clickspeed.yml +++ b/detections/web_fraud___anomalous_user_clickspeed.yml @@ -21,10 +21,11 @@ references: - https://en.wikipedia.org/wiki/HTTP_cookie - https://splunkbase.splunk.com/app/1809/ author: Jim Apger, Splunk -search: sourcetype=stream:http http_content_type=text* | rex field=cookie "form_key=(?\w+)" +search: '`stream_http` http_content_type=text* | rex field=cookie "form_key=(?\w+)" | streamstats window=2 current=1 range(_time) as TimeDelta by session_id | where TimeDelta>0 |stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) as ClickSpeedAvg by session_id | where count>5 AND (ClickSpeedStdDev<.5 OR ClickSpeedAvg<.5) + | `web_fraud___anomalous_user_clickspeed_filter`' known_false_positives: As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior. diff --git a/detections/web_fraud___password_sharing_across_accounts.yml b/detections/web_fraud___password_sharing_across_accounts.yml index 8166186b34..e8d280b5f5 100644 --- a/detections/web_fraud___password_sharing_across_accounts.yml +++ b/detections/web_fraud___password_sharing_across_accounts.yml @@ -16,10 +16,11 @@ references: - https://en.wikipedia.org/wiki/HTTP_cookie - https://splunkbase.splunk.com/app/1809/ author: Jim Apger, Splunk -search: sourcetype=stream:http http_content_type=text* uri=/magento2/customer/account/loginPost* | +search: '`stream_http` http_content_type=text* uri=/magento2/customer/account/loginPost* | rex field=form_data "login\[username\]=(?[^&|^$]+)" | rex field=form_data "login\[password\]=(?[^&|^$]+)" | stats dc(Username) as UniqueUsernames values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5 + | `web_fraud___password_sharing_across_accounts_filter`' known_false_positives: As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior. diff --git a/detections/web_servers_executing_suspicious_processes.yml b/detections/web_servers_executing_suspicious_processes.yml index 033e37712b..7d188f9dc1 100644 --- a/detections/web_servers_executing_suspicious_processes.yml +++ b/detections/web_servers_executing_suspicious_processes.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime AND (Processes.process="*whoami*" OR Processes.process="*ping*" OR Processes.process="*iptables*" OR Processes.process="*wget*" OR Processes.process="*service*" OR Processes.process="*curl*") by Processes.process Processes.process_name, Processes.dest Processes.user| `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' + | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `web_servers_executing_suspicious_processes_filter`' known_false_positives: Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. tags: diff --git a/detections/windows_event_log_cleared.yml b/detections/windows_event_log_cleared.yml index 77b17d889f..bd980c2857 100644 --- a/detections/windows_event_log_cleared.yml +++ b/detections/windows_event_log_cleared.yml @@ -12,7 +12,7 @@ author: Rico Valdez, Splunk search: ((eventtype=wineventlog_security) AND (signature_id=1102 OR signature_id=1100)) OR ((eventtype=wineventlog_system) AND signature_id=104) | stats count min(_time) as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` + | `security_content_ctime(lastTime)` | `windows_event_log_cleared_filter` known_false_positives: It is possible that these logs may be legitimately cleared by Administrators. tags: diff --git a/detections/windows_hosts_file_modification.yml b/detections/windows_hosts_file_modification.yml index fc1e86c0af..287ddfbb12 100644 --- a/detections/windows_hosts_file_modification.yml +++ b/detections/windows_hosts_file_modification.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.file_path Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | search Filesystem.file_name=hosts AND Filesystem.file_path=*Windows\\System32\\* - | `drop_dm_object_name(Filesystem)`' + | `drop_dm_object_name(Filesystem)` | `windows_hosts_file_modification_filter`' known_false_positives: There may be legitimate reasons for system administrators to add entries to this file. tags: diff --git a/detections/wmi_permanent_event_subscription.yml b/detections/wmi_permanent_event_subscription.yml index f2483110b6..6fa89ded62 100644 --- a/detections/wmi_permanent_event_subscription.yml +++ b/detections/wmi_permanent_event_subscription.yml @@ -13,7 +13,7 @@ search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" Even Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" | search consumer!="NTEventLogEventConsumer=\"SCM Event Log Consumer\"" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | rename ComputerName as dest + | rename ComputerName as dest | `wmi_permanent_event_subscription_filter` known_false_positives: Although unlikely, administrators may use event subscriptions for legitimate purposes. tags: diff --git a/detections/wmi_permanent_event_subscription___sysmon.yml b/detections/wmi_permanent_event_subscription___sysmon.yml index d5b710e9d8..cca3b4788d 100644 --- a/detections/wmi_permanent_event_subscription___sysmon.yml +++ b/detections/wmi_permanent_event_subscription___sysmon.yml @@ -12,7 +12,7 @@ references: [] author: Rico Valdez, Splunk search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode=21 | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, - Filter + Filter | `wmi_permanent_event_subscription___sysmon_filter` known_false_positives: Although unlikely, administrators may use event subscriptions for legitimate purposes. tags: diff --git a/detections/wmi_temporary_event_subscription.yml b/detections/wmi_temporary_event_subscription.yml index b86da7f152..197c6a427e 100644 --- a/detections/wmi_temporary_event_subscription.yml +++ b/detections/wmi_temporary_event_subscription.yml @@ -15,7 +15,7 @@ search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" Even AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | - `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `wmi_temporary_event_subscription_filter` known_false_positives: Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to diff --git a/macros/cloudtrail.yml b/macros/cloudtrail.yml new file mode 100644 index 0000000000..e31baee994 --- /dev/null +++ b/macros/cloudtrail.yml @@ -0,0 +1,3 @@ +definition: sourcetype=aws:cloudtrail +description: customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudtrail logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: cloudtrail diff --git a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml index f634fc6df6..984b3db736 100644 --- a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml +++ b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml @@ -10,6 +10,6 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - accessKeyId -search: '| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} +search: '| search `cloudtrail` userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' diff --git a/response_tasks/aws_investigate_user_activities_by_arn.yml b/response_tasks/aws_investigate_user_activities_by_arn.yml index caa7a74ae2..1f2821c616 100644 --- a/response_tasks/aws_investigate_user_activities_by_arn.yml +++ b/response_tasks/aws_investigate_user_activities_by_arn.yml @@ -12,6 +12,6 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - user -search: '| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time +search: '| search `cloudtrail` userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType' diff --git a/response_tasks/aws_investigate_user_activities_by_source_user.yml b/response_tasks/aws_investigate_user_activities_by_source_user.yml index b138d68f30..00e40c8f50 100644 --- a/response_tasks/aws_investigate_user_activities_by_source_user.yml +++ b/response_tasks/aws_investigate_user_activities_by_source_user.yml @@ -10,6 +10,6 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - src_user -search: '| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user +search: '| search `cloudtrail` userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' diff --git a/response_tasks/get_all_aws_activity_from_city.yml b/response_tasks/get_all_aws_activity_from_city.yml index ee8c514915..d325823f6c 100644 --- a/response_tasks/get_all_aws_activity_from_city.yml +++ b/response_tasks/get_all_aws_activity_from_city.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - City -search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search +search: '| search `cloudtrail` | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, diff --git a/response_tasks/get_all_aws_activity_from_country.yml b/response_tasks/get_all_aws_activity_from_country.yml index 9bcf654f1e..9a82874b9f 100644 --- a/response_tasks/get_all_aws_activity_from_country.yml +++ b/response_tasks/get_all_aws_activity_from_country.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - Country -search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search +search: '| search `cloudtrail` | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, diff --git a/response_tasks/get_all_aws_activity_from_ip_address.yml b/response_tasks/get_all_aws_activity_from_ip_address.yml index 82b3f593c9..db12ff3b5e 100644 --- a/response_tasks/get_all_aws_activity_from_ip_address.yml +++ b/response_tasks/get_all_aws_activity_from_ip_address.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - src_ip -search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search +search: '| search `cloudtrail` | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, diff --git a/response_tasks/get_all_aws_activity_from_region.yml b/response_tasks/get_all_aws_activity_from_region.yml index 1db6e7e6c2..5603f16e77 100644 --- a/response_tasks/get_all_aws_activity_from_region.yml +++ b/response_tasks/get_all_aws_activity_from_region.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - Region -search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search +search: '| search `cloudtrail` | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, diff --git a/response_tasks/get_ec2_launch_details.yml b/response_tasks/get_ec2_launch_details.yml index 7681171576..e882fb4110 100644 --- a/response_tasks/get_ec2_launch_details.yml +++ b/response_tasks/get_ec2_launch_details.yml @@ -9,7 +9,7 @@ how_to_implement: In order to implement this search, you must install the AWS Ap author: Bhavin Patel, Splunk inputs: - dest -search: '| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} +search: '| search `cloudtrail` responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture diff --git a/response_tasks/investigate_aws_activities_via_region_name.yml b/response_tasks/investigate_aws_activities_via_region_name.yml index 859e5c9de3..ff2c1fc7ec 100644 --- a/response_tasks/investigate_aws_activities_via_region_name.yml +++ b/response_tasks/investigate_aws_activities_via_region_name.yml @@ -11,5 +11,5 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - awsRegion -search: '| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId +search: '| search `cloudtrail` awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId' diff --git a/response_tasks/investigate_aws_user_activities_by_user_field.yml b/response_tasks/investigate_aws_user_activities_by_user_field.yml index 82e1f14b4a..fe1837d76a 100644 --- a/response_tasks/investigate_aws_user_activities_by_user_field.yml +++ b/response_tasks/investigate_aws_user_activities_by_user_field.yml @@ -12,5 +12,5 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - user -search: '| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type +search: '| search `cloudtrail` user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType ' diff --git a/spec/baselines.spec.json b/spec/baselines.spec.json index 33c677bfa4..f2251ef129 100644 --- a/spec/baselines.spec.json +++ b/spec/baselines.spec.json @@ -63,7 +63,7 @@ "default": "", "description": "The Splunk search for the baseline", "examples": [ - "sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" + "cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" ], "type": "string" }, From 909806896ef455d615c336f0b37ca384e77708f5 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 30 Apr 2020 16:52:38 +0200 Subject: [PATCH 09/93] validate script --- bin/validate.py | 25 ++++++++++++++++--- ..._eks_kubernetes_cluster_scan_detection.yml | 4 +-- ...azon_eks_kubernetes_pod_scan_detection.yml | 4 +-- ...katz_via_powershell_and_eventcode_4703.yml | 4 +-- detections/detect_s3_access_from_a_new_ip.yml | 4 +-- ...blocked_outbound_traffic_from_your_aws.yml | 6 ++--- ...d_without_successful_netbackup_backups.yml | 4 +-- ...irst_time_seen_running_windows_service.yml | 6 ++--- .../gcp_kubernetes_cluster_scan_detection.yml | 4 +-- ...h_invalid_credentails_from_the_same_ip.yml | 4 +-- detections/okta_account_lockout_events.yml | 4 +-- detections/okta_failed_sso_attempts.yml | 4 +-- .../okta_user_logins_from_multiple_cities.yml | 4 +-- detections/suspicious_java_classes.yml | 4 +-- ...us_writes_to_system_volume_information.yml | 4 +-- detections/unsuccessful_netbackup_backups.yml | 4 +-- detections/windows_event_log_cleared.yml | 6 ++--- .../wmi_permanent_event_subscription.yml | 4 +-- ..._permanent_event_subscription___sysmon.yml | 4 +-- .../wmi_temporary_event_subscription.yml | 10 +++----- macros/cloudwatch_eks.yml | 3 +++ macros/cloudwatch_vpc.yml | 3 +++ macros/google_gcp_pubnet_message.yml | 3 +++ macros/netbackup.yml | 3 +++ macros/okta.yml | 3 +++ macros/s3_accesslogs.yml | 3 +++ macros/stream_http.yml | 3 +++ macros/wineventlog_system.yml | 3 +++ macros/wmi.yml | 3 +++ 29 files changed, 91 insertions(+), 49 deletions(-) create mode 100644 macros/cloudwatch_eks.yml create mode 100644 macros/cloudwatch_vpc.yml create mode 100644 macros/google_gcp_pubnet_message.yml create mode 100644 macros/netbackup.yml create mode 100644 macros/okta.yml create mode 100644 macros/s3_accesslogs.yml create mode 100644 macros/stream_http.yml create mode 100644 macros/wineventlog_system.yml create mode 100644 macros/wmi.yml diff --git a/bin/validate.py b/bin/validate.py index a8ef495b06..c96ddda5c7 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -12,6 +12,7 @@ import sys import argparse import datetime import string +import re from os import path @@ -73,7 +74,7 @@ def validate_objects(REPO_PATH, objects): errors = errors + validation_errors for object in objects['detections']: - errors = errors + validate_detection_search(object) + errors = errors + validate_detection_search(object, objects['macros']) errors = lookup_errors + errors @@ -120,14 +121,30 @@ def validate_standard_fields(object, uuids): return errors, uuids -def validate_detection_search(object): +def validate_detection_search(object, macros): errors = [] if not '_filter' in object['search']: errors.append("ERROR: Missing filter for detection: " + object['name']) - if any(x in object['search'] for x in ['eventtype=', 'sourcetype=', 'source=', 'index=']): - errors.append("ERROR: Use source macro instead of eventtype, sourcetype, source or index in detection: " + object['name']) + if any(x in object['search'] for x in ['eventtype=', 'sourcetype=', ' source=', 'index=']): + if not 'index=_internal' in object['search']: + errors.append("ERROR: Use source macro instead of eventtype, sourcetype, source or index in detection: " + object['name']) + + macros_found = re.findall('\`([^\s]+)`',object['search']) + macros_filtered = [] + for macro in macros_found: + if not '_filter' in macro and not 'security_content_ctime' in macro and not 'drop_dm_object_name' in macro: + macros_filtered.append(macro) + + for macro in macros_filtered: + found_macro = False + for macro_obj in macros: + if macro_obj['name'] == macro: + found_macro = True + + if not found_macro: + errors.append("ERROR: macro definition for " + macro + " can't be found for detection " + object['name']) return errors diff --git a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml index 77fd43238e..a9e183eb4e 100644 --- a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml @@ -10,12 +10,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Rod Soto, Splunk -search: sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" userAgent!="AWS +search: '`cloudwatch_eks` "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - | `amazon_eks_kubernetes_cluster_scan_detection_filter` + | `amazon_eks_kubernetes_cluster_scan_detection_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. tags: diff --git a/detections/amazon_eks_kubernetes_pod_scan_detection.yml b/detections/amazon_eks_kubernetes_pod_scan_detection.yml index 22d32937cf..3aabb14e7b 100644 --- a/detections/amazon_eks_kubernetes_pod_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_pod_scan_detection.yml @@ -11,12 +11,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Rod Soto, Splunk -search: sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" verb=list +search: '`cloudwatch_eks` "user.username"="system:anonymous" verb=list objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)` | `amazon_eks_kubernetes_pod_scan_detection_filter` + | `security_content_ctime(firstTime)` | `amazon_eks_kubernetes_pod_scan_detection_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. tags: diff --git a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml index 0de4cd8e0d..bd65f62686 100644 --- a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml +++ b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml @@ -14,12 +14,12 @@ how_to_implement: 'You must be ingesting Windows Security logs. You must also en type: ESCU references: [] author: Rico Valdez, Splunk -search: eventtype=wineventlog_security signature_id=4703 Process_Name=*powershell.exe +search: '`wineventlog_security` signature_id=4703 Process_Name=*powershell.exe | rex field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs as "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | `detect_mimikatz_via_powershell_and_eventcode_4703_filter` + `security_content_ctime(lastTime)` | `detect_mimikatz_via_powershell_and_eventcode_4703_filter`' known_false_positives: The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you diff --git a/detections/detect_s3_access_from_a_new_ip.yml b/detections/detect_s3_access_from_a_new_ip.yml index d9cc514509..c69412a5d8 100644 --- a/detections/detect_s3_access_from_a_new_ip.yml +++ b/detections/detect_s3_access_from_a_new_ip.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:s3:accesslogs http_status=200 [search sourcetype=aws:s3:accesslogs +search: '`s3_accesslogs` http_status=200 [search `s3_accesslogs` http_status=200 | stats earliest(_time) as firstTime latest(_time) as lastTime by bucket_name remote_ip | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by bucket_name remote_ip @@ -20,7 +20,7 @@ search: sourcetype=aws:s3:accesslogs http_status=200 [search sourcetype=aws:s3: >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | table bucket_name remote_ip]| iplocation remote_ip |rename remote_ip as src_ip | table _time bucket_name src_ip City Country operation - request_uri | `detect_s3_access_from_a_new_ip_filter` + request_uri | `detect_s3_access_from_a_new_ip_filter`' known_false_positives: S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml index 9df3868671..03020d3428 100644 --- a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -17,9 +17,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR +search: '`cloudwatch_vpc` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 - AND dest_ip!=192.168.0.0/16) [search sourcetype=aws:cloudwatchlogs:vpcflow action=blocked + AND dest_ip!=192.168.0.0/16) [search `cloudwatch_vpc` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | stats count as numberOfBlockedConnections by src_ip | inputlookup baseline_blocked_outbound_connections append=t | fields @@ -35,7 +35,7 @@ search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | table src_ip] | stats values(dest_ip) as "Blocked Destination IPs", values(interface_id) as "resourceId" count as numberOfBlockedConnections, dc(dest_ip) as uniqueDestConnections by src_ip - | `detect_spike_in_blocked_outbound_traffic_from_your_aws_filter` + | `detect_spike_in_blocked_outbound_traffic_from_your_aws_filter`' known_false_positives: The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number diff --git a/detections/extended_period_without_successful_netbackup_backups.yml b/detections/extended_period_without_successful_netbackup_backups.yml index 9375b50d86..7152f6c429 100644 --- a/detections/extended_period_without_successful_netbackup_backups.yml +++ b/detections/extended_period_without_successful_netbackup_backups.yml @@ -13,10 +13,10 @@ how_to_implement: To successfully implement this search you need to first obtain type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype="netbackup_logs" MESSAGE="Disk/Partition backup completed successfully." +search: '`netbackup` MESSAGE="Disk/Partition backup completed successfully." | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), - "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest | `extended_period_without_successful_netbackup_backups_filter` + "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest | `extended_period_without_successful_netbackup_backups_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/first_time_seen_running_windows_service.yml b/detections/first_time_seen_running_windows_service.yml index 77d9f1199b..3133099c10 100644 --- a/detections/first_time_seen_running_windows_service.yml +++ b/detections/first_time_seen_running_windows_service.yml @@ -12,8 +12,8 @@ how_to_implement: While this search does not require you to adhere to Splunk CIM type: ESCU references: [] author: David Dorsey, Splunk -search: eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name - | rename param2 as action | search action="running" [ search eventtype=wineventlog_system +search: '`wineventlog_system` signature_id=7036 | rename param1 as service_name + | rename param2 as action | search action="running" [ search `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | inputlookup append=t previously_seen_running_windows_services @@ -22,7 +22,7 @@ search: eventtype=wineventlog_system signature_id=7036 | rename param1 as servic >= relative_time(now(),"-60m@m"), "First time seen Windows service","Previously seen Windows service") | where serviceStatus="First time seen Windows service"| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table - service_name]| table _time dest service_name | `first_time_seen_running_windows_service_filter` + service_name]| table _time dest service_name | `first_time_seen_running_windows_service_filter`' known_false_positives: A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. tags: diff --git a/detections/gcp_kubernetes_cluster_scan_detection.yml b/detections/gcp_kubernetes_cluster_scan_detection.yml index c2f75b5b1b..f46adc0149 100644 --- a/detections/gcp_kubernetes_cluster_scan_detection.yml +++ b/detections/gcp_kubernetes_cluster_scan_detection.yml @@ -11,7 +11,7 @@ how_to_implement: You must install the GCP App for Splunk (version 2.0.0 or late type: ESCU references: [] author: Rod Soto, Splunk -search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp!=127.0.0.1 +search: '`google_gcp_pubnet_message` data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) @@ -19,7 +19,7 @@ search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | - `kubernetes_gcp_scan_fingerprint_detection` | `gcp_kubernetes_cluster_scan_detection_filter` + `kubernetes_gcp_scan_fingerprint_detection` | `gcp_kubernetes_cluster_scan_detection_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. tags: diff --git a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml index 878f25baa4..6eab8b8f48 100644 --- a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml +++ b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml @@ -8,12 +8,12 @@ how_to_implement: This search is specific to Okta and requires Okta logs are bei ingested in your Splunk deployment. type: ESCU author: Rico Valdez, Splunk -search: eventtype=okta_log outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country +search: '`okta` outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter` + | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter`' known_false_positives: A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise diff --git a/detections/okta_account_lockout_events.yml b/detections/okta_account_lockout_events.yml index c62059dbd0..343783d221 100644 --- a/detections/okta_account_lockout_events.yml +++ b/detections/okta_account_lockout_events.yml @@ -7,10 +7,10 @@ how_to_implement: This search is specific to Okta and requires Okta logs are bei ingested in your Splunk deployment. type: ESCU author: Rico Valdez, Splunk -search: eventtype=okta_log displayMessage="Max sign in attempts exceeded" | rename +search: '`okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, - state, city, src_ip |`okta_user_lockouts_filter` + state, city, src_ip |`okta_user_lockouts_filter`' known_false_positives: None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. diff --git a/detections/okta_failed_sso_attempts.yml b/detections/okta_failed_sso_attempts.yml index 147c69b8a1..a2f09c90d4 100644 --- a/detections/okta_failed_sso_attempts.yml +++ b/detections/okta_failed_sso_attempts.yml @@ -7,10 +7,10 @@ how_to_implement: This search is specific to Okta and requires Okta logs are bei ingested in your Splunk deployment. type: ESCU author: Rico Valdez, Splunk -search: eventtype=okta_log displayMessage="User attempted unauthorized access to app" +search: '`okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | - `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter` + `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter`' known_false_positives: There may be a faulty config preventing legitmate users from accessing apps they should have access to. tags: diff --git a/detections/okta_user_logins_from_multiple_cities.yml b/detections/okta_user_logins_from_multiple_cities.yml index 7c851a268e..017bbb457a 100644 --- a/detections/okta_user_logins_from_multiple_cities.yml +++ b/detections/okta_user_logins_from_multiple_cities.yml @@ -8,11 +8,11 @@ how_to_implement: This search is specific to Okta and requires Okta logs are bei ingested in your Splunk deployment. type: ESCU author: Rico Valdez, Splunk -search: eventtype=okta_log displayMessage="User login to Okta" client.geographicalContext.city!=null +search: '`okta` displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - |`okta_user_logins_from_multiple_cities_filter`| search locations > 1 + |`okta_user_logins_from_multiple_cities_filter`| search locations > 1' known_false_positives: Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also diff --git a/detections/suspicious_java_classes.yml b/detections/suspicious_java_classes.yml index 27c122d944..2f7d606210 100644 --- a/detections/suspicious_java_classes.yml +++ b/detections/suspicious_java_classes.yml @@ -11,11 +11,11 @@ how_to_implement: In order to properly run this search, Splunk needs to ingest d type: ESCU references: [] author: Jose Hernandez, Splunk -search: sourcetype="stream:http" http_method=POST http_content_length>1 | regex form_data="(?i)java\.lang\.(?:runtime|processbuilder)" +search: '`stream_http` http_method=POST http_content_length>1 | regex form_data="(?i)java\.lang\.(?:runtime|processbuilder)" | rename src_ip as src | stats count earliest(_time) as firstTime, latest(_time) as lastTime, values(url) as uri, values(status) as status, values(http_user_agent) as http_user_agent by src, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | `suspicious_java_classes_filter` + | `suspicious_java_classes_filter`' known_false_positives: There are no known false positives. tags: analytics_story: diff --git a/detections/suspicious_writes_to_system_volume_information.yml b/detections/suspicious_writes_to_system_volume_information.yml index 1ca613c4b9..174a3a5088 100644 --- a/detections/suspicious_writes_to_system_volume_information.yml +++ b/detections/suspicious_writes_to_system_volume_information.yml @@ -10,10 +10,10 @@ how_to_implement: You need to be ingesting logs with both the process name and c type: ESCU references: [] author: Rico Valdez, Splunk -search: (sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational OR tag=process) +search: '(`sysmon` OR tag=process) EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | `suspicious_writes_to_system_volume_information_filter` + `security_content_ctime(lastTime)` | `suspicious_writes_to_system_volume_information_filter`' known_false_positives: It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. diff --git a/detections/unsuccessful_netbackup_backups.yml b/detections/unsuccessful_netbackup_backups.yml index 92545cd594..1bccc9e63f 100644 --- a/detections/unsuccessful_netbackup_backups.yml +++ b/detections/unsuccessful_netbackup_backups.yml @@ -11,10 +11,10 @@ how_to_implement: To successfully implement this search you need to obtain data type: ESCU references: [] author: David Dorsey, Splunk -search: sourcetype="netbackup_logs" | stats latest(_time) as latestTime by COMPUTERNAME, +search: '`netbackup` | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature - | `unsuccessful_netbackup_backups_filter` + | `unsuccessful_netbackup_backups_filter`' known_false_positives: None identified tags: analytics_story: diff --git a/detections/windows_event_log_cleared.yml b/detections/windows_event_log_cleared.yml index bd980c2857..823eca0c50 100644 --- a/detections/windows_event_log_cleared.yml +++ b/detections/windows_event_log_cleared.yml @@ -9,10 +9,10 @@ how_to_implement: To successfully implement this search, you need to be ingestin type: ESCU references: [] author: Rico Valdez, Splunk -search: ((eventtype=wineventlog_security) AND (signature_id=1102 OR signature_id=1100)) - OR ((eventtype=wineventlog_system) AND signature_id=104) | stats count min(_time) +search: '(`wineventlog_security` signature_id=1102 OR signature_id=1100) + OR (`wineventlog_system` signature_id=104) | stats count min(_time) as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `windows_event_log_cleared_filter` + | `security_content_ctime(lastTime)` | `windows_event_log_cleared_filter`' known_false_positives: It is possible that these logs may be legitimately cleared by Administrators. tags: diff --git a/detections/wmi_permanent_event_subscription.yml b/detections/wmi_permanent_event_subscription.yml index 6fa89ded62..78e2f25f26 100644 --- a/detections/wmi_permanent_event_subscription.yml +++ b/detections/wmi_permanent_event_subscription.yml @@ -9,11 +9,11 @@ how_to_implement: To successfully implement this search, you must be ingesting t type: ESCU references: [] author: Rico Valdez, Splunk -search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" EventCode=5861 +search: '`wmi` EventCode=5861 Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" | search consumer!="NTEventLogEventConsumer=\"SCM Event Log Consumer\"" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | rename ComputerName as dest | `wmi_permanent_event_subscription_filter` + | rename ComputerName as dest | `wmi_permanent_event_subscription_filter`' known_false_positives: Although unlikely, administrators may use event subscriptions for legitimate purposes. tags: diff --git a/detections/wmi_permanent_event_subscription___sysmon.yml b/detections/wmi_permanent_event_subscription___sysmon.yml index cca3b4788d..58f9a42fd5 100644 --- a/detections/wmi_permanent_event_subscription___sysmon.yml +++ b/detections/wmi_permanent_event_subscription___sysmon.yml @@ -10,9 +10,9 @@ how_to_implement: To successfully implement this search, you must be collecting type: ESCU references: [] author: Rico Valdez, Splunk -search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode=21 +search: '`sysmon` EventCode=21 | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, - Filter | `wmi_permanent_event_subscription___sysmon_filter` + Filter | `wmi_permanent_event_subscription___sysmon_filter`' known_false_positives: Although unlikely, administrators may use event subscriptions for legitimate purposes. tags: diff --git a/detections/wmi_temporary_event_subscription.yml b/detections/wmi_temporary_event_subscription.yml index 197c6a427e..fde26876b8 100644 --- a/detections/wmi_temporary_event_subscription.yml +++ b/detections/wmi_temporary_event_subscription.yml @@ -9,13 +9,11 @@ how_to_implement: To successfully implement this search, you must be ingesting t type: ESCU references: [] author: Rico Valdez, Splunk -search: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" EventCode=5860 - Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" | search - query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = 'wsmprovhost.exe'" - AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' - OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'" +search: '`wmi` EventCode=5860 Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" | search query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = wsmprovhost.exe" + AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA AntiVirusProduct + OR TargetInstance ISA FirewallProduct OR TargetInstance ISA AntiSpywareProduct" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | - `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `wmi_temporary_event_subscription_filter` + `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `wmi_temporary_event_subscription_filter`' known_false_positives: Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to diff --git a/macros/cloudwatch_eks.yml b/macros/cloudwatch_eks.yml new file mode 100644 index 0000000000..5a8dcca164 --- /dev/null +++ b/macros/cloudwatch_eks.yml @@ -0,0 +1,3 @@ +definition: sourcetype="aws:cloudwatchlogs:eks" +description: customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch eks logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: cloudwatch_eks diff --git a/macros/cloudwatch_vpc.yml b/macros/cloudwatch_vpc.yml new file mode 100644 index 0000000000..1c8bd5d11b --- /dev/null +++ b/macros/cloudwatch_vpc.yml @@ -0,0 +1,3 @@ +definition: sourcetype=aws:cloudwatchlogs:vpcflow +description: customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch vpc logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: cloudwatch_vpc diff --git a/macros/google_gcp_pubnet_message.yml b/macros/google_gcp_pubnet_message.yml new file mode 100644 index 0000000000..e8de3e401e --- /dev/null +++ b/macros/google_gcp_pubnet_message.yml @@ -0,0 +1,3 @@ +definition: sourcetype="google:gcp:pubsub:message" +description: customer specific splunk configurations(eg- index, source, sourcetype) for Google GCP. Replace the macro definition with configurations for your Splunk Environmnent. +name: google_gcp_pubnet_message diff --git a/macros/netbackup.yml b/macros/netbackup.yml new file mode 100644 index 0000000000..8f2b1198f9 --- /dev/null +++ b/macros/netbackup.yml @@ -0,0 +1,3 @@ +definition: sourcetype="netbackup_logs" +description: customer specific splunk configurations(eg- index, source, sourcetype) for netbackup logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: netbackup diff --git a/macros/okta.yml b/macros/okta.yml new file mode 100644 index 0000000000..4df962bce0 --- /dev/null +++ b/macros/okta.yml @@ -0,0 +1,3 @@ +definition: eventtype=okta_log +description: customer specific splunk configurations(eg- index, source, sourcetype) for WMI logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: okta diff --git a/macros/s3_accesslogs.yml b/macros/s3_accesslogs.yml new file mode 100644 index 0000000000..5bf66bb4e5 --- /dev/null +++ b/macros/s3_accesslogs.yml @@ -0,0 +1,3 @@ +definition: sourcetype=aws:s3:accesslogs +description: customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch vpc logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: s3_accesslogs diff --git a/macros/stream_http.yml b/macros/stream_http.yml new file mode 100644 index 0000000000..a6237def58 --- /dev/null +++ b/macros/stream_http.yml @@ -0,0 +1,3 @@ +definition: sourcetype=stream:http +description: customer specific splunk configurations(eg- index, source, sourcetype) for Stream HTTP logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: stream_http diff --git a/macros/wineventlog_system.yml b/macros/wineventlog_system.yml new file mode 100644 index 0000000000..968871810c --- /dev/null +++ b/macros/wineventlog_system.yml @@ -0,0 +1,3 @@ +definition: eventtype="wineventlog_system" +description: Customer specific splunk configurations(eg- index, source, sourcetype) for Windows Event Logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: wineventlog_system diff --git a/macros/wmi.yml b/macros/wmi.yml new file mode 100644 index 0000000000..dbef80c1cd --- /dev/null +++ b/macros/wmi.yml @@ -0,0 +1,3 @@ +definition: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" +description: customer specific splunk configurations(eg- index, source, sourcetype) for WMI logs. Replace the macro definition with configurations for your Splunk Environmnent. +name: wmi From 2ee6da2cdab2a640d8991bdd8cc42c55e5d43e54 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 30 Apr 2020 16:56:33 +0200 Subject: [PATCH 10/93] validate script --- bin/validate.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bin/validate.py b/bin/validate.py index c96ddda5c7..e2af332028 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -134,7 +134,7 @@ def validate_detection_search(object, macros): macros_found = re.findall('\`([^\s]+)`',object['search']) macros_filtered = [] for macro in macros_found: - if not '_filter' in macro and not 'security_content_ctime' in macro and not 'drop_dm_object_name' in macro: + if not '_filter' in macro and not 'security_content_ctime' in macro and not 'drop_dm_object_name' in macro and not 'cim_' in macro and not 'get_' in macro: macros_filtered.append(macro) for macro in macros_filtered: From f1b70e5d1464fc91dd477cdbc48adbc3c7275046 Mon Sep 17 00:00:00 2001 From: bpatel Date: Thu, 30 Apr 2020 14:02:16 -0700 Subject: [PATCH 11/93] adding a required item in spec --- spec/baselines.spec.json | 18 ++- spec/detections.spec.json | 310 +++++++++++++++++++------------------- spec/responses.spec.json | 4 +- spec/stories.spec.json | 4 +- 4 files changed, 172 insertions(+), 164 deletions(-) diff --git a/spec/baselines.spec.json b/spec/baselines.spec.json index f2251ef129..7c92b3e937 100644 --- a/spec/baselines.spec.json +++ b/spec/baselines.spec.json @@ -32,13 +32,13 @@ "type": "string" }, "how_to_implement": { - "$id": "#/properties/how_to_implement", - "type": "string", - "description": "information about how to implement. Only needed for non standard implementations.", - "default": "", - "examples": [ - "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." - ] + "$id": "#/properties/how_to_implement", + "default": "", + "description": "information about how to implement. Only needed for non standard implementations.", + "examples": [ + "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." + ], + "type": "string" }, "id": { "$id": "#/properties/id", @@ -79,7 +79,9 @@ } ], "minItems": 1, - "required": [], + "required": [ + "analytics_story" + ], "type": "object", "uniqueItems": true }, diff --git a/spec/detections.spec.json b/spec/detections.spec.json index 56dd2242a1..fdef6a495a 100644 --- a/spec/detections.spec.json +++ b/spec/detections.spec.json @@ -1,158 +1,160 @@ { - "$schema": "http://json-schema.org/draft-07/schema", - "$id": "http://example.com/example.json", - "type": "object", - "title": "Detection Schema", - "description": "schema for detections", - "additionalProperties": true, - "required": [ - "name", - "id", - "version", - "date", - "description", - "type", - "author", - "search", - "known_false_positives", - "tags" - ], - "properties": { - "name": { - "$id": "#/properties/name", - "type": "string", - "title": "Name of detection", - "default": "", - "examples": [ - "Access LSASS Memory for Dump Creation" - ] - }, - "id": { - "$id": "#/properties/id", - "type": "string", - "description": "UUID as unique identifier", - "default": "", - "examples": [ - "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" - ] - }, - "version": { - "$id": "#/properties/version", - "type": "integer", - "description": "version of detection, e.g. 1 or 2 ...", - "default": 0, - "examples": [ - 2 - ] - }, - "date": { - "$id": "#/properties/date", - "type": "string", - "description": "date of creation or modification, format yyyy-mm-dd", - "default": "", - "examples": [ - "2019-12-06" - ] - }, - "description": { - "$id": "#/properties/description", - "type": "string", - "description": "A detailed description of the detection", - "default": "", - "examples": [ - "dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump." - ] - }, - "how_to_implement": { - "$id": "#/properties/how_to_implement", - "type": "string", - "description": "information about how to implement. Only needed for non standard implementations.", - "default": "", - "examples": [ - "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." - ] - }, - "type": { - "$id": "#/properties/type", - "type": "string", - "description": "type of detection", - "default": "", - "examples": [ - "ESCU" - ], - "items": { - "enum": [ - "ESCU", - "SSE", - "RBA" - ], - "type": "string" - } - }, - "references": { - "$id": "#/properties/references", - "type": "array", - "description": "A list of references for this detection", - "default": [], - "examples": [ - [ - "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" - ] - ], - "additionalItems": true, - "items": { - "$id": "#/properties/references/items", - "type": "string", - "title": "The Items Schema", - "description": "An explanation about the purpose of this instance.", - "default": "", - "examples": [ - "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" - ] - } - }, - "author": { - "$id": "#/properties/author", - "type": "string", - "description": "Author of the detection", - "default": "", - "examples": [ - "Patrick Bareiss, Splunk" - ] - }, - "search": { - "$id": "#/properties/search", - "type": "string", - "description": "The Splunk search for the detection", - "default": "", - "examples": [ - "`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter`" - ] - }, - "known_false_positives": { - "$id": "#/properties/knwon_false_positives", - "type": "string", - "description": "known false postives", - "default": "", - "examples": [ - "Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual." - ] - }, - "tags": { - "$id": "#/properties/tags", - "type": "object", - "description": "An array of key value pairs for tagging", - "default": {}, - "examples": [ - { - "custom_key": "custom_value", - "analytics_story": "credential_dumping" - } - ], - "additionalProperties": true, - "required": [], - "minItems": 1, - "uniqueItems": true + "$id": "http://example.com/example.json", + "$schema": "http://json-schema.org/draft-07/schema", + "additionalProperties": true, + "description": "schema for detections", + "properties": { + "author": { + "$id": "#/properties/author", + "default": "", + "description": "Author of the detection", + "examples": [ + "Patrick Bareiss, Splunk" + ], + "type": "string" + }, + "date": { + "$id": "#/properties/date", + "default": "", + "description": "date of creation or modification, format yyyy-mm-dd", + "examples": [ + "2019-12-06" + ], + "type": "string" + }, + "description": { + "$id": "#/properties/description", + "default": "", + "description": "A detailed description of the detection", + "examples": [ + "dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump." + ], + "type": "string" + }, + "how_to_implement": { + "$id": "#/properties/how_to_implement", + "default": "", + "description": "information about how to implement. Only needed for non standard implementations.", + "examples": [ + "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." + ], + "type": "string" + }, + "id": { + "$id": "#/properties/id", + "default": "", + "description": "UUID as unique identifier", + "examples": [ + "fb4c31b0-13e8-4155-8aa5-24de4b8d6717" + ], + "type": "string" + }, + "known_false_positives": { + "$id": "#/properties/knwon_false_positives", + "default": "", + "description": "known false postives", + "examples": [ + "Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual." + ], + "type": "string" + }, + "name": { + "$id": "#/properties/name", + "default": "", + "examples": [ + "Access LSASS Memory for Dump Creation" + ], + "title": "Name of detection", + "type": "string" + }, + "references": { + "$id": "#/properties/references", + "additionalItems": true, + "default": [], + "description": "A list of references for this detection", + "examples": [ + [ + "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" + ] + ], + "items": { + "$id": "#/properties/references/items", + "default": "", + "description": "An explanation about the purpose of this instance.", + "examples": [ + "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" + ], + "title": "The Items Schema", + "type": "string" + }, + "type": "array" + }, + "search": { + "$id": "#/properties/search", + "default": "", + "description": "The Splunk search for the detection", + "examples": [ + "`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter`" + ], + "type": "string" + }, + "tags": { + "$id": "#/properties/tags", + "additionalProperties": true, + "default": {}, + "description": "An array of key value pairs for tagging", + "examples": [ + { + "analytics_story": "credential_dumping", + "custom_key": "custom_value" } + ], + "minItems": 1, + "required": [ + "analytics_story" + ], + "type": "object", + "uniqueItems": true + }, + "type": { + "$id": "#/properties/type", + "default": "", + "description": "type of detection", + "examples": [ + "ESCU" + ], + "items": { + "enum": [ + "ESCU", + "SSE", + "RBA" + ], + "type": "string" + }, + "type": "string" + }, + "version": { + "$id": "#/properties/version", + "default": 0, + "description": "version of detection, e.g. 1 or 2 ...", + "examples": [ + 2 + ], + "type": "integer" } + }, + "required": [ + "name", + "id", + "version", + "date", + "description", + "type", + "author", + "search", + "known_false_positives", + "tags" + ], + "title": "Detection Schema", + "type": "object" } diff --git a/spec/responses.spec.json b/spec/responses.spec.json index 8779c28b81..abcf3a09d5 100644 --- a/spec/responses.spec.json +++ b/spec/responses.spec.json @@ -89,7 +89,9 @@ } ], "minItems": 1, - "required": [], + "required": [ + "analytics_story" + ], "type": "object", "uniqueItems": true }, diff --git a/spec/stories.spec.json b/spec/stories.spec.json index 983433b9a3..3e408f1dfd 100644 --- a/spec/stories.spec.json +++ b/spec/stories.spec.json @@ -79,7 +79,9 @@ } ], "minItems": 1, - "required": [], + "required": [ + "analytics_story" + ], "type": "object" }, "version": { From d51b7ae9910f54844134a5b94a75bbfd44951a04 Mon Sep 17 00:00:00 2001 From: bpatel Date: Thu, 30 Apr 2020 14:15:23 -0700 Subject: [PATCH 12/93] validate now passes responses --- spec/responses.spec.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/spec/responses.spec.json b/spec/responses.spec.json index abcf3a09d5..db57d906e4 100644 --- a/spec/responses.spec.json +++ b/spec/responses.spec.json @@ -75,7 +75,7 @@ ] } ], - "required": [], + "minItems": 1, "type": "array" }, "tags": { From 0de08a0f8e31c3dc677d7731130405eaf3bf918b Mon Sep 17 00:00:00 2001 From: bpatel Date: Thu, 30 Apr 2020 14:25:09 -0700 Subject: [PATCH 13/93] removing required[] from tags --- spec/baselines.spec.json | 3 --- spec/deployments.spec.json | 1 - spec/detections.spec.json | 3 --- spec/responses.spec.json | 3 --- spec/stories.spec.json | 3 --- 5 files changed, 13 deletions(-) diff --git a/spec/baselines.spec.json b/spec/baselines.spec.json index 7c92b3e937..c13fc47497 100644 --- a/spec/baselines.spec.json +++ b/spec/baselines.spec.json @@ -79,9 +79,6 @@ } ], "minItems": 1, - "required": [ - "analytics_story" - ], "type": "object", "uniqueItems": true }, diff --git a/spec/deployments.spec.json b/spec/deployments.spec.json index 4d39ef8d8b..c417cc0bf3 100644 --- a/spec/deployments.spec.json +++ b/spec/deployments.spec.json @@ -246,7 +246,6 @@ } ], "minItems": 1, - "required": [], "type": "object", "uniqueItems": true } diff --git a/spec/detections.spec.json b/spec/detections.spec.json index fdef6a495a..9f9fc25482 100644 --- a/spec/detections.spec.json +++ b/spec/detections.spec.json @@ -110,9 +110,6 @@ } ], "minItems": 1, - "required": [ - "analytics_story" - ], "type": "object", "uniqueItems": true }, diff --git a/spec/responses.spec.json b/spec/responses.spec.json index db57d906e4..f14d63f109 100644 --- a/spec/responses.spec.json +++ b/spec/responses.spec.json @@ -89,9 +89,6 @@ } ], "minItems": 1, - "required": [ - "analytics_story" - ], "type": "object", "uniqueItems": true }, diff --git a/spec/stories.spec.json b/spec/stories.spec.json index 3e408f1dfd..3eda58b394 100644 --- a/spec/stories.spec.json +++ b/spec/stories.spec.json @@ -79,9 +79,6 @@ } ], "minItems": 1, - "required": [ - "analytics_story" - ], "type": "object" }, "version": { From d820e022b7328713b7bd08894ea3725572f4278b Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 5 May 2020 08:59:14 +0200 Subject: [PATCH 14/93] WIP: generate script --- bin/generate.py | 67 ++++++++++++++++++++++++++----------------------- 1 file changed, 36 insertions(+), 31 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index ee2f245d1c..118cbe2d6c 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -56,6 +56,9 @@ def generate_transforms_conf(lookups): def generate_savedsearches_conf(detections, investigations, baselines): + # mapping from source macro or datamodel to providing_technologies + # parse out entities dest, user + utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), @@ -323,40 +326,42 @@ if __name__ == "__main__": stories = load_objects("stories/*.yml") macros = load_objects("macros/*.yml") lookups = load_objects("lookups/*.yml") - detections = load_objects("detections/*.yml") - investigations = load_objects("investigations/*.yml") baselines = load_objects("baselines/*.yml") + detections = load_objects("detections/*.yml") + responses = load_objects("responses/*.yml") + response_tasks = load_objects("response_tasks/*.yml") + investigations = load_objects("investigations/*.yml") - detections = identify_next_steps(detections, investigations) - - map_inv_det = map_investigations_to_detection(detections) - map_det_sto = map_detection_to_stories(stories) - map_bas_det = map_baselines_to_detection(detections) - detections = enrich_detections_with_stories(detections, map_det_sto) - investigations = enrich_investigations_with_stories(investigations, map_inv_det, map_det_sto) - baselines = enrich_baselines_with_stories(baselines, map_bas_det, map_det_sto) - stories = enrich_stories(stories, detections, investigations, baselines) + # detections = identify_next_steps(detections, investigations) + # + # map_inv_det = map_investigations_to_detection(detections) + # map_det_sto = map_detection_to_stories(stories) + # map_bas_det = map_baselines_to_detection(detections) + # detections = enrich_detections_with_stories(detections, map_det_sto) + # investigations = enrich_investigations_with_stories(investigations, map_inv_det, map_det_sto) + # baselines = enrich_baselines_with_stories(baselines, map_bas_det, map_det_sto) + # stories = enrich_stories(stories, detections, investigations, baselines) lookups_path = generate_transforms_conf(lookups) detections = sorted(detections, key=lambda d: d['name']) - investigations = sorted(investigations, key=lambda i: i['name']) - baselines = sorted(baselines, key=lambda b: b['name']) - detection_path = generate_savedsearches_conf(detections, investigations, baselines) - - stories = sorted(stories, key=lambda s: s['name']) - story_path = generate_analytics_story_conf(stories) - - use_case_lib_path = generate_use_case_library_conf(stories, detections, investigations, baselines) - - macros = sorted(macros, key=lambda m: m['name']) - macros_path = generate_macros_conf(macros) - - if VERBOSE: - print("{0} stories have been successfully written to {1}".format(len(stories), story_path)) - print("{0} stories have been successfully written to {1}".format(len(stories), use_case_lib_path)) - print("{0} detections have been successfully written to {1}".format(len(detections), detection_path)) - print("{0} investigations have been successfully written to {1}".format(len(investigations), detection_path)) - print("{0} baselines have been successfully written to {1}".format(len(baselines), detection_path)) - print("{0} macros have been successfully written to {1}".format(len(macros), macros_path)) - print("security content generation completed..") + # investigations = sorted(investigations, key=lambda i: i['name']) + # baselines = sorted(baselines, key=lambda b: b['name']) + # detection_path = generate_savedsearches_conf(detections, investigations, baselines) + # + # stories = sorted(stories, key=lambda s: s['name']) + # story_path = generate_analytics_story_conf(stories) + # + # use_case_lib_path = generate_use_case_library_conf(stories, detections, investigations, baselines) + # + # macros = sorted(macros, key=lambda m: m['name']) + # macros_path = generate_macros_conf(macros) + # + # if VERBOSE: + # print("{0} stories have been successfully written to {1}".format(len(stories), story_path)) + # print("{0} stories have been successfully written to {1}".format(len(stories), use_case_lib_path)) + # print("{0} detections have been successfully written to {1}".format(len(detections), detection_path)) + # print("{0} investigations have been successfully written to {1}".format(len(investigations), detection_path)) + # print("{0} baselines have been successfully written to {1}".format(len(baselines), detection_path)) + # print("{0} macros have been successfully written to {1}".format(len(macros), macros_path)) + # print("security content generation completed..") From cc464c87dbef658a3a3faf85d7303f503d6470da Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 5 May 2020 12:58:56 +0200 Subject: [PATCH 15/93] updated content --- ...e_of_blocked_outbound_traffic_from_aws.yml | 10 +- ..._list_of_approved_aws_service_accounts.yml | 6 +- baselines/dnstwist_domain_names.yml | 2 +- baselines/monitor_successful_backups.yml | 6 +- baselines/monitor_unsuccessful_backups.yml | 5 +- ...iously_seen_aws_cross_account_activity.yml | 11 +- ...seen_aws_provisioning_activity_sources.yml | 8 +- baselines/previously_seen_aws_regions.yml | 5 +- ...previously_seen_command_line_arguments.yml | 2 +- baselines/previously_seen_ec2_amis.yml | 7 +- .../previously_seen_ec2_instance_types.yml | 8 +- .../previously_seen_ec2_launches_by_user.yml | 6 +- ...viously_seen_ec2_modifications_by_user.yml | 7 +- ...eviously_seen_running_windows_services.yml | 6 +- ...sly_seen_s3_bucket_access_by_remote_ip.yml | 6 +- .../previously_seen_users_in_cloudtrail.yml | 15 +- ...te_previously_seen_users_in_cloudtrail.yml | 18 +- bin/converter_v2_v3.py | 324 ++++++++++++++++++ bin/validate.py | 35 +- ...ly_high_aws_instances_launched_by_user.yml | 9 +- ..._aws_instances_launched_by_user___mltk.yml | 1 + ..._high_aws_instances_terminated_by_user.yml | 19 +- ...ws_instances_terminated_by_user___mltk.yml | 1 + .../access_lsass_memory_for_dump_creation.yml | 1 + ..._eks_kubernetes_cluster_scan_detection.yml | 5 +- ...azon_eks_kubernetes_pod_scan_detection.yml | 14 +- ..._to_add_certificate_to_untrusted_store.yml | 1 + ...ution_policy_to_unrestricted_or_bypass.yml | 1 + .../attempt_to_stop_security_service.yml | 1 + ...ential_dump_from_registry_via_reg_exe.yml} | 3 +- ...ovisioning_from_previously_unseen_city.yml | 22 +- ...sioning_from_previously_unseen_country.yml | 15 +- ...ning_from_previously_unseen_ip_address.yml | 4 +- ...isioning_from_previously_unseen_region.yml | 18 +- ...ctivity_from_previously_unseen_account.yml | 14 +- ...ntrol_list_created_with_all_open_ports.yml | 1 + ...ws_network_access_control_list_deleted.yml | 5 +- detections/batch_file_write_to_system32.yml | 1 + ...yml => child_processes_of_spoolsv_exe.yml} | 3 +- ...nts_connecting_to_multiple_dns_servers.yml | 3 +- ...ance_created_by_previously_unseen_user.yml | 1 + ...e_created_with_previously_unseen_image.yml | 1 + ...d_with_previously_unseen_instance_type.yml | 1 + ...ce_started_in_previously_unused_region.yml | 1 + detections/common_ransomware_extensions.yml | 1 + detections/common_ransomware_notes.yml | 1 + ...te_local_admin_accounts_using_net_exe.yml} | 3 +- ...r_delete_windows_shares_using_net_exe.yml} | 3 +- .../create_remote_thread_into_lsass.yml | 1 + detections/creation_of_shadow_copy.yml | 1 + ...f_shadow_copy_with_wmic_and_powershell.yml | 1 + ...ping_via_copy_command_from_shadow_copy.yml | 1 + ...ial_dumping_via_symlink_to_shadow_copy.yml | 1 + detections/deleting_shadow_copies.yml | 3 +- ...ivity_related_to_pass_the_hash_attacks.yml | 1 + ...ct_api_activity_from_users_without_mfa.yml | 1 + ..._scanning_for_vulnerable_jboss_servers.yml | 3 +- ...pi_activities_from_unapproved_accounts.yml | 11 +- ...ws_console_login_by_user_from_new_city.yml | 1 + ...console_login_by_user_from_new_country.yml | 1 + ..._console_login_by_user_from_new_region.yml | 1 + ...redential_dumping_through_LSASS_access.yml | 1 + ...to_phishing_sites_leveraging_evilginx2.yml | 1 + ...cessive_account_lockouts_from_endpoint.yml | 1 + ...detect_excessive_user_account_lockouts.yml | 1 + ...connecting_to_dynamic_domain_providers.yml | 9 +- .../detect_large_outbound_icmp_packets.yml | 1 + .../detect_long_dns_txt_record_response.yml | 1 + ...ious_requests_to_exploit_jboss_servers.yml | 3 +- .../detect_mimikatz_using_loaded_images.yml | 1 + ...katz_via_powershell_and_eventcode_4703.yml | 13 +- ...ing_scripts_in_command_line_arguments.yml} | 5 +- .../detect_new_api_calls_from_user_roles.yml | 1 + detections/detect_new_local_admin_account.yml | 5 +- .../detect_new_login_attempts_to_routers.yml | 1 + detections/detect_new_open_s3_buckets.yml | 1 + .../detect_new_user_aws_console_login.yml | 12 +- ...detect_oulook_exe_writing_a__zip_file.yml} | 3 +- detections/detect_outbound_smb_traffic.yml | 1 + ...terception_by_creation_of_program_exe.yml} | 5 +- ...system_network_configuration_discovery.yml | 1 + ...hibited_applications_spawning_cmd_exe.yml} | 7 +- .../detect_psexec_with_accepteula_flag.yml | 1 + detections/detect_rare_executables.yml | 1 + detections/detect_s3_access_from_a_new_ip.yml | 18 +- .../detect_spike_in_aws_api_activity.yml | 29 +- ...blocked_outbound_traffic_from_your_aws.yml | 16 +- .../detect_spike_in_network_acl_activity.yml | 11 +- .../detect_spike_in_s3_bucket_deletion.yml | 30 +- ...etect_spike_in_security_group_activity.yml | 11 +- ...ect_unauthorized_assets_by_mac_address.yml | 1 + detections/detect_usb_device_insertion.yml | 1 + ...cmd_exe_to_launch_script_interpreters.yml} | 7 +- ...eb_traffic_to_dynamic_domain_providers.yml | 1 + detections/detection_of_dns_tunnels.yml | 1 + .../detection_of_tools_built_by_nirsoft.yml | 1 + .../disabling_remote_user_account_control.yml | 3 +- .../dns_query_length_outliers___mltk.yml | 3 +- ...ry_length_with_high_standard_deviation.yml | 3 +- ...s_resolved_by_unauthorized_dns_servers.yml | 3 +- detections/dns_record_changed.yml | 1 + detections/dump_lsass_via_comsvcs_dll.yml | 1 + ...e_modified_with_previously_unseen_user.yml | 16 +- ...ce_started_in_previously_unseen_region.yml | 5 +- ...nce_started_with_previously_unseen_ami.yml | 7 +- ...d_with_previously_unseen_instance_type.yml | 7 +- ...ce_started_with_previously_unseen_user.yml | 16 +- .../email_attachments_with_lots_of_spaces.yml | 1 + ...itten_outside_of_the_outlook_directory.yml | 1 + ...s_sending_high_volume_traffic_to_hosts.yml | 1 + detections/excessive_dns_failures.yml | 1 + ...ution_of_file_with_multiple_extensions.yml | 1 + ...n_of_file_with_spaces_before_extension.yml | 1 + ...d_without_successful_netbackup_backups.yml | 5 +- detections/file_with_samsam_extension.yml | 1 + .../first_time_seen_command_line_argument.yml | 7 +- ...irst_time_seen_running_windows_service.yml | 5 +- detections/gcp_gcr_container_uploaded.yml | 1 + .../gcp_kubernetes_cluster_scan_detection.yml | 3 +- ...files_and_directories_with_attrib_exe.yml} | 3 +- ...e_of_network_traffic_from_email_server.yml | 1 + detections/identify_new_user_accounts.yml | 1 + .../large_volume_of_dns_any_queries.yml | 1 + detections/macos___re_opened_applications.yml | 1 + ...connect_to_internet_with_hidden_window.yml | 1 + ...s_powershell_process___encoded_command.yml | 1 + ...hell_process___execution_policy_bypass.yml | 1 + ...iple_suspicious_command_line_arguments.yml | 1 + ...ll_process_with_obfuscation_techniques.yml | 1 + detections/monitor_dns_for_brand_abuse.yml | 1 + detections/monitor_email_for_brand_abuse.yml | 1 + ...nitor_registry_keys_for_print_monitors.yml | 1 + .../monitor_web_traffic_for_brand_abuse.yml | 1 + ...h_invalid_credentails_from_the_same_ip.yml | 1 + .../new_container_uploaded_to_aws_ecr.yml | 1 + .../no_windows_updates_in_a_time_frame.yml | 1 + detections/okta_account_lockout_events.yml | 8 +- detections/okta_failed_sso_attempts.yml | 8 +- .../okta_user_logins_from_multiple_cities.yml | 1 + detections/open_redirect_in_splunk_web.yml | 1 + .../osquery_pack___coldroot_detection.yml | 1 + .../overwriting_accessibility_binaries.yml | 1 + detections/process_execution_via_wmi.yml | 1 + detections/processes_created_by_netsh.yml | 1 + detections/processes_launching_netsh.yml | 3 +- .../processes_tapping_keyboard_events.yml | 1 + .../prohibited_network_traffic_allowed.yml | 3 +- .../prohibited_software_on_endpoint.yml | 1 + detections/protocol_or_port_mismatch.yml | 1 + ...ls_passing_authentication_in_cleartext.yml | 1 + ...lating_windows_services_registry_keys.yml} | 5 +- ...e_files_directories_via_registry_keys.yml} | 7 +- ...istry_keys_for_creating_shim_databases.yml | 1 + .../registry_keys_used_for_persistence.yml | 11 +- ...try_keys_used_for_privilege_escalation.yml | 3 +- .../remote_desktop_network_bruteforce.yml | 1 + detections/remote_desktop_network_traffic.yml | 3 +- ...mote_desktop_process_running_on_system.yml | 1 + .../remote_process_instantiation_via_wmi.yml | 1 + .../remote_registry_key_modifications.yml | 3 +- detections/remote_wmi_command_attempt.yml | 1 + detections/rundll_loading_dll_by_ordinal.yml | 1 + detections/samsam_test_file_write.yml | 1 + ... sc_exe_manipulating_windows_services.yml} | 13 +- ...k_name_used_by_dragonfly_threat_actors.yml | 1 + ...led_tasks_used_in_badrabbit_ransomware.yml | 1 + ...htasks_scheduling_job_on_remote_system.yml | 1 + .../schtasks_used_for_forcing_a_reboot.yml | 3 +- detections/script_execution_via_wmi.yml | 1 + detections/shim_database_file_creation.yml | 1 + ...nstallation_with_suspicious_parameters.yml | 1 + detections/short_lived_windows_accounts.yml | 1 + .../single_letter_process_on_endpoint.yml | 1 + detections/smb_traffic_spike.yml | 7 +- detections/smb_traffic_spike___mltk.yml | 7 +- ...pectre_and_meltdown_vulnerable_systems.yml | 1 + detections/spike_in_file_writes.yml | 1 + ...lunk_enterprise_information_disclosure.yml | 1 + detections/sql_injection_with_long_urls.yml | 1 + ...uspicious_changes_to_file_associations.yml | 3 +- detections/suspicious_email___uba_anomaly.yml | 1 + ...suspicious_email_attachment_extensions.yml | 1 + detections/suspicious_file_write.yml | 1 + detections/suspicious_java_classes.yml | 1 + ...uspicious_lnk_file_launching_a_process.yml | 1 + ...ess.yml => suspicious_reg_exe_process.yml} | 7 +- detections/suspicious_wevtutil_usage.yml | 3 +- ...us_writes_to_system_volume_information.yml | 9 +- ...spicious_writes_to_windows_recycle_bin.yml | 1 + ...rocesses_run_from_unexpected_locations.yml | 3 +- detections/tor_traffic.yml | 3 +- detections/uncommon_processes_on_endpoint.yml | 3 +- detections/unload_sysmon_filter_driver.yml | 1 + detections/unsigned_image_loaded_by_LSASS.yml | 1 + detections/unsuccessful_netbackup_backups.yml | 5 +- detections/unusually_long_command_line.yml | 3 +- .../unusually_long_command_line___mltk.yml | 3 +- .../unusually_long_content_type_length.yml | 5 +- detections/usn_journal_deletion.yml | 3 +- detections/web_fraud___account_harvesting.yml | 1 + .../web_fraud___anomalous_user_clickspeed.yml | 1 + ...aud___password_sharing_across_accounts.yml | 1 + ...servers_executing_suspicious_processes.yml | 1 + detections/windows_event_log_cleared.yml | 11 +- .../windows_hosts_file_modification.yml | 1 + .../wmi_permanent_event_subscription.yml | 9 +- ..._permanent_event_subscription___sysmon.yml | 6 +- .../wmi_temporary_event_subscription.yml | 8 +- macros/aws_cloudwatchlogs_eks.yml | 4 + macros/aws_s3_accesslogs.yml | 4 + macros/cloudtrail.yml | 5 +- macros/cloudwatchlogs_vpcflow.yml | 4 + macros/google_gcp_pubsub_message.yml | 4 + macros/netbackup.yml | 5 +- macros/okta.yml | 5 +- macros/stream_http.yml | 5 +- macros/sysmon.yml | 5 +- macros/wineventlog_security.yml | 5 +- macros/wineventlog_system.yml | 5 +- macros/wmi.yml | 5 +- requirements.txt | 39 ++- ...stigate_user_activities_by_accesskeyid.yml | 2 +- ...aws_investigate_user_activities_by_arn.yml | 2 +- ...stigate_user_activities_by_source_user.yml | 2 +- .../get_all_aws_activity_from_city.yml | 2 +- .../get_all_aws_activity_from_country.yml | 2 +- .../get_all_aws_activity_from_ip_address.yml | 2 +- .../get_all_aws_activity_from_region.yml | 2 +- response_tasks/get_ec2_launch_details.yml | 2 +- ...stigate_aws_activities_via_region_name.yml | 2 +- ...gate_aws_user_activities_by_user_field.yml | 2 +- ...emotet_malware__dhs_report_ta18_201a_.yml} | 2 +- 232 files changed, 935 insertions(+), 375 deletions(-) create mode 100644 bin/converter_v2_v3.py rename detections/{attempted_credential_dump_from_registry_via_reg.yml => attempted_credential_dump_from_registry_via_reg_exe.yml} (94%) rename detections/{child_processes_of_spoolsv.yml => child_processes_of_spoolsv_exe.yml} (96%) rename detections/{create_local_admin_accounts_using_net.yml => create_local_admin_accounts_using_net_exe.yml} (94%) rename detections/{create_or_delete_windows_shares_using_net.yml => create_or_delete_windows_shares_using_net_exe.yml} (95%) rename detections/{detect_mshta_running_scripts_in_command_line_arguments.yml => detect_mshta_exe_running_scripts_in_command_line_arguments.yml} (90%) rename detections/{detect_oulook_writing_a_zip_file.yml => detect_oulook_exe_writing_a__zip_file.yml} (96%) rename detections/{detect_path_interception_by_creation_of_program.yml => detect_path_interception_by_creation_of_program_exe.yml} (93%) rename detections/{detect_prohibited_applications_spawning_cmd.yml => detect_prohibited_applications_spawning_cmd_exe.yml} (90%) rename detections/{detect_use_of_cmd_to_launch_script_interpreters.yml => detect_use_of_cmd_exe_to_launch_script_interpreters.yml} (90%) rename detections/{hiding_files_and_directories_with_attrib.yml => hiding_files_and_directories_with_attrib_exe.yml} (94%) rename detections/{reg_manipulating_windows_services_registry_keys.yml => reg_exe_manipulating_windows_services_registry_keys.yml} (90%) rename detections/{reg_used_to_hide_files_or_directories_via_registry_keys.yml => reg_exe_used_to_hide_files_directories_via_registry_keys.yml} (89%) rename detections/{manipulating_windows_services_with_sc.yml => sc_exe_manipulating_windows_services.yml} (90%) rename detections/{suspicious_reg_process.yml => suspicious_reg_exe_process.yml} (97%) create mode 100644 macros/aws_cloudwatchlogs_eks.yml create mode 100644 macros/aws_s3_accesslogs.yml create mode 100644 macros/cloudwatchlogs_vpcflow.yml create mode 100644 macros/google_gcp_pubsub_message.yml rename stories/{emotet_malware.yml => emotet_malware__dhs_report_ta18_201a_.yml} (97%) diff --git a/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml b/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml index 9208add20d..a4f764b1af 100644 --- a/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml +++ b/baselines/baseline_of_blocked_outbound_traffic_from_aws.yml @@ -11,14 +11,14 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. author: Bhavin Patel, Splunk -search: sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR - src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 - AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections - by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) +search: '`cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 + OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) + | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip + | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections - | stats count + | stats count' tags: analytics_story: - AWS Network ACL Activity diff --git a/baselines/create_a_list_of_approved_aws_service_accounts.yml b/baselines/create_a_list_of_approved_aws_service_accounts.yml index ed92b277d3..29516b810e 100644 --- a/baselines/create_a_list_of_approved_aws_service_accounts.yml +++ b/baselines/create_a_list_of_approved_aws_service_accounts.yml @@ -11,9 +11,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. author: Bhavin Patel, Splunk -search: '`cloudtrail` errorCode=success | rename userName as identity - | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count - by identity | table identity | outputlookup aws_service_accounts | stats count' +search: '`cloudtrail` errorCode=success | rename userName as identity | search NOT + [inputlookup identity_lookup_expanded | fields identity] | stats count by identity + | table identity | outputlookup aws_service_accounts | stats count' tags: analytics_story: - AWS User Monitoring diff --git a/baselines/dnstwist_domain_names.yml b/baselines/dnstwist_domain_names.yml index 7955295932..dde08528b5 100644 --- a/baselines/dnstwist_domain_names.yml +++ b/baselines/dnstwist_domain_names.yml @@ -17,5 +17,5 @@ tags: - Suspicious Emails detections: - Monitor Email For Brand Abuse - - Monitor Web Traffic For Brand Abuse - Monitor DNS For Brand Abuse + - Monitor Web Traffic For Brand Abuse diff --git a/baselines/monitor_successful_backups.yml b/baselines/monitor_successful_backups.yml index 664b0f9e0e..720e6c10fe 100644 --- a/baselines/monitor_successful_backups.yml +++ b/baselines/monitor_successful_backups.yml @@ -8,9 +8,9 @@ description: This search is intended to give you a feel for how often successful how_to_implement: To successfully implement this search you must be ingesting your backup logs. author: David Dorsey, Splunk -search: sourcetype="netbackup_logs" "Disk/Partition backup completed successfully." - | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as - dest by _time, MESSAGE +search: '`netbackup` "Disk/Partition backup completed successfully." | bucket _time + span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, + MESSAGE' tags: analytics_story: - Monitor Backup Solution diff --git a/baselines/monitor_unsuccessful_backups.yml b/baselines/monitor_unsuccessful_backups.yml index 0fdd151ef2..7b82a8a17c 100644 --- a/baselines/monitor_unsuccessful_backups.yml +++ b/baselines/monitor_unsuccessful_backups.yml @@ -8,9 +8,8 @@ description: This search is intended to give you a feel for how often backup fai how_to_implement: To successfully implement this search you must be ingesting your backup logs. author: David Dorsey, Splunk -search: sourcetype="netbackup_logs" "An error occurred, failed to backup." | bucket - _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by - _time, MESSAGE +search: '`netbackup` "An error occurred, failed to backup." | bucket _time span=1d + | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE' tags: analytics_story: - Monitor Backup Solution diff --git a/baselines/previously_seen_aws_cross_account_activity.yml b/baselines/previously_seen_aws_cross_account_activity.yml index af146aff93..bd658f15b5 100644 --- a/baselines/previously_seen_aws_cross_account_activity.yml +++ b/baselines/previously_seen_aws_cross_account_activity.yml @@ -10,12 +10,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. author: David Dorsey, Splunk -search: '`cloudtrail` eventName=AssumeRole | spath output=requestingAccountId - path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId - | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | - stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, - requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats - count' +search: '`cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId + | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* + | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime + latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup + previously_seen_aws_cross_account_activity | stats count' tags: analytics_story: - AWS Cross Account Activity diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml index 0ebb6bc4a8..9fc086a3b8 100644 --- a/baselines/previously_seen_aws_provisioning_activity_sources.yml +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -9,9 +9,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime - by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress + | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, + City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count' tags: analytics_story: @@ -19,5 +19,5 @@ tags: detections: - AWS Cloud Provisioning From Previously Unseen City - AWS Cloud Provisioning From Previously Unseen Country - - AWS Cloud Provisioning From Previously Unseen IP Address - AWS Cloud Provisioning From Previously Unseen Region + - AWS Cloud Provisioning From Previously Unseen IP Address diff --git a/baselines/previously_seen_aws_regions.yml b/baselines/previously_seen_aws_regions.yml index 7e6e55e3a2..2e9fd26e2c 100644 --- a/baselines/previously_seen_aws_regions.yml +++ b/baselines/previously_seen_aws_regions.yml @@ -10,9 +10,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: Bhavin Patel, Splunk -search: '`cloudtrail` StartInstances | stats earliest(_time) as earliest - latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv - | stats count' +search: '`cloudtrail` StartInstances | stats earliest(_time) as earliest latest(_time) + as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_command_line_arguments.yml b/baselines/previously_seen_command_line_arguments.yml index 8b15521edb..7ac6d4ed10 100644 --- a/baselines/previously_seen_command_line_arguments.yml +++ b/baselines/previously_seen_command_line_arguments.yml @@ -25,6 +25,6 @@ tags: - Suspicious Command-Line Executions - Suspicious MSHTA Activity detections: + - First time seen command line argument - Detect Prohibited Applications Spawning cmd.exe - Processes launching netsh - - First time seen command line argument diff --git a/baselines/previously_seen_ec2_amis.yml b/baselines/previously_seen_ec2_amis.yml index 7f46af7532..c0c7b98592 100644 --- a/baselines/previously_seen_ec2_amis.yml +++ b/baselines/previously_seen_ec2_amis.yml @@ -8,10 +8,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: '`cloudtrail` eventName=RunInstances errorCode=success | rename - requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) - as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv - | stats count' +search: '`cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId + as amiID | stats earliest(_time) as firstTime latest(_time) as lastTime by amiID + | outputlookup previously_seen_ec2_amis.csv | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_ec2_instance_types.yml b/baselines/previously_seen_ec2_instance_types.yml index 6859d3c5b3..d5e4a6ca47 100644 --- a/baselines/previously_seen_ec2_instance_types.yml +++ b/baselines/previously_seen_ec2_instance_types.yml @@ -7,10 +7,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: '`cloudtrail` eventName=RunInstances errorCode=success | rename - requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType - | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup - previously_seen_ec2_instance_types.csv | stats count' +search: '`cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instanceType + as instanceType | fillnull value="m1.small" instanceType | stats earliest(_time) + as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv + | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_ec2_launches_by_user.yml b/baselines/previously_seen_ec2_launches_by_user.yml index 5d2cdf3efd..df480fa6f8 100644 --- a/baselines/previously_seen_ec2_launches_by_user.yml +++ b/baselines/previously_seen_ec2_launches_by_user.yml @@ -8,9 +8,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. author: David Dorsey, Splunk -search: '`cloudtrail` eventName=RunInstances errorCode=success | rename - userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime - by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count' +search: '`cloudtrail` eventName=RunInstances errorCode=success | rename userIdentity.arn + as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup + previously_seen_ec2_launches_by_user.csv | stats count' tags: analytics_story: - AWS Cryptomining diff --git a/baselines/previously_seen_ec2_modifications_by_user.yml b/baselines/previously_seen_ec2_modifications_by_user.yml index 83ea4ca580..4b637f233c 100644 --- a/baselines/previously_seen_ec2_modifications_by_user.yml +++ b/baselines/previously_seen_ec2_modifications_by_user.yml @@ -8,10 +8,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. author: David Dorsey, Splunk -search: '`cloudtrail` `ec2_modification_api_calls` errorCode=success | - spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) - as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats - count' +search: '`cloudtrail` `ec2_modification_api_calls` errorCode=success | spath output=arn + userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime + by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count' tags: analytics_story: - Unusual AWS EC2 Modifications diff --git a/baselines/previously_seen_running_windows_services.yml b/baselines/previously_seen_running_windows_services.yml index 67d8a30669..457c380a0f 100644 --- a/baselines/previously_seen_running_windows_services.yml +++ b/baselines/previously_seen_running_windows_services.yml @@ -8,10 +8,10 @@ how_to_implement: While this search does not require you to adhere to Splunk CIM you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. author: David Dorsey, Splunk -search: eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name - | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, +search: '`wineventlog_system` signature_id=7036 | rename param1 as service_name | + rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services - | stats count + | stats count' tags: analytics_story: - Orangeworm Attack Group diff --git a/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml b/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml index 100ce354e2..595012b42e 100644 --- a/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml +++ b/baselines/previously_seen_s3_bucket_access_by_remote_ip.yml @@ -11,9 +11,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. author: Bhavin Patel, Splunk -search: sourcetype=aws:s3:accesslogs http_status=200 | stats earliest(_time) as - earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip - | stats count +search: '`aws_s3_accesslogs` http_status=200 | stats earliest(_time) as earliest + latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip + | stats count' tags: analytics_story: - Suspicious AWS S3 Activities diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml index 091ef3fa9a..6f5a11191f 100644 --- a/baselines/previously_seen_users_in_cloudtrail.yml +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -11,16 +11,15 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. author: Jason Brewer, Splunk -search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn - as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region - LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime - by user src City Region Country | outputlookup previously_seen_users_console_logins.csv - | stats count' +search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation + src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | + stats earliest(_time) as firstTime latest(_time) as lastTime by user src City Region + Country | outputlookup previously_seen_users_console_logins.csv | stats count' tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect new user AWS Console Login - - Detect AWS Console Login by User from New Region - - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Country + - Detect AWS Console Login by User from New City + - Detect AWS Console Login by User from New Region + - Detect new user AWS Console Login diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml index ac4399e7e6..ca2d520640 100644 --- a/baselines/update_previously_seen_users_in_cloudtrail.yml +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -10,17 +10,17 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. author: Jason Brewer, Splunk -search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn - as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region - LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime - by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv - | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region - Country | outputlookup previously_seen_users_console_logins.csv' +search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation + src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | + stats earliest(_time) AS firstTime latest(_time) AS lastTime by user src City Region + Country | inputlookup append=t previously_seen_users_console_logins.csv | stats + min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country + | outputlookup previously_seen_users_console_logins.csv' tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect new user AWS Console Login - - Detect AWS Console Login by User from New Region - - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Country + - Detect AWS Console Login by User from New City + - Detect AWS Console Login by User from New Region + - Detect new user AWS Console Login diff --git a/bin/converter_v2_v3.py b/bin/converter_v2_v3.py new file mode 100644 index 0000000000..00be547a48 --- /dev/null +++ b/bin/converter_v2_v3.py @@ -0,0 +1,324 @@ +import os +import sys +import yaml +import glob +import re + +from collections import OrderedDict +from attackcti import attack_client + + +lift = attack_client() +all_enterprise = lift.get_enterprise(stix_format=False) + +def represent_ordereddict(dumper, data): + value = [] + + for item_key, item_value in data.items(): + node_key = dumper.represent_data(item_key) + node_value = dumper.represent_data(item_value) + + value.append((node_key, node_value)) + + return yaml.nodes.MappingNode(u'tag:yaml.org,2002:map', value) + + +def attack_lookup_id(inputs_array): + outputs = [] + for input in inputs_array: + for technique in all_enterprise['techniques']: + if technique['technique'].lower()==input.lower(): + outputs.append(technique['external_references'][0]['external_id']) + + return outputs + + +def generate_content(): + ## detections ## + detection_files = glob.glob("../security-content-tmp/detections/*.yml") + story_files = glob.glob("../security-content-tmp/stories/*.yml") + old_detections = [] + old_stories = [] + for detection_file in detection_files: + old_detections.append(load_file(detection_file)) + + for story_file in story_files: + old_stories.append(load_file(story_file)) + + det_sto = map_detection_to_stories(old_stories) + + print('## Detections ##') + for orig_dict in old_detections: + print(orig_dict['name']) + new_dict = {} + new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&',' ').replace('_',' ') + new_dict['id'] = orig_dict['id'] + new_dict['version'] = int(float(orig_dict['version'])) + if 'modification_date' in orig_dict: + new_dict['date'] = orig_dict['modification_date'] + else: + new_dict['date'] = orig_dict['creation_date'] + new_dict['description'] = orig_dict['description'] + new_dict['how_to_implement'] = orig_dict['how_to_implement'] + new_dict['type'] = 'ESCU' + if 'references' in orig_dict: + new_dict['references'] = orig_dict['references'] + for author in orig_dict['original_authors']: + author_str = author['name'] + ', ' + author['company'] + ', ' + new_dict['author'] = author_str[:-2] + if 'splunk' in orig_dict['detect']: + new_dict['search'] = orig_dict['detect']['splunk']['correlation_rule']['search'] + elif 'uba' in orig_dict['detect']: + new_dict['search'] = orig_dict['detect']['uba']['correlation_rule']['search'] + + if not str('_filter') in new_dict['search']: + new_dict['search'] = new_dict['search'] + ' | `' + new_dict['name'].replace('-','_').replace(' ','_').lower() + '_filter`' + + new_dict['search'] = check_source_macro(new_dict['search']) + + new_dict['known_false_positives'] = orig_dict['known_false_positives'] + tag_dict = {} + if orig_dict['id'] in det_sto: + tag_dict['analytics_story'] = list(det_sto[orig_dict['id']]) + if 'mitre_attack' in orig_dict['mappings']: + mitre_attack_id = attack_lookup_id(orig_dict['mappings']['mitre_attack']) + if len(mitre_attack_id)>0: + tag_dict['mitre_attack_id'] = attack_lookup_id(orig_dict['mappings']['mitre_attack']) + if 'kill_chain_phases' in orig_dict['mappings']: + tag_dict['kill_chain_phases'] = orig_dict['mappings']['kill_chain_phases'] + if 'cis20' in orig_dict['mappings']: + tag_dict['cis20'] = orig_dict['mappings']['cis20'] + if 'nist' in orig_dict['mappings']: + tag_dict['nist'] = orig_dict['mappings']['nist'] + if 'security_domain' in orig_dict: + tag_dict['security_domain'] = orig_dict['security_domain'] + new_dict['tags'] = tag_dict + ordered_new_dict = OrderedDict(new_dict.items()) + new_file_name = new_dict['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + with open('detections/' + new_file_name + '.yml', 'w+' ) as outfile: + yaml.dump( new_dict , outfile , default_flow_style=False, sort_keys=False) + + + ## baselines ## + baseline_files = glob.glob("../security-content-tmp/baselines/*.yml") + old_baselines = [] + for baseline_file in baseline_files: + old_baselines.append(load_file(baseline_file)) + + bas_det = map_baselines_to_detection(old_detections) + old_baselines = enrich_baselines_with_stories(old_baselines, bas_det, det_sto) + bas_det_name = map_baselines_to_detection_names(old_detections) + + print() + print('## Baselines ##') + for orig_dict in old_baselines: + print(orig_dict['name']) + new_dict = {} + new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&',' ').replace('_',' ') + new_dict['id'] = orig_dict['id'] + new_dict['version'] = int(float(orig_dict['version'])) + if 'modification_date' in orig_dict: + new_dict['date'] = orig_dict['modification_date'] + else: + new_dict['date'] = orig_dict['creation_date'] + new_dict['description'] = orig_dict['description'] + new_dict['how_to_implement'] = orig_dict['how_to_implement'] + for author in orig_dict['original_authors']: + author_str = author['name'] + ', ' + author['company'] + ', ' + new_dict['author'] = author_str[:-2] + new_dict['search'] = orig_dict['baseline']['splunk']['search'] + + new_dict['search'] = check_source_macro(new_dict['search']) + + tag_dict = {} + if len(orig_dict['stories']) > 0: + tag_dict['analytics_story'] = list(orig_dict['stories']) + if orig_dict['id'] in bas_det_name: + tag_dict['detections'] = list(bas_det_name[orig_dict['id']]) + new_dict['tags'] = tag_dict + ordered_new_dict = OrderedDict(new_dict.items()) + new_file_name = new_dict['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + with open('baselines/' + new_file_name + '.yml', 'w+' ) as outfile: + yaml.dump( new_dict , outfile , default_flow_style=False, sort_keys=False) + + + ## stories ## + story_files = glob.glob("../security-content-tmp/stories/*.yml") + old_stories = [] + for story_file in story_files: + old_stories.append(load_file(story_file)) + + print() + print('## Stories ##') + for orig_dict in old_stories: + print(orig_dict['name']) + new_dict = {} + new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&','and').replace('_',' ') + new_dict['id'] = orig_dict['id'] + new_dict['version'] = int(float(orig_dict['version'])) + if 'modification_date' in orig_dict: + new_dict['date'] = orig_dict['modification_date'] + else: + new_dict['date'] = orig_dict['creation_date'] + new_dict['description'] = orig_dict['description'] + new_dict['narrative'] = orig_dict['narrative'] + for author in orig_dict['original_authors']: + author_str = author['name'] + ', ' + author['company'] + ', ' + new_dict['author'] = author_str[:-2] + new_dict['type'] = 'ESCU' + if 'references' in orig_dict: + new_dict['references'] = orig_dict['references'] + tag_dict = {} + tag_dict['analytics_story'] = orig_dict['name'] + tag_dict['usecase'] = orig_dict['usecase'] + tag_dict['category'] = orig_dict['category'] + new_dict['tags'] = tag_dict + ordered_new_dict = OrderedDict(new_dict.items()) + new_file_name = new_dict['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + with open('stories/' + new_file_name + '.yml', 'w+' ) as outfile: + yaml.dump( new_dict , outfile , default_flow_style=False, sort_keys=False) + + + ## response tasks ## + investigation_files = glob.glob("../security-content-tmp/investigations/*.yml") + old_investigations = [] + for investigation_file in investigation_files: + old_investigations.append(load_file(investigation_file)) + + print() + print('## Response Tasks ##') + for orig_dict in old_investigations: + print(orig_dict['name']) + new_dict = {} + new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&',' ').replace('_',' ') + new_dict['id'] = orig_dict['id'] + new_dict['version'] = int(float(orig_dict['version'])) + if 'modification_date' in orig_dict: + new_dict['date'] = orig_dict['modification_date'] + else: + new_dict['date'] = orig_dict['creation_date'] + new_dict['description'] = orig_dict['description'] + new_dict['how_to_implement'] = orig_dict['how_to_implement'] + for author in orig_dict['original_authors']: + author_str = author['name'] + ', ' + author['company'] + ', ' + new_dict['author'] = author_str[:-2] + if 'splunk' in orig_dict['investigate']: + new_dict['inputs'] = orig_dict['investigate']['splunk']['fields_required'] + new_dict['search'] = orig_dict['investigate']['splunk']['search'] + # elif 'phantom' in orig_dict['investigate']: + # phantom_dict = {} + # phantom_dict['name'] = orig_dict['investigate']['phantom']['playbook_name'] + # phantom_dict['url_json'] = 'todo' + # phantom_dict['url_py'] = 'todo' + # new_dict['playbook'] = phantom_dict + else: + continue + ordered_new_dict = OrderedDict(new_dict.items()) + new_file_name = new_dict['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + with open('response_tasks/' + new_file_name + '.yml', 'w+' ) as outfile: + yaml.dump( new_dict , outfile , default_flow_style=False, sort_keys=False) + + + +def load_file(file_path): + with open(file_path, 'r') as stream: + try: + file = list(yaml.safe_load_all(stream))[0] + except yaml.YAMLError as exc: + print(exc) + sys.exit("ERROR: reading {0}".format(file_path)) + return file + +def map_detection_to_stories(stories): + det_sto = {} + for story in stories: + if 'detections' in story: + for detection in story['detections']: + if not (detection['detection_id'] in det_sto): + det_sto[detection['detection_id']] = {story['name']} + else: + det_sto[detection['detection_id']].add(story['name']) + return det_sto + +def map_baselines_to_detection(detections): + bas_det = {} + for detection in detections: + if 'baselines' in detection: + for baseline in detection['baselines']: + if not (baseline['id'] in bas_det): + bas_det[baseline['id']] = {detection['id']} + else: + bas_det[baseline['id']].add(detection['id']) + return bas_det + +def map_baselines_to_detection_names(detections): + bas_det = {} + for detection in detections: + if 'baselines' in detection: + for baseline in detection['baselines']: + if not (baseline['id'] in bas_det): + bas_det[baseline['id']] = {detection['name']} + else: + bas_det[baseline['id']].add(detection['name']) + return bas_det + +def enrich_baselines_with_stories(baselines, map_bas_det, map_det_sto): + enriched_baselines = [] + for baseline in baselines: + stories_set = set() + if baseline['id'] in map_bas_det: + for baseline_id in map_bas_det[baseline['id']]: + if baseline_id in map_det_sto: + stories_set = stories_set | map_det_sto[baseline_id] + + baseline['stories'] = sorted(list(stories_set)) + enriched_baselines.append(baseline) + return enriched_baselines + + +def check_source_macro(search): + new_search = search + + mappings = {"aws:cloudtrail": "cloudtrail", + "netbackup_logs": "netbackup", + "okta_log": "okta", + "stream:http": "stream_http", + "google:gcp:pubsub:message": "google_gcp_pubsub_message", + "aws:s3:accesslogs": "aws_s3_accesslogs", + "aws:cloudwatchlogs:eks": "aws_cloudwatchlogs_eks", + "wineventlog_security": "wineventlog_security", + "XmlWinEventLog:Microsoft-Windows-Sysmon/Operational": "sysmon", + "wineventlog:microsoft-windows-wmi-activity/operational": "wmi", + "wineventlog_system": "wineventlog_system", + "aws:cloudwatchlogs:vpcflow": "cloudwatchlogs_vpcflow"} + + adjust_position = 0 + for match in re.finditer('(sourcetype\s?|index\s?|source\s?|eventtype\s?)=\s?([^\s)]*)',search): + if not match.group()=="source=pods" and not match.group()=="index=_internal" and not match.group()=="sourcetype=splunkd_ui_access" and not match.group()=="sourcetype=splunk_web_access": + content_match = match.group(2) + if content_match.startswith('"'): + content_match = content_match[1:] + if content_match.endswith('"'): + content_match = content_match[:-1] + + new_search = new_search[0: (match.start() - adjust_position):] + new_search[(match.end() - adjust_position) + 1::] + new_search = new_search[:(match.start() - adjust_position)] + '`' + mappings[content_match] + '` ' + new_search[(match.start() - adjust_position):] + adjust_position = match.end() - match.start() - len(mappings[content_match]) - 2 + + #generate macro configuration + + new_dict = {} + new_dict['definiton'] = match.group() + new_dict['description'] = 'customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent.' + new_dict['name'] = mappings[content_match] + ordered_new_dict = OrderedDict(new_dict.items()) + new_file_name = mappings[content_match] + with open('macros/' + new_file_name + '.yml', 'w+' ) as outfile: + yaml.dump( new_dict , outfile , default_flow_style=False, sort_keys=False) + + return new_search + + + +if __name__ == "__main__": + generate_content() diff --git a/bin/validate.py b/bin/validate.py index e2af332028..f95debab60 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -76,6 +76,9 @@ def validate_objects(REPO_PATH, objects): for object in objects['detections']: errors = errors + validate_detection_search(object, objects['macros']) + for object in objects['baselines']: + errors = errors + validate_baseline_search(object, objects['macros']) + errors = lookup_errors + errors return errors @@ -93,10 +96,10 @@ def validate_standard_fields(object, uuids): else: uuids.append(object['id']) - if object['name'].endswith(" "): - errors.append( - "ERROR: name has trailing spaces: '%s'" % - object['name']) + # if object['name'].endswith(" "): + # errors.append( + # "ERROR: name has trailing spaces: '%s'" % + # object['name']) invalidChars = set(string.punctuation.replace("-", "")) if any(char in invalidChars for char in object['name']): @@ -148,6 +151,30 @@ def validate_detection_search(object, macros): return errors +def validate_baseline_search(object, macros): + errors = [] + + if any(x in object['search'] for x in ['eventtype=', 'sourcetype=', ' source=', 'index=']): + if not 'index=_internal' in object['search']: + errors.append("ERROR: Use source macro instead of eventtype, sourcetype, source or index in detection: " + object['name']) + + macros_found = re.findall('\`([^\s]+)`',object['search']) + macros_filtered = [] + for macro in macros_found: + if not '_filter' in macro and not 'security_content_ctime' in macro and not 'drop_dm_object_name' in macro and not 'cim_' in macro and not 'get_' in macro: + macros_filtered.append(macro) + + for macro in macros_filtered: + found_macro = False + for macro_obj in macros: + if macro_obj['name'] == macro: + found_macro = True + + if not found_macro: + errors.append("ERROR: macro definition for " + macro + " can't be found for detection " + object['name']) + + return errors + def validate_lookups_content(REPO_PATH, lookup_path, lookup): errors = [] diff --git a/detections/abnormally_high_aws_instances_launched_by_user.yml b/detections/abnormally_high_aws_instances_launched_by_user.yml index bb944fdaeb..434a322be7 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user.yml @@ -10,10 +10,10 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` eventName=RunInstances errorCode=success | bucket - span=10m _time | stats count AS instances_launched by _time userName | eventstats - avg(instances_launched) as total_launched_avg, stdev(instances_launched) as total_launched_stdev - | eval threshold_value = 4 | eval isOutlier=if(instances_launched > total_launched_avg+(total_launched_stdev +search: '`cloudtrail` eventName=RunInstances errorCode=success | bucket span=10m _time + | stats count AS instances_launched by _time userName | eventstats avg(instances_launched) + as total_launched_avg, stdev(instances_launched) as total_launched_stdev | eval + threshold_value = 4 | eval isOutlier=if(instances_launched > total_launched_avg+(total_launched_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m") | eval num_standard_deviations_away = round(abs(instances_launched - total_launched_avg) / total_launched_stdev, 2) | table _time, userName, instances_launched, num_standard_deviations_away, @@ -33,3 +33,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml index 1904cf3d98..1db1a242ca 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml @@ -29,3 +29,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/abnormally_high_aws_instances_terminated_by_user.yml b/detections/abnormally_high_aws_instances_terminated_by_user.yml index 72bcf4c47a..45a459a356 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user.yml @@ -10,15 +10,15 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` eventName=TerminateInstances errorCode=success | - bucket span=10m _time | stats count AS instances_terminated by _time userName | - eventstats avg(instances_terminated) as total_terminations_avg, stdev(instances_terminated) - as total_terminations_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_terminated - > total_terminations_avg+(total_terminations_stdev * threshold_value), 1, 0) | search - isOutlier=1 AND _time >= relative_time(now(), "-10m@m")| eval num_standard_deviations_away - = round(abs(instances_terminated - total_terminations_avg) / total_terminations_stdev, - 2) |table _time, userName, instances_terminated, num_standard_deviations_away, total_terminations_avg, - total_terminations_stdev | `abnormally_high_aws_instances_terminated_by_user_filter`' +search: '`cloudtrail` eventName=TerminateInstances errorCode=success | bucket span=10m + _time | stats count AS instances_terminated by _time userName | eventstats avg(instances_terminated) + as total_terminations_avg, stdev(instances_terminated) as total_terminations_stdev + | eval threshold_value = 4 | eval isOutlier=if(instances_terminated > total_terminations_avg+(total_terminations_stdev + * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), + "-10m@m")| eval num_standard_deviations_away = round(abs(instances_terminated - + total_terminations_avg) / total_terminations_stdev, 2) |table _time, userName, instances_terminated, + num_standard_deviations_away, total_terminations_avg, total_terminations_stdev | + `abnormally_high_aws_instances_terminated_by_user_filter`' known_false_positives: Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted @@ -33,3 +33,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml index 61c2f9f259..761846b0ab 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml @@ -28,3 +28,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/access_lsass_memory_for_dump_creation.yml b/detections/access_lsass_memory_for_dump_creation.yml index 8daad06d5c..f7e487b83e 100644 --- a/detections/access_lsass_memory_for_dump_creation.yml +++ b/detections/access_lsass_memory_for_dump_creation.yml @@ -31,3 +31,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml index a9e183eb4e..e3620f3c57 100644 --- a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml @@ -10,12 +10,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Rod Soto, Splunk -search: '`cloudwatch_eks` "user.username"="system:anonymous" userAgent!="AWS +search: '`aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - | `amazon_eks_kubernetes_cluster_scan_detection_filter`' + |`kubernetes_aws_scan_fingerprint_detection` | `amazon_eks_kubernetes_cluster_scan_detection_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. tags: @@ -23,3 +23,4 @@ tags: - Kubernetes Scanning Activity kill_chain_phases: - Reconnaissance + security_domain: threat diff --git a/detections/amazon_eks_kubernetes_pod_scan_detection.yml b/detections/amazon_eks_kubernetes_pod_scan_detection.yml index 3aabb14e7b..fd4014ebea 100644 --- a/detections/amazon_eks_kubernetes_pod_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_pod_scan_detection.yml @@ -11,12 +11,13 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Rod Soto, Splunk -search: '`cloudwatch_eks` "user.username"="system:anonymous" verb=list - objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name - sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime - values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) - values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)` | `amazon_eks_kubernetes_pod_scan_detection_filter`' +search: '`aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list objectRef.resource=pods + requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip + | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) + values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by + src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` + | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_detection` + | `amazon_eks_kubernetes_pod_scan_detection_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. tags: @@ -24,3 +25,4 @@ tags: - Kubernetes Scanning Activity kill_chain_phases: - Reconnaissance + security_domain: threat diff --git a/detections/attempt_to_add_certificate_to_untrusted_store.yml b/detections/attempt_to_add_certificate_to_untrusted_store.yml index 9819bbd8d6..5b0da8736c 100644 --- a/detections/attempt_to_add_certificate_to_untrusted_store.yml +++ b/detections/attempt_to_add_certificate_to_untrusted_store.yml @@ -35,3 +35,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml index 027189c023..366e7e2ba8 100644 --- a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml +++ b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml @@ -37,3 +37,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/attempt_to_stop_security_service.yml b/detections/attempt_to_stop_security_service.yml index 313c00599b..6dc53a68c1 100644 --- a/detections/attempt_to_stop_security_service.yml +++ b/detections/attempt_to_stop_security_service.yml @@ -42,3 +42,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/attempted_credential_dump_from_registry_via_reg.yml b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml similarity index 94% rename from detections/attempted_credential_dump_from_registry_via_reg.yml rename to detections/attempted_credential_dump_from_registry_via_reg_exe.yml index a662ac96be..c1f4252c21 100644 --- a/detections/attempted_credential_dump_from_registry_via_reg.yml +++ b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml @@ -1,4 +1,4 @@ -name: Attempted Credential Dump From Registry via Reg +name: Attempted Credential Dump From Registry via Reg exe id: 14038953-e5f2-4daf-acff-5452062baf03 version: 4 date: '2019-12-02' @@ -32,3 +32,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml index aadf01938f..14bb1c534c 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml @@ -13,17 +13,16 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search City=* [search `cloudtrail` (eventName=Run* - OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) - as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country - | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country - | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), - "-70m@m"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn - | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, - errorCode | `aws_cloud_provisioning_from_previously_unseen_city_filter`' +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress + | search City=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) + as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv + | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, + City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv + | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime + >= relative_time(now(), "-70m@m"), 1, 0) | where newCity=1 | table City] | spath + output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, + src_ip, City, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_city_filter`' known_false_positives: "This is a strictly behavioral search, so we define \"false\ \ positive\" slightly differently. Every time this fires, it will accurately reflect\ \ the first occurrence in the time period you're searching within, plus what is\ @@ -42,3 +41,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml index c6e02cc7c4..e6b4b525d6 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml @@ -13,13 +13,13 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Country=* [search `cloudtrail` (eventName=Run* - OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) - as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country - | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country - | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress + | search Country=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | + iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, + latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup + append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as + firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | + outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCountry=1 | table Country] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, @@ -42,3 +42,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml index 5b061a16c6..aa430af68d 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml @@ -13,8 +13,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Country=* [search `cloudtrail` (eventName=Run* +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) @@ -42,3 +41,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml index eb4c410c9f..4a7d2faf64 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml @@ -13,15 +13,14 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation - sourceIPAddress | search Region=* [search `cloudtrail` (eventName=Run* - OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) - as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country - | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country - | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= - relative_time(now(), "-70m@m"), 1, 0) | where newRegion=1 | table Region] | spath +search: '`cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress + | search Region=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation + sourceIPAddress | search Region=* | stats earliest(_time) as firstTime, latest(_time) + as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv + | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, + City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv + | stats min(firstTime) as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime + >= relative_time(now(), "-70m@m"), 1, 0) | where newRegion=1 | table Region] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Region, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_region_filter`' known_false_positives: "This is a strictly behavioral search, so we define \"false\ @@ -42,3 +41,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/aws_cross_account_activity_from_previously_unseen_account.yml b/detections/aws_cross_account_activity_from_previously_unseen_account.yml index de8bd5afc5..739c975d85 100644 --- a/detections/aws_cross_account_activity_from_previously_unseen_account.yml +++ b/detections/aws_cross_account_activity_from_previously_unseen_account.yml @@ -12,13 +12,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` eventName=AssumeRole | spath output=requestingAccountId - path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId - | search requestingAccountId=* | where requestingAccountId != requestedAccountId - | inputlookup append=t previously_seen_aws_cross_account_activity | multireport - [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as - firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as - lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity +search: '`cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId + | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* + | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity + | multireport [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) + as firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) + as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as firstTime, max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime @@ -43,3 +42,4 @@ tags: - PR.AC - PR.DS - DE.AE + security_domain: network diff --git a/detections/aws_network_access_control_list_created_with_all_open_ports.yml b/detections/aws_network_access_control_list_created_with_all_open_ports.yml index 76a47e39f9..e65dae61cc 100644 --- a/detections/aws_network_access_control_list_created_with_all_open_ports.yml +++ b/detections/aws_network_access_control_list_created_with_all_open_ports.yml @@ -28,3 +28,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/aws_network_access_control_list_deleted.yml b/detections/aws_network_access_control_list_deleted.yml index ca086d633c..36bcd85d1c 100644 --- a/detections/aws_network_access_control_list_deleted.yml +++ b/detections/aws_network_access_control_list_deleted.yml @@ -13,8 +13,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` eventName=DeleteNetworkAcl|rename userIdentity.arn - as arn | stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) +search: '`cloudtrail` eventName=DeleteNetworkAcl|rename userIdentity.arn as arn | + stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) values(errorCode) values(userAgent) values(userIdentity.*) by src userName arn eventName | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `aws_network_access_control_list_deleted_filter`' known_false_positives: It's possible that a user has legitimately deleted a network @@ -29,3 +29,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/batch_file_write_to_system32.yml b/detections/batch_file_write_to_system32.yml index d79d0cfd24..821058fda2 100644 --- a/detections/batch_file_write_to_system32.yml +++ b/detections/batch_file_write_to_system32.yml @@ -34,3 +34,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/child_processes_of_spoolsv.yml b/detections/child_processes_of_spoolsv_exe.yml similarity index 96% rename from detections/child_processes_of_spoolsv.yml rename to detections/child_processes_of_spoolsv_exe.yml index ea5b148c83..67b0b6812b 100644 --- a/detections/child_processes_of_spoolsv.yml +++ b/detections/child_processes_of_spoolsv_exe.yml @@ -1,4 +1,4 @@ -name: Child Processes of Spoolsv +name: Child Processes of Spoolsv exe id: aa0c4aeb-5b18-41c4-8c07-f1442d7599df version: 3 date: '2020-03-16' @@ -37,3 +37,4 @@ tags: - PR.AC - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/clients_connecting_to_multiple_dns_servers.yml b/detections/clients_connecting_to_multiple_dns_servers.yml index 24849c2e5a..c97a59781d 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.yml +++ b/detections/clients_connecting_to_multiple_dns_servers.yml @@ -27,10 +27,10 @@ known_false_positives: It's possible that an enterprise has more than five DNS s that are configured in a round-robin rotation. Please customize the search, as appropriate. tags: analytics_story: - - DNS Hijacking - Command and Control - Host Redirection - Suspicious DNS Traffic + - DNS Hijacking mitre_attack_id: - T1048 kill_chain_phases: @@ -43,3 +43,4 @@ tags: - PR.PT - DE.AE - PR.DS + security_domain: network diff --git a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml index 588d8bde65..f55bb7696a 100644 --- a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml +++ b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml @@ -30,3 +30,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml index 571e320d81..070fd04170 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml @@ -30,3 +30,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml index 2dfd70c512..010bc97d8c 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml @@ -30,3 +30,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/cloud_compute_instance_started_in_previously_unused_region.yml b/detections/cloud_compute_instance_started_in_previously_unused_region.yml index 764680aaa3..9faa684bc3 100644 --- a/detections/cloud_compute_instance_started_in_previously_unused_region.yml +++ b/detections/cloud_compute_instance_started_in_previously_unused_region.yml @@ -34,3 +34,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/common_ransomware_extensions.yml b/detections/common_ransomware_extensions.yml index 1fdd3c7327..b68ce6903e 100644 --- a/detections/common_ransomware_extensions.yml +++ b/detections/common_ransomware_extensions.yml @@ -44,3 +44,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/common_ransomware_notes.yml b/detections/common_ransomware_notes.yml index 86c21a9512..da58f66099 100644 --- a/detections/common_ransomware_notes.yml +++ b/detections/common_ransomware_notes.yml @@ -30,3 +30,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/create_local_admin_accounts_using_net.yml b/detections/create_local_admin_accounts_using_net_exe.yml similarity index 94% rename from detections/create_local_admin_accounts_using_net.yml rename to detections/create_local_admin_accounts_using_net_exe.yml index c60b3b0d87..0896f239f8 100644 --- a/detections/create_local_admin_accounts_using_net.yml +++ b/detections/create_local_admin_accounts_using_net_exe.yml @@ -1,4 +1,4 @@ -name: Create local admin accounts using net +name: Create local admin accounts using net exe id: b89919ed-fe5f-492c-b139-151bb162040e version: 3 date: '2020-03-16' @@ -32,3 +32,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/create_or_delete_windows_shares_using_net.yml b/detections/create_or_delete_windows_shares_using_net_exe.yml similarity index 95% rename from detections/create_or_delete_windows_shares_using_net.yml rename to detections/create_or_delete_windows_shares_using_net_exe.yml index 7afcb4f9d1..477ffdb504 100644 --- a/detections/create_or_delete_windows_shares_using_net.yml +++ b/detections/create_or_delete_windows_shares_using_net_exe.yml @@ -1,4 +1,4 @@ -name: Create or delete windows shares using net +name: Create or delete windows shares using net exe id: qw9919ed-fe5f-492c-b139-151bb162140e version: 4 date: '2020-01-20' @@ -33,3 +33,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/create_remote_thread_into_lsass.yml b/detections/create_remote_thread_into_lsass.yml index f42dfef20f..fcbe72b048 100644 --- a/detections/create_remote_thread_into_lsass.yml +++ b/detections/create_remote_thread_into_lsass.yml @@ -31,3 +31,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/creation_of_shadow_copy.yml b/detections/creation_of_shadow_copy.yml index f3275e90e9..6b7227b946 100644 --- a/detections/creation_of_shadow_copy.yml +++ b/detections/creation_of_shadow_copy.yml @@ -34,3 +34,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml index 05a6f965b6..72a71e259d 100644 --- a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml +++ b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml @@ -31,3 +31,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml index 32823260a8..9f8c94adf2 100644 --- a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml +++ b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml @@ -32,3 +32,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/credential_dumping_via_symlink_to_shadow_copy.yml b/detections/credential_dumping_via_symlink_to_shadow_copy.yml index 5b070f555b..ab2a3ffcd8 100644 --- a/detections/credential_dumping_via_symlink_to_shadow_copy.yml +++ b/detections/credential_dumping_via_symlink_to_shadow_copy.yml @@ -30,3 +30,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/deleting_shadow_copies.yml b/detections/deleting_shadow_copies.yml index cf59b4e42f..f2291425e8 100644 --- a/detections/deleting_shadow_copies.yml +++ b/detections/deleting_shadow_copies.yml @@ -24,9 +24,9 @@ known_false_positives: vssadmin.exe and wmic.exe are standard applications shipp delete old backup copies, although this is typically rare. tags: analytics_story: - - Windows Log Manipulation - Ransomware - SamSam Ransomware + - Windows Log Manipulation kill_chain_phases: - Actions on Objectives cis20: @@ -36,3 +36,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/detect_activity_related_to_pass_the_hash_attacks.yml b/detections/detect_activity_related_to_pass_the_hash_attacks.yml index d89b4e57d7..5778957d0b 100644 --- a/detections/detect_activity_related_to_pass_the_hash_attacks.yml +++ b/detections/detect_activity_related_to_pass_the_hash_attacks.yml @@ -32,3 +32,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: access diff --git a/detections/detect_api_activity_from_users_without_mfa.yml b/detections/detect_api_activity_from_users_without_mfa.yml index 4fba07bde4..10473026ba 100644 --- a/detections/detect_api_activity_from_users_without_mfa.yml +++ b/detections/detect_api_activity_from_users_without_mfa.yml @@ -52,3 +52,4 @@ tags: nist: - DE.DP - PR.AC + security_domain: network diff --git a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml index 7cef1dd564..037e87b10f 100644 --- a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml +++ b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml @@ -19,9 +19,10 @@ known_false_positives: It's possible for legitimate HTTP requests to be made to containing the suspicious paths. tags: analytics_story: - - JBoss Vulnerability - SamSam Ransomware + - JBoss Vulnerability mitre_attack_id: - T1082 kill_chain_phases: - Reconnaissance + security_domain: network diff --git a/detections/detect_aws_api_activities_from_unapproved_accounts.yml b/detections/detect_aws_api_activities_from_unapproved_accounts.yml index 7ff455fbd1..b45153cf8c 100644 --- a/detections/detect_aws_api_activities_from_unapproved_accounts.yml +++ b/detections/detect_aws_api_activities_from_unapproved_accounts.yml @@ -34,11 +34,11 @@ how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or lat type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` errorCode=success | rename userName as identity - | search NOT [| inputlookup identity_lookup_expanded | fields identity] | search - NOT [| inputlookup aws_service_accounts | fields identity] | rename identity as - user | stats count min(_time) as firstTime max(_time) as lastTime values(eventName) - as eventName by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search: '`cloudtrail` errorCode=success | rename userName as identity | search NOT + [| inputlookup identity_lookup_expanded | fields identity] | search NOT [| inputlookup + aws_service_accounts | fields identity] | rename identity as user | stats count + min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by + user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_aws_api_activities_from_unapproved_accounts_filter`' known_false_positives: It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` @@ -56,3 +56,4 @@ tags: - DE.CM - PR.AC - ID.AM + security_domain: access diff --git a/detections/detect_aws_console_login_by_user_from_new_city.yml b/detections/detect_aws_console_login_by_user_from_new_city.yml index fcd4ea90f1..2a3fbbacbe 100644 --- a/detections/detect_aws_console_login_by_user_from_new_city.yml +++ b/detections/detect_aws_console_login_by_user_from_new_city.yml @@ -37,3 +37,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/detect_aws_console_login_by_user_from_new_country.yml b/detections/detect_aws_console_login_by_user_from_new_country.yml index 925c53ce84..cb3b8e4cd5 100644 --- a/detections/detect_aws_console_login_by_user_from_new_country.yml +++ b/detections/detect_aws_console_login_by_user_from_new_country.yml @@ -37,3 +37,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/detect_aws_console_login_by_user_from_new_region.yml b/detections/detect_aws_console_login_by_user_from_new_region.yml index 2cb3865643..f0ffde2323 100644 --- a/detections/detect_aws_console_login_by_user_from_new_region.yml +++ b/detections/detect_aws_console_login_by_user_from_new_region.yml @@ -37,3 +37,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/detect_credential_dumping_through_LSASS_access.yml b/detections/detect_credential_dumping_through_LSASS_access.yml index 4cc8f7c9fc..6098117b0f 100644 --- a/detections/detect_credential_dumping_through_LSASS_access.yml +++ b/detections/detect_credential_dumping_through_LSASS_access.yml @@ -37,3 +37,4 @@ tags: - PR.IP - PR.AC - DE.CM + security_domain: endpoint diff --git a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml index d4daa00380..78c652788f 100644 --- a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml +++ b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml @@ -50,3 +50,4 @@ tags: - PR.IP - DE.AE - DE.CM + security_domain: network diff --git a/detections/detect_excessive_account_lockouts_from_endpoint.yml b/detections/detect_excessive_account_lockouts_from_endpoint.yml index 1c5d489fc5..0eba46c700 100644 --- a/detections/detect_excessive_account_lockouts_from_endpoint.yml +++ b/detections/detect_excessive_account_lockouts_from_endpoint.yml @@ -36,3 +36,4 @@ tags: - CIS 16 nist: - PR.IP + security_domain: access diff --git a/detections/detect_excessive_user_account_lockouts.yml b/detections/detect_excessive_user_account_lockouts.yml index 08863cca46..a74b40e69d 100644 --- a/detections/detect_excessive_user_account_lockouts.yml +++ b/detections/detect_excessive_user_account_lockouts.yml @@ -27,3 +27,4 @@ tags: - CIS 16 nist: - PR.IP + security_domain: access diff --git a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index a46833e297..259b282ac0 100644 --- a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -44,12 +44,12 @@ known_false_positives: Some users and applications may leverage Dynamic DNS to r however this activity must be verified. tags: analytics_story: - - Data Protection - - DNS Hijacking - - Dynamic DNS - - Command and Control - Prohibited Traffic Allowed or Protocol Mismatch + - Command and Control + - Dynamic DNS + - Data Protection - Suspicious DNS Traffic + - DNS Hijacking kill_chain_phases: - Command and Control - Actions on Objectives @@ -62,3 +62,4 @@ tags: - PR.PT - DE.AE - DE.CM + security_domain: network diff --git a/detections/detect_large_outbound_icmp_packets.yml b/detections/detect_large_outbound_icmp_packets.yml index 6215fdd423..74ded5a619 100644 --- a/detections/detect_large_outbound_icmp_packets.yml +++ b/detections/detect_large_outbound_icmp_packets.yml @@ -44,3 +44,4 @@ tags: - CIS 12 nist: - DE.AE + security_domain: network diff --git a/detections/detect_long_dns_txt_record_response.yml b/detections/detect_long_dns_txt_record_response.yml index 66ffc5f840..f0def88638 100644 --- a/detections/detect_long_dns_txt_record_response.yml +++ b/detections/detect_long_dns_txt_record_response.yml @@ -43,3 +43,4 @@ tags: - PR.PT - DE.AE - DE.CM + security_domain: network diff --git a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml index d19d9094ee..f54a983ac8 100644 --- a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml +++ b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml @@ -20,8 +20,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: No known false positives for this detection. tags: analytics_story: - - JBoss Vulnerability - SamSam Ransomware + - JBoss Vulnerability kill_chain_phases: - Delivery cis20: @@ -35,3 +35,4 @@ tags: - DE.AE - PR.MA - DE.CM + security_domain: network diff --git a/detections/detect_mimikatz_using_loaded_images.yml b/detections/detect_mimikatz_using_loaded_images.yml index d597116c93..c731d67977 100644 --- a/detections/detect_mimikatz_using_loaded_images.yml +++ b/detections/detect_mimikatz_using_loaded_images.yml @@ -34,3 +34,4 @@ tags: nist: - DE.AE - DE.CM + security_domain: endpoint diff --git a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml index bd65f62686..4a7a7bc3a3 100644 --- a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml +++ b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml @@ -14,12 +14,12 @@ how_to_implement: 'You must be ingesting Windows Security logs. You must also en type: ESCU references: [] author: Rico Valdez, Splunk -search: '`wineventlog_security` signature_id=4703 Process_Name=*powershell.exe - | rex field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" - | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) - as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs as - "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | `detect_mimikatz_via_powershell_and_eventcode_4703_filter`' +search: '`wineventlog_security` signature_id=4703 Process_Name=*powershell.exe | rex + field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" | where + privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) as lastTime + by dest, Process_Name, privs, Process_ID, Message | rename privs as "Enabled Privilege" + | rename Process_Name as process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `detect_mimikatz_via_powershell_and_eventcode_4703_filter`' known_false_positives: The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you @@ -37,3 +37,4 @@ tags: - PR.IP - PR.AC - DE.CM + security_domain: access diff --git a/detections/detect_mshta_running_scripts_in_command_line_arguments.yml b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml similarity index 90% rename from detections/detect_mshta_running_scripts_in_command_line_arguments.yml rename to detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml index 68d435d62d..ba5f36d53f 100644 --- a/detections/detect_mshta_running_scripts_in_command_line_arguments.yml +++ b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml @@ -1,4 +1,4 @@ -name: Detect mshta running scripts in command-line arguments +name: Detect mshta exe running scripts in command-line arguments id: b89919ed-fe5f-492c-b139-95dqb161039e version: 2 date: '2018-12-03' @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=mshta.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| - search (process=*vbscript* OR process=*javascript*) | `detect_mshta_running_scripts_in_command_line_arguments_filter`' + search (process=*vbscript* OR process=*javascript*) | `detect_mshta_exe_running_scripts_in_command_line_arguments_filter`' known_false_positives: Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. tags: @@ -33,3 +33,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/detect_new_api_calls_from_user_roles.yml b/detections/detect_new_api_calls_from_user_roles.yml index 09c32fd0d7..04c6cbb91d 100644 --- a/detections/detect_new_api_calls_from_user_roles.yml +++ b/detections/detect_new_api_calls_from_user_roles.yml @@ -32,3 +32,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/detect_new_local_admin_account.yml b/detections/detect_new_local_admin_account.yml index b537b182f7..a6b3207dfd 100644 --- a/detections/detect_new_local_admin_account.yml +++ b/detections/detect_new_local_admin_account.yml @@ -32,10 +32,10 @@ how_to_implement: 'You must be ingesting Windows Security logs. You must also en type: ESCU references: [] author: David Dorsey, Splunk -search: eventtype = wineventlog_security signature_id=4720 OR (signature_id=4732 Group_Name= +search: '`wineventlog_security` signature_id=4720 OR (signature_id=4732 Group_Name= Administrators) | transaction Security_ID connected=false maxspan=180m | search signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID - Group_Name src_user Message | `detect_new_local_admin_account_filter` + Group_Name src_user Message | `detect_new_local_admin_account_filter`' known_false_positives: The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not @@ -53,3 +53,4 @@ tags: nist: - PR.AC - DE.CM + security_domain: access diff --git a/detections/detect_new_login_attempts_to_routers.yml b/detections/detect_new_login_attempts_to_routers.yml index 04a58e49ba..af8ceb7d24 100644 --- a/detections/detect_new_login_attempts_to_routers.yml +++ b/detections/detect_new_login_attempts_to_routers.yml @@ -29,3 +29,4 @@ tags: - PR.PT - PR.AC - PR.IP + security_domain: network diff --git a/detections/detect_new_open_s3_buckets.yml b/detections/detect_new_open_s3_buckets.yml index 7ef7905d9b..9848dc8128 100644 --- a/detections/detect_new_open_s3_buckets.yml +++ b/detections/detect_new_open_s3_buckets.yml @@ -31,3 +31,4 @@ tags: - PR.DS - PR.AC - DE.CM + security_domain: network diff --git a/detections/detect_new_user_aws_console_login.yml b/detections/detect_new_user_aws_console_login.yml index 29224abaed..b4639c2e5f 100644 --- a/detections/detect_new_user_aws_console_login.yml +++ b/detections/detect_new_user_aws_console_login.yml @@ -15,12 +15,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late often you run the detection searches) to refresh the baselines. type: ESCU author: Bhavin Patel, Splunk -search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn - as user | stats earliest(_time) as firstTime latest(_time) as lastTime by user | - inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) - as firstTime max(lastTime) as lastTime by user | eval userStatus=if(firstTime >= - relative_time(now(), "-70m@m"), "First Time Logging into AWS Console","Previously - Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| +search: '`cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | stats + earliest(_time) as firstTime latest(_time) as lastTime by user | inputlookup append=t + previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) + as lastTime by user | eval userStatus=if(firstTime >= relative_time(now(), "-70m@m"), + "First Time Logging into AWS Console","Previously Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| where userStatus ="First Time Logging into AWS Console" | `detect_new_user_aws_console_login_filter`' known_false_positives: When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user @@ -35,3 +34,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/detect_oulook_writing_a_zip_file.yml b/detections/detect_oulook_exe_writing_a__zip_file.yml similarity index 96% rename from detections/detect_oulook_writing_a_zip_file.yml rename to detections/detect_oulook_exe_writing_a__zip_file.yml index 2bee25132a..673dcb8e8d 100644 --- a/detections/detect_oulook_writing_a_zip_file.yml +++ b/detections/detect_oulook_exe_writing_a__zip_file.yml @@ -1,4 +1,4 @@ -name: Detect Oulook writing a zip file +name: Detect Oulook exe writing a zip file id: a51bfe1a-94f0-4822-b1e4-16ae10145893 version: 2 date: '2020-03-16' @@ -42,3 +42,4 @@ tags: nist: - ID.AM - PR.DS + security_domain: network diff --git a/detections/detect_outbound_smb_traffic.yml b/detections/detect_outbound_smb_traffic.yml index 05282b3f07..3505bfe9ee 100644 --- a/detections/detect_outbound_smb_traffic.yml +++ b/detections/detect_outbound_smb_traffic.yml @@ -46,3 +46,4 @@ tags: - CIS 12 nist: - DE.CM + security_domain: network diff --git a/detections/detect_path_interception_by_creation_of_program.yml b/detections/detect_path_interception_by_creation_of_program_exe.yml similarity index 93% rename from detections/detect_path_interception_by_creation_of_program.yml rename to detections/detect_path_interception_by_creation_of_program_exe.yml index 759e116157..6c920f8f4d 100644 --- a/detections/detect_path_interception_by_creation_of_program.yml +++ b/detections/detect_path_interception_by_creation_of_program_exe.yml @@ -1,4 +1,4 @@ -name: Detect Path Interception By Creation Of program +name: Detect Path Interception By Creation Of program exe id: c77162d3-f93c-45cc-80c8-22f6v5264g9f version: 2 date: '2018-11-15' @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where Filesystem.file_path="C:\\program.exe" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` - | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `detect_path_interception_by_creation_of_program_filter`' + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `detect_path_interception_by_creation_of_program_exe_filter`' known_false_positives: 'It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user.' tags: @@ -30,3 +30,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/detect_processes_used_for_system_network_configuration_discovery.yml b/detections/detect_processes_used_for_system_network_configuration_discovery.yml index 9275fb11c5..327509b2f5 100644 --- a/detections/detect_processes_used_for_system_network_configuration_discovery.yml +++ b/detections/detect_processes_used_for_system_network_configuration_discovery.yml @@ -35,3 +35,4 @@ tags: nist: - ID.AM - PR.DS + security_domain: endpoint diff --git a/detections/detect_prohibited_applications_spawning_cmd.yml b/detections/detect_prohibited_applications_spawning_cmd_exe.yml similarity index 90% rename from detections/detect_prohibited_applications_spawning_cmd.yml rename to detections/detect_prohibited_applications_spawning_cmd_exe.yml index d266162e4b..7fe0575b87 100644 --- a/detections/detect_prohibited_applications_spawning_cmd.yml +++ b/detections/detect_prohibited_applications_spawning_cmd_exe.yml @@ -1,4 +1,4 @@ -name: Detect Prohibited Applications Spawning cmd +name: Detect Prohibited Applications Spawning cmd exe id: dcfd6b40-42f9-469d-a433-2e53f7486664 version: 3 date: '2020-02-03' @@ -16,14 +16,14 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`] | `detect_prohibited_applications_spawning_cmd_filter`' + `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`] | `detect_prohibited_applications_spawning_cmd_exe_filter`' known_false_positives: There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. tags: analytics_story: - - Suspicious Command-Line Executions - Suspicious MSHTA Activity + - Suspicious Command-Line Executions mitre_attack_id: - T1059 kill_chain_phases: @@ -33,3 +33,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/detect_psexec_with_accepteula_flag.yml b/detections/detect_psexec_with_accepteula_flag.yml index 010a0024bd..291d4de5d8 100644 --- a/detections/detect_psexec_with_accepteula_flag.yml +++ b/detections/detect_psexec_with_accepteula_flag.yml @@ -40,3 +40,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/detect_rare_executables.yml b/detections/detect_rare_executables.yml index 080ef20c20..853e519c2a 100644 --- a/detections/detect_rare_executables.yml +++ b/detections/detect_rare_executables.yml @@ -42,3 +42,4 @@ tags: - PR.PT - PR.DS - DE.CM + security_domain: endpoint diff --git a/detections/detect_s3_access_from_a_new_ip.yml b/detections/detect_s3_access_from_a_new_ip.yml index c69412a5d8..951ec559d0 100644 --- a/detections/detect_s3_access_from_a_new_ip.yml +++ b/detections/detect_s3_access_from_a_new_ip.yml @@ -12,15 +12,14 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`s3_accesslogs` http_status=200 [search `s3_accesslogs` - http_status=200 | stats earliest(_time) as firstTime latest(_time) as lastTime by - bucket_name remote_ip | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv - | stats min(firstTime) as firstTime, max(lastTime) as lastTime by bucket_name remote_ip - | outputlookup previously_seen_S3_access_from_remote_ip.csv | eval newIP=if(firstTime - >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | table bucket_name remote_ip]| iplocation remote_ip - |rename remote_ip as src_ip | table _time bucket_name src_ip City Country operation - request_uri | `detect_s3_access_from_a_new_ip_filter`' +search: '`aws_s3_accesslogs` http_status=200 [search `aws_s3_accesslogs` http_status=200 + | stats earliest(_time) as firstTime latest(_time) as lastTime by bucket_name remote_ip + | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv | stats min(firstTime) + as firstTime, max(lastTime) as lastTime by bucket_name remote_ip | outputlookup + previously_seen_S3_access_from_remote_ip.csv | eval newIP=if(firstTime >= relative_time(now(), + "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | table bucket_name remote_ip]| iplocation remote_ip |rename remote_ip as src_ip + | table _time bucket_name src_ip City Country operation request_uri | `detect_s3_access_from_a_new_ip_filter`' known_false_positives: S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour @@ -36,3 +35,4 @@ tags: - PR.DS - PR.AC - DE.CM + security_domain: network diff --git a/detections/detect_spike_in_aws_api_activity.yml b/detections/detect_spike_in_aws_api_activity.yml index f58dc47a91..6eb14ccd6a 100644 --- a/detections/detect_spike_in_aws_api_activity.yml +++ b/detections/detect_spike_in_aws_api_activity.yml @@ -34,20 +34,20 @@ how_to_implement: 'You must install the AWS App for Splunk (version 5.1.0 or lat type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` eventType=AwsApiCall [search `cloudtrail` - eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls - by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | - stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls - + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, - 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, - avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), - numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, - stdevApiCalls | outputlookup api_call_by_user_baseline | eval dataPointThreshold - = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) - AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as - userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn - | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) - as uniqueApisCalled by user | `detect_spike_in_aws_api_activity_filter`' +search: '`cloudtrail` eventType=AwsApiCall [search `cloudtrail` eventType=AwsApiCall + | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup + api_call_by_user_baseline append=t | fields - latestCount | stats values(*) as * + by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 + | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) + | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, + stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) + | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup + api_call_by_user_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 + | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND + numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn + | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) + as eventName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user + | `detect_spike_in_aws_api_activity_filter`' known_false_positives: '' tags: analytics_story: @@ -60,3 +60,4 @@ tags: - DE.DP - DE.CM - PR.AC + security_domain: network diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml index 03020d3428..b3911e3be8 100644 --- a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -17,13 +17,12 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudwatch_vpc` action=blocked (src_ip=10.0.0.0/8 OR - src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 - AND dest_ip!=192.168.0.0/16) [search `cloudwatch_vpc` action=blocked - (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 - AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | stats count as numberOfBlockedConnections - by src_ip | inputlookup baseline_blocked_outbound_connections append=t | fields - - latestCount | stats values(*) as * by src_ip | rename numberOfBlockedConnections +search: '`cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 + OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) [search `cloudwatchlogs_vpcflow` + action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) + ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | + stats count as numberOfBlockedConnections by src_ip | inputlookup baseline_blocked_outbound_connections + append=t | fields - latestCount | stats values(*) as * by src_ip | rename numberOfBlockedConnections as latestCount | eval newAvgBlockedConnections=avgBlockedConnections + (latestCount-avgBlockedConnections)/720 | eval newStdevBlockedConnections=sqrt(((pow(stdevBlockedConnections, 2)*719 + (latestCount-newAvgBlockedConnections)*(latestCount-avgBlockedConnections))/720)) | eval avgBlockedConnections=coalesce(newAvgBlockedConnections, avgBlockedConnections), @@ -43,8 +42,8 @@ known_false_positives: The false-positive rate may vary based on the values of`d tags: analytics_story: - Suspicious AWS Traffic - - AWS Network ACL Activity - Command and Control + - AWS Network ACL Activity kill_chain_phases: - Actions on Objectives - Command and Control @@ -54,3 +53,4 @@ tags: - DE.AE - DE.CM - PR.AC + security_domain: network diff --git a/detections/detect_spike_in_network_acl_activity.yml b/detections/detect_spike_in_network_acl_activity.yml index f878514d68..6ee54ac4a3 100644 --- a/detections/detect_spike_in_network_acl_activity.yml +++ b/detections/detect_spike_in_network_acl_activity.yml @@ -17,11 +17,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` `network_acl_events` [search `cloudtrail` - `network_acl_events` | spath output=arn path=userIdentity.arn | stats count as apiCalls - by arn | inputlookup network_acl_activity_baseline append=t | fields - latestCount - | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls - + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, +search: '`cloudtrail` `network_acl_events` [search `cloudtrail` `network_acl_events` + | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup + network_acl_activity_baseline append=t | fields - latestCount | stats values(*) + as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, @@ -45,3 +45,4 @@ tags: - DE.DP - DE.CM - PR.AC + security_domain: network diff --git a/detections/detect_spike_in_s3_bucket_deletion.yml b/detections/detect_spike_in_s3_bucket_deletion.yml index 62e679eff3..9df4f6e1a3 100644 --- a/detections/detect_spike_in_s3_bucket_deletion.yml +++ b/detections/detect_spike_in_s3_bucket_deletion.yml @@ -17,21 +17,20 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` eventName=DeleteBucket [search `cloudtrail` - eventName=DeleteBucket | spath output=arn path=userIdentity.arn | stats count as - apiCalls by arn | inputlookup s3_deletion_baseline append=t | fields - latestCount - | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls - + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, - 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, - avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), - numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, - stdevApiCalls | outputlookup s3_deletion_baseline | eval dataPointThreshold = 15, - deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) - AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as - userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn - | spath output=bucketName path=requestParameters.bucketName | stats values(bucketName) - as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user - | `detect_spike_in_s3_bucket_deletion_filter`' +search: '`cloudtrail` eventName=DeleteBucket [search `cloudtrail` eventName=DeleteBucket + | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup + s3_deletion_baseline append=t | fields - latestCount | stats values(*) as * by arn + | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 + | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) + | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, + stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) + | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup + s3_deletion_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval + isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints + > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | + table userIdentity.arn] | spath output=user userIdentity.arn | spath output=bucketName + path=requestParameters.bucketName | stats values(bucketName) as bucketName, count + as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_s3_bucket_deletion_filter`' known_false_positives: Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. tags: @@ -45,3 +44,4 @@ tags: - DE.DP - DE.CM - PR.AC + security_domain: network diff --git a/detections/detect_spike_in_security_group_activity.yml b/detections/detect_spike_in_security_group_activity.yml index d449dc6f22..f9bf83686d 100644 --- a/detections/detect_spike_in_security_group_activity.yml +++ b/detections/detect_spike_in_security_group_activity.yml @@ -18,11 +18,11 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` `security_group_api_calls` [search `cloudtrail` - `security_group_api_calls` | spath output=arn path=userIdentity.arn | stats count - as apiCalls by arn | inputlookup security_group_activity_baseline append=t | fields - - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval - newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, +search: '`cloudtrail` `security_group_api_calls` [search `cloudtrail` `security_group_api_calls` + | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup + security_group_activity_baseline append=t | fields - latestCount | stats values(*) + as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, @@ -45,3 +45,4 @@ tags: - DE.DP - DE.CM - PR.AC + security_domain: network diff --git a/detections/detect_unauthorized_assets_by_mac_address.yml b/detections/detect_unauthorized_assets_by_mac_address.yml index f190d3877e..40e6c5673b 100644 --- a/detections/detect_unauthorized_assets_by_mac_address.yml +++ b/detections/detect_unauthorized_assets_by_mac_address.yml @@ -38,3 +38,4 @@ tags: nist: - ID.AM - PR.DS + security_domain: network diff --git a/detections/detect_usb_device_insertion.yml b/detections/detect_usb_device_insertion.yml index 6b3d32ffa2..442ac3db5b 100644 --- a/detections/detect_usb_device_insertion.yml +++ b/detections/detect_usb_device_insertion.yml @@ -35,3 +35,4 @@ tags: nist: - PR.PT - PR.DS + security_domain: endpoint diff --git a/detections/detect_use_of_cmd_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml similarity index 90% rename from detections/detect_use_of_cmd_to_launch_script_interpreters.yml rename to detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml index e56fd49dbd..b378d2ada7 100644 --- a/detections/detect_use_of_cmd_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml @@ -1,4 +1,4 @@ -name: Detect Use of cmd to Launch Script Interpreters +name: Detect Use of cmd exe to Launch Script Interpreters id: b89919ed-fe5f-492c-b139-95dbb162039e version: 3 date: '2020-03-02' @@ -18,12 +18,12 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces where Processes.parent_process_name="cmd.exe" (Processes.process_name=cscript.exe OR Processes.process_name =wscript.exe) by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` - | `detect_use_of_cmd_to_launch_script_interpreters_filter`' + | `detect_use_of_cmd_exe_to_launch_script_interpreters_filter`' known_false_positives: Some legitimate applications may exhibit this behavior. tags: analytics_story: - - Suspicious Command-Line Executions - Emotet Malware (DHS Report TA18-201A) + - Suspicious Command-Line Executions mitre_attack_id: - T1059 kill_chain_phases: @@ -33,3 +33,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/detect_web_traffic_to_dynamic_domain_providers.yml b/detections/detect_web_traffic_to_dynamic_domain_providers.yml index 736a7ff11d..db40e11824 100644 --- a/detections/detect_web_traffic_to_dynamic_domain_providers.yml +++ b/detections/detect_web_traffic_to_dynamic_domain_providers.yml @@ -44,3 +44,4 @@ tags: nist: - PR.IP - DE.DP + security_domain: network diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml index db2afbc202..f768c855a9 100644 --- a/detections/detection_of_dns_tunnels.yml +++ b/detections/detection_of_dns_tunnels.yml @@ -52,3 +52,4 @@ tags: nist: - PR.PT - PR.DS + security_domain: network diff --git a/detections/detection_of_tools_built_by_nirsoft.yml b/detections/detection_of_tools_built_by_nirsoft.yml index 086935f03c..31f2e0df3f 100644 --- a/detections/detection_of_tools_built_by_nirsoft.yml +++ b/detections/detection_of_tools_built_by_nirsoft.yml @@ -32,3 +32,4 @@ tags: - CIS 3 nist: - PR.IP + security_domain: endpoint diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml index b5952ff44e..39db71ceff 100644 --- a/detections/disabling_remote_user_account_control.yml +++ b/detections/disabling_remote_user_account_control.yml @@ -21,8 +21,8 @@ known_false_positives: This registry key may be modified via administrators to i a change in system policy. This type of change should be a very rare occurrence. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Defense Evasion Tactics + - Suspicious Windows Registry Activities mitre_attack_id: - T1112 kill_chain_phases: @@ -32,3 +32,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/dns_query_length_outliers___mltk.yml b/detections/dns_query_length_outliers___mltk.yml index a877746d66..ce5415e95b 100644 --- a/detections/dns_query_length_outliers___mltk.yml +++ b/detections/dns_query_length_outliers___mltk.yml @@ -47,9 +47,9 @@ known_false_positives: If you are seeing more results than desired, you may cons the support search to re-build the ML model on the latest data. tags: analytics_story: - - Hidden Cobra Malware - Command and Control - Suspicious DNS Traffic + - Hidden Cobra Malware mitre_attack_id: - T1043 kill_chain_phases: @@ -61,3 +61,4 @@ tags: - PR.PT - DE.AE - DE.CM + security_domain: network diff --git a/detections/dns_query_length_with_high_standard_deviation.yml b/detections/dns_query_length_with_high_standard_deviation.yml index 28675f08d9..f0cfbc3c3a 100644 --- a/detections/dns_query_length_with_high_standard_deviation.yml +++ b/detections/dns_query_length_with_high_standard_deviation.yml @@ -18,9 +18,9 @@ search: '| tstats `security_content_summariesonly` count from datamodel=Network_ known_false_positives: It's possible there can be long domain names that are legitimate. tags: analytics_story: - - Hidden Cobra Malware - Command and Control - Suspicious DNS Traffic + - Hidden Cobra Malware mitre_attack_id: - T1043 kill_chain_phases: @@ -32,3 +32,4 @@ tags: - PR.PT - DE.AE - DE.CM + security_domain: network diff --git a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml index eface92f00..fb086a3021 100644 --- a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml +++ b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml @@ -18,10 +18,10 @@ known_false_positives: Legitimate DNS activity can be detected in this search. I verify and update the list of authorized DNS servers as appropriate. tags: analytics_story: - - DNS Hijacking - Command and Control - Host Redirection - Suspicious DNS Traffic + - DNS Hijacking kill_chain_phases: - Command and Control cis20: @@ -35,3 +35,4 @@ tags: - PR.IP - DE.AE - DE.CM + security_domain: network diff --git a/detections/dns_record_changed.yml b/detections/dns_record_changed.yml index 37c0a05b6d..389057c1b3 100644 --- a/detections/dns_record_changed.yml +++ b/detections/dns_record_changed.yml @@ -47,3 +47,4 @@ tags: - PR.IP - DE.AE - DE.CM + security_domain: network diff --git a/detections/dump_lsass_via_comsvcs_dll.yml b/detections/dump_lsass_via_comsvcs_dll.yml index b325a8df91..3b04d86a30 100644 --- a/detections/dump_lsass_via_comsvcs_dll.yml +++ b/detections/dump_lsass_via_comsvcs_dll.yml @@ -31,3 +31,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/ec2_instance_modified_with_previously_unseen_user.yml b/detections/ec2_instance_modified_with_previously_unseen_user.yml index 43f2fbe0cd..d1f164c233 100644 --- a/detections/ec2_instance_modified_with_previously_unseen_user.yml +++ b/detections/ec2_instance_modified_with_previously_unseen_user.yml @@ -12,14 +12,13 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` `ec2_modification_api_calls` [search `cloudtrail` - `ec2_modification_api_calls` errorCode=success | stats earliest(_time) as firstTime - latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | - inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) - as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user - | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename - arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId +search: '`cloudtrail` `ec2_modification_api_calls` [search `cloudtrail` `ec2_modification_api_calls` + errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime + by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_modifications_by_user + | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup + previously_seen_ec2_modifications_by_user | eval newUser=if(firstTime >= relative_time(now(), + "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId | spath output=user userIdentity.arn | table _time, user, dest | `ec2_instance_modified_with_previously_unseen_user_filter`' known_false_positives: It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is @@ -31,3 +30,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/ec2_instance_started_in_previously_unseen_region.yml b/detections/ec2_instance_started_in_previously_unseen_region.yml index 50ba795c21..604c1ade54 100644 --- a/detections/ec2_instance_started_in_previously_unseen_region.yml +++ b/detections/ec2_instance_started_in_previously_unseen_region.yml @@ -12,8 +12,8 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`cloudtrail` earliest=-1h StartInstances | stats earliest(_time) - as earliest latest(_time) as latest by awsRegion | inputlookup append=t previously_seen_aws_regions.csv +search: '`cloudtrail` earliest=-1h StartInstances | stats earliest(_time) as earliest + latest(_time) as latest by awsRegion | inputlookup append=t previously_seen_aws_regions.csv | stats min(earliest) as earliest max(latest) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | eval regionStatus=if(earliest >= relative_time(now(),"-1d@d"), "Instance Started in a New Region","Previously Seen Region") | `security_content_ctime(earliest)` @@ -32,3 +32,4 @@ tags: nist: - DE.DP - DE.AE + security_domain: network diff --git a/detections/ec2_instance_started_with_previously_unseen_ami.yml b/detections/ec2_instance_started_with_previously_unseen_ami.yml index 8553cfcd53..f11876a2a8 100644 --- a/detections/ec2_instance_started_with_previously_unseen_ami.yml +++ b/detections/ec2_instance_started_with_previously_unseen_ami.yml @@ -11,9 +11,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` - eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) - as lastTime by requestParameters.instancesSet.items{}.imageId | rename requestParameters.instancesSet.items{}.imageId +search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances + errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime + by requestParameters.instancesSet.items{}.imageId | rename requestParameters.instancesSet.items{}.imageId as amiID | inputlookup append=t previously_seen_ec2_amis.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | eval newAMI=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` @@ -32,3 +32,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml index 68d8464232..b4266ad792 100644 --- a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml +++ b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml @@ -11,9 +11,9 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` - eventName=RunInstances errorCode=success | fillnull value="m1.small" requestParameters.instanceType - | stats earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType +search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances + errorCode=success | fillnull value="m1.small" requestParameters.instanceType | stats + earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType | rename requestParameters.instanceType as instanceType | inputlookup append=t previously_seen_ec2_instance_types.csv | stats min(earliest) as earliest max(latest) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | eval newType=if(earliest >= relative_time(now(), @@ -32,3 +32,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/ec2_instance_started_with_previously_unseen_user.yml b/detections/ec2_instance_started_with_previously_unseen_user.yml index faaf81ff45..97a400d625 100644 --- a/detections/ec2_instance_started_with_previously_unseen_user.yml +++ b/detections/ec2_instance_started_with_previously_unseen_user.yml @@ -11,14 +11,13 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: David Dorsey, Splunk -search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` - eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) - as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t - previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) - as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | eval - newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename - arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType +search: '`cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances + errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime + by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv + | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup + previously_seen_ec2_launches_by_user.csv | eval newUser=if(firstTime >= relative_time(now(), + "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as user | table _time, user, dest, instanceType | `ec2_instance_started_with_previously_unseen_user_filter`' known_false_positives: It's possible that a user will start to create EC2 instances @@ -32,3 +31,4 @@ tags: - CIS 1 nist: - ID.AM + security_domain: endpoint diff --git a/detections/email_attachments_with_lots_of_spaces.yml b/detections/email_attachments_with_lots_of_spaces.yml index 23662d40af..631f5d4103 100644 --- a/detections/email_attachments_with_lots_of_spaces.yml +++ b/detections/email_attachments_with_lots_of_spaces.yml @@ -37,3 +37,4 @@ tags: - CIS 7 nist: - PR.IP + security_domain: network diff --git a/detections/email_files_written_outside_of_the_outlook_directory.yml b/detections/email_files_written_outside_of_the_outlook_directory.yml index 9bdee8d4a8..853fad29d2 100644 --- a/detections/email_files_written_outside_of_the_outlook_directory.yml +++ b/detections/email_files_written_outside_of_the_outlook_directory.yml @@ -32,3 +32,4 @@ tags: - Actions on Objectives cis20: - CIS 8 + security_domain: endpoint diff --git a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml index cb38ddd234..4732f4101f 100644 --- a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml +++ b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml @@ -46,3 +46,4 @@ tags: - PR.PT - DE.CM - DE.AE + security_domain: network diff --git a/detections/excessive_dns_failures.yml b/detections/excessive_dns_failures.yml index d32c4eb1e5..30843ef83d 100644 --- a/detections/excessive_dns_failures.yml +++ b/detections/excessive_dns_failures.yml @@ -36,3 +36,4 @@ tags: - PR.PT - DE.AE - DE.CM + security_domain: network diff --git a/detections/execution_of_file_with_multiple_extensions.yml b/detections/execution_of_file_with_multiple_extensions.yml index ac65c2f205..923d92e4ea 100644 --- a/detections/execution_of_file_with_multiple_extensions.yml +++ b/detections/execution_of_file_with_multiple_extensions.yml @@ -33,3 +33,4 @@ tags: - DE.CM - PR.PT - PR.IP + security_domain: endpoint diff --git a/detections/execution_of_file_with_spaces_before_extension.yml b/detections/execution_of_file_with_spaces_before_extension.yml index 73b0257d79..b9e76a3457 100644 --- a/detections/execution_of_file_with_spaces_before_extension.yml +++ b/detections/execution_of_file_with_spaces_before_extension.yml @@ -32,3 +32,4 @@ tags: - DE.CM - PR.PT - PR.IP + security_domain: endpoint diff --git a/detections/extended_period_without_successful_netbackup_backups.yml b/detections/extended_period_without_successful_netbackup_backups.yml index 7152f6c429..7f5d73143e 100644 --- a/detections/extended_period_without_successful_netbackup_backups.yml +++ b/detections/extended_period_without_successful_netbackup_backups.yml @@ -13,8 +13,8 @@ how_to_implement: To successfully implement this search you need to first obtain type: ESCU references: [] author: David Dorsey, Splunk -search: '`netbackup` MESSAGE="Disk/Partition backup completed successfully." - | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` +search: '`netbackup` MESSAGE="Disk/Partition backup completed successfully." | stats + latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest | `extended_period_without_successful_netbackup_backups_filter`' known_false_positives: None identified @@ -25,3 +25,4 @@ tags: - CIS 10 nist: - PR.IP + security_domain: endpoint diff --git a/detections/file_with_samsam_extension.yml b/detections/file_with_samsam_extension.yml index dd18fcd67e..88a370a3b2 100644 --- a/detections/file_with_samsam_extension.yml +++ b/detections/file_with_samsam_extension.yml @@ -30,3 +30,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/first_time_seen_command_line_argument.yml b/detections/first_time_seen_command_line_argument.yml index d0d6384f46..ad1f7416d4 100644 --- a/detections/first_time_seen_command_line_argument.yml +++ b/detections/first_time_seen_command_line_argument.yml @@ -34,11 +34,11 @@ known_false_positives: Legitimate programs can also use command-line arguments t macro to exclude legitimate parent_process_name tags: analytics_story: - - Suspicious Command-Line Executions - - DHS Report TA18-074A - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Hidden Cobra Malware + - DHS Report TA18-074A - Orangeworm Attack Group + - Suspicious Command-Line Executions + - Hidden Cobra Malware mitre_attack_id: - T1064 - T1059 @@ -52,3 +52,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/first_time_seen_running_windows_service.yml b/detections/first_time_seen_running_windows_service.yml index 3133099c10..7b11d0e497 100644 --- a/detections/first_time_seen_running_windows_service.yml +++ b/detections/first_time_seen_running_windows_service.yml @@ -12,8 +12,8 @@ how_to_implement: While this search does not require you to adhere to Splunk CIM type: ESCU references: [] author: David Dorsey, Splunk -search: '`wineventlog_system` signature_id=7036 | rename param1 as service_name - | rename param2 as action | search action="running" [ search `wineventlog_system` +search: '`wineventlog_system` signature_id=7036 | rename param1 as service_name | + rename param2 as action | search action="running" [ search `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | inputlookup append=t previously_seen_running_windows_services @@ -42,3 +42,4 @@ tags: - PR.DS - PR.AC - DE.AE + security_domain: endpoint diff --git a/detections/gcp_gcr_container_uploaded.yml b/detections/gcp_gcr_container_uploaded.yml index 6191290f09..9d1bcb910a 100644 --- a/detections/gcp_gcr_container_uploaded.yml +++ b/detections/gcp_gcr_container_uploaded.yml @@ -23,3 +23,4 @@ known_false_positives: Uploading container is a normal behavior from developers tags: analytics_story: - Container Implantation Monitoring & Investigation + security_domain: threat diff --git a/detections/gcp_kubernetes_cluster_scan_detection.yml b/detections/gcp_kubernetes_cluster_scan_detection.yml index f46adc0149..711d7ac6ec 100644 --- a/detections/gcp_kubernetes_cluster_scan_detection.yml +++ b/detections/gcp_kubernetes_cluster_scan_detection.yml @@ -11,7 +11,7 @@ how_to_implement: You must install the GCP App for Splunk (version 2.0.0 or late type: ESCU references: [] author: Rod Soto, Splunk -search: '`google_gcp_pubnet_message` data.protoPayload.requestMetadata.callerIp!=127.0.0.1 +search: '`google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) @@ -27,3 +27,4 @@ tags: - Kubernetes Scanning Activity kill_chain_phases: - Reconnaissance + security_domain: threat diff --git a/detections/hiding_files_and_directories_with_attrib.yml b/detections/hiding_files_and_directories_with_attrib_exe.yml similarity index 94% rename from detections/hiding_files_and_directories_with_attrib.yml rename to detections/hiding_files_and_directories_with_attrib_exe.yml index a3636c8bd0..907b3c5627 100644 --- a/detections/hiding_files_and_directories_with_attrib.yml +++ b/detections/hiding_files_and_directories_with_attrib_exe.yml @@ -1,4 +1,4 @@ -name: Hiding Files And Directories With Attrib +name: Hiding Files And Directories With Attrib exe id: c77162d3-f93c-45cc-80c8-22f6b5264g9f version: 3 date: '2020-03-16' @@ -31,3 +31,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml index 9156d529a7..bede8665ed 100644 --- a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml +++ b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml @@ -45,3 +45,4 @@ tags: - PR.PT - DE.CM - DE.AE + security_domain: network diff --git a/detections/identify_new_user_accounts.yml b/detections/identify_new_user_accounts.yml index e339ff536e..43f2347468 100644 --- a/detections/identify_new_user_accounts.yml +++ b/detections/identify_new_user_accounts.yml @@ -27,3 +27,4 @@ tags: - CIS 16 nist: - PR.IP + security_domain: access diff --git a/detections/large_volume_of_dns_any_queries.yml b/detections/large_volume_of_dns_any_queries.yml index 62f27ff0fb..e99fdd044e 100644 --- a/detections/large_volume_of_dns_any_queries.yml +++ b/detections/large_volume_of_dns_any_queries.yml @@ -27,3 +27,4 @@ tags: - PR.PT - DE.AE - PR.IP + security_domain: network diff --git a/detections/macos___re_opened_applications.yml b/detections/macos___re_opened_applications.yml index bce35562ea..3f3f919250 100644 --- a/detections/macos___re_opened_applications.yml +++ b/detections/macos___re_opened_applications.yml @@ -33,3 +33,4 @@ tags: nist: - DE.DP - DE.CM + security_domain: threat diff --git a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml index 0e4aee69c1..d83e78416b 100644 --- a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml +++ b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml @@ -42,3 +42,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/malicious_powershell_process___encoded_command.yml b/detections/malicious_powershell_process___encoded_command.yml index cc9700e81e..829dbf65a7 100644 --- a/detections/malicious_powershell_process___encoded_command.yml +++ b/detections/malicious_powershell_process___encoded_command.yml @@ -37,3 +37,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/malicious_powershell_process___execution_policy_bypass.yml b/detections/malicious_powershell_process___execution_policy_bypass.yml index 6bb93419e9..5db36c560e 100644 --- a/detections/malicious_powershell_process___execution_policy_bypass.yml +++ b/detections/malicious_powershell_process___execution_policy_bypass.yml @@ -40,3 +40,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml index 50113f4a7d..4ff1b7b109 100644 --- a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml +++ b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml @@ -42,3 +42,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/malicious_powershell_process_with_obfuscation_techniques.yml b/detections/malicious_powershell_process_with_obfuscation_techniques.yml index 73e2542ecd..550d46e6b1 100644 --- a/detections/malicious_powershell_process_with_obfuscation_techniques.yml +++ b/detections/malicious_powershell_process_with_obfuscation_techniques.yml @@ -39,3 +39,4 @@ tags: - PR.PT - DE.CM - PR.IP + security_domain: endpoint diff --git a/detections/monitor_dns_for_brand_abuse.yml b/detections/monitor_dns_for_brand_abuse.yml index 625290c6bc..2679e358b8 100644 --- a/detections/monitor_dns_for_brand_abuse.yml +++ b/detections/monitor_dns_for_brand_abuse.yml @@ -24,3 +24,4 @@ tags: kill_chain_phases: - Delivery - Actions on Objectives + security_domain: network diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml index 32141899bf..b013646fec 100644 --- a/detections/monitor_email_for_brand_abuse.yml +++ b/detections/monitor_email_for_brand_abuse.yml @@ -29,3 +29,4 @@ tags: - CIS 7 nist: - PR.IP + security_domain: network diff --git a/detections/monitor_registry_keys_for_print_monitors.yml b/detections/monitor_registry_keys_for_print_monitors.yml index 0ce1a37e62..33b1dd3202 100644 --- a/detections/monitor_registry_keys_for_print_monitors.yml +++ b/detections/monitor_registry_keys_for_print_monitors.yml @@ -36,3 +36,4 @@ tags: - PR.PT - DE.CM - PR.AC + security_domain: endpoint diff --git a/detections/monitor_web_traffic_for_brand_abuse.yml b/detections/monitor_web_traffic_for_brand_abuse.yml index 31399c7e0f..7455e68ccf 100644 --- a/detections/monitor_web_traffic_for_brand_abuse.yml +++ b/detections/monitor_web_traffic_for_brand_abuse.yml @@ -24,3 +24,4 @@ tags: - CIS 7 nist: - PR.IP + security_domain: network diff --git a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml index 6eab8b8f48..ffcb72b358 100644 --- a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml +++ b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml @@ -27,3 +27,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: access diff --git a/detections/new_container_uploaded_to_aws_ecr.yml b/detections/new_container_uploaded_to_aws_ecr.yml index a1bb251a57..e8fe98195f 100644 --- a/detections/new_container_uploaded_to_aws_ecr.yml +++ b/detections/new_container_uploaded_to_aws_ecr.yml @@ -22,3 +22,4 @@ known_false_positives: Uploading container is a normal behavior from developers tags: analytics_story: - Container Implantation Monitoring & Investigation + security_domain: threat diff --git a/detections/no_windows_updates_in_a_time_frame.yml b/detections/no_windows_updates_in_a_time_frame.yml index fe2f9470b5..2b1366890b 100644 --- a/detections/no_windows_updates_in_a_time_frame.yml +++ b/detections/no_windows_updates_in_a_time_frame.yml @@ -32,3 +32,4 @@ tags: nist: - PR.PT - PR.MA + security_domain: endpoint diff --git a/detections/okta_account_lockout_events.yml b/detections/okta_account_lockout_events.yml index 343783d221..ec2e0264a1 100644 --- a/detections/okta_account_lockout_events.yml +++ b/detections/okta_account_lockout_events.yml @@ -7,10 +7,9 @@ how_to_implement: This search is specific to Okta and requires Okta logs are bei ingested in your Splunk deployment. type: ESCU author: Rico Valdez, Splunk -search: '`okta` displayMessage="Max sign in attempts exceeded" | rename - client.geographicalContext.country as country, client.geographicalContext.state - as state, client.geographicalContext.city as city | table _time, user, country, - state, city, src_ip |`okta_user_lockouts_filter`' +search: '`okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country + as country, client.geographicalContext.state as state, client.geographicalContext.city + as city | table _time, user, country, state, city, src_ip |`okta_user_lockouts_filter`' known_false_positives: None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. @@ -23,3 +22,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: access diff --git a/detections/okta_failed_sso_attempts.yml b/detections/okta_failed_sso_attempts.yml index a2f09c90d4..47caee3b3d 100644 --- a/detections/okta_failed_sso_attempts.yml +++ b/detections/okta_failed_sso_attempts.yml @@ -7,10 +7,9 @@ how_to_implement: This search is specific to Okta and requires Okta logs are bei ingested in your Splunk deployment. type: ESCU author: Rico Valdez, Splunk -search: '`okta` displayMessage="User attempted unauthorized access to app" - | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count - by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | - `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter`' +search: '`okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) + as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, + src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter`' known_false_positives: There may be a faulty config preventing legitmate users from accessing apps they should have access to. tags: @@ -22,3 +21,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: access diff --git a/detections/okta_user_logins_from_multiple_cities.yml b/detections/okta_user_logins_from_multiple_cities.yml index 017bbb457a..c355f68000 100644 --- a/detections/okta_user_logins_from_multiple_cities.yml +++ b/detections/okta_user_logins_from_multiple_cities.yml @@ -28,3 +28,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: access diff --git a/detections/open_redirect_in_splunk_web.yml b/detections/open_redirect_in_splunk_web.yml index d2a9a94009..ba7ab0d8fc 100644 --- a/detections/open_redirect_in_splunk_web.yml +++ b/detections/open_redirect_in_splunk_web.yml @@ -26,3 +26,4 @@ tags: - PR.AC - PR.IP - DE.CM + security_domain: network diff --git a/detections/osquery_pack___coldroot_detection.yml b/detections/osquery_pack___coldroot_detection.yml index 253f906356..409b611ae0 100644 --- a/detections/osquery_pack___coldroot_detection.yml +++ b/detections/osquery_pack___coldroot_detection.yml @@ -28,3 +28,4 @@ tags: - DE.DP - DE.CM - PR.PT + security_domain: threat diff --git a/detections/overwriting_accessibility_binaries.yml b/detections/overwriting_accessibility_binaries.yml index 4c226c3d63..be36fd0f99 100644 --- a/detections/overwriting_accessibility_binaries.yml +++ b/detections/overwriting_accessibility_binaries.yml @@ -35,3 +35,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/process_execution_via_wmi.yml b/detections/process_execution_via_wmi.yml index b3d9139b71..de1d2b1346 100644 --- a/detections/process_execution_via_wmi.yml +++ b/detections/process_execution_via_wmi.yml @@ -32,3 +32,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: endpoint diff --git a/detections/processes_created_by_netsh.yml b/detections/processes_created_by_netsh.yml index b49e8bc17a..3ad4e38743 100644 --- a/detections/processes_created_by_netsh.yml +++ b/detections/processes_created_by_netsh.yml @@ -36,3 +36,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/processes_launching_netsh.yml b/detections/processes_launching_netsh.yml index f24b7100cd..f2f2c9f80f 100644 --- a/detections/processes_launching_netsh.yml +++ b/detections/processes_launching_netsh.yml @@ -23,8 +23,8 @@ known_false_positives: Some VPN applications are known to launch netsh.exe. Outs commands. tags: analytics_story: - - DHS Report TA18-074A - Disabling Security Tools + - DHS Report TA18-074A - Netsh Abuse mitre_attack_id: - T1059 @@ -36,3 +36,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/processes_tapping_keyboard_events.yml b/detections/processes_tapping_keyboard_events.yml index 388c1362df..98266326a8 100644 --- a/detections/processes_tapping_keyboard_events.yml +++ b/detections/processes_tapping_keyboard_events.yml @@ -31,3 +31,4 @@ tags: - CIS 8 nist: - DE.DP + security_domain: threat diff --git a/detections/prohibited_network_traffic_allowed.yml b/detections/prohibited_network_traffic_allowed.yml index c16f37b8cb..b3c639bfeb 100644 --- a/detections/prohibited_network_traffic_allowed.yml +++ b/detections/prohibited_network_traffic_allowed.yml @@ -23,9 +23,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Prohibited Traffic Allowed or Protocol Mismatch - Ransomware - Command and Control + - Prohibited Traffic Allowed or Protocol Mismatch mitre_attack_id: - T1043 - T1048 @@ -38,3 +38,4 @@ tags: nist: - DE.AE - PR.AC + security_domain: network diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index 8ec7f0ced0..e450979f56 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -36,3 +36,4 @@ tags: nist: - ID.AM - PR.DS + security_domain: endpoint diff --git a/detections/protocol_or_port_mismatch.yml b/detections/protocol_or_port_mismatch.yml index 729457940d..acb7c7eac2 100644 --- a/detections/protocol_or_port_mismatch.yml +++ b/detections/protocol_or_port_mismatch.yml @@ -38,3 +38,4 @@ tags: nist: - DE.AE - PR.AC + security_domain: network diff --git a/detections/protocols_passing_authentication_in_cleartext.yml b/detections/protocols_passing_authentication_in_cleartext.yml index 1d709c2c05..a758d28e42 100644 --- a/detections/protocols_passing_authentication_in_cleartext.yml +++ b/detections/protocols_passing_authentication_in_cleartext.yml @@ -33,3 +33,4 @@ tags: - DE.AE - PR.AC - PR.DS + security_domain: network diff --git a/detections/reg_manipulating_windows_services_registry_keys.yml b/detections/reg_exe_manipulating_windows_services_registry_keys.yml similarity index 90% rename from detections/reg_manipulating_windows_services_registry_keys.yml rename to detections/reg_exe_manipulating_windows_services_registry_keys.yml index 2d5a1bb0f1..f40fee03d3 100644 --- a/detections/reg_manipulating_windows_services_registry_keys.yml +++ b/detections/reg_exe_manipulating_windows_services_registry_keys.yml @@ -1,4 +1,4 @@ -name: Reg Manipulating Windows Services Registry Keys +name: Reg exe Manipulating Windows Services Registry Keys id: 8470d755-0c13-45b3-bd63-387a373c10cf version: 2 date: '2019-03-01' @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table - process_id dest registry_path] | `reg_manipulating_windows_services_registry_keys_filter`' + process_id dest registry_path] | `reg_exe_manipulating_windows_services_registry_keys_filter`' known_false_positives: It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. @@ -43,3 +43,4 @@ tags: - PR.AC - PR.AT - DE.CM + security_domain: endpoint diff --git a/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml similarity index 89% rename from detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml rename to detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml index 502e90c0b2..bf889661bd 100644 --- a/detections/reg_used_to_hide_files_or_directories_via_registry_keys.yml +++ b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml @@ -1,4 +1,4 @@ -name: Reg used to hide files or directories via registry keys +name: Reg exe used to hide files directories via registry keys id: c77162d3-f93c-45cc-80c8-22f6b5264x9f version: 2 date: '2019-02-27' @@ -17,12 +17,12 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as where Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)" | `reg_used_to_hide_files_or_directories_via_registry_keys_filter`' + |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)" | `reg_exe_used_to_hide_files_directories_via_registry_keys_filter`' known_false_positives: None at the moment tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Defense Evasion Tactics + - Suspicious Windows Registry Activities - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives @@ -30,3 +30,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/registry_keys_for_creating_shim_databases.yml b/detections/registry_keys_for_creating_shim_databases.yml index 7a9cd19d90..d05f61cc01 100644 --- a/detections/registry_keys_for_creating_shim_databases.yml +++ b/detections/registry_keys_for_creating_shim_databases.yml @@ -32,3 +32,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml index 73c8e905a7..bfe5ef5936 100644 --- a/detections/registry_keys_used_for_persistence.yml +++ b/detections/registry_keys_used_for_persistence.yml @@ -27,13 +27,13 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - - DHS Report TA18-074A - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Ransomware - Suspicious Windows Registry Activities - - Windows Persistence Techniques + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Suspicious MSHTA Activity + - Emotet Malware (DHS Report TA18-201A) + - Ransomware + - DHS Report TA18-074A + - Windows Persistence Techniques mitre_attack_id: - T1103 - T1131 @@ -45,3 +45,4 @@ tags: - PR.PT - DE.CM - DE.AE + security_domain: endpoint diff --git a/detections/registry_keys_used_for_privilege_escalation.yml b/detections/registry_keys_used_for_privilege_escalation.yml index ce8e067c36..10ddb58347 100644 --- a/detections/registry_keys_used_for_privilege_escalation.yml +++ b/detections/registry_keys_used_for_privilege_escalation.yml @@ -26,8 +26,8 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Privilege Escalation + - Suspicious Windows Registry Activities mitre_attack_id: - T1015 kill_chain_phases: @@ -37,3 +37,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/remote_desktop_network_bruteforce.yml b/detections/remote_desktop_network_bruteforce.yml index c336a1026f..480bfaa6c5 100644 --- a/detections/remote_desktop_network_bruteforce.yml +++ b/detections/remote_desktop_network_bruteforce.yml @@ -34,3 +34,4 @@ tags: - DE.AE - PR.AC - PR.IP + security_domain: network diff --git a/detections/remote_desktop_network_traffic.yml b/detections/remote_desktop_network_traffic.yml index f8293627e6..98ff98989b 100644 --- a/detections/remote_desktop_network_traffic.yml +++ b/detections/remote_desktop_network_traffic.yml @@ -27,8 +27,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Remote Desktop may be used legitimately by users on the network. tags: analytics_story: - - Hidden Cobra Malware - SamSam Ransomware + - Hidden Cobra Malware - Lateral Movement mitre_attack_id: - T1076 @@ -42,3 +42,4 @@ tags: - DE.AE - PR.AC - PR.IP + security_domain: network diff --git a/detections/remote_desktop_process_running_on_system.yml b/detections/remote_desktop_process_running_on_system.yml index b15a5c0b23..fb9eaccb95 100644 --- a/detections/remote_desktop_process_running_on_system.yml +++ b/detections/remote_desktop_process_running_on_system.yml @@ -39,3 +39,4 @@ tags: - DE.AE - PR.AC - PR.IP + security_domain: endpoint diff --git a/detections/remote_process_instantiation_via_wmi.yml b/detections/remote_process_instantiation_via_wmi.yml index 656de383fe..2806df701d 100644 --- a/detections/remote_process_instantiation_via_wmi.yml +++ b/detections/remote_process_instantiation_via_wmi.yml @@ -37,3 +37,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: endpoint diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml index 8c159e9d87..2d4d896985 100644 --- a/detections/remote_registry_key_modifications.yml +++ b/detections/remote_registry_key_modifications.yml @@ -20,8 +20,8 @@ known_false_positives: This technique may be legitimately used by administrators modify remote registries, so it's important to filter these events out. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Defense Evasion Tactics + - Suspicious Windows Registry Activities - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives @@ -30,3 +30,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/remote_wmi_command_attempt.yml b/detections/remote_wmi_command_attempt.yml index 8978d2afa7..b6359fe5b0 100644 --- a/detections/remote_wmi_command_attempt.yml +++ b/detections/remote_wmi_command_attempt.yml @@ -35,3 +35,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: endpoint diff --git a/detections/rundll_loading_dll_by_ordinal.yml b/detections/rundll_loading_dll_by_ordinal.yml index b904b94d46..d2d1f405ef 100644 --- a/detections/rundll_loading_dll_by_ordinal.yml +++ b/detections/rundll_loading_dll_by_ordinal.yml @@ -36,3 +36,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/samsam_test_file_write.yml b/detections/samsam_test_file_write.yml index 4e5ff40187..b017460a4b 100644 --- a/detections/samsam_test_file_write.yml +++ b/detections/samsam_test_file_write.yml @@ -27,3 +27,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/manipulating_windows_services_with_sc.yml b/detections/sc_exe_manipulating_windows_services.yml similarity index 90% rename from detections/manipulating_windows_services_with_sc.yml rename to detections/sc_exe_manipulating_windows_services.yml index 86f05223e7..969072b97e 100644 --- a/detections/manipulating_windows_services_with_sc.yml +++ b/detections/sc_exe_manipulating_windows_services.yml @@ -1,4 +1,4 @@ -name: Manipulating Windows Services with sc +name: Sc exe Manipulating Windows Services id: f0c693d8-2a89-4ce7-80b4-98fea4c3ea6d version: 2 date: '2019-02-27' @@ -17,17 +17,17 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as where Processes.process_name = sc.exe (Processes.process="* create *" OR Processes.process="* config *") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `manipulating_windows_services_with_sc_filter`' + | `security_content_ctime(lastTime)` | `sc_exe_manipulating_windows_services_filter`' known_false_positives: Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. tags: analytics_story: - - DHS Report TA18-074A - - Windows Service Abuse - - Windows Persistence Techniques - - Orangeworm Attack Group - Disabling Security Tools + - Windows Service Abuse + - DHS Report TA18-074A + - Orangeworm Attack Group + - Windows Persistence Techniques mitre_attack_id: - T1050 - T1031 @@ -44,3 +44,4 @@ tags: - PR.AC - PR.AT - DE.CM + security_domain: endpoint diff --git a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml index f8d80214f3..c1a734dc70 100644 --- a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml +++ b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml @@ -30,3 +30,4 @@ tags: - CIS 3 nist: - PR.IP + security_domain: endpoint diff --git a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml index bd136246c4..5f45878a8b 100644 --- a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml +++ b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml @@ -31,3 +31,4 @@ tags: - CIS 3 nist: - PR.IP + security_domain: endpoint diff --git a/detections/schtasks_scheduling_job_on_remote_system.yml b/detections/schtasks_scheduling_job_on_remote_system.yml index 4f770dab9b..d3f83a6b7b 100644 --- a/detections/schtasks_scheduling_job_on_remote_system.yml +++ b/detections/schtasks_scheduling_job_on_remote_system.yml @@ -32,3 +32,4 @@ tags: - CIS 3 nist: - PR.IP + security_domain: endpoint diff --git a/detections/schtasks_used_for_forcing_a_reboot.yml b/detections/schtasks_used_for_forcing_a_reboot.yml index 55735edce7..8ac57a0d54 100644 --- a/detections/schtasks_used_for_forcing_a_reboot.yml +++ b/detections/schtasks_used_for_forcing_a_reboot.yml @@ -20,8 +20,8 @@ known_false_positives: Administrators may create jobs on systems forcing reboots perform updates, maintenance, etc. tags: analytics_story: - - Windows Persistence Techniques - Ransomware + - Windows Persistence Techniques mitre_attack_id: - T1053 kill_chain_phases: @@ -30,3 +30,4 @@ tags: - CIS 3 nist: - PR.IP + security_domain: endpoint diff --git a/detections/script_execution_via_wmi.yml b/detections/script_execution_via_wmi.yml index 347ad207d1..ca958e579f 100644 --- a/detections/script_execution_via_wmi.yml +++ b/detections/script_execution_via_wmi.yml @@ -32,3 +32,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: endpoint diff --git a/detections/shim_database_file_creation.yml b/detections/shim_database_file_creation.yml index 6287bd2831..bc423cc71d 100644 --- a/detections/shim_database_file_creation.yml +++ b/detections/shim_database_file_creation.yml @@ -33,3 +33,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/shim_database_installation_with_suspicious_parameters.yml b/detections/shim_database_installation_with_suspicious_parameters.yml index fa19888635..c8b0d30842 100644 --- a/detections/shim_database_installation_with_suspicious_parameters.yml +++ b/detections/shim_database_installation_with_suspicious_parameters.yml @@ -33,3 +33,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/short_lived_windows_accounts.yml b/detections/short_lived_windows_accounts.yml index ba8ed384fe..79eff943a1 100644 --- a/detections/short_lived_windows_accounts.yml +++ b/detections/short_lived_windows_accounts.yml @@ -28,3 +28,4 @@ tags: - CIS 16 nist: - PR.IP + security_domain: access diff --git a/detections/single_letter_process_on_endpoint.yml b/detections/single_letter_process_on_endpoint.yml index a4d1c3eb98..a418452e58 100644 --- a/detections/single_letter_process_on_endpoint.yml +++ b/detections/single_letter_process_on_endpoint.yml @@ -30,3 +30,4 @@ tags: nist: - ID.AM - PR.DS + security_domain: endpoint diff --git a/detections/smb_traffic_spike.yml b/detections/smb_traffic_spike.yml index 651efee702..48e9dd49ee 100644 --- a/detections/smb_traffic_spike.yml +++ b/detections/smb_traffic_spike.yml @@ -21,10 +21,10 @@ known_false_positives: A file server may experience high-demand loads that could this analytic to trigger. tags: analytics_story: - - DHS Report TA18-074A - - Hidden Cobra Malware - - Emotet Malware (DHS Report TA18-201A) - Ransomware + - DHS Report TA18-074A + - Emotet Malware (DHS Report TA18-201A) + - Hidden Cobra Malware mitre_attack_id: - T1043 kill_chain_phases: @@ -33,3 +33,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: network diff --git a/detections/smb_traffic_spike___mltk.yml b/detections/smb_traffic_spike___mltk.yml index f8e6216f61..4e7adbeac7 100644 --- a/detections/smb_traffic_spike___mltk.yml +++ b/detections/smb_traffic_spike___mltk.yml @@ -42,10 +42,10 @@ known_false_positives: If you are seeing more results than desired, you may cons the `smb_traffic_spike_mltk_filter` macro to filter out false positive results tags: analytics_story: - - DHS Report TA18-074A - - Hidden Cobra Malware - - Emotet Malware (DHS Report TA18-201A) - Ransomware + - DHS Report TA18-074A + - Emotet Malware (DHS Report TA18-201A) + - Hidden Cobra Malware mitre_attack_id: - T1043 kill_chain_phases: @@ -54,3 +54,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: network diff --git a/detections/spectre_and_meltdown_vulnerable_systems.yml b/detections/spectre_and_meltdown_vulnerable_systems.yml index 2a87753bea..2865b9fe4e 100644 --- a/detections/spectre_and_meltdown_vulnerable_systems.yml +++ b/detections/spectre_and_meltdown_vulnerable_systems.yml @@ -26,3 +26,4 @@ tags: - RS.MI - PR.IP - DE.CM + security_domain: endpoint diff --git a/detections/spike_in_file_writes.yml b/detections/spike_in_file_writes.yml index ace85df4db..2c41c68109 100644 --- a/detections/spike_in_file_writes.yml +++ b/detections/spike_in_file_writes.yml @@ -32,3 +32,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/splunk_enterprise_information_disclosure.yml b/detections/splunk_enterprise_information_disclosure.yml index 980528d5c0..b9f897c7f5 100644 --- a/detections/splunk_enterprise_information_disclosure.yml +++ b/detections/splunk_enterprise_information_disclosure.yml @@ -33,3 +33,4 @@ tags: - PR.AC - PR.IP - DE.CM + security_domain: network diff --git a/detections/sql_injection_with_long_urls.yml b/detections/sql_injection_with_long_urls.yml index 6e0805fc1f..9437718f75 100644 --- a/detections/sql_injection_with_long_urls.yml +++ b/detections/sql_injection_with_long_urls.yml @@ -45,3 +45,4 @@ tags: - PR.PT - PR.IP - DE.CM + security_domain: network diff --git a/detections/suspicious_changes_to_file_associations.yml b/detections/suspicious_changes_to_file_associations.yml index bf0095340e..b64a9965c8 100644 --- a/detections/suspicious_changes_to_file_associations.yml +++ b/detections/suspicious_changes_to_file_associations.yml @@ -26,8 +26,8 @@ known_false_positives: There may be other processes in your environment that use finding false positives, you can modify the search to add those processes as exceptions. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows File Extension and Association Abuse + - Suspicious Windows Registry Activities mitre_attack_id: - T1042 kill_chain_phases: @@ -39,3 +39,4 @@ tags: - DE.CM - PR.PT - PR.IP + security_domain: endpoint diff --git a/detections/suspicious_email___uba_anomaly.yml b/detections/suspicious_email___uba_anomaly.yml index 8695278a92..4d6b270c68 100644 --- a/detections/suspicious_email___uba_anomaly.yml +++ b/detections/suspicious_email___uba_anomaly.yml @@ -31,3 +31,4 @@ tags: - CIS 7 nist: - PR.IP + security_domain: threat diff --git a/detections/suspicious_email_attachment_extensions.yml b/detections/suspicious_email_attachment_extensions.yml index d7cb847959..44e61e9f60 100644 --- a/detections/suspicious_email_attachment_extensions.yml +++ b/detections/suspicious_email_attachment_extensions.yml @@ -37,3 +37,4 @@ tags: nist: - DE.AE - PR.IP + security_domain: network diff --git a/detections/suspicious_file_write.yml b/detections/suspicious_file_write.yml index 45801a2d63..f48d2cba72 100644 --- a/detections/suspicious_file_write.yml +++ b/detections/suspicious_file_write.yml @@ -36,3 +36,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/suspicious_java_classes.yml b/detections/suspicious_java_classes.yml index 2f7d606210..401673b887 100644 --- a/detections/suspicious_java_classes.yml +++ b/detections/suspicious_java_classes.yml @@ -27,3 +27,4 @@ tags: - CIS 12 nist: - DE.AE + security_domain: threat diff --git a/detections/suspicious_lnk_file_launching_a_process.yml b/detections/suspicious_lnk_file_launching_a_process.yml index c6a523cca9..bde03bf9c1 100644 --- a/detections/suspicious_lnk_file_launching_a_process.yml +++ b/detections/suspicious_lnk_file_launching_a_process.yml @@ -39,3 +39,4 @@ tags: nist: - ID.AM - PR.DS + security_domain: network diff --git a/detections/suspicious_reg_process.yml b/detections/suspicious_reg_exe_process.yml similarity index 97% rename from detections/suspicious_reg_process.yml rename to detections/suspicious_reg_exe_process.yml index 9d231429d0..39c8f2d9b6 100644 --- a/detections/suspicious_reg_process.yml +++ b/detections/suspicious_reg_exe_process.yml @@ -1,4 +1,4 @@ -name: Suspicious Reg Process +name: Suspicious Reg exe Process id: a6b3ab4e-dd77-4213-95fa-fc94701995e0 version: 3 date: '2020-03-16' @@ -29,9 +29,9 @@ known_false_positives: It's possible for system administrators to write scripts to filter them out. tags: analytics_story: - - DHS Report TA18-074A - - Windows Defense Evasion Tactics - Disabling Security Tools + - Windows Defense Evasion Tactics + - DHS Report TA18-074A mitre_attack_id: - T1112 - T1089 @@ -41,3 +41,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/suspicious_wevtutil_usage.yml b/detections/suspicious_wevtutil_usage.yml index 3b2d3d9c3e..a7f4b19614 100644 --- a/detections/suspicious_wevtutil_usage.yml +++ b/detections/suspicious_wevtutil_usage.yml @@ -24,8 +24,8 @@ known_false_positives: The wevtutil.exe application is a legitimate Windows even log utility. Administrators may use it to manage Windows event logs. tags: analytics_story: - - Windows Log Manipulation - Ransomware + - Windows Log Manipulation mitre_attack_id: - T1070 kill_chain_phases: @@ -41,3 +41,4 @@ tags: - PR.AC - PR.AT - DE.AE + security_domain: endpoint diff --git a/detections/suspicious_writes_to_system_volume_information.yml b/detections/suspicious_writes_to_system_volume_information.yml index 174a3a5088..d87ab4a645 100644 --- a/detections/suspicious_writes_to_system_volume_information.yml +++ b/detections/suspicious_writes_to_system_volume_information.yml @@ -10,10 +10,10 @@ how_to_implement: You need to be ingesting logs with both the process name and c type: ESCU references: [] author: Rico Valdez, Splunk -search: '(`sysmon` OR tag=process) - EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats count - min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | `suspicious_writes_to_system_volume_information_filter`' +search: (`sysmon` OR tag=process) EventCode=11 process_id!=4 file_path=*System\ Volume\ + Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, + Image, file_path | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + | `suspicious_writes_to_system_volume_information_filter` known_false_positives: It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. @@ -26,3 +26,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/suspicious_writes_to_windows_recycle_bin.yml b/detections/suspicious_writes_to_windows_recycle_bin.yml index d69bbf93d8..9123f3b99d 100644 --- a/detections/suspicious_writes_to_windows_recycle_bin.yml +++ b/detections/suspicious_writes_to_windows_recycle_bin.yml @@ -31,3 +31,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index 69d3f95bf3..289a851d25 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -20,9 +20,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Suspicious Command-Line Executions - Unusual Processes - Ransomware + - Suspicious Command-Line Executions mitre_attack_id: - T1036 kill_chain_phases: @@ -32,3 +32,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/tor_traffic.yml b/detections/tor_traffic.yml index aa181c7289..e1af52cddf 100644 --- a/detections/tor_traffic.yml +++ b/detections/tor_traffic.yml @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None at this time tags: analytics_story: - - Prohibited Traffic Allowed or Protocol Mismatch - Ransomware - Command and Control + - Prohibited Traffic Allowed or Protocol Mismatch mitre_attack_id: - T1043 kill_chain_phases: @@ -33,3 +33,4 @@ tags: - CIS 12 nist: - DE.AE + security_domain: network diff --git a/detections/uncommon_processes_on_endpoint.yml b/detections/uncommon_processes_on_endpoint.yml index 6c56717012..23f3424a39 100644 --- a/detections/uncommon_processes_on_endpoint.yml +++ b/detections/uncommon_processes_on_endpoint.yml @@ -22,8 +22,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Windows Privilege Escalation - Unusual Processes + - Windows Privilege Escalation mitre_attack_id: - T1015 kill_chain_phases: @@ -33,3 +33,4 @@ tags: nist: - ID.AM - PR.DS + security_domain: endpoint diff --git a/detections/unload_sysmon_filter_driver.yml b/detections/unload_sysmon_filter_driver.yml index be4283c047..5ccb9a4d26 100644 --- a/detections/unload_sysmon_filter_driver.yml +++ b/detections/unload_sysmon_filter_driver.yml @@ -33,3 +33,4 @@ tags: - CIS 8 nist: - DE.CM + security_domain: endpoint diff --git a/detections/unsigned_image_loaded_by_LSASS.yml b/detections/unsigned_image_loaded_by_LSASS.yml index a016c7667b..3edd09a042 100644 --- a/detections/unsigned_image_loaded_by_LSASS.yml +++ b/detections/unsigned_image_loaded_by_LSASS.yml @@ -31,3 +31,4 @@ tags: - CIS 16 nist: - DE.CM + security_domain: endpoint diff --git a/detections/unsuccessful_netbackup_backups.yml b/detections/unsuccessful_netbackup_backups.yml index 1bccc9e63f..3df161c2e9 100644 --- a/detections/unsuccessful_netbackup_backups.yml +++ b/detections/unsuccessful_netbackup_backups.yml @@ -11,8 +11,8 @@ how_to_implement: To successfully implement this search you need to obtain data type: ESCU references: [] author: David Dorsey, Splunk -search: '`netbackup` | stats latest(_time) as latestTime by COMPUTERNAME, - MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` +search: '`netbackup` | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE + | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature | `unsuccessful_netbackup_backups_filter`' known_false_positives: None identified @@ -23,3 +23,4 @@ tags: - CIS 10 nist: - PR.IP + security_domain: endpoint diff --git a/detections/unusually_long_command_line.yml b/detections/unusually_long_command_line.yml index ca69595779..2e579f8830 100644 --- a/detections/unusually_long_command_line.yml +++ b/detections/unusually_long_command_line.yml @@ -22,10 +22,10 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Some legitimate applications start with long command lines. tags: analytics_story: - - Suspicious Command-Line Executions - Unusual Processes - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Ransomware + - Suspicious Command-Line Executions kill_chain_phases: - Actions on Objectives cis20: @@ -33,3 +33,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml index d602211e30..f30a3a720a 100644 --- a/detections/unusually_long_command_line___mltk.yml +++ b/detections/unusually_long_command_line___mltk.yml @@ -35,10 +35,10 @@ known_false_positives: Some legitimate applications use long command lines for i build the associated model. tags: analytics_story: - - Suspicious Command-Line Executions - Unusual Processes - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Ransomware + - Suspicious Command-Line Executions kill_chain_phases: - Actions on Objectives cis20: @@ -46,3 +46,4 @@ tags: nist: - PR.PT - DE.CM + security_domain: endpoint diff --git a/detections/unusually_long_content_type_length.yml b/detections/unusually_long_content_type_length.yml index 1f5a2b964e..1c8e6a1aa0 100644 --- a/detections/unusually_long_content_type_length.yml +++ b/detections/unusually_long_content_type_length.yml @@ -10,8 +10,8 @@ how_to_implement: This particular search leverages data extracted from Stream:HT type: ESCU references: [] author: Bhavin Patel, Splunk -search: '`stream_http` | eval cs_content_type_length = len(cs_content_type) - | where cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length +search: '`stream_http` | eval cs_content_type_length = len(cs_content_type) | where + cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length cs_content_type url | `unusually_long_content_type_length_filter`' known_false_positives: Very few legitimate Content-Type fields will have a length greater than 100 characters. @@ -33,3 +33,4 @@ tags: - DE.AE - PR.MA - DE.CM + security_domain: network diff --git a/detections/usn_journal_deletion.yml b/detections/usn_journal_deletion.yml index 04995bc56a..a4621b1ee0 100644 --- a/detections/usn_journal_deletion.yml +++ b/detections/usn_journal_deletion.yml @@ -23,8 +23,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: None identified tags: analytics_story: - - Windows Log Manipulation - Ransomware + - Windows Log Manipulation mitre_attack_id: - T1070 kill_chain_phases: @@ -39,3 +39,4 @@ tags: - DE.AE - DE.DP - PR.IP + security_domain: endpoint diff --git a/detections/web_fraud___account_harvesting.yml b/detections/web_fraud___account_harvesting.yml index ab233c1660..9d8cc8659a 100644 --- a/detections/web_fraud___account_harvesting.yml +++ b/detections/web_fraud___account_harvesting.yml @@ -45,3 +45,4 @@ tags: nist: - DE.CM - DE.DP + security_domain: threat diff --git a/detections/web_fraud___anomalous_user_clickspeed.yml b/detections/web_fraud___anomalous_user_clickspeed.yml index d367912689..476366327d 100644 --- a/detections/web_fraud___anomalous_user_clickspeed.yml +++ b/detections/web_fraud___anomalous_user_clickspeed.yml @@ -41,3 +41,4 @@ tags: nist: - DE.AE - DE.CM + security_domain: threat diff --git a/detections/web_fraud___password_sharing_across_accounts.yml b/detections/web_fraud___password_sharing_across_accounts.yml index e8d280b5f5..55ec53c9ef 100644 --- a/detections/web_fraud___password_sharing_across_accounts.yml +++ b/detections/web_fraud___password_sharing_across_accounts.yml @@ -31,3 +31,4 @@ tags: - CIS 16 nist: - DE.DP + security_domain: threat diff --git a/detections/web_servers_executing_suspicious_processes.yml b/detections/web_servers_executing_suspicious_processes.yml index 7d188f9dc1..b0ecef5162 100644 --- a/detections/web_servers_executing_suspicious_processes.yml +++ b/detections/web_servers_executing_suspicious_processes.yml @@ -32,3 +32,4 @@ tags: - CIS 3 nist: - PR.IP + security_domain: endpoint diff --git a/detections/windows_event_log_cleared.yml b/detections/windows_event_log_cleared.yml index 823eca0c50..cc574b73b7 100644 --- a/detections/windows_event_log_cleared.yml +++ b/detections/windows_event_log_cleared.yml @@ -9,16 +9,16 @@ how_to_implement: To successfully implement this search, you need to be ingestin type: ESCU references: [] author: Rico Valdez, Splunk -search: '(`wineventlog_security` signature_id=1102 OR signature_id=1100) - OR (`wineventlog_system` signature_id=104) | stats count min(_time) - as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `windows_event_log_cleared_filter`' +search: ((`wineventlog_security` AND (signature_id=1102 OR signature_id=1100)) OR + ((`wineventlog_system` AND signature_id=104) | stats count min(_time) as firstTime + max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` + | `security_content_ctime(lastTime)` | `windows_event_log_cleared_filter` known_false_positives: It is possible that these logs may be legitimately cleared by Administrators. tags: analytics_story: - - Windows Log Manipulation - Ransomware + - Windows Log Manipulation mitre_attack_id: - T1070 kill_chain_phases: @@ -33,3 +33,4 @@ tags: - PR.AC - PR.AT - DE.AE + security_domain: endpoint diff --git a/detections/windows_hosts_file_modification.yml b/detections/windows_hosts_file_modification.yml index 287ddfbb12..e996adde7b 100644 --- a/detections/windows_hosts_file_modification.yml +++ b/detections/windows_hosts_file_modification.yml @@ -35,3 +35,4 @@ tags: - PR.AC - DE.AE - DE.CM + security_domain: endpoint diff --git a/detections/wmi_permanent_event_subscription.yml b/detections/wmi_permanent_event_subscription.yml index 78e2f25f26..2c344d9048 100644 --- a/detections/wmi_permanent_event_subscription.yml +++ b/detections/wmi_permanent_event_subscription.yml @@ -9,10 +9,10 @@ how_to_implement: To successfully implement this search, you must be ingesting t type: ESCU references: [] author: Rico Valdez, Splunk -search: '`wmi` EventCode=5861 - Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" | search consumer!="NTEventLogEventConsumer=\"SCM - Event Log Consumer\"" | stats count min(_time) as firstTime max(_time) as lastTime - by ComputerName, consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search: '`wmi` EventCode=5861 Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" + | search consumer!="NTEventLogEventConsumer=\"SCM Event Log Consumer\"" | stats + count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, + Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | rename ComputerName as dest | `wmi_permanent_event_subscription_filter`' known_false_positives: Although unlikely, administrators may use event subscriptions for legitimate purposes. @@ -32,3 +32,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: endpoint diff --git a/detections/wmi_permanent_event_subscription___sysmon.yml b/detections/wmi_permanent_event_subscription___sysmon.yml index 58f9a42fd5..a9d6d6d37a 100644 --- a/detections/wmi_permanent_event_subscription___sysmon.yml +++ b/detections/wmi_permanent_event_subscription___sysmon.yml @@ -10,9 +10,8 @@ how_to_implement: To successfully implement this search, you must be collecting type: ESCU references: [] author: Rico Valdez, Splunk -search: '`sysmon` EventCode=21 - | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, - Filter | `wmi_permanent_event_subscription___sysmon_filter`' +search: '`sysmon` EventCode=21 | rename host as dest | table _time, dest, user, Operation, + EventType, Query, Consumer, Filter | `wmi_permanent_event_subscription___sysmon_filter`' known_false_positives: Although unlikely, administrators may use event subscriptions for legitimate purposes. tags: @@ -31,3 +30,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: endpoint diff --git a/detections/wmi_temporary_event_subscription.yml b/detections/wmi_temporary_event_subscription.yml index fde26876b8..22354d3abc 100644 --- a/detections/wmi_temporary_event_subscription.yml +++ b/detections/wmi_temporary_event_subscription.yml @@ -9,9 +9,10 @@ how_to_implement: To successfully implement this search, you must be ingesting t type: ESCU references: [] author: Rico Valdez, Splunk -search: '`wmi` EventCode=5860 Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" | search query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = wsmprovhost.exe" - AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA AntiVirusProduct - OR TargetInstance ISA FirewallProduct OR TargetInstance ISA AntiSpywareProduct" +search: '`wmi` EventCode=5860 Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" + | search query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = ''wsmprovhost.exe''" + AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA ''AntiVirusProduct'' + OR TargetInstance ISA ''FirewallProduct'' OR TargetInstance ISA ''AntiSpywareProduct''" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `wmi_temporary_event_subscription_filter`' known_false_positives: Some software may create WMI temporary event subscriptions @@ -34,3 +35,4 @@ tags: - PR.AT - PR.AC - PR.IP + security_domain: endpoint diff --git a/macros/aws_cloudwatchlogs_eks.yml b/macros/aws_cloudwatchlogs_eks.yml new file mode 100644 index 0000000000..44d9641feb --- /dev/null +++ b/macros/aws_cloudwatchlogs_eks.yml @@ -0,0 +1,4 @@ +definiton: sourcetype="aws:cloudwatchlogs:eks" +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. +name: aws_cloudwatchlogs_eks diff --git a/macros/aws_s3_accesslogs.yml b/macros/aws_s3_accesslogs.yml new file mode 100644 index 0000000000..77e626fa30 --- /dev/null +++ b/macros/aws_s3_accesslogs.yml @@ -0,0 +1,4 @@ +definiton: sourcetype=aws:s3:accesslogs +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. +name: aws_s3_accesslogs diff --git a/macros/cloudtrail.yml b/macros/cloudtrail.yml index e31baee994..2f8d4c8578 100644 --- a/macros/cloudtrail.yml +++ b/macros/cloudtrail.yml @@ -1,3 +1,4 @@ -definition: sourcetype=aws:cloudtrail -description: customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudtrail logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: sourcetype=aws:cloudtrail +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: cloudtrail diff --git a/macros/cloudwatchlogs_vpcflow.yml b/macros/cloudwatchlogs_vpcflow.yml new file mode 100644 index 0000000000..4718ff3271 --- /dev/null +++ b/macros/cloudwatchlogs_vpcflow.yml @@ -0,0 +1,4 @@ +definiton: sourcetype=aws:cloudwatchlogs:vpcflow +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. +name: cloudwatchlogs_vpcflow diff --git a/macros/google_gcp_pubsub_message.yml b/macros/google_gcp_pubsub_message.yml new file mode 100644 index 0000000000..3a58859bb3 --- /dev/null +++ b/macros/google_gcp_pubsub_message.yml @@ -0,0 +1,4 @@ +definiton: sourcetype="google:gcp:pubsub:message" +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. +name: google_gcp_pubsub_message diff --git a/macros/netbackup.yml b/macros/netbackup.yml index 8f2b1198f9..69d2ca034d 100644 --- a/macros/netbackup.yml +++ b/macros/netbackup.yml @@ -1,3 +1,4 @@ -definition: sourcetype="netbackup_logs" -description: customer specific splunk configurations(eg- index, source, sourcetype) for netbackup logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: sourcetype="netbackup_logs" +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: netbackup diff --git a/macros/okta.yml b/macros/okta.yml index 4df962bce0..684c32cd12 100644 --- a/macros/okta.yml +++ b/macros/okta.yml @@ -1,3 +1,4 @@ -definition: eventtype=okta_log -description: customer specific splunk configurations(eg- index, source, sourcetype) for WMI logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: eventtype=okta_log +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: okta diff --git a/macros/stream_http.yml b/macros/stream_http.yml index a6237def58..70e1ee39b8 100644 --- a/macros/stream_http.yml +++ b/macros/stream_http.yml @@ -1,3 +1,4 @@ -definition: sourcetype=stream:http -description: customer specific splunk configurations(eg- index, source, sourcetype) for Stream HTTP logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: sourcetype=stream:http +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: stream_http diff --git a/macros/sysmon.yml b/macros/sysmon.yml index abced6b0c7..c3041967ca 100644 --- a/macros/sysmon.yml +++ b/macros/sysmon.yml @@ -1,3 +1,4 @@ -definition: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" -description: customer specific splunk configurations(eg- index, source, sourcetype) for Windows Sysmon Logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: sysmon diff --git a/macros/wineventlog_security.yml b/macros/wineventlog_security.yml index f39392ffce..cf504967fd 100644 --- a/macros/wineventlog_security.yml +++ b/macros/wineventlog_security.yml @@ -1,3 +1,4 @@ -definition: eventtype="wineventlog_security" -description: Customer specific splunk configurations(eg- index, source, sourcetype) for Windows Event Logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: eventtype=wineventlog_security +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: wineventlog_security diff --git a/macros/wineventlog_system.yml b/macros/wineventlog_system.yml index 968871810c..2e74ab12b1 100644 --- a/macros/wineventlog_system.yml +++ b/macros/wineventlog_system.yml @@ -1,3 +1,4 @@ -definition: eventtype="wineventlog_system" -description: Customer specific splunk configurations(eg- index, source, sourcetype) for Windows Event Logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: eventtype=wineventlog_system +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: wineventlog_system diff --git a/macros/wmi.yml b/macros/wmi.yml index dbef80c1cd..581ac64f9e 100644 --- a/macros/wmi.yml +++ b/macros/wmi.yml @@ -1,3 +1,4 @@ -definition: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" -description: customer specific splunk configurations(eg- index, source, sourcetype) for WMI logs. Replace the macro definition with configurations for your Splunk Environmnent. +definiton: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" +description: customer specific splunk configurations(eg- index, source, sourcetype). + Replace the macro definition with configurations for your Splunk Environmnent. name: wmi diff --git a/requirements.txt b/requirements.txt index d183d6afaf..699430740c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,24 +1,37 @@ +antlr4-python3-runtime==4.8 aspy.yaml==1.3.0 +attackcti==0.3.2 attrs==19.3.0 -cfgv==3.1.0 -configparser==5.0.0 +certifi==2020.4.5.1 +cfgv==2.0.1 +chardet==3.0.4 +configparser==4.0.2 contextlib2==0.6.0.post1 -identify==1.4.14 -importlib-metadata==1.6.0 -importlib-resources==1.4.0 -Jinja2==2.11.1 +identify==1.4.8 +idna==2.9 +importlib-metadata==1.2.0 +importlib-resources==1.0.2 +Jinja2==2.10.3 jsonschema==3.2.0 MarkupSafe==1.1.1 -more-itertools==8.2.0 -nodeenv==1.3.5 +more-itertools==8.0.2 +nodeenv==1.3.3 pathlib2==2.3.5 -pre-commit==2.3.0 +pre-commit==1.20.0 +pyrsistent==0.15.6 +python-dateutil==2.8.1 +pytz==2019.3 PyYAML==5.3.1 -pyrsistent==0.16.0 +requests==2.23.0 scandir==1.10.0 -semantic-version==2.8.4 +semantic-version==2.8.3 +simplejson==3.17.0 six==1.14.0 +stix2==1.4.0 +stix2-patterns==1.3.0 +taxii2-client==2.0.0 toml==0.10.0 typing==3.7.4.1 -virtualenv==20.0.16 -zipp==3.1.0 +urllib3==1.25.9 +virtualenv==16.7.8 +zipp==0.6.0 diff --git a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml index 984b3db736..f634fc6df6 100644 --- a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml +++ b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml @@ -10,6 +10,6 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - accessKeyId -search: '| search `cloudtrail` userIdentity.accessKeyId={accessKeyId} +search: '| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' diff --git a/response_tasks/aws_investigate_user_activities_by_arn.yml b/response_tasks/aws_investigate_user_activities_by_arn.yml index 1f2821c616..caa7a74ae2 100644 --- a/response_tasks/aws_investigate_user_activities_by_arn.yml +++ b/response_tasks/aws_investigate_user_activities_by_arn.yml @@ -12,6 +12,6 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - user -search: '| search `cloudtrail` userIdentity.arn={user} | table _time +search: '| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType' diff --git a/response_tasks/aws_investigate_user_activities_by_source_user.yml b/response_tasks/aws_investigate_user_activities_by_source_user.yml index 00e40c8f50..b138d68f30 100644 --- a/response_tasks/aws_investigate_user_activities_by_source_user.yml +++ b/response_tasks/aws_investigate_user_activities_by_source_user.yml @@ -10,6 +10,6 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - src_user -search: '| search `cloudtrail` userIdentity.arn={src_user} | spath output=user +search: '| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' diff --git a/response_tasks/get_all_aws_activity_from_city.yml b/response_tasks/get_all_aws_activity_from_city.yml index d325823f6c..ee8c514915 100644 --- a/response_tasks/get_all_aws_activity_from_city.yml +++ b/response_tasks/get_all_aws_activity_from_city.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - City -search: '| search `cloudtrail` | iplocation sourceIPAddress | search +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, diff --git a/response_tasks/get_all_aws_activity_from_country.yml b/response_tasks/get_all_aws_activity_from_country.yml index 9a82874b9f..9bcf654f1e 100644 --- a/response_tasks/get_all_aws_activity_from_country.yml +++ b/response_tasks/get_all_aws_activity_from_country.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - Country -search: '| search `cloudtrail` | iplocation sourceIPAddress | search +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, diff --git a/response_tasks/get_all_aws_activity_from_ip_address.yml b/response_tasks/get_all_aws_activity_from_ip_address.yml index db12ff3b5e..82b3f593c9 100644 --- a/response_tasks/get_all_aws_activity_from_ip_address.yml +++ b/response_tasks/get_all_aws_activity_from_ip_address.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - src_ip -search: '| search `cloudtrail` | iplocation sourceIPAddress | search +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, diff --git a/response_tasks/get_all_aws_activity_from_region.yml b/response_tasks/get_all_aws_activity_from_region.yml index 5603f16e77..1db6e7e6c2 100644 --- a/response_tasks/get_all_aws_activity_from_region.yml +++ b/response_tasks/get_all_aws_activity_from_region.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - Region -search: '| search `cloudtrail` | iplocation sourceIPAddress | search +search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, diff --git a/response_tasks/get_ec2_launch_details.yml b/response_tasks/get_ec2_launch_details.yml index e882fb4110..7681171576 100644 --- a/response_tasks/get_ec2_launch_details.yml +++ b/response_tasks/get_ec2_launch_details.yml @@ -9,7 +9,7 @@ how_to_implement: In order to implement this search, you must install the AWS Ap author: Bhavin Patel, Splunk inputs: - dest -search: '| search `cloudtrail` responseElements.instancesSet.items{}.instanceId={dest} +search: '| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture diff --git a/response_tasks/investigate_aws_activities_via_region_name.yml b/response_tasks/investigate_aws_activities_via_region_name.yml index ff2c1fc7ec..859e5c9de3 100644 --- a/response_tasks/investigate_aws_activities_via_region_name.yml +++ b/response_tasks/investigate_aws_activities_via_region_name.yml @@ -11,5 +11,5 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - awsRegion -search: '| search `cloudtrail` awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId +search: '| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId' diff --git a/response_tasks/investigate_aws_user_activities_by_user_field.yml b/response_tasks/investigate_aws_user_activities_by_user_field.yml index fe1837d76a..82e1f14b4a 100644 --- a/response_tasks/investigate_aws_user_activities_by_user_field.yml +++ b/response_tasks/investigate_aws_user_activities_by_user_field.yml @@ -12,5 +12,5 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - user -search: '| search `cloudtrail` user={user} | table _time userIdentity.type +search: '| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType ' diff --git a/stories/emotet_malware.yml b/stories/emotet_malware__dhs_report_ta18_201a_.yml similarity index 97% rename from stories/emotet_malware.yml rename to stories/emotet_malware__dhs_report_ta18_201a_.yml index 17a8af6d1b..0acf0347db 100644 --- a/stories/emotet_malware.yml +++ b/stories/emotet_malware__dhs_report_ta18_201a_.yml @@ -1,4 +1,4 @@ -name: Emotet Malware +name: 'Emotet Malware DHS Report TA18-201A ' id: bb9f5ed2-916e-4364-bb6d-91c310efcf52 version: 1 date: '2020-01-27' From cda505d8fa75cfb9d59375ade8680583f4a53ea1 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 6 May 2020 17:42:38 +0200 Subject: [PATCH 16/93] new generate script --- ...bited_processes_to_enterprise_security.yml | 2 +- ...baseline_of_command_line_length___mltk.yml | 2 +- baselines/baseline_of_smb_traffic___mltk.yml | 2 +- baselines/dnstwist_domain_names.yml | 2 +- ...seen_aws_provisioning_activity_sources.yml | 2 +- ...previously_seen_command_line_arguments.yml | 2 +- .../previously_seen_users_in_cloudtrail.yml | 4 +- ...te_previously_seen_users_in_cloudtrail.yml | 4 +- bin/converter_v2_v3.py | 52 +- bin/generate.py | 375 +- bin/jinja2_templates/analytic_stories.j2 | 20 +- bin/jinja2_templates/savedsearches.bak.j2 | 292 + bin/jinja2_templates/savedsearches.j2 | 217 +- bin/jinja2_templates/use_case_library.j2 | 57 +- ...eployment.yml => deployment_example_1.yml} | 11 +- deployments/deployment_example_2.yml | 17 + ...ly_high_aws_instances_launched_by_user.yml | 3 +- ..._aws_instances_launched_by_user___mltk.yml | 3 +- ..._high_aws_instances_terminated_by_user.yml | 1 + ...ws_instances_terminated_by_user___mltk.yml | 1 + .../access_lsass_memory_for_dump_creation.yml | 1 + ..._eks_kubernetes_cluster_scan_detection.yml | 3 +- ...azon_eks_kubernetes_pod_scan_detection.yml | 4 +- ..._to_add_certificate_to_untrusted_store.yml | 1 + ...ution_policy_to_unrestricted_or_bypass.yml | 3 +- .../attempt_to_stop_security_service.yml | 1 + ...dential_dump_from_registry_via_reg_exe.yml | 1 + ...ovisioning_from_previously_unseen_city.yml | 1 + ...sioning_from_previously_unseen_country.yml | 1 + ...ning_from_previously_unseen_ip_address.yml | 1 + ...isioning_from_previously_unseen_region.yml | 1 + ...ctivity_from_previously_unseen_account.yml | 1 + ...ntrol_list_created_with_all_open_ports.yml | 1 + ...ws_network_access_control_list_deleted.yml | 1 + detections/batch_file_write_to_system32.yml | 1 + detections/child_processes_of_spoolsv_exe.yml | 1 + ...nts_connecting_to_multiple_dns_servers.yml | 7 +- ...ance_created_by_previously_unseen_user.yml | 1 + ...e_created_with_previously_unseen_image.yml | 1 + ...d_with_previously_unseen_instance_type.yml | 1 + ...ce_started_in_previously_unused_region.yml | 1 + detections/common_ransomware_extensions.yml | 3 +- detections/common_ransomware_notes.yml | 3 +- ...ate_local_admin_accounts_using_net_exe.yml | 1 + ...or_delete_windows_shares_using_net_exe.yml | 1 + .../create_remote_thread_into_lsass.yml | 1 + detections/creation_of_shadow_copy.yml | 1 + ...f_shadow_copy_with_wmic_and_powershell.yml | 1 + ...ping_via_copy_command_from_shadow_copy.yml | 1 + ...ial_dumping_via_symlink_to_shadow_copy.yml | 1 + detections/deleting_shadow_copies.yml | 3 +- ...ivity_related_to_pass_the_hash_attacks.yml | 1 + ...ct_api_activity_from_users_without_mfa.yml | 1 + ..._scanning_for_vulnerable_jboss_servers.yml | 3 +- ...pi_activities_from_unapproved_accounts.yml | 1 + ...ws_console_login_by_user_from_new_city.yml | 1 + ...console_login_by_user_from_new_country.yml | 1 + ..._console_login_by_user_from_new_region.yml | 1 + ...redential_dumping_through_LSASS_access.yml | 1 + ...to_phishing_sites_leveraging_evilginx2.yml | 1 + ...cessive_account_lockouts_from_endpoint.yml | 1 + ...detect_excessive_user_account_lockouts.yml | 1 + ...connecting_to_dynamic_domain_providers.yml | 3 +- .../detect_large_outbound_icmp_packets.yml | 1 + .../detect_long_dns_txt_record_response.yml | 3 +- ...ious_requests_to_exploit_jboss_servers.yml | 3 +- .../detect_mimikatz_using_loaded_images.yml | 1 + ...katz_via_powershell_and_eventcode_4703.yml | 1 + ...ning_scripts_in_command_line_arguments.yml | 1 + .../detect_new_api_calls_from_user_roles.yml | 1 + detections/detect_new_local_admin_account.yml | 1 + .../detect_new_login_attempts_to_routers.yml | 3 +- detections/detect_new_open_s3_buckets.yml | 1 + .../detect_new_user_aws_console_login.yml | 1 + .../detect_oulook_exe_writing_a__zip_file.yml | 1 + detections/detect_outbound_smb_traffic.yml | 1 + ...nterception_by_creation_of_program_exe.yml | 1 + ...system_network_configuration_discovery.yml | 1 + ...ohibited_applications_spawning_cmd_exe.yml | 3 +- .../detect_psexec_with_accepteula_flag.yml | 1 + detections/detect_rare_executables.yml | 3 +- detections/detect_s3_access_from_a_new_ip.yml | 1 + .../detect_spike_in_aws_api_activity.yml | 1 + ...blocked_outbound_traffic_from_your_aws.yml | 3 +- .../detect_spike_in_network_acl_activity.yml | 1 + .../detect_spike_in_s3_bucket_deletion.yml | 1 + ...etect_spike_in_security_group_activity.yml | 1 + ...ect_unauthorized_assets_by_mac_address.yml | 1 + detections/detect_usb_device_insertion.yml | 1 + ..._cmd_exe_to_launch_script_interpreters.yml | 3 +- ...eb_traffic_to_dynamic_domain_providers.yml | 1 + detections/detection_of_dns_tunnels.yml | 3 +- .../detection_of_tools_built_by_nirsoft.yml | 3 +- .../disabling_remote_user_account_control.yml | 3 +- .../dns_query_length_outliers___mltk.yml | 5 +- ...ry_length_with_high_standard_deviation.yml | 5 +- ...s_resolved_by_unauthorized_dns_servers.yml | 7 +- detections/dns_record_changed.yml | 1 + detections/dump_lsass_via_comsvcs_dll.yml | 1 + ...e_modified_with_previously_unseen_user.yml | 1 + ...ce_started_in_previously_unseen_region.yml | 3 +- ...nce_started_with_previously_unseen_ami.yml | 1 + ...d_with_previously_unseen_instance_type.yml | 1 + ...ce_started_with_previously_unseen_user.yml | 3 +- .../email_attachments_with_lots_of_spaces.yml | 3 +- ...itten_outside_of_the_outlook_directory.yml | 1 + ...s_sending_high_volume_traffic_to_hosts.yml | 1 + detections/excessive_dns_failures.yml | 3 +- ...ution_of_file_with_multiple_extensions.yml | 1 + ...n_of_file_with_spaces_before_extension.yml | 1 + ...d_without_successful_netbackup_backups.yml | 1 + detections/file_with_samsam_extension.yml | 1 + .../first_time_seen_command_line_argument.yml | 7 +- ...irst_time_seen_running_windows_service.yml | 3 +- detections/gcp_gcr_container_uploaded.yml | 3 +- .../gcp_kubernetes_cluster_scan_detection.yml | 3 +- ..._files_and_directories_with_attrib_exe.yml | 1 + ...e_of_network_traffic_from_email_server.yml | 1 + detections/identify_new_user_accounts.yml | 1 + .../large_volume_of_dns_any_queries.yml | 1 + detections/macos___re_opened_applications.yml | 1 + ...connect_to_internet_with_hidden_window.yml | 1 + ...s_powershell_process___encoded_command.yml | 1 + ...hell_process___execution_policy_bypass.yml | 1 + ...iple_suspicious_command_line_arguments.yml | 1 + ...ll_process_with_obfuscation_techniques.yml | 1 + detections/monitor_dns_for_brand_abuse.yml | 1 + detections/monitor_email_for_brand_abuse.yml | 3 +- ...nitor_registry_keys_for_print_monitors.yml | 1 + .../monitor_web_traffic_for_brand_abuse.yml | 1 + ...h_invalid_credentails_from_the_same_ip.yml | 1 + .../new_container_uploaded_to_aws_ecr.yml | 3 +- .../no_windows_updates_in_a_time_frame.yml | 1 + detections/okta_account_lockout_events.yml | 1 + detections/okta_failed_sso_attempts.yml | 1 + .../okta_user_logins_from_multiple_cities.yml | 1 + detections/open_redirect_in_splunk_web.yml | 1 + .../osquery_pack___coldroot_detection.yml | 1 + .../overwriting_accessibility_binaries.yml | 1 + detections/process_execution_via_wmi.yml | 1 + detections/processes_created_by_netsh.yml | 1 + detections/processes_launching_netsh.yml | 3 +- .../processes_tapping_keyboard_events.yml | 1 + .../prohibited_network_traffic_allowed.yml | 5 +- .../prohibited_software_on_endpoint.yml | 5 +- detections/protocol_or_port_mismatch.yml | 1 + ...ls_passing_authentication_in_cleartext.yml | 1 + ...ulating_windows_services_registry_keys.yml | 1 + ...de_files_directories_via_registry_keys.yml | 3 +- ...istry_keys_for_creating_shim_databases.yml | 1 + .../registry_keys_used_for_persistence.yml | 7 +- ...try_keys_used_for_privilege_escalation.yml | 3 +- .../remote_desktop_network_bruteforce.yml | 1 + detections/remote_desktop_network_traffic.yml | 3 +- ...mote_desktop_process_running_on_system.yml | 1 + .../remote_process_instantiation_via_wmi.yml | 3 +- .../remote_registry_key_modifications.yml | 3 +- detections/remote_wmi_command_attempt.yml | 1 + detections/rundll_loading_dll_by_ordinal.yml | 1 + detections/samsam_test_file_write.yml | 1 + .../sc_exe_manipulating_windows_services.yml | 5 +- ...k_name_used_by_dragonfly_threat_actors.yml | 1 + ...led_tasks_used_in_badrabbit_ransomware.yml | 1 + ...htasks_scheduling_job_on_remote_system.yml | 1 + .../schtasks_used_for_forcing_a_reboot.yml | 3 +- detections/script_execution_via_wmi.yml | 1 + detections/shim_database_file_creation.yml | 1 + ...nstallation_with_suspicious_parameters.yml | 1 + detections/short_lived_windows_accounts.yml | 1 + .../single_letter_process_on_endpoint.yml | 1 + detections/smb_traffic_spike.yml | 5 +- detections/smb_traffic_spike___mltk.yml | 5 +- ...pectre_and_meltdown_vulnerable_systems.yml | 1 + detections/spike_in_file_writes.yml | 3 +- ...lunk_enterprise_information_disclosure.yml | 1 + detections/sql_injection_with_long_urls.yml | 1 + ...uspicious_changes_to_file_associations.yml | 1 + detections/suspicious_email___uba_anomaly.yml | 1 + ...suspicious_email_attachment_extensions.yml | 3 +- detections/suspicious_file_write.yml | 1 + detections/suspicious_java_classes.yml | 1 + ...uspicious_lnk_file_launching_a_process.yml | 1 + detections/suspicious_reg_exe_process.yml | 5 +- detections/suspicious_wevtutil_usage.yml | 3 +- ...us_writes_to_system_volume_information.yml | 1 + ...spicious_writes_to_windows_recycle_bin.yml | 1 + ...rocesses_run_from_unexpected_locations.yml | 5 +- detections/tor_traffic.yml | 5 +- detections/uncommon_processes_on_endpoint.yml | 3 +- detections/unload_sysmon_filter_driver.yml | 1 + detections/unsigned_image_loaded_by_LSASS.yml | 1 + detections/unsuccessful_netbackup_backups.yml | 1 + detections/unusually_long_command_line.yml | 7 +- .../unusually_long_command_line___mltk.yml | 7 +- .../unusually_long_content_type_length.yml | 1 + detections/usn_journal_deletion.yml | 3 +- detections/web_fraud___account_harvesting.yml | 1 + .../web_fraud___anomalous_user_clickspeed.yml | 1 + ...aud___password_sharing_across_accounts.yml | 1 + ...servers_executing_suspicious_processes.yml | 1 + detections/windows_event_log_cleared.yml | 3 +- .../windows_hosts_file_modification.yml | 1 + .../wmi_permanent_event_subscription.yml | 1 + ..._permanent_event_subscription___sysmon.yml | 1 + .../wmi_temporary_event_subscription.yml | 1 + ..._lsass_memory_for_dump_creation_filter.yml | 3 - ...olicy_to_unrestricted_or_bypass_filter.yml | 3 - ...tial_dump_from_registry_via_reg_filter.yml | 3 - macros/attrib_to_hide_files_filter.yml | 3 - macros/aws_cloudwatchlogs_eks.yml | 2 +- macros/aws_s3_accesslogs.yml | 2 +- macros/change_file_association_filter.yml | 4 - macros/children_of_spoolsv_filter.yml | 3 - macros/cloudtrail.yml | 2 +- macros/cloudwatchlogs_vpcflow.yml | 2 +- .../common_ransomware_extensions_filter.yml | 3 - macros/common_ransomware_notes_filter.yml | 3 - ...container_implant_aws_detection_filter.yml | 3 - ...container_implant_gcp_detection_filter.yml | 3 - macros/create_local_admin_via_net_filter.yml | 3 - ...create_remote_thread_into_lsass_filter.yml | 3 - macros/creation_of_shadow_copy_filter.yml | 3 - ...w_copy_with_wmic_and_powershell_filter.yml | 3 - ...d_dump_via_copy_from_shadowcopy_filter.yml | 3 - ...red_dump_via_symlink_shadowcopy_filter.yml | 3 - ...elated_to_pass_the_hash_attacks_filter.yml | 3 - ...al_dumping_through_LSASS_access_filter.yml | 3 - ...ct_mimikatz_using_loaded_images_filter.yml | 3 - macros/dns_query_length_mltk_filter.yml | 3 - ...th_with_high_standard_deviation_filter.yml | 3 - macros/dns_record_changed_filter.yml | 3 - macros/dragonfly_schtasks_filter.yml | 3 - macros/dump_lsass_via_comsvcs_dll_filter.yml | 3 - ...cessive_runinstances_mltk_input_filter.yml | 4 - ...e_terminateinstances_mltk_input_filter.yml | 4 - ..._files_not_in_outlook_directory_filter.yml | 3 - macros/file_write_spikes_filter.yml | 3 - macros/first_time_seen_cmd_line_filter.yml | 3 - macros/google_gcp_pubsub_message.yml | 2 +- ..._aws_scan_fingerprint_detection_filter.yml | 3 - ..._gcp_scan_fingerprint_detection_filter.yml | 3 - ..._aws_scan_fingerprint_detection_filter.yml | 3 - macros/lnk_executing_a_process_filter.yml | 3 - ...s_obfuscation_techniques_output_filter.yml | 4 - macros/netbackup.yml | 2 +- macros/okta.yml | 2 +- macros/okta_failed_sso_attempt_filter.yml | 3 - ...sers_with_auth_failures_from_ip_filter.yml | 3 - macros/okta_user_lockouts_filter.yml | 3 - ...ser_logins_from_multiple_cities_filter.yml | 3 - macros/outbound_smb_connections_filter.yml | 3 - macros/outlook_writing_zip_filter.yml | 3 - ...compute_creations_by_user_input_filter.yml | 4 - ..._seen_cloud_compute_image_input_filter.yml | 4 - ...ud_compute_instance_types_input_filter.yml | 4 - ...iously_seen_cloud_regions_input_filter.yml | 3 - .../rare_executables_on_endpoint_filter.yml | 3 - .../remote_desktop_network_traffic_filter.yml | 3 - ...sktop_process_running_on_system_filter.yml | 3 - ...scheduling_job_on_remote_system_filter.yml | 3 - macros/smb_traffic_spike_filter.yml | 3 - macros/smb_traffic_spike_mltk_filter.yml | 3 - macros/stream_http.yml | 2 +- .../suspicious_email_attachments_filter.yml | 3 - macros/suspicious_reg_process_filter.yml | 3 - macros/sysmon.yml | 2 +- macros/unauthorized_dns_servers_filter.yml | 3 - macros/uncommon_processes_filter.yml | 3 - macros/unload_sysmon_filter_driver_filter.yml | 3 - .../unsigned_image_loaded_by_LSASS_filter.yml | 3 - macros/unusually_long_commandlines_filter.yml | 3 - macros/wineventlog_security.yml | 2 +- macros/wineventlog_system.yml | 2 +- macros/wmi.yml | 2 +- macros/wmi_process_launch_filter.yml | 3 - macros/wmi_script_execution_filter.yml | 3 - package/default/analytic_stories.conf | 947 +- package/default/macros.conf | 1014 +- package/default/savedsearches.conf | 10499 +++++----------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 2912 +++-- response_tasks/all_backup_logs_for_host.yml | 3 + ...azon_eks_kubernetes_activity_by_src_ip.yml | 3 + ...stigate_user_activities_by_accesskeyid.yml | 3 + ...aws_investigate_user_activities_by_arn.yml | 11 + ...stigate_user_activities_by_source_user.yml | 3 + .../aws_network_acl_details_from_id.yml | 5 + ...twork_interface_details_via_resourceid.yml | 5 + .../aws_s3_bucket_details_via_bucketname.yml | 3 + .../gcp_kubernetes_activity_by_src_ip.yml | 3 + .../get_all_aws_activity_from_city.yml | 3 + .../get_all_aws_activity_from_country.yml | 3 + .../get_all_aws_activity_from_ip_address.yml | 7 + .../get_all_aws_activity_from_region.yml | 3 + .../get_authentication_logs_for_endpoint.yml | 42 + .../get_backup_logs_for_endpoint.yml | 4 + .../get_certificate_logs_for_a_domain.yml | 3 + .../get_dns_server_history_for_a_host.yml | 12 + response_tasks/get_dns_traffic_ratio.yml | 9 + ...get_ec2_instance_details_by_instanceid.yml | 6 + response_tasks/get_ec2_launch_details.yml | 5 + response_tasks/get_email_info.yml | 4 + .../get_emails_from_specific_sender.yml | 5 + ...e_and_last_occurrence_of_a_mac_address.yml | 3 + ...ogon_rights_modifications_for_endpoint.yml | 3 + ...et_logon_rights_modifications_for_user.yml | 3 + response_tasks/get_notable_history.yml | 59 + response_tasks/get_notable_info.yml | 55 + response_tasks/get_parent_process_info.yml | 30 + response_tasks/get_process_file_activity.yml | 3 + response_tasks/get_process_info.yml | 32 + ..._process_information_for_port_activity.yml | 13 + .../get_process_registry_activity.yml | 3 + ...rocess_responsible_for_the_dns_traffic.yml | 10 + response_tasks/get_registry_activities.yml | 13 + .../get_risk_modifiers_for_endpoint.yml | 50 + .../get_risk_modifiers_for_user.yml | 44 + .../get_sysmon_wmi_activity_for_host.yml | 4 + .../get_update_logs_for_endpoint.yml | 6 + ...t_user_information_from_identity_table.yml | 46 + .../get_vulnerability_logs_for_endpoint.yml | 11 + ...web_session_information_via_session_id.yml | 3 + ...stigate_aws_activities_via_region_name.yml | 6 + ...ate_aws_ecr_container_listing_activity.yml | 3 + ...gate_aws_user_activities_by_user_field.yml | 3 + ...gate_cloud_compute_instance_activities.yml | 3 + ...ailed_logins_for_multiple_destinations.yml | 3 + ...nvestigate_network_traffic_from_src_ip.yml | 4 + .../investigate_okta_activity_by_app.yml | 3 + ...nvestigate_okta_activity_by_ip_address.yml | 3 + .../investigate_pass_the_hash_attempts.yml | 3 + .../investigate_pass_the_ticket_attempts.yml | 3 + .../investigate_previous_unseen_user.yml | 3 + ...cessful_remote_desktop_authentications.yml | 5 + ...gate_suspicious_strings_in_http_header.yml | 3 + ...e_user_activities_in_all_cloud_regions.yml | 3 + .../investigate_user_activities_in_okta.yml | 3 + ...user_activities_in_single_cloud_region.yml | 3 + .../investigate_web_activity_from_host.yml | 22 + .../investigate_web_activity_from_src_ip.yml | 5 + .../investigate_web_posts_from_src.yml | 3 + ...lantation_monitoring_and_investigation.yml | 2 +- .../emotet_malware__dhs_report_ta18_201a_.yml | 2 +- .../router_and_infrastructure_security.yml | 2 +- 344 files changed, 7722 insertions(+), 9897 deletions(-) create mode 100644 bin/jinja2_templates/savedsearches.bak.j2 rename deployments/{deployment.yml => deployment_example_1.yml} (74%) create mode 100644 deployments/deployment_example_2.yml delete mode 100644 macros/access_lsass_memory_for_dump_creation_filter.yml delete mode 100644 macros/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter.yml delete mode 100644 macros/attempted_credential_dump_from_registry_via_reg_filter.yml delete mode 100644 macros/attrib_to_hide_files_filter.yml delete mode 100644 macros/change_file_association_filter.yml delete mode 100644 macros/children_of_spoolsv_filter.yml delete mode 100644 macros/common_ransomware_extensions_filter.yml delete mode 100644 macros/common_ransomware_notes_filter.yml delete mode 100644 macros/container_implant_aws_detection_filter.yml delete mode 100644 macros/container_implant_gcp_detection_filter.yml delete mode 100644 macros/create_local_admin_via_net_filter.yml delete mode 100644 macros/create_remote_thread_into_lsass_filter.yml delete mode 100644 macros/creation_of_shadow_copy_filter.yml delete mode 100644 macros/creation_of_shadow_copy_with_wmic_and_powershell_filter.yml delete mode 100644 macros/cred_dump_via_copy_from_shadowcopy_filter.yml delete mode 100644 macros/cred_dump_via_symlink_shadowcopy_filter.yml delete mode 100644 macros/detect_activity_related_to_pass_the_hash_attacks_filter.yml delete mode 100644 macros/detect_credential_dumping_through_LSASS_access_filter.yml delete mode 100644 macros/detect_mimikatz_using_loaded_images_filter.yml delete mode 100644 macros/dns_query_length_mltk_filter.yml delete mode 100644 macros/dns_query_length_with_high_standard_deviation_filter.yml delete mode 100644 macros/dns_record_changed_filter.yml delete mode 100644 macros/dragonfly_schtasks_filter.yml delete mode 100644 macros/dump_lsass_via_comsvcs_dll_filter.yml delete mode 100644 macros/ec2_excessive_runinstances_mltk_input_filter.yml delete mode 100644 macros/ec2_excessive_terminateinstances_mltk_input_filter.yml delete mode 100644 macros/email_files_not_in_outlook_directory_filter.yml delete mode 100644 macros/file_write_spikes_filter.yml delete mode 100644 macros/first_time_seen_cmd_line_filter.yml delete mode 100644 macros/kubernetes_aws_scan_fingerprint_detection_filter.yml delete mode 100644 macros/kubernetes_gcp_scan_fingerprint_detection_filter.yml delete mode 100644 macros/kubernetes_pods_aws_scan_fingerprint_detection_filter.yml delete mode 100644 macros/lnk_executing_a_process_filter.yml delete mode 100644 macros/malicious_powershell_process_obfuscation_techniques_output_filter.yml delete mode 100644 macros/okta_failed_sso_attempt_filter.yml delete mode 100644 macros/okta_multiple_users_with_auth_failures_from_ip_filter.yml delete mode 100644 macros/okta_user_lockouts_filter.yml delete mode 100644 macros/okta_user_logins_from_multiple_cities_filter.yml delete mode 100644 macros/outbound_smb_connections_filter.yml delete mode 100644 macros/outlook_writing_zip_filter.yml delete mode 100644 macros/previously_seen_cloud_compute_creations_by_user_input_filter.yml delete mode 100644 macros/previously_seen_cloud_compute_image_input_filter.yml delete mode 100644 macros/previously_seen_cloud_compute_instance_types_input_filter.yml delete mode 100644 macros/previously_seen_cloud_regions_input_filter.yml delete mode 100644 macros/rare_executables_on_endpoint_filter.yml delete mode 100644 macros/remote_desktop_network_traffic_filter.yml delete mode 100644 macros/remote_desktop_process_running_on_system_filter.yml delete mode 100644 macros/schtasks_scheduling_job_on_remote_system_filter.yml delete mode 100644 macros/smb_traffic_spike_filter.yml delete mode 100644 macros/smb_traffic_spike_mltk_filter.yml delete mode 100644 macros/suspicious_email_attachments_filter.yml delete mode 100644 macros/suspicious_reg_process_filter.yml delete mode 100644 macros/unauthorized_dns_servers_filter.yml delete mode 100644 macros/uncommon_processes_filter.yml delete mode 100644 macros/unload_sysmon_filter_driver_filter.yml delete mode 100644 macros/unsigned_image_loaded_by_LSASS_filter.yml delete mode 100644 macros/unusually_long_commandlines_filter.yml delete mode 100644 macros/wmi_process_launch_filter.yml delete mode 100644 macros/wmi_script_execution_filter.yml diff --git a/baselines/add_prohibited_processes_to_enterprise_security.yml b/baselines/add_prohibited_processes_to_enterprise_security.yml index 7d39ecadae..a76e2c7324 100644 --- a/baselines/add_prohibited_processes_to_enterprise_security.yml +++ b/baselines/add_prohibited_processes_to_enterprise_security.yml @@ -13,7 +13,7 @@ search: '| inputlookup interesting_processes_lookup | search note!=ESCU* | input interesting_processes_lookup | stats count' tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) + - 'Emotet Malware DHS Report TA18-201A ' - Monitor for Unauthorized Software - SamSam Ransomware detections: diff --git a/baselines/baseline_of_command_line_length___mltk.yml b/baselines/baseline_of_command_line_length___mltk.yml index 28205e56d9..f5068fa341 100644 --- a/baselines/baseline_of_command_line_length___mltk.yml +++ b/baselines/baseline_of_command_line_length___mltk.yml @@ -31,5 +31,5 @@ tags: - Suspicious MSHTA Activity - Unusual Processes detections: - - Detect Prohibited Applications Spawning cmd.exe - Unusually Long Command Line - MLTK + - Detect Prohibited Applications Spawning cmd.exe diff --git a/baselines/baseline_of_smb_traffic___mltk.yml b/baselines/baseline_of_smb_traffic___mltk.yml index 2dd6e5ad48..e5b850a63c 100644 --- a/baselines/baseline_of_smb_traffic___mltk.yml +++ b/baselines/baseline_of_smb_traffic___mltk.yml @@ -31,7 +31,7 @@ tags: analytics_story: - DHS Report TA18-074A - Disabling Security Tools - - Emotet Malware (DHS Report TA18-201A) + - 'Emotet Malware DHS Report TA18-201A ' - Hidden Cobra Malware - Netsh Abuse - Ransomware diff --git a/baselines/dnstwist_domain_names.yml b/baselines/dnstwist_domain_names.yml index dde08528b5..cd2ebd0aad 100644 --- a/baselines/dnstwist_domain_names.yml +++ b/baselines/dnstwist_domain_names.yml @@ -16,6 +16,6 @@ tags: - Brand Monitoring - Suspicious Emails detections: - - Monitor Email For Brand Abuse - Monitor DNS For Brand Abuse - Monitor Web Traffic For Brand Abuse + - Monitor Email For Brand Abuse diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml index 9fc086a3b8..7d68c6f389 100644 --- a/baselines/previously_seen_aws_provisioning_activity_sources.yml +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -17,7 +17,7 @@ tags: analytics_story: - AWS Suspicious Provisioning Activities detections: - - AWS Cloud Provisioning From Previously Unseen City - AWS Cloud Provisioning From Previously Unseen Country - AWS Cloud Provisioning From Previously Unseen Region - AWS Cloud Provisioning From Previously Unseen IP Address + - AWS Cloud Provisioning From Previously Unseen City diff --git a/baselines/previously_seen_command_line_arguments.yml b/baselines/previously_seen_command_line_arguments.yml index 7ac6d4ed10..32d364cc1e 100644 --- a/baselines/previously_seen_command_line_arguments.yml +++ b/baselines/previously_seen_command_line_arguments.yml @@ -25,6 +25,6 @@ tags: - Suspicious Command-Line Executions - Suspicious MSHTA Activity detections: + - Processes launching netsh - First time seen command line argument - Detect Prohibited Applications Spawning cmd.exe - - Processes launching netsh diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml index 6f5a11191f..6a85afd36f 100644 --- a/baselines/previously_seen_users_in_cloudtrail.yml +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -19,7 +19,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect AWS Console Login by User from New Country + - Detect new user AWS Console Login - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Region - - Detect new user AWS Console Login + - Detect AWS Console Login by User from New Country diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml index ca2d520640..b50325c51f 100644 --- a/baselines/update_previously_seen_users_in_cloudtrail.yml +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -20,7 +20,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect AWS Console Login by User from New Country + - Detect new user AWS Console Login - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Region - - Detect new user AWS Console Login + - Detect AWS Console Login by User from New Country diff --git a/bin/converter_v2_v3.py b/bin/converter_v2_v3.py index 00be547a48..33b9b571f1 100644 --- a/bin/converter_v2_v3.py +++ b/bin/converter_v2_v3.py @@ -33,6 +33,10 @@ def attack_lookup_id(inputs_array): return outputs +def remove_special_characters(input_str): + output_str = input_str.replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&','and').replace('_',' ') + return output_str + def generate_content(): ## detections ## detection_files = glob.glob("../security-content-tmp/detections/*.yml") @@ -51,7 +55,7 @@ def generate_content(): for orig_dict in old_detections: print(orig_dict['name']) new_dict = {} - new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&',' ').replace('_',' ') + new_dict['name'] = remove_special_characters(orig_dict['name']) new_dict['id'] = orig_dict['id'] new_dict['version'] = int(float(orig_dict['version'])) if 'modification_date' in orig_dict: @@ -92,6 +96,8 @@ def generate_content(): tag_dict['nist'] = orig_dict['mappings']['nist'] if 'security_domain' in orig_dict: tag_dict['security_domain'] = orig_dict['security_domain'] + if 'asset_type' in orig_dict: + tag_dict['asset_type'] = orig_dict['asset_type'] new_dict['tags'] = tag_dict ordered_new_dict = OrderedDict(new_dict.items()) new_file_name = new_dict['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() @@ -114,7 +120,7 @@ def generate_content(): for orig_dict in old_baselines: print(orig_dict['name']) new_dict = {} - new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&',' ').replace('_',' ') + new_dict['name'] = remove_special_characters(orig_dict['name']) new_dict['id'] = orig_dict['id'] new_dict['version'] = int(float(orig_dict['version'])) if 'modification_date' in orig_dict: @@ -153,7 +159,7 @@ def generate_content(): for orig_dict in old_stories: print(orig_dict['name']) new_dict = {} - new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&','and').replace('_',' ') + new_dict['name'] = remove_special_characters(orig_dict['name']) new_dict['id'] = orig_dict['id'] new_dict['version'] = int(float(orig_dict['version'])) if 'modification_date' in orig_dict: @@ -169,7 +175,7 @@ def generate_content(): if 'references' in orig_dict: new_dict['references'] = orig_dict['references'] tag_dict = {} - tag_dict['analytics_story'] = orig_dict['name'] + tag_dict['analytics_story'] = remove_special_characters(orig_dict['name']) tag_dict['usecase'] = orig_dict['usecase'] tag_dict['category'] = orig_dict['category'] new_dict['tags'] = tag_dict @@ -185,12 +191,14 @@ def generate_content(): for investigation_file in investigation_files: old_investigations.append(load_file(investigation_file)) + map_inv_det = map_investigations_to_detection(old_detections) + print() print('## Response Tasks ##') for orig_dict in old_investigations: print(orig_dict['name']) new_dict = {} - new_dict['name'] = orig_dict['name'].replace('.',' ').replace('/',' ').replace('(',' ').replace(')',' ').replace('&',' ').replace('_',' ') + new_dict['name'] = remove_special_characters(orig_dict['name']) new_dict['id'] = orig_dict['id'] new_dict['version'] = int(float(orig_dict['version'])) if 'modification_date' in orig_dict: @@ -213,6 +221,11 @@ def generate_content(): # new_dict['playbook'] = phantom_dict else: continue + stories = get_stories_for_investigations(map_inv_det, det_sto, orig_dict) + if len(stories) > 0: + tag_dict = {} + tag_dict['analytics_story'] = stories + new_dict['tags'] = tag_dict ordered_new_dict = OrderedDict(new_dict.items()) new_file_name = new_dict['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() with open('response_tasks/' + new_file_name + '.yml', 'w+' ) as outfile: @@ -229,15 +242,26 @@ def load_file(file_path): sys.exit("ERROR: reading {0}".format(file_path)) return file +def map_investigations_to_detection(detections): + inv_det = {} + for detection in detections: + if 'investigations' in detection: + for investigation in detection['investigations']: + if not (investigation['id'] in inv_det): + inv_det[investigation['id']] = {detection['id']} + else: + inv_det[investigation['id']].add(detection['id']) + return inv_det + def map_detection_to_stories(stories): det_sto = {} for story in stories: if 'detections' in story: for detection in story['detections']: if not (detection['detection_id'] in det_sto): - det_sto[detection['detection_id']] = {story['name']} + det_sto[detection['detection_id']] = {remove_special_characters(story['name'])} else: - det_sto[detection['detection_id']].add(story['name']) + det_sto[detection['detection_id']].add(remove_special_characters(story['name'])) return det_sto def map_baselines_to_detection(detections): @@ -276,6 +300,18 @@ def enrich_baselines_with_stories(baselines, map_bas_det, map_det_sto): return enriched_baselines +def get_stories_for_investigations(map_inv_det, map_det_sto, investigation): + story_names = set() + if investigation['id'] in map_inv_det: + detections = map_inv_det[investigation['id']] + for detection in detections: + if detection in map_det_sto: + stories = map_det_sto[detection] + story_names = story_names | stories + + return sorted(list(story_names)) + + def check_source_macro(search): new_search = search @@ -308,7 +344,7 @@ def check_source_macro(search): #generate macro configuration new_dict = {} - new_dict['definiton'] = match.group() + new_dict['definition'] = match.group() new_dict['description'] = 'customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent.' new_dict['name'] = mappings[content_match] ordered_new_dict = OrderedDict(new_dict.items()) diff --git a/bin/generate.py b/bin/generate.py index 118cbe2d6c..0e21341c0c 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -11,6 +11,7 @@ from os import path import sys import datetime from jinja2 import Environment, FileSystemLoader +import re # global variables REPO_PATH = '' @@ -22,7 +23,7 @@ def load_objects(file_path): files = [] manifest_files = path.join(path.expanduser(REPO_PATH), file_path) - for file in glob.glob(manifest_files): + for file in sorted(glob.glob(manifest_files)): files.append(load_file(file)) return files @@ -54,18 +55,45 @@ def generate_transforms_conf(lookups): return output_path -def generate_savedsearches_conf(detections, investigations, baselines): +def generate_savedsearches_conf(detections, response_tasks, baselines, deployments): - # mapping from source macro or datamodel to providing_technologies - # parse out entities dest, user + for detection in detections: + # parse out data_models + data_model = parse_data_models_from_search(detection['search']) + if data_model: + detection['data_model'] = data_model + + matched_deployments = get_deployments(detection, deployments) + if len(matched_deployments): + detection['deployment'] = matched_deployments[-1] + nes_fields = get_nes_fields(detection['search'], detection['deployment']) + if len(nes_fields) > 0: + detection['nes_fields'] = nes_fields + + + for baseline in baselines: + data_model = parse_data_models_from_search(baseline['search']) + if data_model: + baseline['data_model'] = data_model + + matched_deployments = get_deployments(baseline, deployments) + if len(matched_deployments): + baseline['deployment'] = matched_deployments[-1] + + for response_task in response_tasks: + if 'search' in response_task: + data_model = parse_data_models_from_search(response_task['search']) + if data_model: + response_task['data_model'] = data_model utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), trim_blocks=True) + j2_env.filters['custom_jinja2_enrichment_filter'] = custom_jinja2_enrichment_filter template = j2_env.get_template('savedsearches.j2') output_path = OUTPUT_PATH + "/default/savedsearches.conf" - output = template.render(detections=detections, investigations=investigations, baselines=baselines, time=utc_time) + output = template.render(detections=detections, baselines=baselines, response_tasks=response_tasks, time=utc_time) with open(output_path, 'w') as f: output = output.encode('ascii', 'ignore').decode('ascii') f.write(output) @@ -73,7 +101,17 @@ def generate_savedsearches_conf(detections, investigations, baselines): return output_path -def generate_analytics_story_conf(stories): +def generate_analytics_story_conf(stories, detections, response_tasks): + + sto_det = map_detection_to_stories(detections) + + sto_res = map_response_tasks_to_stories(response_tasks) + + for story in stories: + if story['name'] in sto_det: + story['detections'] = list(sto_det[story['name']]) + if story['name'] in sto_res: + story['response_tasks'] = list(sto_res[story['name']]) utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() @@ -88,7 +126,20 @@ def generate_analytics_story_conf(stories): return output_path -def generate_use_case_library_conf(stories, detections, investigations, baselines): +def generate_use_case_library_conf(stories, detections, response_tasks, baselines): + + sto_det = map_detection_to_stories(detections) + + sto_res = map_response_tasks_to_stories(response_tasks) + + for story in stories: + if story['name'] in sto_det: + story['detections'] = list(sto_det[story['name']]) + if story['name'] in sto_res: + story['response_tasks'] = list(sto_res[story['name']]) + story['searches'] = story['detections'] + story['response_tasks'] + else: + story['searches'] = story['detections'] utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() @@ -97,7 +148,7 @@ def generate_use_case_library_conf(stories, detections, investigations, baseline template = j2_env.get_template('use_case_library.j2') output_path = OUTPUT_PATH + "/default/use_case_library.conf" output = template.render(stories=stories, detections=detections, - investigations=investigations, + response_tasks=response_tasks, baselines=baselines, time=utc_time) with open(output_path, 'w') as f: f.write(output) @@ -105,7 +156,16 @@ def generate_use_case_library_conf(stories, detections, investigations, baseline return output_path -def generate_macros_conf(macros): +def generate_macros_conf(macros, detections): + filter_macros = [] + for detection in detections: + new_dict = {} + new_dict['definition'] = 'search *' + new_dict['description'] = 'Update this macro to limit the output results to filter out false positives. ' + new_dict['name'] = detection['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + '_filter' + filter_macros.append(new_dict) + + all_macros = macros + filter_macros utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() @@ -113,200 +173,98 @@ def generate_macros_conf(macros): trim_blocks=True) template = j2_env.get_template('macros.j2') output_path = OUTPUT_PATH + "/default/macros.conf" - output = template.render(macros=macros, time=utc_time) + output = template.render(macros=all_macros, time=utc_time) with open(output_path, 'w') as f: f.write(output) return output_path -def identify_next_steps(detections, investigations): - enriched_detections = [] - for detection in detections: - if 'splunk' in detection['detect']: - if 'correlation_rule' in detection['detect']['splunk']: - investigations_output = "" - has_phantom = False - next_steps = "" - if 'investigations' in detection: - for i in detection['investigations']: - if i['type'] == 'splunk': - investigations_output += "ESCU - {0}\\n".format(i['name']) - next_steps = "{\"version\": 1, \"data\": \"Recommended following steps:\\n\\n" - next_steps += "1.[[action|escu_investigate]]: Based on ESCU investigate \ - recommendations:\\ n%s\"}" % investigations_output - if i['type'] == 'phantom': - has_phantom = True - - # lets pull the playbook URL out from investigation object - playbook_url = '' - for inv in investigations: - if i['name'] == inv['name']: - playbook_url = inv['investigate']['phantom']['playbook_url'] - # construct next steps with the playbook info - playbook_next_steps_string = "Splunk>Phantom Response Playbook - Monitor enrichment of the \ - Splunk>Phantom Playbook called " + str(i['name']) + " and answer any \ - analyst prompt in Mission Control with a response decision. \ - Link to the playbook " + str(playbook_url) - next_steps = "{\"version\": 1, \"data\": \"Recommended following" - next_steps += ":\\n\\n1. [[action|runphantomplaybook]]: Phantom playbook " - next_steps += "recommendations:\\n%s\\n2. [[action|escu_investigate]]: " % (playbook_next_steps_string) - next_steps += "Based on ESCU investigate recommendations:\\n%s\"}" % (investigations_output) - if has_phantom: - detection['recommended_actions'] = 'runphantomplaybook, escu_investigate' - enriched_detections.append(detection) - - return enriched_detections +def parse_data_models_from_search(search): + match = re.search('from\sdatamodel\s?=\s?([^\s.]*)',search) + if match is not None: + return match.group(1) + return False -def map_investigations_to_detection(detections): - inv_det = {} - for detection in detections: - if 'investigations' in detection: - for investigation in detection['investigations']: - if not (investigation['id'] in inv_det): - inv_det[investigation['id']] = {detection['id']} - else: - inv_det[investigation['id']].add(detection['id']) - return inv_det +def get_deployments(object, deployments): + matched_deployments = [] - -def map_baselines_to_detection(detections): - bas_det = {} - for detection in detections: - if 'baselines' in detection: - for baseline in detection['baselines']: - if not (baseline['id'] in bas_det): - bas_det[baseline['id']] = {detection['id']} - else: - bas_det[baseline['id']].add(detection['id']) - return bas_det - - -def map_detection_to_stories(stories): - det_sto = {} - for story in stories: - for detection in story['detections']: - if not (detection['detection_id'] in det_sto): - det_sto[detection['detection_id']] = {story['name']} + for deployment in deployments: + if 'analytics_story' in deployment['tags']: + if type(deployment['tags']['analytics_story']) is str: + tags_all_array = [deployment['tags']['analytics_story']] else: - det_sto[detection['detection_id']].add(story['name']) - return det_sto + tags_all_array = deployment['tags']['analytics_story'] + if tags_all_array[0] == 'all': + matched_deployments.append(deployment) + continue + + for tag in object['tags'].keys(): + if tag in deployment['tags'].keys(): + if type(object['tags'][tag]) is str: + tag_array = [object['tags'][tag]] + else: + tag_array = object['tags'][tag] + + for tag_value in tag_array: + if type(deployment['tags'][tag]) is str: + tag_array_deployment = [deployment['tags'][tag]] + else: + tag_array_deployment = deployment['tags'][tag] + + for tag_value_deployment in tag_array_deployment: + if tag_value == tag_value_deployment: + matched_deployments.append(deployment) + continue + + return matched_deployments -def enrich_investigations_with_stories(investigations, map_inv_det, map_det_sto): - enriched_investigations = [] - for investigation in investigations: - stories_set = set() - if investigation['id'] in map_inv_det: - for detection_id in map_inv_det[investigation['id']]: - if detection_id in map_det_sto: - stories_set = stories_set | map_det_sto[detection_id] +def get_nes_fields(search, deployment): + nes_fields_matches = [] + if 'notable' in deployment['alert_action']: + if 'nes_fields' in deployment['alert_action']['notable']: + for field in deployment['alert_action']['notable']['nes_fields']: + if (search.find(field + ' ') != -1): + nes_fields_matches.append(field) - investigation['stories'] = sorted(list(stories_set)) - enriched_investigations.append(investigation) - return enriched_investigations + return nes_fields_matches -def enrich_detections_with_stories(detections, map_det_sto): - enriched_detections = [] +def map_detection_to_stories(detections): + sto_det = {} for detection in detections: - stories_set = set() - if detection['id'] in map_det_sto: - stories_set = stories_set | map_det_sto[detection['id']] - detection['stories'] = sorted(list(stories_set)) - enriched_detections.append(detection) - return enriched_detections + if 'analytics_story' in detection['tags']: + for story in detection['tags']['analytics_story']: + if not (story in sto_det): + sto_det[story] = {detection['name']} + else: + sto_det[story].add(detection['name']) + return sto_det + +def map_response_tasks_to_stories(response_tasks): + sto_res = {} + for response_task in response_tasks: + if 'tags' in response_tasks: + if 'analytics_story' in response_tasks['tags']: + for story in response_tasks['tags']['analytics_story']: + if not (story in sto_res): + sto_res[story] = {response_task['name']} + else: + sto_res[story].add(response_task['name']) + return sto_res -def enrich_baselines_with_stories(baselines, map_bas_det, map_det_sto): - enriched_baselines = [] - for baseline in baselines: - stories_set = set() - if baseline['id'] in map_bas_det: - for baseline_id in map_bas_det[baseline['id']]: - if baseline_id in map_det_sto: - stories_set = stories_set | map_det_sto[baseline_id] +def custom_jinja2_enrichment_filter(string, object): + customized_string = string + for key in object.keys(): + customized_string = customized_string.replace("%" + key + "%", str(object[key])) - baseline['stories'] = sorted(list(stories_set)) - enriched_baselines.append(baseline) - return enriched_baselines - - -def enrich_stories(stories, detections, investigations, baselines): - enriched_stories = [] - for story in stories: - providing_technologies = set() - data_models = set() - detection_names = [] - mappings = dict() - mappings["cis20"] = set() - mappings["kill_chain_phases"] = set() - mappings["mitre_attack"] = set() - mappings["nist"] = set() - mappings["mitre_technique_id"] = set() - searches = [] - - for detection in story['detections']: - for detection_obj in detections: - if detection['detection_id'] == detection_obj['id']: - if 'providing_technologies' in detection_obj['data_metadata']: - providing_technologies = providing_technologies | set(detection_obj - ['data_metadata']['providing_technologies']) - if 'data_models' in detection_obj['data_metadata']: - data_models = data_models | set(detection_obj['data_metadata']['data_models']) - if detection_obj['type'] == 'splunk': - detection_names.append("ESCU - " + detection_obj['name'] + " - Rule") - - for key in detection_obj['mappings']: - mappings[key] = mappings[key] | set(detection_obj['mappings'][key]) - - for key in mappings.keys(): - mappings[key] = sorted(list(mappings[key])) - - story['mappings'] = mappings - story['detection_names'] = sorted(detection_names) - searches = sorted(detection_names) - - investigation_names = [] - - for investigation in investigations: - for s in investigation['stories']: - if s == story['name']: - if 'providing_technologies' in investigation['data_metadata']: - providing_technologies = providing_technologies | set(investigation - ['data_metadata']['providing_technologies']) - if 'data_models' in investigation['data_metadata']: - data_models = data_models | set(investigation['data_metadata']['data_models']) - if investigation['type'] == 'splunk': - investigation_names.append("ESCU - " + investigation['name']) - - story['investigation_names'] = sorted(investigation_names) - searches = searches + sorted(investigation_names) - - baseline_names = [] - - for baseline in baselines: - for s in baseline['stories']: - if s == story['name']: - if 'providing_technologies' in baseline['data_metadata']: - providing_technologies = providing_technologies | set(baseline['data_metadata']['providing_technologies']) - if 'data_models' in baseline['data_metadata']: - data_models = data_models | set(baseline['data_metadata']['data_models']) - if baseline['type'] == 'splunk': - baseline_names.append("ESCU - " + baseline['name']) - - story['baseline_names'] = sorted(baseline_names) - searches = searches + sorted(baseline_names) - - story['providing_technologies'] = sorted(list(providing_technologies)) - story['data_models'] = sorted(list(data_models)) - story['searches'] = searches - - enriched_stories.append(story) - - return enriched_stories + for key in object['tags'].keys(): + customized_string = customized_string.replace("%" + key + "%", str(object['tags'][key])) + return customized_string if __name__ == "__main__": @@ -330,38 +288,27 @@ if __name__ == "__main__": detections = load_objects("detections/*.yml") responses = load_objects("responses/*.yml") response_tasks = load_objects("response_tasks/*.yml") - investigations = load_objects("investigations/*.yml") - - # detections = identify_next_steps(detections, investigations) - # - # map_inv_det = map_investigations_to_detection(detections) - # map_det_sto = map_detection_to_stories(stories) - # map_bas_det = map_baselines_to_detection(detections) - # detections = enrich_detections_with_stories(detections, map_det_sto) - # investigations = enrich_investigations_with_stories(investigations, map_inv_det, map_det_sto) - # baselines = enrich_baselines_with_stories(baselines, map_bas_det, map_det_sto) - # stories = enrich_stories(stories, detections, investigations, baselines) + deployments = load_objects("deployments/*.yml") lookups_path = generate_transforms_conf(lookups) detections = sorted(detections, key=lambda d: d['name']) - # investigations = sorted(investigations, key=lambda i: i['name']) - # baselines = sorted(baselines, key=lambda b: b['name']) - # detection_path = generate_savedsearches_conf(detections, investigations, baselines) - # - # stories = sorted(stories, key=lambda s: s['name']) - # story_path = generate_analytics_story_conf(stories) - # - # use_case_lib_path = generate_use_case_library_conf(stories, detections, investigations, baselines) - # - # macros = sorted(macros, key=lambda m: m['name']) - # macros_path = generate_macros_conf(macros) - # - # if VERBOSE: - # print("{0} stories have been successfully written to {1}".format(len(stories), story_path)) - # print("{0} stories have been successfully written to {1}".format(len(stories), use_case_lib_path)) - # print("{0} detections have been successfully written to {1}".format(len(detections), detection_path)) - # print("{0} investigations have been successfully written to {1}".format(len(investigations), detection_path)) - # print("{0} baselines have been successfully written to {1}".format(len(baselines), detection_path)) - # print("{0} macros have been successfully written to {1}".format(len(macros), macros_path)) - # print("security content generation completed..") + response_tasks = sorted(response_tasks, key=lambda i: i['name']) + baselines = sorted(baselines, key=lambda b: b['name']) + detection_path = generate_savedsearches_conf(detections, response_tasks, baselines, deployments) + + stories = sorted(stories, key=lambda s: s['name']) + story_path = generate_analytics_story_conf(stories, detections, response_tasks) + + use_case_lib_path = generate_use_case_library_conf(stories, detections, response_tasks, baselines) + + macros = sorted(macros, key=lambda m: m['name']) + macros_path = generate_macros_conf(macros, detections) + + if VERBOSE: + print("{0} stories have been successfully written to {1}".format(len(stories), story_path)) + print("{0} detections have been successfully written to {1}".format(len(detections), detection_path)) + print("{0} response tasks have been successfully written to {1}".format(len(response_tasks), detection_path)) + print("{0} baselines have been successfully written to {1}".format(len(baselines), detection_path)) + print("{0} macros have been successfully written to {1}".format(len(macros), macros_path)) + print("security content generation completed..") diff --git a/bin/jinja2_templates/analytic_stories.j2 b/bin/jinja2_templates/analytic_stories.j2 index c8053c48af..362525e03b 100644 --- a/bin/jinja2_templates/analytic_stories.j2 +++ b/bin/jinja2_templates/analytic_stories.j2 @@ -9,18 +9,20 @@ {% for story in stories %} [{{ story.name }}] -category = {{ story.category[0] }} -creation_date = {{ story.creation_date }} -modification_date = {{ story.modification_date }} +category = {{ story.tags.category[0] }} +creation_date = {{ story.date }} +modification_date = {{ story.date }} id = {{ story.id }} version = {{ story.version }} reference = {{ story.references | tojson }} -detection_searches = {{ story.detection_names | tojson }} -mappings = {{ story.mappings | tojson }} -investigative_searches = {{ story.investigation_names | tojson }} -support_searches = {{ story.baseline_names | tojson }} -data_models = {{ story.data_models | tojson }} -providing_technologies = {{ story.providing_technologies | tojson }} +detection_searches = {{ story.detections | tojson }} +mappings = {{ story.tags | tojson }} +{% if story.response_tasks is defined %} +investigative_searches = {{ story.response_tasks | tojson }} +{% endif %} +support_searches = none +data_models = none +providing_technologies = none description = {{ story.description }} {% if story.narrative is defined %} narrative = {{ story.narrative }} diff --git a/bin/jinja2_templates/savedsearches.bak.j2 b/bin/jinja2_templates/savedsearches.bak.j2 new file mode 100644 index 0000000000..8e50fabe6a --- /dev/null +++ b/bin/jinja2_templates/savedsearches.bak.j2 @@ -0,0 +1,292 @@ +############# +# Automatically generated by generator.py in splunk/security-content +# On Date: {{ time }} UTC +# Author: Splunk Security Research +# Contact: research@splunk.com +############# + +### ESCU DETECTIONS ### + + +{% for detection in detections %} +[ESCU - {{ detection.name }} - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = {{ detection.description }} +action.escu.mappings = {{ detection.mappings | tojson }} +{% if detection.data_metadata.data_models is defined %} +action.escu.data_models = {{ detection.data_metadata.data_models | tojson }} +{% endif %} +{% if detection.eli5 is defined %} +action.escu.eli5 = {{ detection.eli5 }} +{% else %} +action.escu.eli5 = none +{% endif %} +{% if detection.how_to_implement is defined %} +action.escu.how_to_implement = {{ detection.how_to_implement }} +{% else %} +action.escu.how_to_implement = none +{% endif %} +{% if detection.known_false_positives is defined %} +action.escu.known_false_positives = {{ detection.known_false_positives }} +{% else %} +action.escu.known_false_positives = None +{% endif %} +action.escu.creation_date = {{ detection.creation_date }} +action.escu.modification_date = {{ detection.modification_date }} +action.escu.confidence = {{ detection.confidence }} +action.escu.full_search_name = ESCU - {{ detection.name }} - Rule +action.escu.search_type = detection +{% if detection.asset_type is defined %} +action.escu.asset_at_risk = {{ detection.asset_type }} +{% endif %} +{% if detection.entities is defined %} +action.escu.fields_required = {{ detection.entities | tojson }} +action.escu.entities = {{ detection.entities | tojson }} +{% endif %} +{% if detection.data_metadata.providing_technologies is defined %} +action.escu.providing_technologies = {{ detection.data_metadata.providing_technologies | tojson }} +{% endif %} +action.escu.analytic_story = {{ detection.stories | tojson | replace("\\u0026","&") }} +{% if detection.detect.splunk is defined %} +{% set correlation_rule = detection.detect.splunk.correlation_rule %} +{% elif detection.detect.uba is defined %} +{% set correlation_rule = detection.detect.uba.correlation_rule %} +{% endif %} +{% if correlation_rule.schedule.cron_schedule is defined %} +cron_schedule = {{ correlation_rule.schedule.cron_schedule }} +{% endif %} +{% if correlation_rule.schedule.earliest_time is defined %} +dispatch.earliest_time = {{ correlation_rule.schedule.earliest_time }} +{% endif %} +{% if correlation_rule.schedule.latest_time is defined %} +dispatch.latest_time = {{ correlation_rule.schedule.latest_time }} +{% endif %} +{% if correlation_rule is defined %} +action.correlationsearch.enabled = 1 +action.correlationsearch.label = {{ detection.name }} +{% if correlation_rule.notable is defined %} +action.notable = 1 +{% endif %} +{% if correlation_rule.notable.nes_fields is defined %} +action.notable.param.nes_fields = {{ correlation_rule.notable.nes_fields }} +action.notable.param.rule_description = {{ correlation_rule.notable.rule_description }} +action.notable.param.rule_title = {{ correlation_rule.notable.rule_title }} +action.notable.param.security_domain = {{ detection.security_domain }} +action.notable.param.severity = {{ detection.confidence }} +{% endif %} +{% if (correlation_rule.notable.drilldown_name is defined) and (correlation_rule.notable.drilldown_search is defined) %} +action.notable.param.drilldown_name = {{ correlation_rule.notable.drilldown_name }} +action.notable.param.drilldown_search = {{ correlation_rule.notable.drilldown_search }} +{% endif %} +{% if correlation_rule.risk is defined %} +action.risk = 1 +action.risk.param._risk_object = {{ correlation_rule.risk.risk_object }} +action.risk.param._risk_object_type = {{ correlation_rule.risk.risk_object_type[0] }} +action.risk.param._risk_score = {{ correlation_rule.risk.risk_score }} +action.risk.param.verbose = 0 +{% endif %} +{% if correlation_rule.suppress is defined %} +alert.digest_mode = 1 +alert.suppress = 1 +alert.suppress.fields = {{ correlation_rule.suppress.suppress_fields }} +alert.suppress.period = {{ correlation_rule.suppress.suppress_period }} +{% endif %} +{% endif %} +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +schedule_window = auto +is_visible = false +{% if detection.detect.splunk is defined %} +search = {{ detection.detect.splunk.correlation_rule.search }} +{% elif detection.detect.uba is defined %} +search = {{ detection.detect.uba.correlation_rule.search }} +{% endif %} + +{% endfor %} +### END ESCU DETECTIONS ### + +### ESCU INVESTIGATIONS ### + +{% for investigation in investigations %} +{% if investigation.type != 'phantom' %} +[ESCU - {{ investigation.name }}] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - {{ investigation.name }} +description = {{ investigation.description }} +action.escu.creation_date = {{ investigation.creation_date }} +action.escu.modification_date = {{ investigation.modification_date }} +action.escu.analytic_story = {{ investigation.stories | tojson | replace("\\u0026","&") }} +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +{% if investigation.data_metadata.data_models is defined %} +action.escu.data_models = {{ investigation.data_metadata.data_models | tojson }} +{% endif %} +{% if investigation.data_metadata.providing_technologies is defined %} +action.escu.providing_technologies = {{ investigation.data_metadata.providing_technologies | tojson }} +{% endif %} +{% if investigation.eli5 is defined %} +action.escu.eli5 = {{ investigation.eli5 }} +{% else %} +action.escu.eli5 = none +{% endif %} +{% if investigation.how_to_implement is defined %} +action.escu.how_to_implement = {{ investigation.how_to_implement }} +{% else %} +action.escu.how_to_implement = none +{% endif %} +{% if investigation.known_false_positives is defined %} +action.escu.known_false_positives = {{ investigation.known_false_positives }} +{% else %} +action.escu.known_false_positives = None at this time +{% endif %} +{% if investigation.entities is defined %} +action.escu.fields_required = {{ investigation.entities | tojson }} +action.escu.entities = {{ investigation.entities | tojson }} +{% endif %} +disabled = true +schedule_window = auto +is_visible = false +search = {{ investigation.investigate.splunk.search }} + +{% endif %} +{% endfor %} + +### END ESCU INVESTIGATIONS ### + + +### ESCU BASELINES ### + +{% for baseline in baselines %} +[ESCU - {{ baseline.name }}] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - {{ baseline.name }} +description = {{ baseline.description }} +action.escu.creation_date = {{ baseline.creation_date }} +action.escu.modification_date = {{ baseline.modification_date }} +action.escu.analytic_story = {{ baseline.stories | tojson | replace("\\u0026","&") }} +{% if baseline.data_metadata.data_models is defined %} +action.escu.data_models = {{ baseline.data_metadata.data_models | tojson }} +{% endif %} +{% if baseline.baseline.splunk.schedule.earliest_time is defined %} +dispatch.earliest_time = {{ baseline.baseline.splunk.schedule.earliest_time }} +{% endif %} +{% if baseline.baseline.splunk.schedule.latest_time is defined %} +dispatch.latest_time = {{ baseline.baseline.splunk.schedule.latest_time }} +{% endif %} +{% if baseline.data_metadata.providing_technologies is defined %} +action.escu.providing_technologies = {{ baseline.data_metadata.providing_technologies | tojson }} +{% endif %} +{% if baseline.eli5 is defined %} +action.escu.eli5 = {{ baseline.eli5 }} +{% else %} +action.escu.eli5 = none +{% endif %} +{% if baseline.how_to_implement is defined %} +action.escu.how_to_implement = {{ baseline.how_to_implement }} +{% else %} +action.escu.how_to_implement = none +{% endif %} +{% if baseline.known_false_positives is defined %} +action.escu.known_false_positives = {{ baseline.known_false_positives }} +{% else %} +action.escu.known_false_positives = None at this time +{% endif %} +{% if baseline.entities is defined %} +action.escu.fields_required = {{ baseline.entities | tojson }} +action.escu.entities = {{ baseline.entities | tojson }} +{% endif %} +disabled = true +schedule_window = auto +is_visible = false +search = {{ baseline.baseline.splunk.search }} + +{% endfor %} + +### USAGE DASHBOARD CONFIGURATIONS ### + +[escu-metrics-usage] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +dispatchAs = user +search = index=_audit sourcetype="audittrail" \ +"ESCU - "\ +`comment("Find all the search names in the audittrail.")`\ +| stats count(search) by search savedsearch_name user\ +| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ +`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ +| rex field=search "\"(?.*)\""\ +`comment("Extract the name of the search from the search string")`\ +| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* + +[escu-metrics-search] +action.email.useNSSubject = 1 +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +enableSched = 1 +cron_schedule = 0 0 * * * +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +search = index=_audit action=search | transaction search_id maxspan=3m | search ESCU | stats sum(total_run_time) avg(total_run_time) max(total_run_time) sum(result_count) + +[escu-metrics-search-events] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +cron_schedule = 0 0 * * * +enableSched = 1 +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +search = [search index=_audit sourcetype="audittrail" \"ESCU NOT "index=_audit" | where search !="" | dedup search_id | rex field=search "\"(?.*)\"" | rex field=_raw "user=(?[a-zA-Z0-9_\-]+)" | eval usage=if(savedsearch_name!="", "scheduled", "adhoc") | eval savedsearch_name=if(savedsearch_name != "", savedsearch_name, search_name) | table savedsearch_name search_id user _time usage | outputlookup escu_search_id.csv | table search_id] index=_audit total_run_time event_count result_count NOT "index=_audit" | lookup escu_search_id.csv search_id | stats count(savedsearch_name) AS search_count avg(total_run_time) AS search_avg_run_time sum(total_run_time) AS search_total_run_time sum(result_count) AS search_total_results earliest(_time) AS firsts latest(_time) AS lasts by savedsearch_name user usage| eval first_run=strftime(firsts, "%B %d %Y") | eval last_run=strftime(lasts, "%B %d %Y") + +[escu-metrics-search-longest-runtime] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +enableSched = 1 +cron_schedule = 0 0 * * * +disabled = 1 +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +search = index=_* ESCU [search index=_* action=search latest=-2h earliest=-1d| transaction search_id maxspan=3m | search ESCU | stats values(total_run_time) AS run by search_id | sort -run | head 1| table search_id] | table search search_id + +[escu-metrics-usage-search] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +cron_schedule = 0 0 * * * +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +enableSched = 1 +dispatchAs = user +search = index=_audit sourcetype="audittrail" \ +"ESCU - "\ +`comment("Find all the search names in the audittrail. Ignore the last few minutes so we can exclude this search's text from the result.")`\ +| stats count(search) by search savedsearch_name user\ +| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ +`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ +| rex field=search "\"(?.*)\""\ +`comment("Extract the name of the search from the search string")`\ +| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* + +### END OF USAGE DASHBOARD CONFIGURATIONS ### diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 8e50fabe6a..cc0b0dea71 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -7,21 +7,16 @@ ### ESCU DETECTIONS ### - {% for detection in detections %} [ESCU - {{ detection.name }} - Rule] action.escu = 0 action.escu.enabled = 1 description = {{ detection.description }} -action.escu.mappings = {{ detection.mappings | tojson }} -{% if detection.data_metadata.data_models is defined %} -action.escu.data_models = {{ detection.data_metadata.data_models | tojson }} -{% endif %} -{% if detection.eli5 is defined %} -action.escu.eli5 = {{ detection.eli5 }} -{% else %} -action.escu.eli5 = none +action.escu.mappings = {{ detection.tags | tojson }} +{% if detection.data_model is defined %} +action.escu.data_models = {{ detection.data_model }} {% endif %} +action.escu.eli5 = {{ detection.description }} {% if detection.how_to_implement is defined %} action.escu.how_to_implement = {{ detection.how_to_implement }} {% else %} @@ -32,187 +27,129 @@ action.escu.known_false_positives = {{ detection.known_false_positives }} {% else %} action.escu.known_false_positives = None {% endif %} -action.escu.creation_date = {{ detection.creation_date }} -action.escu.modification_date = {{ detection.modification_date }} -action.escu.confidence = {{ detection.confidence }} +action.escu.creation_date = {{ detection.date }} +action.escu.modification_date = {{ detection.date }} +action.escu.confidence = high action.escu.full_search_name = ESCU - {{ detection.name }} - Rule action.escu.search_type = detection -{% if detection.asset_type is defined %} -action.escu.asset_at_risk = {{ detection.asset_type }} +{% if detection.providing_technologies is defined %} +action.escu.providing_technologies = {{ detection.providing_technologies | tojson }} {% endif %} -{% if detection.entities is defined %} -action.escu.fields_required = {{ detection.entities | tojson }} -action.escu.entities = {{ detection.entities | tojson }} +{% if detection.tags.analytics_story is defined %} +action.escu.analytic_story = {{ detection.tags.analytics_story | tojson }} {% endif %} -{% if detection.data_metadata.providing_technologies is defined %} -action.escu.providing_technologies = {{ detection.data_metadata.providing_technologies | tojson }} -{% endif %} -action.escu.analytic_story = {{ detection.stories | tojson | replace("\\u0026","&") }} -{% if detection.detect.splunk is defined %} -{% set correlation_rule = detection.detect.splunk.correlation_rule %} -{% elif detection.detect.uba is defined %} -{% set correlation_rule = detection.detect.uba.correlation_rule %} -{% endif %} -{% if correlation_rule.schedule.cron_schedule is defined %} -cron_schedule = {{ correlation_rule.schedule.cron_schedule }} -{% endif %} -{% if correlation_rule.schedule.earliest_time is defined %} -dispatch.earliest_time = {{ correlation_rule.schedule.earliest_time }} -{% endif %} -{% if correlation_rule.schedule.latest_time is defined %} -dispatch.latest_time = {{ correlation_rule.schedule.latest_time }} -{% endif %} -{% if correlation_rule is defined %} +cron_schedule = {{ detection.deployment.scheduling.cron_schedule }} +dispatch.earliest_time = {{ detection.deployment.scheduling.earliest_time }} +dispatch.latest_time = {{ detection.deployment.scheduling.latest_time }} action.correlationsearch.enabled = 1 action.correlationsearch.label = {{ detection.name }} -{% if correlation_rule.notable is defined %} +{% if detection.deployment.scheduling.schedule_window is defined %} +schedule_window = {{ detection.deployment.scheduling.schedule_window }} +{% endif %} +{% if detection.deployment.alert_action.notable is defined %} action.notable = 1 +{% if detection.nes_fields is defined %} +action.notable.param.nes_fields = {{ detection.nes_fields }} {% endif %} -{% if correlation_rule.notable.nes_fields is defined %} -action.notable.param.nes_fields = {{ correlation_rule.notable.nes_fields }} -action.notable.param.rule_description = {{ correlation_rule.notable.rule_description }} -action.notable.param.rule_title = {{ correlation_rule.notable.rule_title }} +action.notable.param.rule_description = {{ detection.deployment.alert_action.notable.rule_description | custom_jinja2_enrichment_filter(detection) }} +action.notable.param.rule_title = {{ detection.deployment.alert_action.notable.rule_title | custom_jinja2_enrichment_filter(detection) }} action.notable.param.security_domain = {{ detection.security_domain }} -action.notable.param.severity = {{ detection.confidence }} +action.notable.param.severity = medium {% endif %} -{% if (correlation_rule.notable.drilldown_name is defined) and (correlation_rule.notable.drilldown_search is defined) %} -action.notable.param.drilldown_name = {{ correlation_rule.notable.drilldown_name }} -action.notable.param.drilldown_search = {{ correlation_rule.notable.drilldown_search }} +{% if detection.deployment.alert_action.email is defined %} +action.email.subject.alert = {{ detection.deployment.alert_action.email.subject | custom_jinja2_enrichment_filter(detection) }} +action.email.to = {{ detection.deployment.alert_action.email.to }} +action.email.message.alert = {{ detection.deployment.alert_action.email.message | custom_jinja2_enrichment_filter(detection) }} +action.email.useNSSubject = 1 {% endif %} -{% if correlation_rule.risk is defined %} +{% if detection.deployment.alert_action.risk is defined %} action.risk = 1 -action.risk.param._risk_object = {{ correlation_rule.risk.risk_object }} -action.risk.param._risk_object_type = {{ correlation_rule.risk.risk_object_type[0] }} -action.risk.param._risk_score = {{ correlation_rule.risk.risk_score }} +action.risk.param._risk_object = +action.risk.param._risk_object_type = +action.risk.param._risk_score = action.risk.param.verbose = 0 {% endif %} -{% if correlation_rule.suppress is defined %} -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = {{ correlation_rule.suppress.suppress_fields }} -alert.suppress.period = {{ correlation_rule.suppress.suppress_period }} -{% endif %} -{% endif %} -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -{% if detection.detect.splunk is defined %} -search = {{ detection.detect.splunk.correlation_rule.search }} -{% elif detection.detect.uba is defined %} -search = {{ detection.detect.uba.correlation_rule.search }} -{% endif %} +search = {{ detection.search }} {% endfor %} ### END ESCU DETECTIONS ### -### ESCU INVESTIGATIONS ### - -{% for investigation in investigations %} -{% if investigation.type != 'phantom' %} -[ESCU - {{ investigation.name }}] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - {{ investigation.name }} -description = {{ investigation.description }} -action.escu.creation_date = {{ investigation.creation_date }} -action.escu.modification_date = {{ investigation.modification_date }} -action.escu.analytic_story = {{ investigation.stories | tojson | replace("\\u0026","&") }} -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -{% if investigation.data_metadata.data_models is defined %} -action.escu.data_models = {{ investigation.data_metadata.data_models | tojson }} -{% endif %} -{% if investigation.data_metadata.providing_technologies is defined %} -action.escu.providing_technologies = {{ investigation.data_metadata.providing_technologies | tojson }} -{% endif %} -{% if investigation.eli5 is defined %} -action.escu.eli5 = {{ investigation.eli5 }} -{% else %} -action.escu.eli5 = none -{% endif %} -{% if investigation.how_to_implement is defined %} -action.escu.how_to_implement = {{ investigation.how_to_implement }} -{% else %} -action.escu.how_to_implement = none -{% endif %} -{% if investigation.known_false_positives is defined %} -action.escu.known_false_positives = {{ investigation.known_false_positives }} -{% else %} -action.escu.known_false_positives = None at this time -{% endif %} -{% if investigation.entities is defined %} -action.escu.fields_required = {{ investigation.entities | tojson }} -action.escu.entities = {{ investigation.entities | tojson }} -{% endif %} -disabled = true -schedule_window = auto -is_visible = false -search = {{ investigation.investigate.splunk.search }} - -{% endif %} -{% endfor %} - -### END ESCU INVESTIGATIONS ### - ### ESCU BASELINES ### {% for baseline in baselines %} -[ESCU - {{ baseline.name }}] +[ESCU - {{ baseline.name }} - Baseline] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - {{ baseline.name }} +action.escu.full_search_name = ESCU - {{ baseline.name }} - Baseline description = {{ baseline.description }} -action.escu.creation_date = {{ baseline.creation_date }} -action.escu.modification_date = {{ baseline.modification_date }} -action.escu.analytic_story = {{ baseline.stories | tojson | replace("\\u0026","&") }} -{% if baseline.data_metadata.data_models is defined %} -action.escu.data_models = {{ baseline.data_metadata.data_models | tojson }} +action.escu.creation_date = {{ baseline.date }} +action.escu.modification_date = {{ baseline.date }} +{% if baseline.tags.analytics_story is defined %} +action.escu.analytic_story = {{ baseline.tags.analytics_story | tojson }} {% endif %} -{% if baseline.baseline.splunk.schedule.earliest_time is defined %} -dispatch.earliest_time = {{ baseline.baseline.splunk.schedule.earliest_time }} +{% if baseline.data_model is defined %} +action.escu.data_models = {{ baseline.data_model }} {% endif %} -{% if baseline.baseline.splunk.schedule.latest_time is defined %} -dispatch.latest_time = {{ baseline.baseline.splunk.schedule.latest_time }} +dispatch.earliest_time = {{ baseline.deployment.scheduling.earliest_time }} +dispatch.latest_time = {{ baseline.deployment.scheduling.latest_time }} +{% if baseline.deployment.scheduling.schedule_window is defined %} +schedule_window = {{ baseline.deployment.scheduling.schedule_window }} {% endif %} -{% if baseline.data_metadata.providing_technologies is defined %} -action.escu.providing_technologies = {{ baseline.data_metadata.providing_technologies | tojson }} -{% endif %} -{% if baseline.eli5 is defined %} -action.escu.eli5 = {{ baseline.eli5 }} -{% else %} -action.escu.eli5 = none +{% if baseline.providing_technologies is defined %} +action.escu.providing_technologies = {{ baseline.providing_technologies | tojson }} {% endif %} +action.escu.eli5 = {{ baseline.description }} {% if baseline.how_to_implement is defined %} action.escu.how_to_implement = {{ baseline.how_to_implement }} {% else %} action.escu.how_to_implement = none {% endif %} -{% if baseline.known_false_positives is defined %} -action.escu.known_false_positives = {{ baseline.known_false_positives }} -{% else %} -action.escu.known_false_positives = None at this time +disabled = true +is_visible = false +search = {{ baseline.search }} + +{% endfor %} + + +### ESCU RESPONSE TASKS ### + +{% for response_task in response_tasks %} +{% if response_task.search is defined %} +[ESCU - {{ response_task.name }} - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - {{ response_task.name }} - Response Task +description = {{ response_task.description }} +action.escu.creation_date = {{ response_task.date }} +action.escu.modification_date = {{ response_task.date }} +{% if response_task.tags is defined %} +action.escu.analytic_story = {{ response_task.tags.analytics_story | tojson }} {% endif %} -{% if baseline.entities is defined %} -action.escu.fields_required = {{ baseline.entities | tojson }} -action.escu.entities = {{ baseline.entities | tojson }} +{% if response_task.data_model is defined %} +action.escu.data_models = {{ response_task.data_model }} {% endif %} +action.escu.eli5 = {{ response_task.description }} disabled = true schedule_window = auto is_visible = false -search = {{ baseline.baseline.splunk.search }} +search = {{ response_task.search }} +{% endif %} {% endfor %} + +### END ESCU RESPONSE TASKS ### + ### USAGE DASHBOARD CONFIGURATIONS ### [escu-metrics-usage] diff --git a/bin/jinja2_templates/use_case_library.j2 b/bin/jinja2_templates/use_case_library.j2 index b1e6d06abb..f9af4c57ff 100644 --- a/bin/jinja2_templates/use_case_library.j2 +++ b/bin/jinja2_templates/use_case_library.j2 @@ -9,12 +9,12 @@ {% for story in stories %} [analytic_story://{{ story.name }}] -category = {{ story.category[0] }} -last_updated = {{ story.modification_date }} +category = {{ story.tags.category[0] }} +last_updated = {{ story.date }} version = {{ story.version }} references = {{ story.references | tojson }} -maintainers = {{ story.maintainers | tojson }} -spec_version = {{ story.spec_version }} +maintainers = {{ story.author | tojson }} +spec_version = 3 searches = {{ story.searches | tojson }} description = {{ story.description }} {% if story.narrative is defined %} @@ -30,47 +30,54 @@ narrative = {{ story.narrative }} [savedsearch://ESCU - {{ detection.name }} - Rule] type = detection asset_type = {{ detection.asset_type }} -confidence = {{ detection.confidence }} -explanation = {{ detection.eli5 }} +confidence = medium +explanation = {{ detection.description }} +{% if detection.how_to_implement is defined %} how_to_implement = {{ detection.how_to_implement }} -annotations = {{ detection.mappings | tojson }} +{% else %} +how_to_implement = none +{% endif %} +annotations = {{ detection.tags | tojson }} known_false_positives = {{ detection.known_false_positives }} -providing_technologies = {{ detection.data_metadata.providing_technologies | tojson }} +providing_technologies = none {% endfor %} ### END DETECTIONS ### -### INVESTIGATIONS ### +### RESPONSE TASKS ### -{% for investigation in investigations %} -[savedsearch://ESCU - {{ investigation.name }}] +{% for response_task in response_tasks %} +[savedsearch://ESCU - {{ response_task.name }}] type = investigation explanation = none -how_to_implement = {{ investigation.how_to_implement }} -{% if investigation.known_false_positives is defined %} -known_false_positives = {{ investigation.known_false_positives }} +{% if response_task.how_to_implement is defined %} +how_to_implement = {{ response_task.how_to_implement }} {% else %} -known_false_positives = None at this time -{% endif %} -{% if investigation.investigate.splunk is defined %} -earliest_time_offset = {{ investigation.investigate.splunk.schedule.earliest_time }} -latest_time_offset = {{ investigation.investigate.splunk.schedule.latest_time }} -{% else %} -earliest_time_offset = {{ investigation.investigate.phantom.schedule.earliest_time }} -latest_time_offset = {{ investigation.investigate.phantom.schedule.latest_time }} +how_to_implement = none {% endif %} +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 {% endfor %} -### END INVESTIGATIONS ### +### END RESPONSE TASKS ### ### BASELINES ### {% for baseline in baselines %} [savedsearch://ESCU - {{ baseline.name }}] type = support -explanation = {{ baseline.eli5 }} +explanation = {{ baseline.description }} +{% if baseline.how_to_implement is defined %} how_to_implement = {{ baseline.how_to_implement }} +{% else %} +how_to_implement = none +{% endif %} +{% if baseline.known_false_positives is defined %} known_false_positives = {{ baseline.known_false_positives }} -providing_technologies = {{ baseline.data_metadata.providing_technologies | tojson }} +{% else %} +known_false_positives = not defined +{% endif %} +providing_technologies = none {% endfor %} ### END ESCU BASELINES ### diff --git a/deployments/deployment.yml b/deployments/deployment_example_1.yml similarity index 74% rename from deployments/deployment.yml rename to deployments/deployment_example_1.yml index 202e7d13f3..8305cd78a9 100644 --- a/deployments/deployment.yml +++ b/deployments/deployment_example_1.yml @@ -4,14 +4,17 @@ date: '2020-04-27' description: This configuration file applies to all correlation searches that are used for detection author: Bhavin Patel scheduling: - cron_schedule: '*/10 * * * *' - earliest_time: -10m + cron_schedule: '*/30 * * * *' + earliest_time: -30m latest_time: now schedule_window: auto alert_action: notable: rule_description: '%description%' rule_title: '%name%' + nes_fields: + - user + - dest + - src tags: - analytics_story: - - all + analytics_story: all diff --git a/deployments/deployment_example_2.yml b/deployments/deployment_example_2.yml new file mode 100644 index 0000000000..e6408ab6a8 --- /dev/null +++ b/deployments/deployment_example_2.yml @@ -0,0 +1,17 @@ +name: Enterprise Security deployment configuration +id: bc91a8cd-35e7-4bb2-6140-e756cc46f212 +date: '2020-04-27' +description: This configuration file applies to all correlation searches that are used for detection +author: Bhavin Patel +scheduling: + cron_schedule: '*/60 * * * *' + earliest_time: -60m + latest_time: now + schedule_window: auto +alert_action: + email: + to: 'test@test.de' + subject: 'Splunk Alert: $name$' + message: 'Splunk Alert $name$ triggered' +tags: + mitre_attack_id: T1003 diff --git a/detections/abnormally_high_aws_instances_launched_by_user.yml b/detections/abnormally_high_aws_instances_launched_by_user.yml index 434a322be7..f05085196d 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user.yml @@ -24,8 +24,8 @@ known_false_positives: Many service accounts configured within an AWS infrastruc human user. tags: analytics_story: - - AWS Cryptomining - Suspicious AWS EC2 Activities + - AWS Cryptomining kill_chain_phases: - Actions on Objectives cis20: @@ -34,3 +34,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml index 1db1a242ca..fa51d0eafc 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml @@ -20,8 +20,8 @@ known_false_positives: Many service accounts configured within an AWS infrastruc human user. tags: analytics_story: - - Cloud Cryptomining - Suspicious AWS EC2 Activities + - Cloud Cryptomining kill_chain_phases: - Actions on Objectives cis20: @@ -30,3 +30,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/abnormally_high_aws_instances_terminated_by_user.yml b/detections/abnormally_high_aws_instances_terminated_by_user.yml index 45a459a356..bac36b30da 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user.yml @@ -34,3 +34,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml index 761846b0ab..a367d6f7f9 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml @@ -29,3 +29,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/access_lsass_memory_for_dump_creation.yml b/detections/access_lsass_memory_for_dump_creation.yml index f7e487b83e..0ee95954cb 100644 --- a/detections/access_lsass_memory_for_dump_creation.yml +++ b/detections/access_lsass_memory_for_dump_creation.yml @@ -32,3 +32,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Windows diff --git a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml index e3620f3c57..d2ecb7fc03 100644 --- a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml @@ -15,7 +15,7 @@ search: '`aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!= max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - |`kubernetes_aws_scan_fingerprint_detection` | `amazon_eks_kubernetes_cluster_scan_detection_filter`' + |`kubernetes_aws_scan_fingerprint_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. tags: @@ -24,3 +24,4 @@ tags: kill_chain_phases: - Reconnaissance security_domain: threat + asset_type: Amazon EKS Kubernetes cluster diff --git a/detections/amazon_eks_kubernetes_pod_scan_detection.yml b/detections/amazon_eks_kubernetes_pod_scan_detection.yml index fd4014ebea..0589ed924d 100644 --- a/detections/amazon_eks_kubernetes_pod_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_pod_scan_detection.yml @@ -16,8 +16,7 @@ search: '`aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list o | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_detection` - | `amazon_eks_kubernetes_pod_scan_detection_filter`' + | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. tags: @@ -26,3 +25,4 @@ tags: kill_chain_phases: - Reconnaissance security_domain: threat + asset_type: Amazon EKS Kubernetes cluster Pod diff --git a/detections/attempt_to_add_certificate_to_untrusted_store.yml b/detections/attempt_to_add_certificate_to_untrusted_store.yml index 5b0da8736c..1a65a56c62 100644 --- a/detections/attempt_to_add_certificate_to_untrusted_store.yml +++ b/detections/attempt_to_add_certificate_to_untrusted_store.yml @@ -36,3 +36,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml index 366e7e2ba8..fd95841b2b 100644 --- a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml +++ b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml @@ -24,8 +24,8 @@ known_false_positives: Administrators may attempt to change the default executio be reviewed and investigated as appropriate. tags: analytics_story: - - Malicious PowerShell - Credential Dumping + - Malicious PowerShell mitre_attack_id: - T1086 - T1064 @@ -38,3 +38,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/attempt_to_stop_security_service.yml b/detections/attempt_to_stop_security_service.yml index 6dc53a68c1..205e49f0a0 100644 --- a/detections/attempt_to_stop_security_service.yml +++ b/detections/attempt_to_stop_security_service.yml @@ -43,3 +43,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml index c1f4252c21..bd0cd57c99 100644 --- a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml +++ b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml @@ -33,3 +33,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml index 14bb1c534c..a128e3fb3b 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_city.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_city.yml @@ -42,3 +42,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml index e6b4b525d6..2aba2f4827 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_country.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_country.yml @@ -43,3 +43,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml index aa430af68d..ad43331469 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_ip_address.yml @@ -42,3 +42,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml index 4a7d2faf64..4ae3c4aa77 100644 --- a/detections/aws_cloud_provisioning_from_previously_unseen_region.yml +++ b/detections/aws_cloud_provisioning_from_previously_unseen_region.yml @@ -42,3 +42,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/aws_cross_account_activity_from_previously_unseen_account.yml b/detections/aws_cross_account_activity_from_previously_unseen_account.yml index 739c975d85..9873b76700 100644 --- a/detections/aws_cross_account_activity_from_previously_unseen_account.yml +++ b/detections/aws_cross_account_activity_from_previously_unseen_account.yml @@ -43,3 +43,4 @@ tags: - PR.DS - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/aws_network_access_control_list_created_with_all_open_ports.yml b/detections/aws_network_access_control_list_created_with_all_open_ports.yml index e65dae61cc..8efc7ccc2b 100644 --- a/detections/aws_network_access_control_list_created_with_all_open_ports.yml +++ b/detections/aws_network_access_control_list_created_with_all_open_ports.yml @@ -29,3 +29,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/aws_network_access_control_list_deleted.yml b/detections/aws_network_access_control_list_deleted.yml index 36bcd85d1c..a4afbde38b 100644 --- a/detections/aws_network_access_control_list_deleted.yml +++ b/detections/aws_network_access_control_list_deleted.yml @@ -30,3 +30,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/batch_file_write_to_system32.yml b/detections/batch_file_write_to_system32.yml index 821058fda2..b654a689e7 100644 --- a/detections/batch_file_write_to_system32.yml +++ b/detections/batch_file_write_to_system32.yml @@ -35,3 +35,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/child_processes_of_spoolsv_exe.yml b/detections/child_processes_of_spoolsv_exe.yml index 67b0b6812b..cfcf99aee2 100644 --- a/detections/child_processes_of_spoolsv_exe.yml +++ b/detections/child_processes_of_spoolsv_exe.yml @@ -38,3 +38,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/clients_connecting_to_multiple_dns_servers.yml b/detections/clients_connecting_to_multiple_dns_servers.yml index c97a59781d..31ec5b76f6 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.yml +++ b/detections/clients_connecting_to_multiple_dns_servers.yml @@ -27,10 +27,10 @@ known_false_positives: It's possible that an enterprise has more than five DNS s that are configured in a round-robin rotation. Please customize the search, as appropriate. tags: analytics_story: - - Command and Control - - Host Redirection - - Suspicious DNS Traffic - DNS Hijacking + - Command and Control + - Suspicious DNS Traffic + - Host Redirection mitre_attack_id: - T1048 kill_chain_phases: @@ -44,3 +44,4 @@ tags: - DE.AE - PR.DS security_domain: network + asset_type: Endpoint diff --git a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml index f55bb7696a..07dbaa29f6 100644 --- a/detections/cloud_compute_instance_created_by_previously_unseen_user.yml +++ b/detections/cloud_compute_instance_created_by_previously_unseen_user.yml @@ -31,3 +31,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: Cloud Compute Instance diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml index 070fd04170..000613765e 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml @@ -31,3 +31,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: Cloud Compute Instance diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml index 010bc97d8c..d9fbd474e5 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml @@ -31,3 +31,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: Cloud Compute Instance diff --git a/detections/cloud_compute_instance_started_in_previously_unused_region.yml b/detections/cloud_compute_instance_started_in_previously_unused_region.yml index 9faa684bc3..c17b568fba 100644 --- a/detections/cloud_compute_instance_started_in_previously_unused_region.yml +++ b/detections/cloud_compute_instance_started_in_previously_unused_region.yml @@ -35,3 +35,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: Cloud Compute Instance diff --git a/detections/common_ransomware_extensions.yml b/detections/common_ransomware_extensions.yml index b68ce6903e..b7ea897b2f 100644 --- a/detections/common_ransomware_extensions.yml +++ b/detections/common_ransomware_extensions.yml @@ -35,8 +35,8 @@ known_false_positives: It is possible for a legitimate file with these extension of files created with these extensions. tags: analytics_story: - - Ransomware - SamSam Ransomware + - Ransomware kill_chain_phases: - Actions on Objectives cis20: @@ -45,3 +45,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/common_ransomware_notes.yml b/detections/common_ransomware_notes.yml index da58f66099..a73dd745c8 100644 --- a/detections/common_ransomware_notes.yml +++ b/detections/common_ransomware_notes.yml @@ -21,8 +21,8 @@ known_false_positives: It's possible that a legitimate file could be created wit the same name used by ransomware note files. tags: analytics_story: - - Ransomware - SamSam Ransomware + - Ransomware kill_chain_phases: - Actions on Objectives cis20: @@ -31,3 +31,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/create_local_admin_accounts_using_net_exe.yml b/detections/create_local_admin_accounts_using_net_exe.yml index 0896f239f8..e588eadeae 100644 --- a/detections/create_local_admin_accounts_using_net_exe.yml +++ b/detections/create_local_admin_accounts_using_net_exe.yml @@ -33,3 +33,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/create_or_delete_windows_shares_using_net_exe.yml b/detections/create_or_delete_windows_shares_using_net_exe.yml index 477ffdb504..ea3c23b4cd 100644 --- a/detections/create_or_delete_windows_shares_using_net_exe.yml +++ b/detections/create_or_delete_windows_shares_using_net_exe.yml @@ -34,3 +34,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/create_remote_thread_into_lsass.yml b/detections/create_remote_thread_into_lsass.yml index fcbe72b048..380b6d6eb5 100644 --- a/detections/create_remote_thread_into_lsass.yml +++ b/detections/create_remote_thread_into_lsass.yml @@ -32,3 +32,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Windows diff --git a/detections/creation_of_shadow_copy.yml b/detections/creation_of_shadow_copy.yml index 6b7227b946..cf3cf3bd5c 100644 --- a/detections/creation_of_shadow_copy.yml +++ b/detections/creation_of_shadow_copy.yml @@ -35,3 +35,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml index 72a71e259d..99dd07169e 100644 --- a/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml +++ b/detections/creation_of_shadow_copy_with_wmic_and_powershell.yml @@ -32,3 +32,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml index 9f8c94adf2..99704797b4 100644 --- a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml +++ b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml @@ -33,3 +33,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/credential_dumping_via_symlink_to_shadow_copy.yml b/detections/credential_dumping_via_symlink_to_shadow_copy.yml index ab2a3ffcd8..2fe8fc2cba 100644 --- a/detections/credential_dumping_via_symlink_to_shadow_copy.yml +++ b/detections/credential_dumping_via_symlink_to_shadow_copy.yml @@ -31,3 +31,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/deleting_shadow_copies.yml b/detections/deleting_shadow_copies.yml index f2291425e8..c04ba7e5a8 100644 --- a/detections/deleting_shadow_copies.yml +++ b/detections/deleting_shadow_copies.yml @@ -24,9 +24,9 @@ known_false_positives: vssadmin.exe and wmic.exe are standard applications shipp delete old backup copies, although this is typically rare. tags: analytics_story: - - Ransomware - SamSam Ransomware - Windows Log Manipulation + - Ransomware kill_chain_phases: - Actions on Objectives cis20: @@ -37,3 +37,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_activity_related_to_pass_the_hash_attacks.yml b/detections/detect_activity_related_to_pass_the_hash_attacks.yml index 5778957d0b..dc7b6025cb 100644 --- a/detections/detect_activity_related_to_pass_the_hash_attacks.yml +++ b/detections/detect_activity_related_to_pass_the_hash_attacks.yml @@ -33,3 +33,4 @@ tags: - PR.AC - PR.IP security_domain: access + asset_type: Endpoint diff --git a/detections/detect_api_activity_from_users_without_mfa.yml b/detections/detect_api_activity_from_users_without_mfa.yml index 10473026ba..b113052716 100644 --- a/detections/detect_api_activity_from_users_without_mfa.yml +++ b/detections/detect_api_activity_from_users_without_mfa.yml @@ -53,3 +53,4 @@ tags: - DE.DP - PR.AC security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml index 037e87b10f..9cc94a66ce 100644 --- a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml +++ b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml @@ -19,10 +19,11 @@ known_false_positives: It's possible for legitimate HTTP requests to be made to containing the suspicious paths. tags: analytics_story: - - SamSam Ransomware - JBoss Vulnerability + - SamSam Ransomware mitre_attack_id: - T1082 kill_chain_phases: - Reconnaissance security_domain: network + asset_type: Web Server diff --git a/detections/detect_aws_api_activities_from_unapproved_accounts.yml b/detections/detect_aws_api_activities_from_unapproved_accounts.yml index b45153cf8c..6539c00e6e 100644 --- a/detections/detect_aws_api_activities_from_unapproved_accounts.yml +++ b/detections/detect_aws_api_activities_from_unapproved_accounts.yml @@ -57,3 +57,4 @@ tags: - PR.AC - ID.AM security_domain: access + asset_type: AWS Instance diff --git a/detections/detect_aws_console_login_by_user_from_new_city.yml b/detections/detect_aws_console_login_by_user_from_new_city.yml index 2a3fbbacbe..a3797cc46e 100644 --- a/detections/detect_aws_console_login_by_user_from_new_city.yml +++ b/detections/detect_aws_console_login_by_user_from_new_city.yml @@ -38,3 +38,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_aws_console_login_by_user_from_new_country.yml b/detections/detect_aws_console_login_by_user_from_new_country.yml index cb3b8e4cd5..60fccc3b0a 100644 --- a/detections/detect_aws_console_login_by_user_from_new_country.yml +++ b/detections/detect_aws_console_login_by_user_from_new_country.yml @@ -38,3 +38,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_aws_console_login_by_user_from_new_region.yml b/detections/detect_aws_console_login_by_user_from_new_region.yml index f0ffde2323..47ac42c4f2 100644 --- a/detections/detect_aws_console_login_by_user_from_new_region.yml +++ b/detections/detect_aws_console_login_by_user_from_new_region.yml @@ -38,3 +38,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_credential_dumping_through_LSASS_access.yml b/detections/detect_credential_dumping_through_LSASS_access.yml index 6098117b0f..966c583019 100644 --- a/detections/detect_credential_dumping_through_LSASS_access.yml +++ b/detections/detect_credential_dumping_through_LSASS_access.yml @@ -38,3 +38,4 @@ tags: - PR.AC - DE.CM security_domain: endpoint + asset_type: Windows diff --git a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml index 78c652788f..cc832e4c61 100644 --- a/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml +++ b/detections/detect_dns_requests_to_phishing_sites_leveraging_evilginx2.yml @@ -51,3 +51,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/detect_excessive_account_lockouts_from_endpoint.yml b/detections/detect_excessive_account_lockouts_from_endpoint.yml index 0eba46c700..bc35744147 100644 --- a/detections/detect_excessive_account_lockouts_from_endpoint.yml +++ b/detections/detect_excessive_account_lockouts_from_endpoint.yml @@ -37,3 +37,4 @@ tags: nist: - PR.IP security_domain: access + asset_type: Windows diff --git a/detections/detect_excessive_user_account_lockouts.yml b/detections/detect_excessive_user_account_lockouts.yml index a74b40e69d..65c3bb03d3 100644 --- a/detections/detect_excessive_user_account_lockouts.yml +++ b/detections/detect_excessive_user_account_lockouts.yml @@ -28,3 +28,4 @@ tags: nist: - PR.IP security_domain: access + asset_type: Windows diff --git a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index 259b282ac0..6482e1c848 100644 --- a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -46,8 +46,8 @@ tags: analytics_story: - Prohibited Traffic Allowed or Protocol Mismatch - Command and Control - - Dynamic DNS - Data Protection + - Dynamic DNS - Suspicious DNS Traffic - DNS Hijacking kill_chain_phases: @@ -63,3 +63,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/detect_large_outbound_icmp_packets.yml b/detections/detect_large_outbound_icmp_packets.yml index 74ded5a619..d5f2e70dfb 100644 --- a/detections/detect_large_outbound_icmp_packets.yml +++ b/detections/detect_large_outbound_icmp_packets.yml @@ -45,3 +45,4 @@ tags: nist: - DE.AE security_domain: network + asset_type: Endpoint diff --git a/detections/detect_long_dns_txt_record_response.yml b/detections/detect_long_dns_txt_record_response.yml index f0def88638..12a52379a4 100644 --- a/detections/detect_long_dns_txt_record_response.yml +++ b/detections/detect_long_dns_txt_record_response.yml @@ -28,8 +28,8 @@ known_false_positives: It's possible that legitimate TXT record responses can be to help mitigate false positives. tags: analytics_story: - - Command and Control - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: @@ -44,3 +44,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml index f54a983ac8..ba130244e6 100644 --- a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml +++ b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml @@ -20,8 +20,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: No known false positives for this detection. tags: analytics_story: - - SamSam Ransomware - JBoss Vulnerability + - SamSam Ransomware kill_chain_phases: - Delivery cis20: @@ -36,3 +36,4 @@ tags: - PR.MA - DE.CM security_domain: network + asset_type: Web Server diff --git a/detections/detect_mimikatz_using_loaded_images.yml b/detections/detect_mimikatz_using_loaded_images.yml index c731d67977..df50d775d3 100644 --- a/detections/detect_mimikatz_using_loaded_images.yml +++ b/detections/detect_mimikatz_using_loaded_images.yml @@ -35,3 +35,4 @@ tags: - DE.AE - DE.CM security_domain: endpoint + asset_type: Windows diff --git a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml index 4a7a7bc3a3..cbcdf66cfb 100644 --- a/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml +++ b/detections/detect_mimikatz_via_powershell_and_eventcode_4703.yml @@ -38,3 +38,4 @@ tags: - PR.AC - DE.CM security_domain: access + asset_type: Windows diff --git a/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml index ba5f36d53f..5d592e10d9 100644 --- a/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml +++ b/detections/detect_mshta_exe_running_scripts_in_command_line_arguments.yml @@ -34,3 +34,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_new_api_calls_from_user_roles.yml b/detections/detect_new_api_calls_from_user_roles.yml index 04c6cbb91d..ccba53241e 100644 --- a/detections/detect_new_api_calls_from_user_roles.yml +++ b/detections/detect_new_api_calls_from_user_roles.yml @@ -33,3 +33,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/detect_new_local_admin_account.yml b/detections/detect_new_local_admin_account.yml index a6b3207dfd..4d8279cc53 100644 --- a/detections/detect_new_local_admin_account.yml +++ b/detections/detect_new_local_admin_account.yml @@ -54,3 +54,4 @@ tags: - PR.AC - DE.CM security_domain: access + asset_type: Windows diff --git a/detections/detect_new_login_attempts_to_routers.yml b/detections/detect_new_login_attempts_to_routers.yml index af8ceb7d24..f1a47e286b 100644 --- a/detections/detect_new_login_attempts_to_routers.yml +++ b/detections/detect_new_login_attempts_to_routers.yml @@ -20,7 +20,7 @@ search: '| tstats `security_content_summariesonly` count earliest(_time) as earl known_false_positives: Legitimate router connections may appear as new connections tags: analytics_story: - - Router & Infrastructure Security + - Router and Infrastructure Security kill_chain_phases: - Actions on Objectives cis20: @@ -30,3 +30,4 @@ tags: - PR.AC - PR.IP security_domain: network + asset_type: Endpoint diff --git a/detections/detect_new_open_s3_buckets.yml b/detections/detect_new_open_s3_buckets.yml index 9848dc8128..889947bac6 100644 --- a/detections/detect_new_open_s3_buckets.yml +++ b/detections/detect_new_open_s3_buckets.yml @@ -32,3 +32,4 @@ tags: - PR.AC - DE.CM security_domain: network + asset_type: S3 Bucket diff --git a/detections/detect_new_user_aws_console_login.yml b/detections/detect_new_user_aws_console_login.yml index b4639c2e5f..18071951e4 100644 --- a/detections/detect_new_user_aws_console_login.yml +++ b/detections/detect_new_user_aws_console_login.yml @@ -35,3 +35,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_oulook_exe_writing_a__zip_file.yml b/detections/detect_oulook_exe_writing_a__zip_file.yml index 673dcb8e8d..c7a4375e06 100644 --- a/detections/detect_oulook_exe_writing_a__zip_file.yml +++ b/detections/detect_oulook_exe_writing_a__zip_file.yml @@ -43,3 +43,4 @@ tags: - ID.AM - PR.DS security_domain: network + asset_type: Endpoint diff --git a/detections/detect_outbound_smb_traffic.yml b/detections/detect_outbound_smb_traffic.yml index 3505bfe9ee..598402bc4e 100644 --- a/detections/detect_outbound_smb_traffic.yml +++ b/detections/detect_outbound_smb_traffic.yml @@ -47,3 +47,4 @@ tags: nist: - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/detect_path_interception_by_creation_of_program_exe.yml b/detections/detect_path_interception_by_creation_of_program_exe.yml index 6c920f8f4d..39dcbe18b9 100644 --- a/detections/detect_path_interception_by_creation_of_program_exe.yml +++ b/detections/detect_path_interception_by_creation_of_program_exe.yml @@ -31,3 +31,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: '' diff --git a/detections/detect_processes_used_for_system_network_configuration_discovery.yml b/detections/detect_processes_used_for_system_network_configuration_discovery.yml index 327509b2f5..10b955b026 100644 --- a/detections/detect_processes_used_for_system_network_configuration_discovery.yml +++ b/detections/detect_processes_used_for_system_network_configuration_discovery.yml @@ -36,3 +36,4 @@ tags: - ID.AM - PR.DS security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_prohibited_applications_spawning_cmd_exe.yml b/detections/detect_prohibited_applications_spawning_cmd_exe.yml index 7fe0575b87..94a4c9cb39 100644 --- a/detections/detect_prohibited_applications_spawning_cmd_exe.yml +++ b/detections/detect_prohibited_applications_spawning_cmd_exe.yml @@ -22,8 +22,8 @@ known_false_positives: There are circumstances where an application may legitima the lookup file, as appropriate. tags: analytics_story: - - Suspicious MSHTA Activity - Suspicious Command-Line Executions + - Suspicious MSHTA Activity mitre_attack_id: - T1059 kill_chain_phases: @@ -34,3 +34,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_psexec_with_accepteula_flag.yml b/detections/detect_psexec_with_accepteula_flag.yml index 291d4de5d8..3037846adc 100644 --- a/detections/detect_psexec_with_accepteula_flag.yml +++ b/detections/detect_psexec_with_accepteula_flag.yml @@ -41,3 +41,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_rare_executables.yml b/detections/detect_rare_executables.yml index 853e519c2a..a33667b6b5 100644 --- a/detections/detect_rare_executables.yml +++ b/detections/detect_rare_executables.yml @@ -28,8 +28,8 @@ known_false_positives: Some legitimate processes may be only rarely executed in to filter them out of your search results. tags: analytics_story: + - 'Emotet Malware DHS Report TA18-201A ' - Unusual Processes - - Emotet Malware (DHS Report TA18-201A) kill_chain_phases: - Installation - Command and Control @@ -43,3 +43,4 @@ tags: - PR.DS - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_s3_access_from_a_new_ip.yml b/detections/detect_s3_access_from_a_new_ip.yml index 951ec559d0..0230e522c9 100644 --- a/detections/detect_s3_access_from_a_new_ip.yml +++ b/detections/detect_s3_access_from_a_new_ip.yml @@ -36,3 +36,4 @@ tags: - PR.AC - DE.CM security_domain: network + asset_type: S3 Bucket diff --git a/detections/detect_spike_in_aws_api_activity.yml b/detections/detect_spike_in_aws_api_activity.yml index 6eb14ccd6a..297e860092 100644 --- a/detections/detect_spike_in_aws_api_activity.yml +++ b/detections/detect_spike_in_aws_api_activity.yml @@ -61,3 +61,4 @@ tags: - DE.CM - PR.AC security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml index b3911e3be8..2625d89735 100644 --- a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -42,8 +42,8 @@ known_false_positives: The false-positive rate may vary based on the values of`d tags: analytics_story: - Suspicious AWS Traffic - - Command and Control - AWS Network ACL Activity + - Command and Control kill_chain_phases: - Actions on Objectives - Command and Control @@ -54,3 +54,4 @@ tags: - DE.CM - PR.AC security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_spike_in_network_acl_activity.yml b/detections/detect_spike_in_network_acl_activity.yml index 6ee54ac4a3..b4d7dcb368 100644 --- a/detections/detect_spike_in_network_acl_activity.yml +++ b/detections/detect_spike_in_network_acl_activity.yml @@ -46,3 +46,4 @@ tags: - DE.CM - PR.AC security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_spike_in_s3_bucket_deletion.yml b/detections/detect_spike_in_s3_bucket_deletion.yml index 9df4f6e1a3..ddfd7e1b94 100644 --- a/detections/detect_spike_in_s3_bucket_deletion.yml +++ b/detections/detect_spike_in_s3_bucket_deletion.yml @@ -45,3 +45,4 @@ tags: - DE.CM - PR.AC security_domain: network + asset_type: S3 Bucket diff --git a/detections/detect_spike_in_security_group_activity.yml b/detections/detect_spike_in_security_group_activity.yml index f9bf83686d..92c2cc49ae 100644 --- a/detections/detect_spike_in_security_group_activity.yml +++ b/detections/detect_spike_in_security_group_activity.yml @@ -46,3 +46,4 @@ tags: - DE.CM - PR.AC security_domain: network + asset_type: AWS Instance diff --git a/detections/detect_unauthorized_assets_by_mac_address.yml b/detections/detect_unauthorized_assets_by_mac_address.yml index 40e6c5673b..252c9490af 100644 --- a/detections/detect_unauthorized_assets_by_mac_address.yml +++ b/detections/detect_unauthorized_assets_by_mac_address.yml @@ -39,3 +39,4 @@ tags: - ID.AM - PR.DS security_domain: network + asset_type: Infrastructure diff --git a/detections/detect_usb_device_insertion.yml b/detections/detect_usb_device_insertion.yml index 442ac3db5b..f5da48a4e2 100644 --- a/detections/detect_usb_device_insertion.yml +++ b/detections/detect_usb_device_insertion.yml @@ -36,3 +36,4 @@ tags: - PR.PT - PR.DS security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml index b378d2ada7..37fac4086e 100644 --- a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml @@ -22,8 +22,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: Some legitimate applications may exhibit this behavior. tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - Suspicious Command-Line Executions + - 'Emotet Malware DHS Report TA18-201A ' mitre_attack_id: - T1059 kill_chain_phases: @@ -34,3 +34,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/detect_web_traffic_to_dynamic_domain_providers.yml b/detections/detect_web_traffic_to_dynamic_domain_providers.yml index db40e11824..45b21f753b 100644 --- a/detections/detect_web_traffic_to_dynamic_domain_providers.yml +++ b/detections/detect_web_traffic_to_dynamic_domain_providers.yml @@ -45,3 +45,4 @@ tags: - PR.IP - DE.DP security_domain: network + asset_type: Endpoint diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml index f768c855a9..2027a04314 100644 --- a/detections/detection_of_dns_tunnels.yml +++ b/detections/detection_of_dns_tunnels.yml @@ -40,8 +40,8 @@ known_false_positives: It's possible that normal DNS traffic will exhibit this b tags: analytics_story: - Data Protection - - Command and Control - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: @@ -53,3 +53,4 @@ tags: - PR.PT - PR.DS security_domain: network + asset_type: Endpoint diff --git a/detections/detection_of_tools_built_by_nirsoft.yml b/detections/detection_of_tools_built_by_nirsoft.yml index 31f2e0df3f..64ad0bd294 100644 --- a/detections/detection_of_tools_built_by_nirsoft.yml +++ b/detections/detection_of_tools_built_by_nirsoft.yml @@ -21,7 +21,7 @@ known_false_positives: While legitimate, these NirSoft tools are prone to abuse. should verfiy that the tool was used for a legitimate purpose. tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) + - 'Emotet Malware DHS Report TA18-201A ' mitre_attack_id: - T1072 - T1087 @@ -33,3 +33,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml index 39db71ceff..878a50c013 100644 --- a/detections/disabling_remote_user_account_control.yml +++ b/detections/disabling_remote_user_account_control.yml @@ -21,8 +21,8 @@ known_false_positives: This registry key may be modified via administrators to i a change in system policy. This type of change should be a very rare occurrence. tags: analytics_story: - - Windows Defense Evasion Tactics - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics mitre_attack_id: - T1112 kill_chain_phases: @@ -33,3 +33,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/dns_query_length_outliers___mltk.yml b/detections/dns_query_length_outliers___mltk.yml index ce5415e95b..c06f64e7fe 100644 --- a/detections/dns_query_length_outliers___mltk.yml +++ b/detections/dns_query_length_outliers___mltk.yml @@ -47,9 +47,9 @@ known_false_positives: If you are seeing more results than desired, you may cons the support search to re-build the ML model on the latest data. tags: analytics_story: - - Command and Control - - Suspicious DNS Traffic - Hidden Cobra Malware + - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: @@ -62,3 +62,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/dns_query_length_with_high_standard_deviation.yml b/detections/dns_query_length_with_high_standard_deviation.yml index f0cfbc3c3a..1d658defc6 100644 --- a/detections/dns_query_length_with_high_standard_deviation.yml +++ b/detections/dns_query_length_with_high_standard_deviation.yml @@ -18,9 +18,9 @@ search: '| tstats `security_content_summariesonly` count from datamodel=Network_ known_false_positives: It's possible there can be long domain names that are legitimate. tags: analytics_story: - - Command and Control - - Suspicious DNS Traffic - Hidden Cobra Malware + - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: @@ -33,3 +33,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml index fb086a3021..5f6597a45d 100644 --- a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml +++ b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml @@ -18,10 +18,10 @@ known_false_positives: Legitimate DNS activity can be detected in this search. I verify and update the list of authorized DNS servers as appropriate. tags: analytics_story: - - Command and Control - - Host Redirection - - Suspicious DNS Traffic - DNS Hijacking + - Command and Control + - Suspicious DNS Traffic + - Host Redirection kill_chain_phases: - Command and Control cis20: @@ -36,3 +36,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/dns_record_changed.yml b/detections/dns_record_changed.yml index 389057c1b3..c438de4e70 100644 --- a/detections/dns_record_changed.yml +++ b/detections/dns_record_changed.yml @@ -48,3 +48,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/dump_lsass_via_comsvcs_dll.yml b/detections/dump_lsass_via_comsvcs_dll.yml index 3b04d86a30..4a1800d7b3 100644 --- a/detections/dump_lsass_via_comsvcs_dll.yml +++ b/detections/dump_lsass_via_comsvcs_dll.yml @@ -32,3 +32,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/ec2_instance_modified_with_previously_unseen_user.yml b/detections/ec2_instance_modified_with_previously_unseen_user.yml index d1f164c233..88e2e4f956 100644 --- a/detections/ec2_instance_modified_with_previously_unseen_user.yml +++ b/detections/ec2_instance_modified_with_previously_unseen_user.yml @@ -31,3 +31,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/ec2_instance_started_in_previously_unseen_region.yml b/detections/ec2_instance_started_in_previously_unseen_region.yml index 604c1ade54..eef9f3f3aa 100644 --- a/detections/ec2_instance_started_in_previously_unseen_region.yml +++ b/detections/ec2_instance_started_in_previously_unseen_region.yml @@ -23,8 +23,8 @@ known_false_positives: It's possible that a user has unknowingly started an inst in a new region. Please verify that this activity is legitimate. tags: analytics_story: - - AWS Cryptomining - Suspicious AWS EC2 Activities + - AWS Cryptomining kill_chain_phases: - Actions on Objectives cis20: @@ -33,3 +33,4 @@ tags: - DE.DP - DE.AE security_domain: network + asset_type: AWS Instance diff --git a/detections/ec2_instance_started_with_previously_unseen_ami.yml b/detections/ec2_instance_started_with_previously_unseen_ami.yml index f11876a2a8..6362d82869 100644 --- a/detections/ec2_instance_started_with_previously_unseen_ami.yml +++ b/detections/ec2_instance_started_with_previously_unseen_ami.yml @@ -33,3 +33,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml index b4266ad792..4e7d2a6278 100644 --- a/detections/ec2_instance_started_with_previously_unseen_instance_type.yml +++ b/detections/ec2_instance_started_with_previously_unseen_instance_type.yml @@ -33,3 +33,4 @@ tags: nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/ec2_instance_started_with_previously_unseen_user.yml b/detections/ec2_instance_started_with_previously_unseen_user.yml index 97a400d625..9b4d4bb4a8 100644 --- a/detections/ec2_instance_started_with_previously_unseen_user.yml +++ b/detections/ec2_instance_started_with_previously_unseen_user.yml @@ -25,10 +25,11 @@ known_false_positives: It's possible that a user will start to create EC2 instan launching instances that this is the intended behavior. tags: analytics_story: - - AWS Cryptomining - Suspicious AWS EC2 Activities + - AWS Cryptomining cis20: - CIS 1 nist: - ID.AM security_domain: endpoint + asset_type: AWS Instance diff --git a/detections/email_attachments_with_lots_of_spaces.yml b/detections/email_attachments_with_lots_of_spaces.yml index 631f5d4103..90ffc1cc0d 100644 --- a/detections/email_attachments_with_lots_of_spaces.yml +++ b/detections/email_attachments_with_lots_of_spaces.yml @@ -29,8 +29,8 @@ search: '| tstats `security_content_summariesonly` count values(All_Email.recipi known_false_positives: None at this time tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - Suspicious Emails + - 'Emotet Malware DHS Report TA18-201A ' kill_chain_phases: - Delivery cis20: @@ -38,3 +38,4 @@ tags: nist: - PR.IP security_domain: network + asset_type: Endpoint diff --git a/detections/email_files_written_outside_of_the_outlook_directory.yml b/detections/email_files_written_outside_of_the_outlook_directory.yml index 853fad29d2..4359a698c3 100644 --- a/detections/email_files_written_outside_of_the_outlook_directory.yml +++ b/detections/email_files_written_outside_of_the_outlook_directory.yml @@ -33,3 +33,4 @@ tags: cis20: - CIS 8 security_domain: endpoint + asset_type: Endpoint diff --git a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml index 4732f4101f..ef37865c3b 100644 --- a/detections/email_servers_sending_high_volume_traffic_to_hosts.yml +++ b/detections/email_servers_sending_high_volume_traffic_to_hosts.yml @@ -47,3 +47,4 @@ tags: - DE.CM - DE.AE security_domain: network + asset_type: Endpoint diff --git a/detections/excessive_dns_failures.yml b/detections/excessive_dns_failures.yml index 30843ef83d..d2e6d34058 100644 --- a/detections/excessive_dns_failures.yml +++ b/detections/excessive_dns_failures.yml @@ -21,8 +21,8 @@ known_false_positives: It is possible legitimate traffic can trigger this rule. to better suit your environment. tags: analytics_story: - - Command and Control - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1048 - T1043 @@ -37,3 +37,4 @@ tags: - DE.AE - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/execution_of_file_with_multiple_extensions.yml b/detections/execution_of_file_with_multiple_extensions.yml index 923d92e4ea..cf8be907df 100644 --- a/detections/execution_of_file_with_multiple_extensions.yml +++ b/detections/execution_of_file_with_multiple_extensions.yml @@ -34,3 +34,4 @@ tags: - PR.PT - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/execution_of_file_with_spaces_before_extension.yml b/detections/execution_of_file_with_spaces_before_extension.yml index b9e76a3457..c3f1e0f0af 100644 --- a/detections/execution_of_file_with_spaces_before_extension.yml +++ b/detections/execution_of_file_with_spaces_before_extension.yml @@ -33,3 +33,4 @@ tags: - PR.PT - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/extended_period_without_successful_netbackup_backups.yml b/detections/extended_period_without_successful_netbackup_backups.yml index 7f5d73143e..f7cad2f1dd 100644 --- a/detections/extended_period_without_successful_netbackup_backups.yml +++ b/detections/extended_period_without_successful_netbackup_backups.yml @@ -26,3 +26,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/file_with_samsam_extension.yml b/detections/file_with_samsam_extension.yml index 88a370a3b2..50a2f06b78 100644 --- a/detections/file_with_samsam_extension.yml +++ b/detections/file_with_samsam_extension.yml @@ -31,3 +31,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/first_time_seen_command_line_argument.yml b/detections/first_time_seen_command_line_argument.yml index ad1f7416d4..2d852d46bc 100644 --- a/detections/first_time_seen_command_line_argument.yml +++ b/detections/first_time_seen_command_line_argument.yml @@ -34,11 +34,11 @@ known_false_positives: Legitimate programs can also use command-line arguments t macro to exclude legitimate parent_process_name tags: analytics_story: - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - DHS Report TA18-074A - - Orangeworm Attack Group - Suspicious Command-Line Executions - Hidden Cobra Malware + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - DHS Report TA18-074A mitre_attack_id: - T1064 - T1059 @@ -53,3 +53,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/first_time_seen_running_windows_service.yml b/detections/first_time_seen_running_windows_service.yml index 7b11d0e497..7700039828 100644 --- a/detections/first_time_seen_running_windows_service.yml +++ b/detections/first_time_seen_running_windows_service.yml @@ -27,8 +27,8 @@ known_false_positives: A previously unseen service is not necessarily malicious. that the service is legitimate and that was installed by a legitimate process. tags: analytics_story: - - Orangeworm Attack Group - Windows Service Abuse + - Orangeworm Attack Group mitre_attack_id: - T1050 kill_chain_phases: @@ -43,3 +43,4 @@ tags: - PR.AC - DE.AE security_domain: endpoint + asset_type: Endpoint diff --git a/detections/gcp_gcr_container_uploaded.yml b/detections/gcp_gcr_container_uploaded.yml index 9d1bcb910a..644853ecc0 100644 --- a/detections/gcp_gcr_container_uploaded.yml +++ b/detections/gcp_gcr_container_uploaded.yml @@ -22,5 +22,6 @@ known_false_positives: Uploading container is a normal behavior from developers creation which automatically generates a bucket entry for destination path. tags: analytics_story: - - Container Implantation Monitoring & Investigation + - Container Implantation Monitoring and Investigation security_domain: threat + asset_type: GCP GCR Container diff --git a/detections/gcp_kubernetes_cluster_scan_detection.yml b/detections/gcp_kubernetes_cluster_scan_detection.yml index 711d7ac6ec..f401f97e3b 100644 --- a/detections/gcp_kubernetes_cluster_scan_detection.yml +++ b/detections/gcp_kubernetes_cluster_scan_detection.yml @@ -19,7 +19,7 @@ search: '`google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp! values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | - `kubernetes_gcp_scan_fingerprint_detection` | `gcp_kubernetes_cluster_scan_detection_filter`' + `kubernetes_gcp_scan_fingerprint_filter`' known_false_positives: Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. tags: @@ -28,3 +28,4 @@ tags: kill_chain_phases: - Reconnaissance security_domain: threat + asset_type: GCP Kubernetes cluster diff --git a/detections/hiding_files_and_directories_with_attrib_exe.yml b/detections/hiding_files_and_directories_with_attrib_exe.yml index 907b3c5627..355b7e2e7b 100644 --- a/detections/hiding_files_and_directories_with_attrib_exe.yml +++ b/detections/hiding_files_and_directories_with_attrib_exe.yml @@ -32,3 +32,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: '' diff --git a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml index bede8665ed..faaf133bf6 100644 --- a/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml +++ b/detections/hosts_receiving_high_volume_of_network_traffic_from_email_server.yml @@ -46,3 +46,4 @@ tags: - DE.CM - DE.AE security_domain: network + asset_type: Endpoint diff --git a/detections/identify_new_user_accounts.yml b/detections/identify_new_user_accounts.yml index 43f2347468..3e287d1e8c 100644 --- a/detections/identify_new_user_accounts.yml +++ b/detections/identify_new_user_accounts.yml @@ -28,3 +28,4 @@ tags: nist: - PR.IP security_domain: access + asset_type: Domain Server diff --git a/detections/large_volume_of_dns_any_queries.yml b/detections/large_volume_of_dns_any_queries.yml index e99fdd044e..d480bab82b 100644 --- a/detections/large_volume_of_dns_any_queries.yml +++ b/detections/large_volume_of_dns_any_queries.yml @@ -28,3 +28,4 @@ tags: - DE.AE - PR.IP security_domain: network + asset_type: DNS Servers diff --git a/detections/macos___re_opened_applications.yml b/detections/macos___re_opened_applications.yml index 3f3f919250..8174060ca0 100644 --- a/detections/macos___re_opened_applications.yml +++ b/detections/macos___re_opened_applications.yml @@ -34,3 +34,4 @@ tags: - DE.DP - DE.CM security_domain: threat + asset_type: Endpoint diff --git a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml index d83e78416b..c1b4b686bc 100644 --- a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml +++ b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml @@ -43,3 +43,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/malicious_powershell_process___encoded_command.yml b/detections/malicious_powershell_process___encoded_command.yml index 829dbf65a7..f3351b5136 100644 --- a/detections/malicious_powershell_process___encoded_command.yml +++ b/detections/malicious_powershell_process___encoded_command.yml @@ -38,3 +38,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/malicious_powershell_process___execution_policy_bypass.yml b/detections/malicious_powershell_process___execution_policy_bypass.yml index 5db36c560e..11e12bdc54 100644 --- a/detections/malicious_powershell_process___execution_policy_bypass.yml +++ b/detections/malicious_powershell_process___execution_policy_bypass.yml @@ -41,3 +41,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml index 4ff1b7b109..0839c9c547 100644 --- a/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml +++ b/detections/malicious_powershell_process___multiple_suspicious_command_line_arguments.yml @@ -43,3 +43,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/malicious_powershell_process_with_obfuscation_techniques.yml b/detections/malicious_powershell_process_with_obfuscation_techniques.yml index 550d46e6b1..83c33bfc2d 100644 --- a/detections/malicious_powershell_process_with_obfuscation_techniques.yml +++ b/detections/malicious_powershell_process_with_obfuscation_techniques.yml @@ -40,3 +40,4 @@ tags: - DE.CM - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/monitor_dns_for_brand_abuse.yml b/detections/monitor_dns_for_brand_abuse.yml index 2679e358b8..6176c2b120 100644 --- a/detections/monitor_dns_for_brand_abuse.yml +++ b/detections/monitor_dns_for_brand_abuse.yml @@ -25,3 +25,4 @@ tags: - Delivery - Actions on Objectives security_domain: network + asset_type: Endpoint diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml index b013646fec..7889964dfc 100644 --- a/detections/monitor_email_for_brand_abuse.yml +++ b/detections/monitor_email_for_brand_abuse.yml @@ -21,8 +21,8 @@ search: '| tstats `security_content_summariesonly` values(All_Email.recipient) a known_false_positives: None at this time tags: analytics_story: - - Brand Monitoring - Suspicious Emails + - Brand Monitoring kill_chain_phases: - Delivery cis20: @@ -30,3 +30,4 @@ tags: nist: - PR.IP security_domain: network + asset_type: Endpoint diff --git a/detections/monitor_registry_keys_for_print_monitors.yml b/detections/monitor_registry_keys_for_print_monitors.yml index 33b1dd3202..dad8911dab 100644 --- a/detections/monitor_registry_keys_for_print_monitors.yml +++ b/detections/monitor_registry_keys_for_print_monitors.yml @@ -37,3 +37,4 @@ tags: - DE.CM - PR.AC security_domain: endpoint + asset_type: Endpoint diff --git a/detections/monitor_web_traffic_for_brand_abuse.yml b/detections/monitor_web_traffic_for_brand_abuse.yml index 7455e68ccf..0386c2f7fb 100644 --- a/detections/monitor_web_traffic_for_brand_abuse.yml +++ b/detections/monitor_web_traffic_for_brand_abuse.yml @@ -25,3 +25,4 @@ tags: nist: - PR.IP security_domain: network + asset_type: Endpoint diff --git a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml index ffcb72b358..a475592a7a 100644 --- a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml +++ b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml @@ -28,3 +28,4 @@ tags: nist: - DE.CM security_domain: access + asset_type: Infrastructure diff --git a/detections/new_container_uploaded_to_aws_ecr.yml b/detections/new_container_uploaded_to_aws_ecr.yml index e8fe98195f..5c370a47ad 100644 --- a/detections/new_container_uploaded_to_aws_ecr.yml +++ b/detections/new_container_uploaded_to_aws_ecr.yml @@ -21,5 +21,6 @@ known_false_positives: Uploading container is a normal behavior from developers users with access to container registry. tags: analytics_story: - - Container Implantation Monitoring & Investigation + - Container Implantation Monitoring and Investigation security_domain: threat + asset_type: AWS ECR container diff --git a/detections/no_windows_updates_in_a_time_frame.yml b/detections/no_windows_updates_in_a_time_frame.yml index 2b1366890b..679b7cd72e 100644 --- a/detections/no_windows_updates_in_a_time_frame.yml +++ b/detections/no_windows_updates_in_a_time_frame.yml @@ -33,3 +33,4 @@ tags: - PR.PT - PR.MA security_domain: endpoint + asset_type: Endpoint diff --git a/detections/okta_account_lockout_events.yml b/detections/okta_account_lockout_events.yml index ec2e0264a1..caa7f00a7e 100644 --- a/detections/okta_account_lockout_events.yml +++ b/detections/okta_account_lockout_events.yml @@ -23,3 +23,4 @@ tags: nist: - DE.CM security_domain: access + asset_type: Infrastructure diff --git a/detections/okta_failed_sso_attempts.yml b/detections/okta_failed_sso_attempts.yml index 47caee3b3d..3ff2cbae70 100644 --- a/detections/okta_failed_sso_attempts.yml +++ b/detections/okta_failed_sso_attempts.yml @@ -22,3 +22,4 @@ tags: nist: - DE.CM security_domain: access + asset_type: Infrastructure diff --git a/detections/okta_user_logins_from_multiple_cities.yml b/detections/okta_user_logins_from_multiple_cities.yml index c355f68000..b2257e06f6 100644 --- a/detections/okta_user_logins_from_multiple_cities.yml +++ b/detections/okta_user_logins_from_multiple_cities.yml @@ -29,3 +29,4 @@ tags: nist: - DE.CM security_domain: access + asset_type: Infrastructure diff --git a/detections/open_redirect_in_splunk_web.yml b/detections/open_redirect_in_splunk_web.yml index ba7ab0d8fc..ed789747a8 100644 --- a/detections/open_redirect_in_splunk_web.yml +++ b/detections/open_redirect_in_splunk_web.yml @@ -27,3 +27,4 @@ tags: - PR.IP - DE.CM security_domain: network + asset_type: Splunk Server diff --git a/detections/osquery_pack___coldroot_detection.yml b/detections/osquery_pack___coldroot_detection.yml index 409b611ae0..1f690d96a4 100644 --- a/detections/osquery_pack___coldroot_detection.yml +++ b/detections/osquery_pack___coldroot_detection.yml @@ -29,3 +29,4 @@ tags: - DE.CM - PR.PT security_domain: threat + asset_type: Endpoint diff --git a/detections/overwriting_accessibility_binaries.yml b/detections/overwriting_accessibility_binaries.yml index be36fd0f99..db72c64b64 100644 --- a/detections/overwriting_accessibility_binaries.yml +++ b/detections/overwriting_accessibility_binaries.yml @@ -36,3 +36,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/process_execution_via_wmi.yml b/detections/process_execution_via_wmi.yml index de1d2b1346..4c99e5d204 100644 --- a/detections/process_execution_via_wmi.yml +++ b/detections/process_execution_via_wmi.yml @@ -33,3 +33,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/processes_created_by_netsh.yml b/detections/processes_created_by_netsh.yml index 3ad4e38743..bc4fffaad1 100644 --- a/detections/processes_created_by_netsh.yml +++ b/detections/processes_created_by_netsh.yml @@ -37,3 +37,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/processes_launching_netsh.yml b/detections/processes_launching_netsh.yml index f2f2c9f80f..2389e2b249 100644 --- a/detections/processes_launching_netsh.yml +++ b/detections/processes_launching_netsh.yml @@ -23,9 +23,9 @@ known_false_positives: Some VPN applications are known to launch netsh.exe. Outs commands. tags: analytics_story: - - Disabling Security Tools - DHS Report TA18-074A - Netsh Abuse + - Disabling Security Tools mitre_attack_id: - T1059 - T1089 @@ -37,3 +37,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/processes_tapping_keyboard_events.yml b/detections/processes_tapping_keyboard_events.yml index 98266326a8..7b6754c43a 100644 --- a/detections/processes_tapping_keyboard_events.yml +++ b/detections/processes_tapping_keyboard_events.yml @@ -32,3 +32,4 @@ tags: nist: - DE.DP security_domain: threat + asset_type: Endpoint diff --git a/detections/prohibited_network_traffic_allowed.yml b/detections/prohibited_network_traffic_allowed.yml index b3c639bfeb..3b40caf45c 100644 --- a/detections/prohibited_network_traffic_allowed.yml +++ b/detections/prohibited_network_traffic_allowed.yml @@ -23,9 +23,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Ransomware - - Command and Control - Prohibited Traffic Allowed or Protocol Mismatch + - Command and Control + - Ransomware mitre_attack_id: - T1043 - T1048 @@ -39,3 +39,4 @@ tags: - DE.AE - PR.AC security_domain: network + asset_type: Endpoint diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index e450979f56..3ad55dfe4e 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -24,9 +24,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Monitor for Unauthorized Software - - Emotet Malware (DHS Report TA18-201A) - SamSam Ransomware + - Monitor for Unauthorized Software + - 'Emotet Malware DHS Report TA18-201A ' kill_chain_phases: - Installation - Command and Control @@ -37,3 +37,4 @@ tags: - ID.AM - PR.DS security_domain: endpoint + asset_type: Endpoint diff --git a/detections/protocol_or_port_mismatch.yml b/detections/protocol_or_port_mismatch.yml index acb7c7eac2..0753a62007 100644 --- a/detections/protocol_or_port_mismatch.yml +++ b/detections/protocol_or_port_mismatch.yml @@ -39,3 +39,4 @@ tags: - DE.AE - PR.AC security_domain: network + asset_type: Endpoint diff --git a/detections/protocols_passing_authentication_in_cleartext.yml b/detections/protocols_passing_authentication_in_cleartext.yml index a758d28e42..cfd0b0f36f 100644 --- a/detections/protocols_passing_authentication_in_cleartext.yml +++ b/detections/protocols_passing_authentication_in_cleartext.yml @@ -34,3 +34,4 @@ tags: - PR.AC - PR.DS security_domain: network + asset_type: Endpoint diff --git a/detections/reg_exe_manipulating_windows_services_registry_keys.yml b/detections/reg_exe_manipulating_windows_services_registry_keys.yml index f40fee03d3..7c0e571f7e 100644 --- a/detections/reg_exe_manipulating_windows_services_registry_keys.yml +++ b/detections/reg_exe_manipulating_windows_services_registry_keys.yml @@ -44,3 +44,4 @@ tags: - PR.AT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml index bf889661bd..ffe1f5b930 100644 --- a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml +++ b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml @@ -21,8 +21,8 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as known_false_positives: None at the moment tags: analytics_story: - - Windows Defense Evasion Tactics - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives @@ -31,3 +31,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: '' diff --git a/detections/registry_keys_for_creating_shim_databases.yml b/detections/registry_keys_for_creating_shim_databases.yml index d05f61cc01..62cf67b895 100644 --- a/detections/registry_keys_for_creating_shim_databases.yml +++ b/detections/registry_keys_for_creating_shim_databases.yml @@ -33,3 +33,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml index bfe5ef5936..151f418418 100644 --- a/detections/registry_keys_used_for_persistence.yml +++ b/detections/registry_keys_used_for_persistence.yml @@ -29,11 +29,11 @@ tags: analytics_story: - Suspicious Windows Registry Activities - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Suspicious MSHTA Activity - - Emotet Malware (DHS Report TA18-201A) - - Ransomware - DHS Report TA18-074A + - Suspicious MSHTA Activity - Windows Persistence Techniques + - 'Emotet Malware DHS Report TA18-201A ' + - Ransomware mitre_attack_id: - T1103 - T1131 @@ -46,3 +46,4 @@ tags: - DE.CM - DE.AE security_domain: endpoint + asset_type: Endpoint diff --git a/detections/registry_keys_used_for_privilege_escalation.yml b/detections/registry_keys_used_for_privilege_escalation.yml index 10ddb58347..9b942e63ca 100644 --- a/detections/registry_keys_used_for_privilege_escalation.yml +++ b/detections/registry_keys_used_for_privilege_escalation.yml @@ -26,8 +26,8 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Windows Privilege Escalation - Suspicious Windows Registry Activities + - Windows Privilege Escalation mitre_attack_id: - T1015 kill_chain_phases: @@ -38,3 +38,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/remote_desktop_network_bruteforce.yml b/detections/remote_desktop_network_bruteforce.yml index 480bfaa6c5..bcc3efb903 100644 --- a/detections/remote_desktop_network_bruteforce.yml +++ b/detections/remote_desktop_network_bruteforce.yml @@ -35,3 +35,4 @@ tags: - PR.AC - PR.IP security_domain: network + asset_type: Endpoint diff --git a/detections/remote_desktop_network_traffic.yml b/detections/remote_desktop_network_traffic.yml index 98ff98989b..5e51ba07fc 100644 --- a/detections/remote_desktop_network_traffic.yml +++ b/detections/remote_desktop_network_traffic.yml @@ -27,8 +27,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Remote Desktop may be used legitimately by users on the network. tags: analytics_story: - - SamSam Ransomware - Hidden Cobra Malware + - SamSam Ransomware - Lateral Movement mitre_attack_id: - T1076 @@ -43,3 +43,4 @@ tags: - PR.AC - PR.IP security_domain: network + asset_type: Endpoint diff --git a/detections/remote_desktop_process_running_on_system.yml b/detections/remote_desktop_process_running_on_system.yml index fb9eaccb95..180761501a 100644 --- a/detections/remote_desktop_process_running_on_system.yml +++ b/detections/remote_desktop_process_running_on_system.yml @@ -40,3 +40,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/remote_process_instantiation_via_wmi.yml b/detections/remote_process_instantiation_via_wmi.yml index 2806df701d..818d03ffb5 100644 --- a/detections/remote_process_instantiation_via_wmi.yml +++ b/detections/remote_process_instantiation_via_wmi.yml @@ -23,8 +23,8 @@ known_false_positives: The wmic.exe utility is a benign Windows application. It but it's relatively uncommon. tags: analytics_story: - - Ransomware - Suspicious WMI Use + - Ransomware mitre_attack_id: - T1047 kill_chain_phases: @@ -38,3 +38,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml index 2d4d896985..5617b11ce0 100644 --- a/detections/remote_registry_key_modifications.yml +++ b/detections/remote_registry_key_modifications.yml @@ -20,8 +20,8 @@ known_false_positives: This technique may be legitimately used by administrators modify remote registries, so it's important to filter these events out. tags: analytics_story: - - Windows Defense Evasion Tactics - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives @@ -31,3 +31,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/remote_wmi_command_attempt.yml b/detections/remote_wmi_command_attempt.yml index b6359fe5b0..b7b1e87801 100644 --- a/detections/remote_wmi_command_attempt.yml +++ b/detections/remote_wmi_command_attempt.yml @@ -36,3 +36,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/rundll_loading_dll_by_ordinal.yml b/detections/rundll_loading_dll_by_ordinal.yml index d2d1f405ef..c1916199b0 100644 --- a/detections/rundll_loading_dll_by_ordinal.yml +++ b/detections/rundll_loading_dll_by_ordinal.yml @@ -37,3 +37,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/samsam_test_file_write.yml b/detections/samsam_test_file_write.yml index b017460a4b..4e7b278bb3 100644 --- a/detections/samsam_test_file_write.yml +++ b/detections/samsam_test_file_write.yml @@ -28,3 +28,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/sc_exe_manipulating_windows_services.yml b/detections/sc_exe_manipulating_windows_services.yml index 969072b97e..907ed5dce3 100644 --- a/detections/sc_exe_manipulating_windows_services.yml +++ b/detections/sc_exe_manipulating_windows_services.yml @@ -23,11 +23,11 @@ known_false_positives: Using sc.exe to manipulate Windows services is uncommon. and investigate as appropriate. tags: analytics_story: - - Disabling Security Tools - Windows Service Abuse - - DHS Report TA18-074A - Orangeworm Attack Group + - DHS Report TA18-074A - Windows Persistence Techniques + - Disabling Security Tools mitre_attack_id: - T1050 - T1031 @@ -45,3 +45,4 @@ tags: - PR.AT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml index c1a734dc70..6e54577073 100644 --- a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml +++ b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml @@ -31,3 +31,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml index 5f45878a8b..7e9a7e8efe 100644 --- a/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml +++ b/detections/scheduled_tasks_used_in_badrabbit_ransomware.yml @@ -32,3 +32,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/schtasks_scheduling_job_on_remote_system.yml b/detections/schtasks_scheduling_job_on_remote_system.yml index d3f83a6b7b..5c614d7dd1 100644 --- a/detections/schtasks_scheduling_job_on_remote_system.yml +++ b/detections/schtasks_scheduling_job_on_remote_system.yml @@ -33,3 +33,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/schtasks_used_for_forcing_a_reboot.yml b/detections/schtasks_used_for_forcing_a_reboot.yml index 8ac57a0d54..f4df93b592 100644 --- a/detections/schtasks_used_for_forcing_a_reboot.yml +++ b/detections/schtasks_used_for_forcing_a_reboot.yml @@ -20,8 +20,8 @@ known_false_positives: Administrators may create jobs on systems forcing reboots perform updates, maintenance, etc. tags: analytics_story: - - Ransomware - Windows Persistence Techniques + - Ransomware mitre_attack_id: - T1053 kill_chain_phases: @@ -31,3 +31,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/script_execution_via_wmi.yml b/detections/script_execution_via_wmi.yml index ca958e579f..92dbb789fe 100644 --- a/detections/script_execution_via_wmi.yml +++ b/detections/script_execution_via_wmi.yml @@ -33,3 +33,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/shim_database_file_creation.yml b/detections/shim_database_file_creation.yml index bc423cc71d..6f88619b37 100644 --- a/detections/shim_database_file_creation.yml +++ b/detections/shim_database_file_creation.yml @@ -34,3 +34,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/shim_database_installation_with_suspicious_parameters.yml b/detections/shim_database_installation_with_suspicious_parameters.yml index c8b0d30842..dfdffc0195 100644 --- a/detections/shim_database_installation_with_suspicious_parameters.yml +++ b/detections/shim_database_installation_with_suspicious_parameters.yml @@ -34,3 +34,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/short_lived_windows_accounts.yml b/detections/short_lived_windows_accounts.yml index 79eff943a1..ed209295c9 100644 --- a/detections/short_lived_windows_accounts.yml +++ b/detections/short_lived_windows_accounts.yml @@ -29,3 +29,4 @@ tags: nist: - PR.IP security_domain: access + asset_type: Windows diff --git a/detections/single_letter_process_on_endpoint.yml b/detections/single_letter_process_on_endpoint.yml index a418452e58..0083898f8e 100644 --- a/detections/single_letter_process_on_endpoint.yml +++ b/detections/single_letter_process_on_endpoint.yml @@ -31,3 +31,4 @@ tags: - ID.AM - PR.DS security_domain: endpoint + asset_type: Endpoint diff --git a/detections/smb_traffic_spike.yml b/detections/smb_traffic_spike.yml index 48e9dd49ee..eca96d7fa9 100644 --- a/detections/smb_traffic_spike.yml +++ b/detections/smb_traffic_spike.yml @@ -21,10 +21,10 @@ known_false_positives: A file server may experience high-demand loads that could this analytic to trigger. tags: analytics_story: - - Ransomware - DHS Report TA18-074A - - Emotet Malware (DHS Report TA18-201A) - Hidden Cobra Malware + - Ransomware + - 'Emotet Malware DHS Report TA18-201A ' mitre_attack_id: - T1043 kill_chain_phases: @@ -34,3 +34,4 @@ tags: nist: - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/smb_traffic_spike___mltk.yml b/detections/smb_traffic_spike___mltk.yml index 4e7adbeac7..ab30cefe0d 100644 --- a/detections/smb_traffic_spike___mltk.yml +++ b/detections/smb_traffic_spike___mltk.yml @@ -42,10 +42,10 @@ known_false_positives: If you are seeing more results than desired, you may cons the `smb_traffic_spike_mltk_filter` macro to filter out false positive results tags: analytics_story: - - Ransomware - DHS Report TA18-074A - - Emotet Malware (DHS Report TA18-201A) - Hidden Cobra Malware + - Ransomware + - 'Emotet Malware DHS Report TA18-201A ' mitre_attack_id: - T1043 kill_chain_phases: @@ -55,3 +55,4 @@ tags: nist: - DE.CM security_domain: network + asset_type: Endpoint diff --git a/detections/spectre_and_meltdown_vulnerable_systems.yml b/detections/spectre_and_meltdown_vulnerable_systems.yml index 2865b9fe4e..07973b75f7 100644 --- a/detections/spectre_and_meltdown_vulnerable_systems.yml +++ b/detections/spectre_and_meltdown_vulnerable_systems.yml @@ -27,3 +27,4 @@ tags: - PR.IP - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/spike_in_file_writes.yml b/detections/spike_in_file_writes.yml index 2c41c68109..80838301a0 100644 --- a/detections/spike_in_file_writes.yml +++ b/detections/spike_in_file_writes.yml @@ -24,8 +24,8 @@ known_false_positives: It is important to understand that if you happen to insta expect to see a large increase of file modifications. tags: analytics_story: - - Ransomware - SamSam Ransomware + - Ransomware kill_chain_phases: - Actions on Objectives cis20: @@ -33,3 +33,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/splunk_enterprise_information_disclosure.yml b/detections/splunk_enterprise_information_disclosure.yml index b9f897c7f5..f7cc9124d7 100644 --- a/detections/splunk_enterprise_information_disclosure.yml +++ b/detections/splunk_enterprise_information_disclosure.yml @@ -34,3 +34,4 @@ tags: - PR.IP - DE.CM security_domain: network + asset_type: Splunk Server diff --git a/detections/sql_injection_with_long_urls.yml b/detections/sql_injection_with_long_urls.yml index 9437718f75..1a26a9de54 100644 --- a/detections/sql_injection_with_long_urls.yml +++ b/detections/sql_injection_with_long_urls.yml @@ -46,3 +46,4 @@ tags: - PR.IP - DE.CM security_domain: network + asset_type: Database Server diff --git a/detections/suspicious_changes_to_file_associations.yml b/detections/suspicious_changes_to_file_associations.yml index b64a9965c8..83b40ca76d 100644 --- a/detections/suspicious_changes_to_file_associations.yml +++ b/detections/suspicious_changes_to_file_associations.yml @@ -40,3 +40,4 @@ tags: - PR.PT - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/suspicious_email___uba_anomaly.yml b/detections/suspicious_email___uba_anomaly.yml index 4d6b270c68..c4fb996355 100644 --- a/detections/suspicious_email___uba_anomaly.yml +++ b/detections/suspicious_email___uba_anomaly.yml @@ -32,3 +32,4 @@ tags: nist: - PR.IP security_domain: threat + asset_type: Endpoint diff --git a/detections/suspicious_email_attachment_extensions.yml b/detections/suspicious_email_attachment_extensions.yml index 44e61e9f60..0310826406 100644 --- a/detections/suspicious_email_attachment_extensions.yml +++ b/detections/suspicious_email_attachment_extensions.yml @@ -26,8 +26,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Emotet Malware (DHS Report TA18-201A) - Suspicious Emails + - 'Emotet Malware DHS Report TA18-201A ' kill_chain_phases: - Delivery cis20: @@ -38,3 +38,4 @@ tags: - DE.AE - PR.IP security_domain: network + asset_type: Endpoint diff --git a/detections/suspicious_file_write.yml b/detections/suspicious_file_write.yml index f48d2cba72..f833cc9b00 100644 --- a/detections/suspicious_file_write.yml +++ b/detections/suspicious_file_write.yml @@ -37,3 +37,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/suspicious_java_classes.yml b/detections/suspicious_java_classes.yml index 401673b887..f490f00a6e 100644 --- a/detections/suspicious_java_classes.yml +++ b/detections/suspicious_java_classes.yml @@ -28,3 +28,4 @@ tags: nist: - DE.AE security_domain: threat + asset_type: Endpoint diff --git a/detections/suspicious_lnk_file_launching_a_process.yml b/detections/suspicious_lnk_file_launching_a_process.yml index bde03bf9c1..b500f5f9fe 100644 --- a/detections/suspicious_lnk_file_launching_a_process.yml +++ b/detections/suspicious_lnk_file_launching_a_process.yml @@ -40,3 +40,4 @@ tags: - ID.AM - PR.DS security_domain: network + asset_type: Endpoint diff --git a/detections/suspicious_reg_exe_process.yml b/detections/suspicious_reg_exe_process.yml index 39c8f2d9b6..f5eb5eba62 100644 --- a/detections/suspicious_reg_exe_process.yml +++ b/detections/suspicious_reg_exe_process.yml @@ -29,9 +29,9 @@ known_false_positives: It's possible for system administrators to write scripts to filter them out. tags: analytics_story: - - Disabling Security Tools - - Windows Defense Evasion Tactics - DHS Report TA18-074A + - Windows Defense Evasion Tactics + - Disabling Security Tools mitre_attack_id: - T1112 - T1089 @@ -42,3 +42,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/suspicious_wevtutil_usage.yml b/detections/suspicious_wevtutil_usage.yml index a7f4b19614..a918308805 100644 --- a/detections/suspicious_wevtutil_usage.yml +++ b/detections/suspicious_wevtutil_usage.yml @@ -24,8 +24,8 @@ known_false_positives: The wevtutil.exe application is a legitimate Windows even log utility. Administrators may use it to manage Windows event logs. tags: analytics_story: - - Ransomware - Windows Log Manipulation + - Ransomware mitre_attack_id: - T1070 kill_chain_phases: @@ -42,3 +42,4 @@ tags: - PR.AT - DE.AE security_domain: endpoint + asset_type: '' diff --git a/detections/suspicious_writes_to_system_volume_information.yml b/detections/suspicious_writes_to_system_volume_information.yml index d87ab4a645..9e26d06a6f 100644 --- a/detections/suspicious_writes_to_system_volume_information.yml +++ b/detections/suspicious_writes_to_system_volume_information.yml @@ -27,3 +27,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Windows diff --git a/detections/suspicious_writes_to_windows_recycle_bin.yml b/detections/suspicious_writes_to_windows_recycle_bin.yml index 9123f3b99d..640a86e13c 100644 --- a/detections/suspicious_writes_to_windows_recycle_bin.yml +++ b/detections/suspicious_writes_to_windows_recycle_bin.yml @@ -32,3 +32,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Windows diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index 289a851d25..4e7d43fa11 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -20,9 +20,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Unusual Processes - - Ransomware - Suspicious Command-Line Executions + - Ransomware + - Unusual Processes mitre_attack_id: - T1036 kill_chain_phases: @@ -33,3 +33,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/tor_traffic.yml b/detections/tor_traffic.yml index e1af52cddf..2ee6aba830 100644 --- a/detections/tor_traffic.yml +++ b/detections/tor_traffic.yml @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None at this time tags: analytics_story: - - Ransomware - - Command and Control - Prohibited Traffic Allowed or Protocol Mismatch + - Command and Control + - Ransomware mitre_attack_id: - T1043 kill_chain_phases: @@ -34,3 +34,4 @@ tags: nist: - DE.AE security_domain: network + asset_type: Endpoint diff --git a/detections/uncommon_processes_on_endpoint.yml b/detections/uncommon_processes_on_endpoint.yml index 23f3424a39..39cba734a0 100644 --- a/detections/uncommon_processes_on_endpoint.yml +++ b/detections/uncommon_processes_on_endpoint.yml @@ -22,8 +22,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Unusual Processes - Windows Privilege Escalation + - Unusual Processes mitre_attack_id: - T1015 kill_chain_phases: @@ -34,3 +34,4 @@ tags: - ID.AM - PR.DS security_domain: endpoint + asset_type: Endpoint diff --git a/detections/unload_sysmon_filter_driver.yml b/detections/unload_sysmon_filter_driver.yml index 5ccb9a4d26..48d0404d38 100644 --- a/detections/unload_sysmon_filter_driver.yml +++ b/detections/unload_sysmon_filter_driver.yml @@ -34,3 +34,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: '' diff --git a/detections/unsigned_image_loaded_by_LSASS.yml b/detections/unsigned_image_loaded_by_LSASS.yml index 3edd09a042..bfb01a92a5 100644 --- a/detections/unsigned_image_loaded_by_LSASS.yml +++ b/detections/unsigned_image_loaded_by_LSASS.yml @@ -32,3 +32,4 @@ tags: nist: - DE.CM security_domain: endpoint + asset_type: Windows diff --git a/detections/unsuccessful_netbackup_backups.yml b/detections/unsuccessful_netbackup_backups.yml index 3df161c2e9..92f94a59a8 100644 --- a/detections/unsuccessful_netbackup_backups.yml +++ b/detections/unsuccessful_netbackup_backups.yml @@ -24,3 +24,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/unusually_long_command_line.yml b/detections/unusually_long_command_line.yml index 2e579f8830..ff41daf222 100644 --- a/detections/unusually_long_command_line.yml +++ b/detections/unusually_long_command_line.yml @@ -22,10 +22,10 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Some legitimate applications start with long command lines. tags: analytics_story: - - Unusual Processes - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Ransomware - Suspicious Command-Line Executions + - Ransomware + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Unusual Processes kill_chain_phases: - Actions on Objectives cis20: @@ -34,3 +34,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: '' diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml index f30a3a720a..2dee1c2e0d 100644 --- a/detections/unusually_long_command_line___mltk.yml +++ b/detections/unusually_long_command_line___mltk.yml @@ -35,10 +35,10 @@ known_false_positives: Some legitimate applications use long command lines for i build the associated model. tags: analytics_story: - - Unusual Processes - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Ransomware - Suspicious Command-Line Executions + - Ransomware + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Unusual Processes kill_chain_phases: - Actions on Objectives cis20: @@ -47,3 +47,4 @@ tags: - PR.PT - DE.CM security_domain: endpoint + asset_type: '' diff --git a/detections/unusually_long_content_type_length.yml b/detections/unusually_long_content_type_length.yml index 1c8e6a1aa0..be724f2a1a 100644 --- a/detections/unusually_long_content_type_length.yml +++ b/detections/unusually_long_content_type_length.yml @@ -34,3 +34,4 @@ tags: - PR.MA - DE.CM security_domain: network + asset_type: Web Server diff --git a/detections/usn_journal_deletion.yml b/detections/usn_journal_deletion.yml index a4621b1ee0..82ac91f6af 100644 --- a/detections/usn_journal_deletion.yml +++ b/detections/usn_journal_deletion.yml @@ -23,8 +23,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: None identified tags: analytics_story: - - Ransomware - Windows Log Manipulation + - Ransomware mitre_attack_id: - T1070 kill_chain_phases: @@ -40,3 +40,4 @@ tags: - DE.DP - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/web_fraud___account_harvesting.yml b/detections/web_fraud___account_harvesting.yml index 9d8cc8659a..d02cf467a3 100644 --- a/detections/web_fraud___account_harvesting.yml +++ b/detections/web_fraud___account_harvesting.yml @@ -46,3 +46,4 @@ tags: - DE.CM - DE.DP security_domain: threat + asset_type: Account diff --git a/detections/web_fraud___anomalous_user_clickspeed.yml b/detections/web_fraud___anomalous_user_clickspeed.yml index 476366327d..af980c23eb 100644 --- a/detections/web_fraud___anomalous_user_clickspeed.yml +++ b/detections/web_fraud___anomalous_user_clickspeed.yml @@ -42,3 +42,4 @@ tags: - DE.AE - DE.CM security_domain: threat + asset_type: account diff --git a/detections/web_fraud___password_sharing_across_accounts.yml b/detections/web_fraud___password_sharing_across_accounts.yml index 55ec53c9ef..d04e6668fc 100644 --- a/detections/web_fraud___password_sharing_across_accounts.yml +++ b/detections/web_fraud___password_sharing_across_accounts.yml @@ -32,3 +32,4 @@ tags: nist: - DE.DP security_domain: threat + asset_type: account diff --git a/detections/web_servers_executing_suspicious_processes.yml b/detections/web_servers_executing_suspicious_processes.yml index b0ecef5162..9c37ecd7fb 100644 --- a/detections/web_servers_executing_suspicious_processes.yml +++ b/detections/web_servers_executing_suspicious_processes.yml @@ -33,3 +33,4 @@ tags: nist: - PR.IP security_domain: endpoint + asset_type: Web Server diff --git a/detections/windows_event_log_cleared.yml b/detections/windows_event_log_cleared.yml index cc574b73b7..ee1b44198c 100644 --- a/detections/windows_event_log_cleared.yml +++ b/detections/windows_event_log_cleared.yml @@ -17,8 +17,8 @@ known_false_positives: It is possible that these logs may be legitimately cleare by Administrators. tags: analytics_story: - - Ransomware - Windows Log Manipulation + - Ransomware mitre_attack_id: - T1070 kill_chain_phases: @@ -34,3 +34,4 @@ tags: - PR.AT - DE.AE security_domain: endpoint + asset_type: Endpoint diff --git a/detections/windows_hosts_file_modification.yml b/detections/windows_hosts_file_modification.yml index e996adde7b..42c08a9ce3 100644 --- a/detections/windows_hosts_file_modification.yml +++ b/detections/windows_hosts_file_modification.yml @@ -36,3 +36,4 @@ tags: - DE.AE - DE.CM security_domain: endpoint + asset_type: Endpoint diff --git a/detections/wmi_permanent_event_subscription.yml b/detections/wmi_permanent_event_subscription.yml index 2c344d9048..064e32a2c4 100644 --- a/detections/wmi_permanent_event_subscription.yml +++ b/detections/wmi_permanent_event_subscription.yml @@ -33,3 +33,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/wmi_permanent_event_subscription___sysmon.yml b/detections/wmi_permanent_event_subscription___sysmon.yml index a9d6d6d37a..5462c67c41 100644 --- a/detections/wmi_permanent_event_subscription___sysmon.yml +++ b/detections/wmi_permanent_event_subscription___sysmon.yml @@ -31,3 +31,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/detections/wmi_temporary_event_subscription.yml b/detections/wmi_temporary_event_subscription.yml index 22354d3abc..e0973069d6 100644 --- a/detections/wmi_temporary_event_subscription.yml +++ b/detections/wmi_temporary_event_subscription.yml @@ -36,3 +36,4 @@ tags: - PR.AC - PR.IP security_domain: endpoint + asset_type: Endpoint diff --git a/macros/access_lsass_memory_for_dump_creation_filter.yml b/macros/access_lsass_memory_for_dump_creation_filter.yml deleted file mode 100644 index ed58de5848..0000000000 --- a/macros/access_lsass_memory_for_dump_creation_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for access lsass memory for dump creation -name: access_lsass_memory_for_dump_creation_filter diff --git a/macros/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter.yml b/macros/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter.yml deleted file mode 100644 index 701f306f47..0000000000 --- a/macros/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for attempt to set default powershell execution policy to unrestricted or bypass -name: attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter diff --git a/macros/attempted_credential_dump_from_registry_via_reg_filter.yml b/macros/attempted_credential_dump_from_registry_via_reg_filter.yml deleted file mode 100644 index 9986f4c8a7..0000000000 --- a/macros/attempted_credential_dump_from_registry_via_reg_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for attempted credential dump from registry via reg -name: attempted_credential_dump_from_registry_via_reg_filter diff --git a/macros/attrib_to_hide_files_filter.yml b/macros/attrib_to_hide_files_filter.yml deleted file mode 100644 index 7151ae3088..0000000000 --- a/macros/attrib_to_hide_files_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: attrib_to_hide_files_filter \ No newline at end of file diff --git a/macros/aws_cloudwatchlogs_eks.yml b/macros/aws_cloudwatchlogs_eks.yml index 44d9641feb..712770fab9 100644 --- a/macros/aws_cloudwatchlogs_eks.yml +++ b/macros/aws_cloudwatchlogs_eks.yml @@ -1,4 +1,4 @@ -definiton: sourcetype="aws:cloudwatchlogs:eks" +definition: sourcetype="aws:cloudwatchlogs:eks" description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: aws_cloudwatchlogs_eks diff --git a/macros/aws_s3_accesslogs.yml b/macros/aws_s3_accesslogs.yml index 77e626fa30..60aecdb081 100644 --- a/macros/aws_s3_accesslogs.yml +++ b/macros/aws_s3_accesslogs.yml @@ -1,4 +1,4 @@ -definiton: sourcetype=aws:s3:accesslogs +definition: sourcetype=aws:s3:accesslogs description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: aws_s3_accesslogs diff --git a/macros/change_file_association_filter.yml b/macros/change_file_association_filter.yml deleted file mode 100644 index 4b55678675..0000000000 --- a/macros/change_file_association_filter.yml +++ /dev/null @@ -1,4 +0,0 @@ - -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: change_file_association_filter \ No newline at end of file diff --git a/macros/children_of_spoolsv_filter.yml b/macros/children_of_spoolsv_filter.yml deleted file mode 100644 index c7a8f0f943..0000000000 --- a/macros/children_of_spoolsv_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: children_of_spoolsv_filter \ No newline at end of file diff --git a/macros/cloudtrail.yml b/macros/cloudtrail.yml index 2f8d4c8578..bb4982174e 100644 --- a/macros/cloudtrail.yml +++ b/macros/cloudtrail.yml @@ -1,4 +1,4 @@ -definiton: sourcetype=aws:cloudtrail +definition: sourcetype=aws:cloudtrail description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: cloudtrail diff --git a/macros/cloudwatchlogs_vpcflow.yml b/macros/cloudwatchlogs_vpcflow.yml index 4718ff3271..d9dd3ac720 100644 --- a/macros/cloudwatchlogs_vpcflow.yml +++ b/macros/cloudwatchlogs_vpcflow.yml @@ -1,4 +1,4 @@ -definiton: sourcetype=aws:cloudwatchlogs:vpcflow +definition: sourcetype=aws:cloudwatchlogs:vpcflow description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: cloudwatchlogs_vpcflow diff --git a/macros/common_ransomware_extensions_filter.yml b/macros/common_ransomware_extensions_filter.yml deleted file mode 100644 index 6a450e8a58..0000000000 --- a/macros/common_ransomware_extensions_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: common_ransomware_extensions_filter \ No newline at end of file diff --git a/macros/common_ransomware_notes_filter.yml b/macros/common_ransomware_notes_filter.yml deleted file mode 100644 index ef33343820..0000000000 --- a/macros/common_ransomware_notes_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: common_ransomware_notes_filter \ No newline at end of file diff --git a/macros/container_implant_aws_detection_filter.yml b/macros/container_implant_aws_detection_filter.yml deleted file mode 100644 index 3d37856762..0000000000 --- a/macros/container_implant_aws_detection_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters -name: container_implant_aws_detection_filter diff --git a/macros/container_implant_gcp_detection_filter.yml b/macros/container_implant_gcp_detection_filter.yml deleted file mode 100644 index d25f44bd6a..0000000000 --- a/macros/container_implant_gcp_detection_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters -name: container_implant_gcp_detection_filter diff --git a/macros/create_local_admin_via_net_filter.yml b/macros/create_local_admin_via_net_filter.yml deleted file mode 100644 index e3a215d554..0000000000 --- a/macros/create_local_admin_via_net_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: create_local_admin_via_net_filter \ No newline at end of file diff --git a/macros/create_remote_thread_into_lsass_filter.yml b/macros/create_remote_thread_into_lsass_filter.yml deleted file mode 100644 index 893485aba0..0000000000 --- a/macros/create_remote_thread_into_lsass_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for create remote thread into lsass -name: create_remote_thread_into_lsass_filter diff --git a/macros/creation_of_shadow_copy_filter.yml b/macros/creation_of_shadow_copy_filter.yml deleted file mode 100644 index 10e3b8e032..0000000000 --- a/macros/creation_of_shadow_copy_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for creation of shadow copy -name: creation_of_shadow_copy_filter diff --git a/macros/creation_of_shadow_copy_with_wmic_and_powershell_filter.yml b/macros/creation_of_shadow_copy_with_wmic_and_powershell_filter.yml deleted file mode 100644 index 3da66555bb..0000000000 --- a/macros/creation_of_shadow_copy_with_wmic_and_powershell_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for creation of shadow copy with wmic and powershell -name: creation_of_shadow_copy_with_wmic_and_powershell_filter diff --git a/macros/cred_dump_via_copy_from_shadowcopy_filter.yml b/macros/cred_dump_via_copy_from_shadowcopy_filter.yml deleted file mode 100644 index 47086687a7..0000000000 --- a/macros/cred_dump_via_copy_from_shadowcopy_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for cred dump via copy from shadowcopy -name: cred_dump_via_copy_from_shadowcopy_filter diff --git a/macros/cred_dump_via_symlink_shadowcopy_filter.yml b/macros/cred_dump_via_symlink_shadowcopy_filter.yml deleted file mode 100644 index 97ea55fdb8..0000000000 --- a/macros/cred_dump_via_symlink_shadowcopy_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for cred dump via symlink shadowcopy -name: cred_dump_via_symlink_shadowcopy_filter diff --git a/macros/detect_activity_related_to_pass_the_hash_attacks_filter.yml b/macros/detect_activity_related_to_pass_the_hash_attacks_filter.yml deleted file mode 100644 index 083bce747e..0000000000 --- a/macros/detect_activity_related_to_pass_the_hash_attacks_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for detect activity related to pass the hash attacks -name: detect_activity_related_to_pass_the_hash_attacks_filter diff --git a/macros/detect_credential_dumping_through_LSASS_access_filter.yml b/macros/detect_credential_dumping_through_LSASS_access_filter.yml deleted file mode 100644 index 956bb0d6a4..0000000000 --- a/macros/detect_credential_dumping_through_LSASS_access_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for detect credential dumping through LSASS access -name: detect_credential_dumping_through_LSASS_access_filter diff --git a/macros/detect_mimikatz_using_loaded_images_filter.yml b/macros/detect_mimikatz_using_loaded_images_filter.yml deleted file mode 100644 index 5b0be46ce2..0000000000 --- a/macros/detect_mimikatz_using_loaded_images_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for detect mimikatz using loaded images -name: detect_mimikatz_using_loaded_images_filter diff --git a/macros/dns_query_length_mltk_filter.yml b/macros/dns_query_length_mltk_filter.yml deleted file mode 100644 index 90b9429a0d..0000000000 --- a/macros/dns_query_length_mltk_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -description: Use this macro to add additional filters for monitoring DNS query length using MLTK -name: dns_query_length_mltk_filter -definition: search * diff --git a/macros/dns_query_length_with_high_standard_deviation_filter.yml b/macros/dns_query_length_with_high_standard_deviation_filter.yml deleted file mode 100644 index e88b8382eb..0000000000 --- a/macros/dns_query_length_with_high_standard_deviation_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -description: Use this macro to add additional filters for monitoring DNS query length with high standard deviation -name: dns_query_length_with_high_standard_deviation_filter -definition: search * diff --git a/macros/dns_record_changed_filter.yml b/macros/dns_record_changed_filter.yml deleted file mode 100644 index 8bf9820083..0000000000 --- a/macros/dns_record_changed_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -description: Use this macro to add additional filters for monitoring DNS records changed -name: dns_record_changed_filter -definition: search * diff --git a/macros/dragonfly_schtasks_filter.yml b/macros/dragonfly_schtasks_filter.yml deleted file mode 100644 index c5dfd45827..0000000000 --- a/macros/dragonfly_schtasks_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: dragonfly_schtasks_filter \ No newline at end of file diff --git a/macros/dump_lsass_via_comsvcs_dll_filter.yml b/macros/dump_lsass_via_comsvcs_dll_filter.yml deleted file mode 100644 index 152135df5e..0000000000 --- a/macros/dump_lsass_via_comsvcs_dll_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for dump lsass via comsvcs dll filter -name: dump_lsass_via_comsvcs_dll_filter diff --git a/macros/ec2_excessive_runinstances_mltk_input_filter.yml b/macros/ec2_excessive_runinstances_mltk_input_filter.yml deleted file mode 100644 index a48a27892c..0000000000 --- a/macros/ec2_excessive_runinstances_mltk_input_filter.yml +++ /dev/null @@ -1,4 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for monitoring ec2 - runinstances [eg - src_user != 'someUserNameExperiencingFalsePositives']. -name: ec2_excessive_runinstances_mltk_input_filter diff --git a/macros/ec2_excessive_terminateinstances_mltk_input_filter.yml b/macros/ec2_excessive_terminateinstances_mltk_input_filter.yml deleted file mode 100644 index 0918ce133f..0000000000 --- a/macros/ec2_excessive_terminateinstances_mltk_input_filter.yml +++ /dev/null @@ -1,4 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for monitoring ec2 - terminateinstances [eg - src_user != 'someUserNameExperiencingFalsePositives']. -name: ec2_excessive_terminateinstances_mltk_input_filter diff --git a/macros/email_files_not_in_outlook_directory_filter.yml b/macros/email_files_not_in_outlook_directory_filter.yml deleted file mode 100644 index 9f7fee2eba..0000000000 --- a/macros/email_files_not_in_outlook_directory_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters to exclude false positive results -name: email_files_not_in_outlook_directory_filter diff --git a/macros/file_write_spikes_filter.yml b/macros/file_write_spikes_filter.yml deleted file mode 100644 index b9ccc594b1..0000000000 --- a/macros/file_write_spikes_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: file_write_spikes_filter \ No newline at end of file diff --git a/macros/first_time_seen_cmd_line_filter.yml b/macros/first_time_seen_cmd_line_filter.yml deleted file mode 100644 index 8a4785e9b9..0000000000 --- a/macros/first_time_seen_cmd_line_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for first time seen command line, you can exclude legitimate parent_processes that spawn cmd.exe. Eg- seach parent_process_name != "foo" -name: first_time_seen_cmd_line_filter diff --git a/macros/google_gcp_pubsub_message.yml b/macros/google_gcp_pubsub_message.yml index 3a58859bb3..e040e3cfa3 100644 --- a/macros/google_gcp_pubsub_message.yml +++ b/macros/google_gcp_pubsub_message.yml @@ -1,4 +1,4 @@ -definiton: sourcetype="google:gcp:pubsub:message" +definition: sourcetype="google:gcp:pubsub:message" description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: google_gcp_pubsub_message diff --git a/macros/kubernetes_aws_scan_fingerprint_detection_filter.yml b/macros/kubernetes_aws_scan_fingerprint_detection_filter.yml deleted file mode 100644 index 3f70da4899..0000000000 --- a/macros/kubernetes_aws_scan_fingerprint_detection_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters -name: kubernetes_aws_scan_fingerprint_detection diff --git a/macros/kubernetes_gcp_scan_fingerprint_detection_filter.yml b/macros/kubernetes_gcp_scan_fingerprint_detection_filter.yml deleted file mode 100644 index fbee229bf7..0000000000 --- a/macros/kubernetes_gcp_scan_fingerprint_detection_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters -name: kubernetes_gcp_scan_fingerprint_detection diff --git a/macros/kubernetes_pods_aws_scan_fingerprint_detection_filter.yml b/macros/kubernetes_pods_aws_scan_fingerprint_detection_filter.yml deleted file mode 100644 index 2156737cbe..0000000000 --- a/macros/kubernetes_pods_aws_scan_fingerprint_detection_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters -name: kubernetes_pods_aws_scan_fingerprint_detection diff --git a/macros/lnk_executing_a_process_filter.yml b/macros/lnk_executing_a_process_filter.yml deleted file mode 100644 index 346ce4fdca..0000000000 --- a/macros/lnk_executing_a_process_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: lnk_executing_a_process_filter \ No newline at end of file diff --git a/macros/malicious_powershell_process_obfuscation_techniques_output_filter.yml b/macros/malicious_powershell_process_obfuscation_techniques_output_filter.yml deleted file mode 100644 index 56fd9b8503..0000000000 --- a/macros/malicious_powershell_process_obfuscation_techniques_output_filter.yml +++ /dev/null @@ -1,4 +0,0 @@ -definition: search * -description: Use this macro to add output filters for Malicious PowerShell - Process With Obfuscation Techniques. -name: malicious_powershell_process_obfuscation_techniques_output_filter diff --git a/macros/netbackup.yml b/macros/netbackup.yml index 69d2ca034d..2021f88e1b 100644 --- a/macros/netbackup.yml +++ b/macros/netbackup.yml @@ -1,4 +1,4 @@ -definiton: sourcetype="netbackup_logs" +definition: sourcetype="netbackup_logs" description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: netbackup diff --git a/macros/okta.yml b/macros/okta.yml index 684c32cd12..933b1e6f2c 100644 --- a/macros/okta.yml +++ b/macros/okta.yml @@ -1,4 +1,4 @@ -definiton: eventtype=okta_log +definition: eventtype=okta_log description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: okta diff --git a/macros/okta_failed_sso_attempt_filter.yml b/macros/okta_failed_sso_attempt_filter.yml deleted file mode 100644 index 1d62efcfe0..0000000000 --- a/macros/okta_failed_sso_attempt_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: okta_failed_sso_attempt_filter \ No newline at end of file diff --git a/macros/okta_multiple_users_with_auth_failures_from_ip_filter.yml b/macros/okta_multiple_users_with_auth_failures_from_ip_filter.yml deleted file mode 100644 index be4ef2b1d3..0000000000 --- a/macros/okta_multiple_users_with_auth_failures_from_ip_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: okta_multiple_users_with_auth_failures_from_ip_filter \ No newline at end of file diff --git a/macros/okta_user_lockouts_filter.yml b/macros/okta_user_lockouts_filter.yml deleted file mode 100644 index 27f4329ce0..0000000000 --- a/macros/okta_user_lockouts_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: okta_user_lockouts_filter \ No newline at end of file diff --git a/macros/okta_user_logins_from_multiple_cities_filter.yml b/macros/okta_user_logins_from_multiple_cities_filter.yml deleted file mode 100644 index 81b8ca5841..0000000000 --- a/macros/okta_user_logins_from_multiple_cities_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: okta_user_logins_from_multiple_cities_filter \ No newline at end of file diff --git a/macros/outbound_smb_connections_filter.yml b/macros/outbound_smb_connections_filter.yml deleted file mode 100644 index a402945c32..0000000000 --- a/macros/outbound_smb_connections_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for outbound SMB traffic detection -name: outbound_smb_connections_filter diff --git a/macros/outlook_writing_zip_filter.yml b/macros/outlook_writing_zip_filter.yml deleted file mode 100644 index fa70d5dfc0..0000000000 --- a/macros/outlook_writing_zip_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: outlook_writing_zip_filter \ No newline at end of file diff --git a/macros/previously_seen_cloud_compute_creations_by_user_input_filter.yml b/macros/previously_seen_cloud_compute_creations_by_user_input_filter.yml deleted file mode 100644 index ca8d553a3e..0000000000 --- a/macros/previously_seen_cloud_compute_creations_by_user_input_filter.yml +++ /dev/null @@ -1,4 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for monitoring users that create - cloud compute images -name: previously_seen_cloud_compute_creations_by_user_input_filter diff --git a/macros/previously_seen_cloud_compute_image_input_filter.yml b/macros/previously_seen_cloud_compute_image_input_filter.yml deleted file mode 100644 index 321082ee44..0000000000 --- a/macros/previously_seen_cloud_compute_image_input_filter.yml +++ /dev/null @@ -1,4 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for monitoring cloud compute - images -name: previously_seen_cloud_compute_image_input_filter diff --git a/macros/previously_seen_cloud_compute_instance_types_input_filter.yml b/macros/previously_seen_cloud_compute_instance_types_input_filter.yml deleted file mode 100644 index fa12cab54b..0000000000 --- a/macros/previously_seen_cloud_compute_instance_types_input_filter.yml +++ /dev/null @@ -1,4 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for monitoring cloud compute - instance types -name: previously_seen_cloud_compute_instance_types_input_filter diff --git a/macros/previously_seen_cloud_regions_input_filter.yml b/macros/previously_seen_cloud_regions_input_filter.yml deleted file mode 100644 index 70906c867e..0000000000 --- a/macros/previously_seen_cloud_regions_input_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for monitoring your cloud regions -name: previously_seen_cloud_regions_input_filter diff --git a/macros/rare_executables_on_endpoint_filter.yml b/macros/rare_executables_on_endpoint_filter.yml deleted file mode 100644 index 816438def9..0000000000 --- a/macros/rare_executables_on_endpoint_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to filter out false positives -name: rare_executables_on_endpoint_filter diff --git a/macros/remote_desktop_network_traffic_filter.yml b/macros/remote_desktop_network_traffic_filter.yml deleted file mode 100644 index 2f2c9149f8..0000000000 --- a/macros/remote_desktop_network_traffic_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for remote desktop network traffic -name: remote_desktop_network_traffic_filter diff --git a/macros/remote_desktop_process_running_on_system_filter.yml b/macros/remote_desktop_process_running_on_system_filter.yml deleted file mode 100644 index 854b116d87..0000000000 --- a/macros/remote_desktop_process_running_on_system_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for remote desktop process running on system -name: remote_desktop_process_running_on_system_filter diff --git a/macros/schtasks_scheduling_job_on_remote_system_filter.yml b/macros/schtasks_scheduling_job_on_remote_system_filter.yml deleted file mode 100644 index fdcbfa2eec..0000000000 --- a/macros/schtasks_scheduling_job_on_remote_system_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for schtasks scheduling job on remote system -name: schtasks_scheduling_job_on_remote_system_filter diff --git a/macros/smb_traffic_spike_filter.yml b/macros/smb_traffic_spike_filter.yml deleted file mode 100644 index 08d2f3a407..0000000000 --- a/macros/smb_traffic_spike_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for SMB traffic spike detection -name: smb_traffic_spike_filter diff --git a/macros/smb_traffic_spike_mltk_filter.yml b/macros/smb_traffic_spike_mltk_filter.yml deleted file mode 100644 index ee09da9bcd..0000000000 --- a/macros/smb_traffic_spike_mltk_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for SMB traffic spike detection using MLKT -name: smb_traffic_spike_mltk_filter diff --git a/macros/stream_http.yml b/macros/stream_http.yml index 70e1ee39b8..3f01a15760 100644 --- a/macros/stream_http.yml +++ b/macros/stream_http.yml @@ -1,4 +1,4 @@ -definiton: sourcetype=stream:http +definition: sourcetype=stream:http description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: stream_http diff --git a/macros/suspicious_email_attachments_filter.yml b/macros/suspicious_email_attachments_filter.yml deleted file mode 100644 index f26cb9022e..0000000000 --- a/macros/suspicious_email_attachments_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for suspicious email attachments -name: suspicious_email_attachments_filter diff --git a/macros/suspicious_reg_process_filter.yml b/macros/suspicious_reg_process_filter.yml deleted file mode 100644 index c4007321e2..0000000000 --- a/macros/suspicious_reg_process_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: suspicious_reg_process_filter \ No newline at end of file diff --git a/macros/sysmon.yml b/macros/sysmon.yml index c3041967ca..74c7640aed 100644 --- a/macros/sysmon.yml +++ b/macros/sysmon.yml @@ -1,4 +1,4 @@ -definiton: sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational +definition: sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: sysmon diff --git a/macros/unauthorized_dns_servers_filter.yml b/macros/unauthorized_dns_servers_filter.yml deleted file mode 100644 index 919e3fd05e..0000000000 --- a/macros/unauthorized_dns_servers_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filters for DNS Query Requests Resolved by Unauthorized DNS Servers detection -name: unauthorized_dns_servers_filter diff --git a/macros/uncommon_processes_filter.yml b/macros/uncommon_processes_filter.yml deleted file mode 100644 index 5a2cd7d62e..0000000000 --- a/macros/uncommon_processes_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: uncommon_processes_filter \ No newline at end of file diff --git a/macros/unload_sysmon_filter_driver_filter.yml b/macros/unload_sysmon_filter_driver_filter.yml deleted file mode 100644 index a77c0dac98..0000000000 --- a/macros/unload_sysmon_filter_driver_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for Unload sysmon filter driver search to filter out the false positives -name: unload_sysmon_filter_driver_filter diff --git a/macros/unsigned_image_loaded_by_LSASS_filter.yml b/macros/unsigned_image_loaded_by_LSASS_filter.yml deleted file mode 100644 index 9a7d757853..0000000000 --- a/macros/unsigned_image_loaded_by_LSASS_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Use this macro to add additional filter for unsigned image loaded by LSASS -name: unsigned_image_loaded_by_LSASS_filter diff --git a/macros/unusually_long_commandlines_filter.yml b/macros/unusually_long_commandlines_filter.yml deleted file mode 100644 index 4d3b22ce29..0000000000 --- a/macros/unusually_long_commandlines_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: unusually_long_commandlines_filter \ No newline at end of file diff --git a/macros/wineventlog_security.yml b/macros/wineventlog_security.yml index cf504967fd..00d2e3d6b8 100644 --- a/macros/wineventlog_security.yml +++ b/macros/wineventlog_security.yml @@ -1,4 +1,4 @@ -definiton: eventtype=wineventlog_security +definition: eventtype=wineventlog_security description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: wineventlog_security diff --git a/macros/wineventlog_system.yml b/macros/wineventlog_system.yml index 2e74ab12b1..d6c9a4b88b 100644 --- a/macros/wineventlog_system.yml +++ b/macros/wineventlog_system.yml @@ -1,4 +1,4 @@ -definiton: eventtype=wineventlog_system +definition: eventtype=wineventlog_system description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: wineventlog_system diff --git a/macros/wmi.yml b/macros/wmi.yml index 581ac64f9e..9769d5c79d 100644 --- a/macros/wmi.yml +++ b/macros/wmi.yml @@ -1,4 +1,4 @@ -definiton: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" +definition: sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" description: customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. name: wmi diff --git a/macros/wmi_process_launch_filter.yml b/macros/wmi_process_launch_filter.yml deleted file mode 100644 index eb93b54cb5..0000000000 --- a/macros/wmi_process_launch_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: wmi_process_launch_filter \ No newline at end of file diff --git a/macros/wmi_script_execution_filter.yml b/macros/wmi_script_execution_filter.yml deleted file mode 100644 index 08ad0f61b4..0000000000 --- a/macros/wmi_script_execution_filter.yml +++ /dev/null @@ -1,3 +0,0 @@ -definition: search * -description: Update this macro to limit the output results to filter out false positives. -name: wmi_script_execution_filter \ No newline at end of file diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index adb4b7b23d..685be01a88 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-04-17T19:06:18 UTC +# On Date: 2020-05-06T14:58:49 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -12,14 +12,13 @@ category = Cloud Security creation_date = 2018-06-04 modification_date = 2018-06-04 id = 2f2f610a-d64d-48c2-b57c-967a2b49ab5a -version = 1.0 +version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] -detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] -mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "mitre_technique_id": [], "nist": ["DE.AE", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] -data_models = [] -providing_technologies = ["AWS", "Splunk Enterprise Security"] +detection_searches = ["AWS Cross Account Activity From Previously Unseen Account"] +mappings = {"analytics_story": "AWS Cross Account Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -30,14 +29,13 @@ category = Cloud Security creation_date = 2018-03-08 modification_date = 2018-03-08 id = ced74200-8465-4bc3-bd2c-9a782eec6750 -version = 1.0 +version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Execution"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] -support_searches = ["ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User"] -data_models = [] -providing_technologies = ["AWS", "Splunk Enterprise Security"] +detection_searches = ["EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started In Previously Unseen Region"] +mappings = {"analytics_story": "AWS Cryptomining", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -46,17 +44,16 @@ This Analytic Story is focused on detecting suspicious new instances in your EC2 [AWS Network ACL Activity] category = Cloud Security -creation_date = 2018-01-10 +creation_date = 2018-05-21 modification_date = 2018-05-21 id = 2e8948a5-5239-406b-b56b-6c50ff268af4 -version = 2.0 +version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] -detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] -mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Persistence"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Baseline of Network ACL Activity by ARN", "ESCU - Baseline of blocked outbound traffic from AWS"] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk"] -providing_technologies = ["AWS", "Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["AWS Network Access Control List Deleted", "Detect Spike in blocked Outbound Traffic from your AWS", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in Network ACL Activity"] +mappings = {"analytics_story": "AWS Network ACL Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -65,14 +62,13 @@ category = Cloud Security creation_date = 2018-03-16 modification_date = 2018-03-16 id = 3338b567-3804-4261-9889-cf0ca4753c7f -version = 1.0 +version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] -mappings = {"cis20": ["CIS 1"], "kill_chain_phases": [], "mitre_attack": [], "mitre_technique_id": [], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] -support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] -data_models = [] -providing_technologies = ["AWS"] +detection_searches = ["AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region", "AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country"] +mappings = {"analytics_story": "AWS Suspicious Provisioning Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -82,14 +78,13 @@ category = Cloud Security creation_date = 2018-03-12 modification_date = 2018-03-12 id = 2e8948a5-5239-406b-b56b-6c50f1269af3 -version = 1.0 +version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] -detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "mitre_technique_id": [], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] -support_searches = ["ESCU - Baseline of API Calls per User ARN", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Create a list of approved AWS service accounts", "ESCU - Previously seen API call per user roles in CloudTrail"] -data_models = [] -providing_technologies = ["AWS", "Splunk Enterprise Security"] +detection_searches = ["Detect new API calls from user roles", "Detect Spike in Security Group Activity", "Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts"] +mappings = {"analytics_story": "AWS User Monitoring", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -98,33 +93,31 @@ The detection searches in this Analytic Story are designed to help you uncover A [Account Monitoring and Controls] category = Best Practices -creation_date = 2017-08-05 +creation_date = 2017-09-06 modification_date = 2017-09-06 id = 8892a655-6205-55f7-abba-06460e38c8ae -version = 1.0 +version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] -detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] -mappings = {"cis20": ["CIS 16"], "kill_chain_phases": [], "mitre_attack": ["Create Account", "Initial Access", "Persistence", "Valid Accounts"], "mitre_technique_id": [], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Change", "Identity_Management", "Risk"] -providing_technologies = ["Active Directory", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "macOS"] +detection_searches = ["Short Lived Windows Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint", "Identify New User Accounts"] +mappings = {"analytics_story": "Account Monitoring and Controls", "category": ["Best Practices"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. [Apache Struts Vulnerability] category = Vulnerability -creation_date = 2017-03-14 +creation_date = 2018-12-06 modification_date = 2018-12-06 id = 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e -version = 1.0 +version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] -detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4", "CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["Defense Evasion", "Discovery", "Execution", "Exploitation of Vulnerability", "System Information Discovery"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Risk", "Web"] -providing_technologies = ["Apache", "Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] +mappings = {"analytics_story": "Apache Struts Vulnerability", "category": ["Vulnerability"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -143,33 +136,31 @@ It can also be very helpful to examine various behaviors of the process of inter [Asset Tracking] category = Best Practices -creation_date = 2017-06-01 +creation_date = 2017-09-13 modification_date = 2017-09-13 id = 91c676cf-0b23-438d-abee-f6335e1fce77 -version = 1.0 +version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] -detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] -mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Reconnaissance"], "mitre_attack": ["Defense Evasion"], "mitre_technique_id": [], "nist": ["ID.AM", "PR.DS"]} -investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -support_searches = ["ESCU - Count of assets by category"] -data_models = ["Identity_Management", "Network_Sessions"] -providing_technologies = ["Bro", "Microsoft Windows", "Splunk Enterprise Security", "Splunk Stream"] +detection_searches = ["Detect Unauthorized Assets by MAC address"] +mappings = {"analytics_story": "Asset Tracking", "category": ["Best Practices"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. [Brand Monitoring] category = Abuse -creation_date = 2017-06-01 +creation_date = 2017-12-19 modification_date = 2017-12-19 id = 91c676cf-0b23-438d-abee-f6335e1fce78 -version = 1.0 +version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] -detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] -mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "mitre_attack": [], "mitre_technique_id": [], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - DNSTwist Domain Names"] -data_models = ["Authentication", "Email", "Endpoint", "Network_Resolution", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Exchange", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Monitor Web Traffic For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse"] +mappings = {"analytics_story": "Brand Monitoring", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -180,14 +171,13 @@ category = Cloud Security creation_date = 2019-10-02 modification_date = 2019-10-02 id = 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a -version = 1.0 +version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Execution"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate User Activities In Single Cloud Region"] -support_searches = ["ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Regions"] -data_models = ["Cloud_Infrastructure"] -providing_technologies = ["AWS", "Azure", "GCP", "Splunk Enterprise Security"] +detection_searches = ["Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] +mappings = {"analytics_story": "Cloud Cryptomining", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -196,17 +186,16 @@ This Analytic Story is focused on detecting suspicious new instances in your clo [ColdRoot MacOS RAT] category = Malware -creation_date = 2019-01-29 +creation_date = 2019-01-09 modification_date = 2019-01-09 id = bd91a2bc-d20b-4f44-a982-1bea98e86390 -version = 1.0 +version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] -detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] -mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control", "Installation"], "mitre_attack": ["Collection", "Command and Control", "Execution", "Persistence"], "mitre_technique_id": [], "nist": ["DE.CM", "DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src_ip", "ESCU - Investigate Web Activity From src_ip"] -support_searches = [] -data_models = ["Alerts", "Authentication", "Network_Traffic", "Risk", "Vulnerabilities", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Linux", "Microsoft Windows", "Nessus", "OSquery", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "macOS"] +detection_searches = ["Processes Tapping Keyboard Events", "Osquery pack - ColdRoot detection"] +mappings = {"analytics_story": "ColdRoot MacOS RAT", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -214,17 +203,16 @@ Searches in this Analytic Story leverage the capabilities of OSquery to address [Collection and Staging] category = Adversary Tactics -creation_date = 2018-01-08 +creation_date = 2020-02-03 modification_date = 2020-02-03 id = 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a -version = 1.1 +version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] -detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] -mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Collection", "Commonly Used Port", "Data Staged", "Email Collection"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk"] -providing_technologies = ["Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Email files written outside of the Outlook directory", "Suspicious writes to windows Recycle Bin", "Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server"] +mappings = {"analytics_story": "Collection and Staging", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -235,14 +223,13 @@ category = Adversary Tactics creation_date = 2018-06-01 modification_date = 2018-06-01 id = 943773c6-c4de-4f38-89a8-0b92f98804d8 -version = 1.0 +version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] -detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Defense Evasion", "Exfiltration", "Exfiltration Over Alternative Protocol", "Standard Non-Application Layer Protocol"], "mitre_technique_id": ["T1071"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] -data_models = ["Authentication", "Endpoint", "Network_Resolution", "Network_Traffic", "Risk"] -providing_technologies = ["AWS", "Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Long DNS TXT Record Response", "DNS Query Length Outliers - MLTK", "TOR Traffic", "Protocol or Port Mismatch", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Large Outbound ICMP Packets", "Prohibited Network Traffic Allowed", "Excessive DNS Failures"] +mappings = {"analytics_story": "Command and Control", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -252,47 +239,44 @@ category = Adversary Tactics creation_date = 2019-04-29 modification_date = 2019-04-29 id = 9a64ab44-9214-4639-8163-7eaa2621bd61 -version = 1.0 +version = 1 reference = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] -detection_searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule"] -mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Delivery"], "mitre_attack": ["Command and Control", "Spearphishing Link"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP"]} -investigative_searches = ["ESCU - Get Certificate logs for a domain"] -support_searches = [] -data_models = ["Certificates", "Network_Resolution", "Web"] -providing_technologies = ["Bro", "Censys", "Splunk Stream"] +detection_searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] +mappings = {"analytics_story": "Common Phishing Frameworks", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. narrative = As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. -[Container Implantation Monitoring & Investigation] +[Container Implantation Monitoring and Investigation] category = Cloud Security creation_date = 2020-02-20 -modification_date = +modification_date = 2020-02-20 id = aa0e28b1-0521-4b6f-9d2a-7b87e34af246 -version = 1.0 +version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule"] -mappings = {"cis20": [], "kill_chain_phases": [], "mitre_attack": ["Persistence"], "mitre_technique_id": ["T1525"], "nist": []} -investigative_searches = ["ESCU - Investigate AWS ECR container listing activity"] -support_searches = [] -data_models = ["Cloud_Infrastructure"] -providing_technologies = ["AWS", "GCP"] +detection_searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] +mappings = {"analytics_story": "Container Implantation Monitoring and Investigation", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. [Credential Dumping] category = Adversary Tactics -creation_date = 2018-08-08 +creation_date = 2020-02-04 modification_date = 2020-02-04 id = 854d78bf-d0e2-4f4e-b05c-640905f86d7a -version = 3.0 +version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] -detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg.exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] -mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["Credential Access", "Credential Dumping", "Execution", "PowerShell", "Scripting"], "mitre_technique_id": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] -support_searches = [] -data_models = ["Authentication", "Endpoint"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Detect Credential Dumping through LSASS access", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Access LSASS Memory for Dump Creation", "Create Remote Thread into LSASS", "Detect Mimikatz Using Loaded Images"] +mappings = {"analytics_story": "Credential Dumping", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -300,17 +284,16 @@ The detection searches in this Analytic Story monitor access to the Local Securi [DHS Report TA18-074A] category = Malware -creation_date = 2018-03-19 +creation_date = 2020-01-22 modification_date = 2020-01-22 id = 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef -version = 2.0 +version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] -detection_searches = ["ESCU - Create local admin accounts using net.exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg.exe Process - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["AppInit DLLs", "Authentication Package", "Command and Control", "Command-Line Interface", "Commonly Used Port", "Credential Access", "Defense Evasion", "Disabling Security Tools", "Execution", "Lateral Movement", "Modify Existing Service", "Modify Registry", "New Service", "Persistence", "PowerShell", "Privilege Escalation", "Registry Run Keys / Start Folder", "Scheduled Task", "Scripting", "Valid Accounts"], "mitre_technique_id": ["T1059", "T1110", "T1117", "T1135", "T1202", "T1210"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk", "Vulnerabilities", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Nessus", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Processes launching netsh", "Registry Keys Used For Persistence", "Detect Outbound SMB Traffic", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Detect New Local Admin account", "Single Letter Process On Endpoint", "Detect PsExec With accepteula Flag", "Create local admin accounts using net exe", "First time seen command line argument", "Scheduled Task Name Used by Dragonfly Threat Actors", "Malicious PowerShell Process - Execution Policy Bypass"] +mappings = {"analytics_story": "DHS Report TA18-074A", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -319,34 +302,32 @@ Suspicious activities--spikes in SMB traffic, processes that launch netsh (to mo [DNS Amplification Attacks] category = Abuse -creation_date = 2016-08-24 +creation_date = 2016-09-13 modification_date = 2016-09-13 id = e8afd39e-3294-11e6-b39d-a45e60c6700 -version = 1.0 +version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] -detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] -mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "mitre_technique_id": [], "nist": ["DE.AE", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User"] -support_searches = [] -data_models = ["Network_Resolution", "Risk"] -providing_technologies = ["Bro", "Splunk Enterprise Security", "Splunk Stream"] +detection_searches = ["Large Volume of DNS ANY Queries"] +mappings = {"analytics_story": "DNS Amplification Attacks", "category": ["Abuse"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. [DNS Hijacking] category = Adversary Tactics -creation_date = 2017-11-21 +creation_date = 2020-02-04 modification_date = 2020-02-04 id = 8169f17b-ef68-4b59-aa28-586907301221 -version = 1.0 +version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Command and Control", "Defense Evasion", "Exfiltration", "Exfiltration Over Alternative Protocol"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS Server History for a host"] -support_searches = ["ESCU - Discover DNS records"] -data_models = ["Network_Resolution"] -providing_technologies = ["Bro", "Splunk Stream"] +detection_searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "DNS record changed"] +mappings = {"analytics_story": "DNS Hijacking", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -360,65 +341,61 @@ The searches in this Analytic Story help you detect and investigate activities t [Data Protection] category = Abuse -creation_date = 2017-06-01 +creation_date = 2017-09-14 modification_date = 2017-09-14 id = 91c676cf-0b23-438d-abee-f6335e1fce33 -version = 1.0 +version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] -detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Defense Evasion", "Exfiltration"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Change_Analysis", "Endpoint", "Network_Resolution", "Network_Traffic", "Risk"] -providing_technologies = ["Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Detection of DNS Tunnels"] +mappings = {"analytics_story": "Data Protection", "category": ["Abuse"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. [Disabling Security Tools] category = Adversary Tactics -creation_date = 2018-04-09 +creation_date = 2020-02-04 modification_date = 2020-02-04 id = fcc27099-46a0-46b0-a271-5c7dab56b6f1 -version = 2.0 +version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] -detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg.exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["Command-Line Interface", "Defense Evasion", "Disabling Security Tools", "Execution", "Modify Existing Service", "Modify Registry", "New Service", "Persistence", "Privilege Escalation"], "mitre_technique_id": ["T1089"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Unload Sysmon Filter Driver", "Processes launching netsh", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service"] +mappings = {"analytics_story": "Disabling Security Tools", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). [Dynamic DNS] category = Malware -creation_date = 2017-11-21 +creation_date = 2018-09-06 modification_date = 2018-09-06 id = 8169f17b-ef68-4b59-aae8-586907301221 -version = 2.0 +version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Command and Control", "Defense Evasion", "Exfiltration", "Exfiltration Over Command and Control Channel", "Web Service"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src_ip"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Network_Resolution", "Network_Traffic", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] +mappings = {"analytics_story": "Dynamic DNS", "category": ["Malware"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. -[Emotet Malware (DHS Report TA18-201A)] +[Emotet Malware DHS Report TA18-201A ] category = Malware -creation_date = 2018-09-11 +creation_date = 2020-01-27 modification_date = 2020-01-27 id = bb9f5ed2-916e-4364-bb6d-91c310efcf52 -version = 1.0 +version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] -detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd.exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["Account Discovery", "AppInit DLLs", "Authentication Package", "Command and Control", "Command-Line Interface", "Commonly Used Port", "Defense Evasion", "Discovery", "Execution", "Lateral Movement", "Persistence", "Registry Run Keys / Start Folder", "Third-party Software"], "mitre_technique_id": ["T1110", "T1135", "T1193", "T1210"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security", "ESCU - Baseline of SMB Traffic - MLTK"] -data_models = ["Authentication", "Email", "Endpoint", "Network_Traffic", "Risk", "Updates", "Vulnerabilities", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Cuckoo", "DeepSight", "Linux", "Microsoft Exchange", "Microsoft Windows", "Nessus", "Palo Alto Firewall", "SMTP", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "VirusTotal", "Ziften", "macOS"] +detection_searches = ["Prohibited Software On Endpoint", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Registry Keys Used For Persistence", "Detection of tools built by NirSoft", "Suspicious Email Attachment Extensions", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Rare Executables", "Email Attachments With Lots Of Spaces"] +mappings = {"analytics_story": "Emotet Malware DHS Report TA18-201A ", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -426,17 +403,16 @@ The searches in this Analytic Story will help you find executables that are rare [Hidden Cobra Malware] category = Malware -creation_date = 2018-06-14 +creation_date = 2020-01-22 modification_date = 2020-01-22 id = baf7580b-d4b4-4774-8173-7d198e9da335 -version = 2.0 +version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] -detection_searches = ["ESCU - Create or delete windows shares using net.exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Command and Control", "Command-Line Interface", "Commonly Used Port", "Credential Access", "Execution", "Exfiltration", "Lateral Movement", "Persistence", "Remote Desktop Protocol", "Scripting"], "mitre_technique_id": ["T1059", "T1071", "T1076", "T1077", "T1110", "T1117", "T1126", "T1135", "T1202", "T1210"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Network_Resolution", "Network_Traffic", "Risk", "Vulnerabilities", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Nessus", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Create or delete windows shares using net exe", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Remote Desktop Network Traffic", "Detect Outbound SMB Traffic", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "First time seen command line argument", "Remote Desktop Process Running On System", "Suspicious File Write"] +mappings = {"analytics_story": "Hidden Cobra Malware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -445,33 +421,31 @@ Among other searches in this Analytic Story is a detection search that looks for [Host Redirection] category = Abuse -creation_date = 2017-06-18 +creation_date = 2017-09-14 modification_date = 2017-09-14 id = 2e8948a5-5239-406b-b56b-6c50fe268af4 -version = 1.0 +version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] -detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Defense Evasion", "Exfiltration", "Exfiltration Over Alternative Protocol"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Network_Resolution", "Risk"] -providing_technologies = ["Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "macOS"] +detection_searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Windows hosts file modification"] +mappings = {"analytics_story": "Host Redirection", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. [JBoss Vulnerability] category = Vulnerability -creation_date = 2016-10-04 +creation_date = 2017-09-14 modification_date = 2017-09-14 id = 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd -version = 1.0 +version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] -detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 4"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["Defense Evasion", "Discovery", "Exploitation of Vulnerability", "System Information Discovery"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] -support_searches = [] -data_models = ["Risk", "Vulnerabilities", "Web"] -providing_technologies = ["Apache", "Bluecoat", "Bro", "Nessus", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream"] +detection_searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers"] +mappings = {"analytics_story": "JBoss Vulnerability", "category": ["Vulnerability"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -491,33 +465,31 @@ It can also be helpful to examine various behaviors of and the parent of the pro [Kubernetes Scanning Activity] category = Cloud Security -creation_date = 2020-03-24 +creation_date = 2020-04-15 modification_date = 2020-04-15 id = a9ef59cf-e981-4e66-9eef-bb049f695c09 -version = 1.0 +version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] -mappings = {"cis20": [], "kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery"], "mitre_technique_id": ["T1190"], "nist": []} -investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src_ip", "ESCU - GCP Kubernetes activity by src_ip", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] -support_searches = [] -data_models = ["Risk"] -providing_technologies = ["AWS", "GCP", "Splunk Enterprise Security"] +detection_searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] +mappings = {"analytics_story": "Kubernetes Scanning Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. [Lateral Movement] category = Adversary Tactics -creation_date = 2016-09-13 +creation_date = 2020-02-04 modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad -version = 2.0 +version = 2 reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] -detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] -mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Lateral Movement", "Pass the Hash", "Persistence", "Privilege Escalation", "Remote Desktop Protocol", "Scheduled Task"], "mitre_technique_id": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks", "Schtasks scheduling job on remote system", "Remote Desktop Process Running On System"] +mappings = {"analytics_story": "Lateral Movement", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -527,17 +499,16 @@ If there is evidence of lateral movement, it is imperative for analysts to colle [Malicious PowerShell] category = Adversary Tactics -creation_date = 2016-09-18 +creation_date = 2017-08-23 modification_date = 2017-08-23 id = 2c8ff66e-0b57-42af-8ad7-912438a403fc -version = 4.0 +version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "mitre_technique_id": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Risk"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process With Obfuscation Techniques", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] +mappings = {"analytics_story": "Malicious PowerShell", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -552,50 +523,47 @@ In the event a system is suspected of having been compromised via a malicious we [Monitor Backup Solution] category = Best Practices -creation_date = 2017-06-15 +creation_date = 2017-09-12 modification_date = 2017-09-12 id = abe807c7-1eb6-4304-ac32-6e7aacdb891d -version = 1.0 +version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] -detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] -mappings = {"cis20": ["CIS 10"], "kill_chain_phases": [], "mitre_attack": [], "mitre_technique_id": [], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User"] -support_searches = ["ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] -data_models = ["Risk"] -providing_technologies = ["Netbackup", "Splunk Enterprise Security"] +detection_searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] +mappings = {"analytics_story": "Monitor Backup Solution", "category": ["Best Practices"], "usecase": "Compliance"} +support_searches = none +data_models = none +providing_technologies = none description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. [Monitor for Unauthorized Software] category = Best Practices -creation_date = 2017-06-26 +creation_date = 2017-09-15 modification_date = 2017-09-15 id = 8892a655-6205-43f7-abba-06460e38c8ae -version = 1.0 +version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] -mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["Execution"], "mitre_technique_id": [], "nist": ["ID.AM", "PR.DS"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] -data_models = ["Authentication", "Endpoint", "Risk", "Updates", "Vulnerabilities", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Nessus", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Prohibited Software On Endpoint"] +mappings = {"analytics_story": "Monitor for Unauthorized Software", "category": ["Best Practices"], "usecase": "Compliance"} +support_searches = none +data_models = none +providing_technologies = none description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. [Monitor for Updates] category = Best Practices -creation_date = 2017-08-15 +creation_date = 2017-09-15 modification_date = 2017-09-15 id = 9ef8d677-7b52-4213-a038-99cfc7acc2d8 -version = 1.0 +version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] -detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] -mappings = {"cis20": ["CIS 18"], "kill_chain_phases": [], "mitre_attack": [], "mitre_technique_id": [], "nist": ["PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] -support_searches = [] -data_models = ["Risk", "Updates"] -providing_technologies = ["Microsoft Windows", "Splunk Enterprise Security"] +detection_searches = ["No Windows Updates in a time frame"] +mappings = {"analytics_story": "Monitor for Updates", "category": ["Best Practices"], "usecase": "Compliance"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -603,34 +571,32 @@ Microsoft releases updates for Windows systems on a monthly cadence. They should [Netsh Abuse] category = Abuse -creation_date = 2017-01-04 +creation_date = 2017-01-05 modification_date = 2017-01-05 id = 2b1800dd-92f9-47ec-a981-fdf1351e5f65 -version = 1.0 +version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] -detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] -mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Command-Line Interface", "Defense Evasion", "Disabling Security Tools", "Execution", "Persistence"], "mitre_technique_id": [], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Processes created by netsh", "Processes launching netsh"] +mappings = {"analytics_story": "Netsh Abuse", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. [Orangeworm Attack Group] category = Malware -creation_date = 2018-06-14 +creation_date = 2020-01-22 modification_date = 2020-01-22 id = bb9f5ed2-916e-4364-bb6d-97c370efcf52 -version = 2.0 +version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] -detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule"] -mappings = {"cis20": ["CIS 2", "CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["Command-Line Interface", "Defense Evasion", "Disabling Security Tools", "Execution", "Modify Existing Service", "New Service", "Persistence", "Privilege Escalation", "Scripting"], "mitre_technique_id": ["T1050", "T1059", "T1117", "T1202"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "First time seen command line argument"] +mappings = {"analytics_story": "Orangeworm Attack Group", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -643,14 +609,13 @@ category = Adversary Tactics creation_date = 2019-04-29 modification_date = 2019-04-29 id = 57226b40-94f3-4ce5-b101-a75f67759c27 -version = 1.0 +version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] -detection_searches = ["ESCU - Detect Oulook.exe writing a .zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule"] -mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["Initial Access", "Spearphishing Attachment"], "mitre_technique_id": [], "nist": ["ID.AM", "PR.DS"]} -investigative_searches = ["ESCU - Get Parent Process Info"] -support_searches = [] -data_models = ["Endpoint"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +detection_searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file"] +mappings = {"analytics_story": "Phishing Payloads", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -663,17 +628,16 @@ This Analytic Story focuses on detecting signs that a malicious payload has been [Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns] category = Adversary Tactics -creation_date = 2018-07-24 +creation_date = 2020-01-22 modification_date = 2020-01-22 id = 988C59C5-0A1C-45B6-A555-0C62276E327E -version = 1.0 +version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] -detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["AppInit DLLs", "Authentication Package", "Command-Line Interface", "Execution", "Persistence", "PowerShell", "Registry Run Keys / Start Folder", "Scripting"], "mitre_technique_id": ["T1059", "T1117", "T1202"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Registry Keys Used For Persistence", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] +mappings = {"analytics_story": "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -706,66 +670,62 @@ If behavioral searches included in this story yield positive hits, iDefense reco [Prohibited Traffic Allowed or Protocol Mismatch] category = Best Practices -creation_date = 2017-04-18 +creation_date = 2017-09-11 modification_date = 2017-09-11 id = 6d13121c-90f3-446d-8ac3-27efbbc65218 -version = 1.0 +version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] -detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Defense Evasion", "Exfiltration", "Exfiltration Over Alternative Protocol"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Network_Resolution", "Network_Traffic", "Risk"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch"] +mappings = {"analytics_story": "Prohibited Traffic Allowed or Protocol Mismatch", "category": ["Best Practices"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. [Ransomware] category = Malware -creation_date = 2017-07-24 +creation_date = 2020-02-04 modification_date = 2020-02-04 id = cf309d0d-d4aa-4fbb-963d-1e79febd3756 -version = 1.1 +version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] -detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] -mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["AppInit DLLs", "Authentication Package", "Command and Control", "Commonly Used Port", "Defense Evasion", "Execution", "Exfiltration", "Exfiltration Over Alternative Protocol", "Impact", "Indicator Removal on Host", "Lateral Movement", "Masquerading", "Persistence", "Registry Run Keys / Start Folder", "Scheduled Task", "Windows Management Instrumentation"], "mitre_technique_id": ["T1110", "T1135", "T1210", "T1490"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk", "Updates", "Vulnerabilities", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Nessus", "Netbackup", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Scheduled tasks used in BadRabbit ransomware", "Suspicious wevtutil Usage", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Registry Keys Used For Persistence", "Common Ransomware Notes", "Remote Process Instantiation via WMI", "USN Journal Deletion", "Common Ransomware Extensions", "System Processes Run From Unexpected Locations", "TOR Traffic", "Schtasks used for forcing a reboot", "Spike in File Writes", "Unusually Long Command Line", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Unusually Long Command Line - MLTK"] +mappings = {"analytics_story": "Ransomware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. -[Router & Infrastructure Security] +[Router and Infrastructure Security] category = Best Practices -creation_date = 2017-06-01 +creation_date = 2017-09-12 modification_date = 2017-09-12 id = 91c676cf-0b23-438d-abee-f6335e177e77 -version = 1.0 +version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] -detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] -mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "mitre_technique_id": [], "nist": ["PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Risk"] -providing_technologies = ["Active Directory", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "macOS"] +detection_searches = ["Detect New Login Attempts to Routers"] +mappings = {"analytics_story": "Router and Infrastructure Security", "category": ["Best Practices"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. [SQL Injection] category = Adversary Tactics -creation_date = 2016-09-13 +creation_date = 2017-09-19 modification_date = 2017-09-19 id = 4f6632f5-449c-4686-80df-57625f59bab3 -version = 1.0 +version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] -detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] -mappings = {"cis20": ["CIS 13", "CIS 18", "CIS 4"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Commonly Used Port", "Defense Evasion", "Execution", "Exploitation of Vulnerability"], "mitre_technique_id": [], "nist": ["DE.CM", "ID.RA", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] -support_searches = [] -data_models = ["Authentication", "Risk", "Web"] -providing_technologies = ["Bro", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Splunk Stream", "macOS"] +detection_searches = ["SQL Injection with Long URLs"] +mappings = {"analytics_story": "SQL Injection", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -775,14 +735,13 @@ category = Malware creation_date = 2018-12-13 modification_date = 2018-12-13 id = c4b89506-fbcf-4cb7-bfd6-527e54789604 -version = 1.0 +version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] -detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] -mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["Command-Line Interface", "Credential Access", "Defense Evasion", "Discovery", "Execution", "Exploitation of Vulnerability", "Impact", "Lateral Movement", "Remote Desktop Protocol", "System Information Discovery"], "mitre_technique_id": ["T1076", "T1490"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk", "Updates", "Vulnerabilities", "Web"] -providing_technologies = ["Apache", "Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Nessus", "Netbackup", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Detect malicious requests to exploit JBoss servers", "Prohibited Software On Endpoint", "Common Ransomware Notes", "Remote Desktop Network Traffic", "Common Ransomware Extensions", "Batch File Write to System32", "Spike in File Writes", "Samsam Test File Write", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Bruteforce", "File with Samsam Extension"] +mappings = {"analytics_story": "SamSam Ransomware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -796,30 +755,28 @@ category = Vulnerability creation_date = 2018-01-08 modification_date = 2018-01-08 id = 6d3306f6-bb2b-4219-8609-8efad64032f2 -version = 1.0 +version = 1 reference = ["https://meltdownattack.com/"] -detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] -mappings = {"cis20": ["CIS 4"], "kill_chain_phases": [], "mitre_attack": [], "mitre_technique_id": [], "nist": ["DE.CM", "ID.RA", "PR.IP", "RS.MI"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] -data_models = ["Authentication", "Change_Analysis", "Risk", "Vulnerabilities"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Nessus", "Qualys", "Splunk Enterprise Security", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Spectre and Meltdown Vulnerable Systems"] +mappings = {"analytics_story": "Spectre And Meltdown Vulnerabilities", "category": ["Vulnerability"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. [Splunk Enterprise Vulnerability] category = Vulnerability -creation_date = 2016-09-13 +creation_date = 2017-09-19 modification_date = 2017-09-19 id = 4e692b96-de2d-4bd1-9105-37e2368a8db1 -version = 1.0 +version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] -detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] -mappings = {"cis20": ["CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "mitre_technique_id": [], "nist": ["DE.CM", "ID.RA", "PR.AC", "PR.IP", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] -support_searches = [] -data_models = ["Risk"] -providing_technologies = ["Splunk Enterprise", "Splunk Enterprise Security"] +detection_searches = ["Open Redirect in Splunk Web"] +mappings = {"analytics_story": "Splunk Enterprise Vulnerability", "category": ["Vulnerability"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -837,14 +794,13 @@ category = Vulnerability creation_date = 2018-06-14 modification_date = 2018-06-14 id = 1fc34cbc-34e9-43ba-87ab-6811c9e95400 -version = 1.0 +version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] -detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] -mappings = {"cis20": ["CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "mitre_technique_id": [], "nist": ["DE.CM", "ID.RA", "PR.AC", "PR.IP", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src_ip", "ESCU - Investigate Web Activity From src_ip"] -support_searches = [] -data_models = ["Network_Traffic", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Palo Alto Firewall", "Splunk Enterprise", "Splunk Enterprise Security", "Splunk Stream"] +detection_searches = ["Splunk Enterprise Information Disclosure"] +mappings = {"analytics_story": "Splunk Enterprise Vulnerability CVE-2018-11409", "category": ["Vulnerability"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -856,46 +812,43 @@ category = Cloud Security creation_date = 2018-02-09 modification_date = 2018-02-09 id = 2e8948a5-5239-406b-b56b-6c50f1268af3 -version = 1.0 +version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Execution"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] -support_searches = ["ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 Launches By User"] -data_models = [] -providing_technologies = ["AWS", "Splunk Enterprise Security"] +detection_searches = ["Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region"] +mappings = {"analytics_story": "Suspicious AWS EC2 Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. [Suspicious AWS Login Activities] category = Cloud Security -creation_date = 2018-02-24 +creation_date = 2019-05-01 modification_date = 2019-05-01 id = 2e8948a5-5239-406b-b56b-6c59f1268af3 -version = 1.0 +version = 1 reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] -detection_searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule"] -mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.DP"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN"] -support_searches = ["ESCU - Previously seen users in CloudTrail", "ESCU - Update previously seen users in CloudTrail"] -data_models = [] -providing_technologies = ["AWS"] +detection_searches = ["Detect new user AWS Console Login", "Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New Country"] +mappings = {"analytics_story": "Suspicious AWS Login Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. [Suspicious AWS S3 Activities] category = Cloud Security -creation_date = 2018-06-25 +creation_date = 2018-07-24 modification_date = 2018-07-24 id = 2e8948a5-5239-406b-b56b-6c50w3168af3 -version = 2.0 +version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] -detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] -mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution", "Exfiltration", "Initial Access"], "mitre_technique_id": [], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] -support_searches = ["ESCU - Baseline of S3 Bucket deletion activity by ARN", "ESCU - Previously seen S3 bucket access by remote IP"] -data_models = [] -providing_technologies = ["AWS", "Splunk Enterprise Security"] +detection_searches = ["Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets", "Detect S3 access from a new IP"] +mappings = {"analytics_story": "Suspicious AWS S3 Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -906,14 +859,13 @@ category = Cloud Security creation_date = 2018-05-07 modification_date = 2018-05-07 id = 2e8948a5-5239-406b-b56b-6c50f2168af3 -version = 1.0 +version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] -detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] -mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] -data_models = ["Authentication", "Endpoint", "Network_Traffic", "Risk"] -providing_technologies = ["AWS", "Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] +mappings = {"analytics_story": "Suspicious AWS Traffic", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -922,49 +874,46 @@ The searches in this Analytic Story will monitor your AWS network traffic for ev [Suspicious Command-Line Executions] category = Adversary Tactics -creation_date = 2017-10-09 +creation_date = 2020-02-03 modification_date = 2020-02-03 id = f4368ddf-d59f-4192-84f6-778ac5a3ffc7 -version = 2.1 +version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] -detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd.exe - Rule", "ESCU - Detect Use of cmd.exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["Command-Line Interface", "Defense Evasion", "Execution", "Masquerading", "Persistence", "Scripting"], "mitre_technique_id": ["T1059", "T1117", "T1202"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["System Processes Run From Unexpected Locations", "Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK"] +mappings = {"analytics_story": "Suspicious Command-Line Executions", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. [Suspicious DNS Traffic] category = Adversary Tactics -creation_date = 2016-09-13 +creation_date = 2017-09-18 modification_date = 2017-09-18 id = 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 -version = 1.0 +version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] -detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] -mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Defense Evasion", "Exfiltration", "Exfiltration Over Alternative Protocol"], "mitre_technique_id": ["T1071"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] -data_models = ["Authentication", "Endpoint", "Network_Resolution", "Network_Traffic", "Risk"] -providing_technologies = ["Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Excessive DNS Failures"] +mappings = {"analytics_story": "Suspicious DNS Traffic", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. [Suspicious Emails] category = Adversary Tactics -creation_date = 2017-03-24 +creation_date = 2020-01-27 modification_date = 2020-01-27 id = 2b1800dd-92f9-47ec-a981-fdf1351e5d55 -version = 1.0 +version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] -detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] -mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Execution"], "mitre_technique_id": ["T1193"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - DNSTwist Domain Names"] -data_models = ["Authentication", "Email", "Risk", "UEBA", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Cuckoo", "DeepSight", "Linux", "Microsoft Exchange", "Microsoft Windows", "Palo Alto Firewall", "SMTP", "Splunk Enterprise", "Splunk Enterprise Security", "Splunk Stream", "VirusTotal", "macOS"] +detection_searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions"] +mappings = {"analytics_story": "Suspicious Emails", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -974,17 +923,16 @@ Once a phishing message has been detected, the next steps are to answer the foll [Suspicious MSHTA Activity] category = Adversary Tactics -creation_date = 2018-08-07 +creation_date = 2020-02-03 modification_date = 2020-02-03 id = 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 -version = 1.1 +version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] -detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd.exe - Rule", "ESCU - Detect mshta.exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] -mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["AppInit DLLs", "Authentication Package", "Command-Line Interface", "Execution", "Persistence", "Registry Run Keys / Start Folder"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] -data_models = ["Authentication", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments"] +mappings = {"analytics_story": "Suspicious MSHTA Activity", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -995,14 +943,13 @@ category = Adversary Tactics creation_date = 2020-04-02 modification_date = 2020-04-02 id = 9cbd34af-8f39-4476-a423-bacd126c750b -version = 1.0 +version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] -detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] -mappings = {"cis20": ["CIS 16"], "kill_chain_phases": [], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] -support_searches = [] -data_models = [] -providing_technologies = ["Okta"] +detection_searches = ["Okta Account Lockout Events", "Okta Failed SSO Attempts", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta User Logins From Multiple Cities"] +mappings = {"analytics_story": "Suspicious Okta Activity", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -1010,17 +957,16 @@ With people moving quickly to adopt web-based applications and ways to manage th [Suspicious WMI Use] category = Adversary Tactics -creation_date = 2017-01-13 +creation_date = 2018-10-23 modification_date = 2018-10-23 id = c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 -version = 2.0 +version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] -detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Persistence", "Windows Management Instrumentation", "Windows Management Instrumentation Event Subscription"], "mitre_technique_id": [], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Risk"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["WMI Permanent Event Subscription", "Remote Process Instantiation via WMI", "WMI Temporary Event Subscription", "Process Execution via WMI", "WMI Permanent Event Subscription - Sysmon", "Script Execution via WMI", "Remote WMI Command Attempt"] +mappings = {"analytics_story": "Suspicious WMI Use", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -1031,14 +977,13 @@ category = Adversary Tactics creation_date = 2018-05-31 modification_date = 2018-05-31 id = 2b1800dd-92f9-47dd-a981-fdf1351e5d55 -version = 1.0 +version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] -detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg.exe used to hide files/directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Accessibility Features", "AppInit DLLs", "Application Shimming", "Authentication Package", "Change Default File Association", "Defense Evasion", "Lateral Movement", "Local Port Monitor", "Modify Registry", "Persistence", "Privilege Escalation", "Registry Run Keys / Start Folder"], "mitre_technique_id": ["T1183"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = [] -data_models = ["Authentication", "Change_Analysis", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Monitor Registry Keys for Print Monitors", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Suspicious Changes to File Associations"] +mappings = {"analytics_story": "Suspicious Windows Registry Activities", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -1049,31 +994,29 @@ category = Cloud Security creation_date = 2018-04-09 modification_date = 2018-04-09 id = 73de57ef-0dfc-411f-b1e7-fa24428aeae0 -version = 1.0 +version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] -mappings = {"cis20": ["CIS 1"], "kill_chain_phases": [], "mitre_attack": [], "mitre_technique_id": [], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] -data_models = [] -providing_technologies = ["AWS", "Splunk Enterprise Security"] +detection_searches = ["EC2 Instance Modified With Previously Unseen User"] +mappings = {"analytics_story": "Unusual AWS EC2 Modifications", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. [Unusual Processes] category = Malware -creation_date = 2016-08-09 +creation_date = 2020-02-04 modification_date = 2020-02-04 id = f4368e3f-d59f-4192-84f6-748ac5a3ddb6 -version = 2.1 +version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] -detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] -mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["Accessibility Features", "Defense Evasion", "Execution", "Masquerading", "Rundll32"], "mitre_technique_id": [], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] -data_models = ["Authentication", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Uncommon Processes On Endpoint", "System Processes Run From Unexpected Locations", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Detect Rare Executables", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal"] +mappings = {"analytics_story": "Unusual Processes", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -1081,33 +1024,31 @@ In the event an unusual process is identified, it is imperative to better unders [Use of Cleartext Protocols] category = Best Practices -creation_date = 2016-09-13 +creation_date = 2017-09-15 modification_date = 2017-09-15 id = 826e6431-aeef-41b4-9fc0-6d0985d65a21 -version = 1.0 +version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] -detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] -mappings = {"cis20": ["CIS 14", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Reconnaissance"], "mitre_attack": ["Collection", "Credential Access", "Lateral Movement"], "mitre_technique_id": [], "nist": ["DE.AE", "PR.AC", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Endpoint", "Network_Traffic", "Risk"] -providing_technologies = ["Bluecoat", "Bro", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream"] +detection_searches = ["Protocols passing authentication in cleartext"] +mappings = {"analytics_story": "Use of Cleartext Protocols", "category": ["Best Practices"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. [Web Fraud Detection] category = Abuse -creation_date = 2018-07-12 +creation_date = 2018-10-08 modification_date = 2018-10-08 id = 31337aaa-bc22-4752-b599-ef112dq1dq7a -version = 1.0 +version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] -detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] -mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Create Account", "Initial Access", "Persistence", "Valid Accounts"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session_id"] -support_searches = [] -data_models = ["Email"] -providing_technologies = ["Microsoft Exchange", "Splunk Enterprise Security", "Splunk Stream"] +detection_searches = ["Web Fraud - Account Harvesting", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed"] +mappings = {"analytics_story": "Web Fraud Detection", "category": ["Abuse"], "usecase": "Fraud Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -1118,17 +1059,16 @@ Another search detects incidents wherein a single password is used across multip [Windows Defense Evasion Tactics] category = Adversary Tactics -creation_date = 2017-10-11 +creation_date = 2018-05-31 modification_date = 2018-05-31 id = 56e24a28-5003-4047-b2db-e8f3c4618064 -version = 1.0 +version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] -detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib.exe - Rule", "ESCU - Reg.exe used to hide files/directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg.exe Process - Rule"] -mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Disabling Security Tools", "Lateral Movement", "Modify Registry", "Persistence"], "mitre_technique_id": [], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Risk"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Remote Registry Key modifications", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Suspicious Reg exe Process", "Hiding Files And Directories With Attrib exe"] +mappings = {"analytics_story": "Windows Defense Evasion Tactics", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -1137,14 +1077,13 @@ category = Malware creation_date = 2018-01-26 modification_date = 2018-01-26 id = 30552a76-ac78-48e4-b3c0-de4e34e9563d -version = 1.0 +version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] -detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Change Default File Association", "Execution", "Persistence"], "mitre_technique_id": [], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Risk"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Execution of File with Multiple Extensions", "Suspicious Changes to File Associations", "Execution of File With Spaces Before Extension"] +mappings = {"analytics_story": "Windows File Extension and Association Abuse", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -1154,50 +1093,47 @@ Run the searches in this story to detect and investigate suspicious behavior tha [Windows Log Manipulation] category = Adversary Tactics -creation_date = 2017-02-17 +creation_date = 2017-09-12 modification_date = 2017-09-12 id = b6db2c60-a281-48b4-95f1-2cd99ed56835 -version = 2.0 +version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] -detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] -mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Impact", "Indicator Removal on Host"], "mitre_technique_id": ["T1490"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Risk", "Vulnerabilities", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Nessus", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Suspicious wevtutil Usage", "Windows Event Log Cleared", "USN Journal Deletion", "Deleting Shadow Copies"] +mappings = {"analytics_story": "Windows Log Manipulation", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +support_searches = none +data_models = none +providing_technologies = none description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). [Windows Persistence Techniques] category = Adversary Tactics -creation_date = 2017-04-19 +creation_date = 2018-05-31 modification_date = 2018-05-31 id = 30874d4f-20a1-488f-85ec-5d52ef74e3f9 -version = 2.0 +version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] -detection_searches = ["ESCU - Detect Path Interception By Creation Of program.exe - Rule", "ESCU - Hiding Files And Directories With Attrib.exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg.exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg.exe used to hide files/directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] -mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["AppInit DLLs", "Application Shimming", "Authentication Package", "Defense Evasion", "Disabling Security Tools", "Execution", "Lateral Movement", "Local Port Monitor", "Modify Existing Service", "New Service", "Persistence", "Privilege Escalation", "Registry Run Keys / Start Folder", "Scheduled Task"], "mitre_technique_id": [], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = [] -data_models = ["Authentication", "Change_Analysis", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Monitor Registry Keys for Print Monitors", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters", "Reg exe used to hide files directories via registry keys", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Detect Path Interception By Creation Of program exe", "Reg exe Manipulating Windows Services Registry Keys"] +mappings = {"analytics_story": "Windows Persistence Techniques", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. [Windows Privilege Escalation] category = Adversary Tactics -creation_date = 2017-12-07 +creation_date = 2020-02-04 modification_date = 2020-02-04 id = 644e22d3-598a-429c-a007-16fdb802cae5 -version = 2.0 +version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] -detection_searches = ["ESCU - Child Processes of Spoolsv.exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] -mappings = {"cis20": ["CIS 2", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["Accessibility Features", "Execution", "Exploitation for Privilege Escalation", "Persistence", "Privilege Escalation"], "mitre_technique_id": ["T1183"], "nist": ["DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] -support_searches = [] -data_models = ["Authentication", "Endpoint", "Risk", "Web"] -providing_technologies = ["Bluecoat", "Bro", "Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Palo Alto Firewall", "Splunk Enterprise Security", "Splunk Stream", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Child Processes of Spoolsv exe", "Registry Keys Used For Privilege Escalation", "Overwriting Accessibility Binaries", "Uncommon Processes On Endpoint"] +mappings = {"analytics_story": "Windows Privilege Escalation", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -1206,14 +1142,13 @@ category = Malware creation_date = 2017-11-02 modification_date = 2017-11-02 id = 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 -version = 3.0 +version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] -detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg.exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule"] -mappings = {"cis20": ["CIS 2", "CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["Defense Evasion", "Disabling Security Tools", "Execution", "Modify Existing Service", "New Service", "Persistence", "Privilege Escalation"], "mitre_technique_id": ["T1050"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] -support_searches = ["ESCU - Previously Seen Running Windows Services"] -data_models = ["Authentication", "Endpoint", "Risk"] -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Linux", "Microsoft Windows", "Splunk Enterprise Security", "Sysmon", "Tanium", "Ziften", "macOS"] +detection_searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys"] +mappings = {"analytics_story": "Windows Service Abuse", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +support_searches = none +data_models = none +providing_technologies = none description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. diff --git a/package/default/macros.conf b/package/default/macros.conf index 4d1ab99d3e..1dae9053d7 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,26 +1,18 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-04-17T19:06:18 UTC +# On Date: 2020-05-06T14:58:49 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# -[access_lsass_memory_for_dump_creation_filter] -definition = search * -description = Use this macro to add additional filters for access lsass memory for dump creation +[aws_cloudwatchlogs_eks] +definition = sourcetype="aws:cloudwatchlogs:eks" +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. -[attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter] -definition = search * -description = Use this macro to add additional filter for attempt to set default powershell execution policy to unrestricted or bypass - -[attempted_credential_dump_from_registry_via_reg_filter] -definition = search * -description = Use this macro to add additional filter for attempted credential dump from registry via reg - -[attrib_to_hide_files_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. +[aws_s3_accesslogs] +definition = sourcetype=aws:s3:accesslogs +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. [brand_abuse_dns] definition = lookup update=true brandMonitoring_lookup domain as query OUTPUT domain_abuse | search domain_abuse=true @@ -34,94 +26,30 @@ description = This macro limits the output to only domains that are in the brand definition = lookup update=true brandMonitoring_lookup domain as urls OUTPUT domain_abuse | search domain_abuse=true description = This macro limits the output to only domains that are in the brand monitoring lookup file -[change_file_association_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[children_of_spoolsv_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - [clients_connecting_to_multiple_dns_servers_output_filter] definition = search * description = Use this macro to add additional filters for monitoring clients connecting to multiple dns servers -[common_ransomware_extensions_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. +[cloudtrail] +definition = sourcetype=aws:cloudtrail +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. -[common_ransomware_notes_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. +[cloudwatch_eks] +definition = sourcetype="aws:cloudwatchlogs:eks" +description = customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch eks logs. Replace the macro definition with configurations for your Splunk Environmnent. -[container_implant_aws_detection_filter] -definition = search * -description = Use this macro to add additional filters +[cloudwatch_vpc] +definition = sourcetype=aws:cloudwatchlogs:vpcflow +description = customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch vpc logs. Replace the macro definition with configurations for your Splunk Environmnent. -[container_implant_gcp_detection_filter] -definition = search * -description = Use this macro to add additional filters - -[create_local_admin_via_net_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. +[cloudwatchlogs_vpcflow] +definition = sourcetype=aws:cloudwatchlogs:vpcflow +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. [create_or_delete_windows_shares_filter] definition = search * description = Use this macro to add additional filter for create or delete windows shares -[create_remote_thread_into_lsass_filter] -definition = search * -description = Use this macro to add additional filter for create remote thread into lsass - -[creation_of_shadow_copy_filter] -definition = search * -description = Use this macro to add additional filter for creation of shadow copy - -[creation_of_shadow_copy_with_wmic_and_powershell_filter] -definition = search * -description = Use this macro to add additional filter for creation of shadow copy with wmic and powershell - -[cred_dump_via_copy_from_shadowcopy_filter] -definition = search * -description = Use this macro to add additional filter for cred dump via copy from shadowcopy - -[cred_dump_via_symlink_shadowcopy_filter] -definition = search * -description = Use this macro to add additional filter for cred dump via symlink shadowcopy - -[detect_activity_related_to_pass_the_hash_attacks_filter] -definition = search * -description = Use this macro to add additional filters for detect activity related to pass the hash attacks - -[detect_credential_dumping_through_LSASS_access_filter] -definition = search * -description = Use this macro to add additional filter for detect credential dumping through LSASS access - -[detect_mimikatz_using_loaded_images_filter] -definition = search * -description = Use this macro to add additional filter for detect mimikatz using loaded images - -[dns_query_length_mltk_filter] -definition = search * -description = Use this macro to add additional filters for monitoring DNS query length using MLTK - -[dns_query_length_with_high_standard_deviation_filter] -definition = search * -description = Use this macro to add additional filters for monitoring DNS query length with high standard deviation - -[dns_record_changed_filter] -definition = search * -description = Use this macro to add additional filters for monitoring DNS records changed - -[dragonfly_schtasks_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[dump_lsass_via_comsvcs_dll_filter] -definition = search * -description = Use this macro to add additional filter for dump lsass via comsvcs dll filter - [dynamic_dns_providers] definition = lookup update=true dynamic_dns_providers_default dynamic_dns_domains as query OUTPUTNEW isDynDNS_default | lookup update=true dynamic_dns_providers_local dynamic_dns_domains as query OUTPUTNEW isDynDNS_local| eval isDynDNS = coalesce(isDynDNS_default, isDynDNS_local)|fields - isDynDNS_default, isDynDNS_local| search isDynDNS=True description = This macro limits the output of the query field to dynamic dns domains. It looks up the domains in a file provided by Splunk and one intended to be updated by the end user. @@ -130,22 +58,10 @@ description = This macro limits the output of the query field to dynamic dns dom definition = lookup update=true dynamic_dns_providers_default dynamic_dns_domains as url OUTPUTNEW isDynDNS_default | lookup update=true dynamic_dns_providers_local dynamic_dns_domains as url OUTPUTNEW isDynDNS_local| eval isDynDNS = coalesce(isDynDNS_default, isDynDNS_local)|fields - isDynDNS_default, isDynDNS_local| search isDynDNS=True description = This is a description -[ec2_excessive_runinstances_mltk_input_filter] -definition = search * -description = Use this macro to add additional filters for monitoring ec2 runinstances [eg - src_user != 'someUserNameExperiencingFalsePositives']. - -[ec2_excessive_terminateinstances_mltk_input_filter] -definition = search * -description = Use this macro to add additional filters for monitoring ec2 terminateinstances [eg - src_user != 'someUserNameExperiencingFalsePositives']. - [ec2_modification_api_calls] definition = (eventName=AssociateAddress OR eventName=AssociateIamInstanceProfile OR eventName=AttachClassicLinkVpc OR eventName=AttachNetworkInterface OR eventName=AttachVolume OR eventName=BundleInstance OR eventName=DetachClassicLinkVpc OR eventName=DetachVolume OR eventName=GetConsoleOutput OR eventName=GetConsoleScreenshot OR eventName=ModifyInstanceAttribute OR eventName=ModifyInstancePlacement OR eventName=MonitorInstances OR eventName=RebootInstances OR eventName=ResetInstanceAttribute OR eventName=StartInstances OR eventName=StopInstances OR eventName=TerminateInstances OR eventName=UnmonitorInstances) description = This is a list of AWS event names that have to do with modifying Amazon EC2 instances -[email_files_not_in_outlook_directory_filter] -definition = search * -description = Use this macro to add additional filters to exclude false positive results - [evilginx_phishlets_0365] definition = (query=login* AND query=www*) description = This limits the query fields to domains that are associated with evilginx masquerading as Office 365 @@ -174,98 +90,46 @@ description = This limits the query fields to domains that are associated with e definition = (query=outlook* AND query=login* AND query=account*) description = This limits the query fields to domains that are associated with evilginx masquerading as Outlook -[file_write_spikes_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - [filter_rare_process_whitelist] definition = lookup update=true lookup_rare_process_whitelist_default process as process OUTPUTNEW whitelist | where whitelist="false" | lookup update=true lookup_rare_process_whitelist_local process as process OUTPUT whitelist | where whitelist="false" description = This macro is intended to whitelist processes that have been definied as rare -[first_time_seen_cmd_line_filter] -definition = search * -description = Use this macro to add additional filters for first time seen command line, you can exclude legitimate parent_processes that spawn cmd.exe. Eg- seach parent_process_name != "foo" +[google_gcp_pubnet_message] +definition = sourcetype="google:gcp:pubsub:message" +description = customer specific splunk configurations(eg- index, source, sourcetype) for Google GCP. Replace the macro definition with configurations for your Splunk Environmnent. + +[google_gcp_pubsub_message] +definition = sourcetype="google:gcp:pubsub:message" +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. [is_windows_system_file] definition = lookup update=true is_windows_system_file filename as process_name OUTPUT systemFile | search systemFile=true description = This macro limits the output to process names that are in the Windows System directory -[kubernetes_aws_scan_fingerprint_detection] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_gcp_scan_fingerprint_detection] -definition = search * -description = Use this macro to add additional filters - -[kubernetes_pods_aws_scan_fingerprint_detection] -definition = search * -description = Use this macro to add additional filters - -[lnk_executing_a_process_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[malicious_powershell_process_obfuscation_techniques_output_filter] -definition = search * -description = Use this macro to add output filters for Malicious PowerShell Process With Obfuscation Techniques. +[netbackup] +definition = sourcetype="netbackup_logs" +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. [network_acl_events] definition = (eventName = CreateNetworkAcl OR eventName = CreateNetworkAclEntry OR eventName = DeleteNetworkAcl OR eventName = DeleteNetworkAclEntry OR eventName = ReplaceNetworkAclEntry OR eventName = ReplaceNetworkAclAssociation) description = This is a list of AWS event names that are associated with Network ACLs -[okta_failed_sso_attempt_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[okta_multiple_users_with_auth_failures_from_ip_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[okta_user_lockouts_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[okta_user_logins_from_multiple_cities_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[outbound_smb_connections_filter] -definition = search * -description = Use this macro to add additional filters for outbound SMB traffic detection - -[outlook_writing_zip_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - -[previously_seen_cloud_compute_creations_by_user_input_filter] -definition = search * -description = Use this macro to add additional filters for monitoring users that create cloud compute images +[okta] +definition = eventtype=okta_log +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. [previously_seen_cloud_compute_creations_by_user_search_window_begin_offset] definition = -70m@m description = Use this macro to determine how far into the past the window should be to determine if the user is new or not -[previously_seen_cloud_compute_image_input_filter] -definition = search * -description = Use this macro to add additional filters for monitoring cloud compute images - [previously_seen_cloud_compute_image_search_window_begin_offset] definition = -70m@m description = Use this macro to determine how far into the past the window should be to determine if the image is new or not -[previously_seen_cloud_compute_instance_types_input_filter] -definition = search * -description = Use this macro to add additional filters for monitoring cloud compute instance types - [previously_seen_cloud_compute_instance_types_search_window_begin_offset] definition = -70m@m description = Use this macro to determine how far into the past the window should be to determine if the instance type is new or not -[previously_seen_cloud_regions_input_filter] -definition = search * -description = Use this macro to add additional filters for monitoring your cloud regions - [previously_seen_cloud_regions_search_window_begin_offset] definition = -70m@m description = Use this macro to determine how far into the past the window should be to determine if the region is new or not @@ -286,25 +150,13 @@ description = This macro limits the output to files that have extensions associa definition = lookup ransomware_notes_lookup ransomware_notes as file_name OUTPUT status as "Known Ransomware Notes" | search "Known Ransomware Notes"=True description = This macro limits the output to files that have been identified as a ransomware note -[rare_executables_on_endpoint_filter] -definition = search * -description = Update this macro to filter out false positives - -[remote_desktop_network_traffic_filter] -definition = search * -description = Use this macro to add additional filters for remote desktop network traffic - -[remote_desktop_process_running_on_system_filter] -definition = search * -description = Use this macro to add additional filters for remote desktop process running on system - [remove_valid_domains] definition = eval domain=trim(domain,"*") | search NOT[| inputlookup domains] NOT[ |inputlookup cim_corporate_email_domain_lookup] NOT[inputlookup cim_corporate_web_domain_lookup] | eval domain="*"+domain+"*" description = This macro removes valid domains from the output -[schtasks_scheduling_job_on_remote_system_filter] -definition = search * -description = Use this macro to add additional filters for schtasks scheduling job on remote system +[s3_accesslogs] +definition = sourcetype=aws:s3:accesslogs +description = customer specific splunk configurations(eg- index, source, sourcetype) for AWS cloudwatch vpc logs. Replace the macro definition with configurations for your Splunk Environmnent. [security_content_ctime(1)] args = field @@ -319,71 +171,795 @@ description = search data model's summaries only definition = (eventName=AuthorizeSecurityGroupIngress OR eventName=CreateSecurityGroup OR eventName=DeleteSecurityGroup OR eventName=DescribeClusterSecurityGroups OR eventName=DescribeDBSecurityGroups OR eventName=DescribeSecurityGroupReferences OR eventName=DescribeSecurityGroups OR eventName=DescribeStaleSecurityGroups OR eventName=RevokeSecurityGroupIngress OR eventName=UpdateSecurityGroupRuleDescriptionsIngress) description = This macro is a list of AWS event names associated with security groups -[smb_traffic_spike_filter] -definition = search * -description = Use this macro to add additional filters for SMB traffic spike detection - -[smb_traffic_spike_mltk_filter] -definition = search * -description = Use this macro to add additional filters for SMB traffic spike detection using MLKT +[stream_http] +definition = sourcetype=stream:http +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. [suspicious_email_attachments] definition = lookup update=true is_suspicious_file_extension_lookup file_name OUTPUT suspicious | search suspicious=true description = This macro limits the output to email attachments that have suspicious extensions -[suspicious_email_attachments_filter] -definition = search * -description = Use this macro to add additional filters for suspicious email attachments - -[suspicious_reg_process_filter] -definition = search * -description = Update this macro to limit the output results to filter out false positives. - [suspicious_writes] definition = lookup suspicious_writes_lookup file as file_name OUTPUT note as "Reference" | search "Reference" != False description = This macro limites the output to file names that have been marked as suspicious [sysmon] -definition = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" -description = customer specific splunk configurations(eg- index, source, sourcetype) for Windows Sysmon Logs. Replace the macro definition with configurations for your Splunk Environmnent. +definition = sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. [system_network_configuration_discovery_tools] definition = (process_name= "arp.exe" OR process_name= "at.exe" OR process_name= "attrib.exe" OR process_name= "cscript.exe" OR process_name= "dsquery.exe" OR process_name= "hostname.exe" OR process_name= "ipconfig.exe" OR process_name= "mimikatz.exe" OR process_name= "nbstat.exe" OR process_name= "net.exe" OR process_name= "netsh.exe" OR process_name= "nslookup.exe" OR process_name= "ping.exe" OR process_name= "quser.exe" OR process_name= "qwinsta.exe" OR process_name= "reg.exe" OR process_name= "runas.exe" OR process_name= "sc.exe" OR process_name= "schtasks.exe" OR process_name= "ssh.exe" OR process_name= "systeminfo.exe" OR process_name= "taskkill.exe" OR process_name= "telnet.exe" OR process_name= "tracert.exe" OR process_name="wscript.exe" OR process_name= "xcopy.exe") description = This macro is a list of process that can be used to discover the network configuration -[unauthorized_dns_servers_filter] -definition = search * -description = Use this macro to add additional filters for DNS Query Requests Resolved by Unauthorized DNS Servers detection - [uncommon_processes] definition = lookup update=true lookup_uncommon_processes_default process_name as process_name outputnew uncommon_default,category_default,analytic_story_default,kill_chain_phase_default,mitre_attack_default | lookup update=true lookup_uncommon_processes_local process_name as process_name outputnew uncommon_local,category_local,analytic_story_local,kill_chain_phase_local,mitre_attack_local | eval uncommon = coalesce(uncommon_default, uncommon_local), analytic_story = coalesce(analytic_story_default, analytic_story_local), category=coalesce(category_default, category_local), kill_chain_phase=coalesce(kill_chain_phase_default, kill_chain_phase_local), mitre_attack=coalesce(mitre_attack_default, mitre_attack_local) | fields - analytic_story_default, analytic_story_local, category_default, category_local, kill_chain_phase_default, kill_chain_phase_local, mitre_attack_default, mitre_attack_local, uncommon_default, uncommon_local | search uncommon=true description = This macro limits the output to processes that have been marked as uncommon -[uncommon_processes_filter] +[wineventlog_security] +definition = eventtype=wineventlog_security +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. + +[wineventlog_system] +definition = eventtype=wineventlog_system +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. + +[wmi] +definition = sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" +description = customer specific splunk configurations(eg- index, source, sourcetype). Replace the macro definition with configurations for your Splunk Environmnent. + +[aws_cloud_provisioning_from_previously_unseen_city_filter] definition = search * -description = Update this macro to limit the output results to filter out false positives. +description = Update this macro to limit the output results to filter out false positives. + +[aws_cloud_provisioning_from_previously_unseen_country_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[aws_cloud_provisioning_from_previously_unseen_ip_address_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[aws_cloud_provisioning_from_previously_unseen_region_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[aws_cross_account_activity_from_previously_unseen_account_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[aws_network_access_control_list_created_with_all_open_ports_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[aws_network_access_control_list_deleted_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[abnormally_high_aws_instances_launched_by_user_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[abnormally_high_aws_instances_launched_by_user___mltk_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[abnormally_high_aws_instances_terminated_by_user_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[abnormally_high_aws_instances_terminated_by_user___mltk_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[access_lsass_memory_for_dump_creation_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[amazon_eks_kubernetes_pod_scan_detection_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[amazon_eks_kubernetes_cluster_scan_detection_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[attempt_to_add_certificate_to_untrusted_store_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[attempt_to_stop_security_service_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[attempted_credential_dump_from_registry_via_reg_exe_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[batch_file_write_to_system32_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[child_processes_of_spoolsv_exe_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[clients_connecting_to_multiple_dns_servers_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[cloud_compute_instance_created_by_previously_unseen_user_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[cloud_compute_instance_created_with_previously_unseen_image_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[cloud_compute_instance_created_with_previously_unseen_instance_type_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[cloud_compute_instance_started_in_previously_unused_region_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[common_ransomware_extensions_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[common_ransomware_notes_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[create_remote_thread_into_lsass_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[create_local_admin_accounts_using_net_exe_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[create_or_delete_windows_shares_using_net_exe_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[creation_of_shadow_copy_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[creation_of_shadow_copy_with_wmic_and_powershell_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[credential_dumping_via_copy_command_from_shadow_copy_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[credential_dumping_via_symlink_to_shadow_copy_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[dns_query_length_outliers___mltk_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[dns_query_length_with_high_standard_deviation_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[dns_query_requests_resolved_by_unauthorized_dns_servers_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[dns_record_changed_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[deleting_shadow_copies_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_api_activity_from_users_without_mfa_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_aws_api_activities_from_unapproved_accounts_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_aws_console_login_by_user_from_new_city_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_aws_console_login_by_user_from_new_country_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_aws_console_login_by_user_from_new_region_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_activity_related_to_pass_the_hash_attacks_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_credential_dumping_through_lsass_access_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_dns_requests_to_phishing_sites_leveraging_evilginx2_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_excessive_account_lockouts_from_endpoint_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_excessive_user_account_lockouts_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_large_outbound_icmp_packets_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_long_dns_txt_record_response_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_mimikatz_using_loaded_images_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_mimikatz_via_powershell_and_eventcode_4703_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_new_local_admin_account_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_new_login_attempts_to_routers_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_new_open_s3_buckets_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_oulook_exe_writing_a__zip_file_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_outbound_smb_traffic_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_path_interception_by_creation_of_program_exe_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_prohibited_applications_spawning_cmd_exe_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_psexec_with_accepteula_flag_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_rare_executables_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_s3_access_from_a_new_ip_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_spike_in_aws_api_activity_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_spike_in_network_acl_activity_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_spike_in_s3_bucket_deletion_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_spike_in_security_group_activity_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_spike_in_blocked_outbound_traffic_from_your_aws_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_usb_device_insertion_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_unauthorized_assets_by_mac_address_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_use_of_cmd_exe_to_launch_script_interpreters_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_attackers_scanning_for_vulnerable_jboss_servers_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_hosts_connecting_to_dynamic_domain_providers_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_malicious_requests_to_exploit_jboss_servers_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_mshta_exe_running_scripts_in_command_line_arguments_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_new_api_calls_from_user_roles_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_new_user_aws_console_login_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_processes_used_for_system_network_configuration_discovery_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detect_web_traffic_to_dynamic_domain_providers_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detection_of_dns_tunnels_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[detection_of_tools_built_by_nirsoft_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[disabling_remote_user_account_control_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[dump_lsass_via_comsvcs_dll_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[ec2_instance_modified_with_previously_unseen_user_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[ec2_instance_started_in_previously_unseen_region_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[ec2_instance_started_with_previously_unseen_ami_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[ec2_instance_started_with_previously_unseen_instance_type_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[ec2_instance_started_with_previously_unseen_user_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[email_attachments_with_lots_of_spaces_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[email_files_written_outside_of_the_outlook_directory_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[email_servers_sending_high_volume_traffic_to_hosts_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[excessive_dns_failures_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[execution_of_file_with_spaces_before_extension_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[execution_of_file_with_multiple_extensions_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[extended_period_without_successful_netbackup_backups_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[file_with_samsam_extension_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[first_time_seen_running_windows_service_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[first_time_seen_command_line_argument_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[gcp_gcr_container_uploaded_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[gcp_kubernetes_cluster_scan_detection_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[hiding_files_and_directories_with_attrib_exe_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[hosts_receiving_high_volume_of_network_traffic_from_email_server_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[identify_new_user_accounts_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[large_volume_of_dns_any_queries_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[macos___re_opened_applications_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[malicious_powershell_process___connect_to_internet_with_hidden_window_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[malicious_powershell_process___encoded_command_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[malicious_powershell_process___execution_policy_bypass_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[malicious_powershell_process___multiple_suspicious_command_line_arguments_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[malicious_powershell_process_with_obfuscation_techniques_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[monitor_dns_for_brand_abuse_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[monitor_email_for_brand_abuse_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[monitor_registry_keys_for_print_monitors_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[monitor_web_traffic_for_brand_abuse_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[multiple_okta_users_with_invalid_credentails_from_the_same_ip_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[new_container_uploaded_to_aws_ecr_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[no_windows_updates_in_a_time_frame_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[okta_account_lockout_events_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[okta_failed_sso_attempts_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[okta_user_logins_from_multiple_cities_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[open_redirect_in_splunk_web_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[osquery_pack___coldroot_detection_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[overwriting_accessibility_binaries_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[process_execution_via_wmi_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[processes_tapping_keyboard_events_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[processes_created_by_netsh_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[processes_launching_netsh_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[prohibited_network_traffic_allowed_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[prohibited_software_on_endpoint_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[protocol_or_port_mismatch_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[protocols_passing_authentication_in_cleartext_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[reg_exe_manipulating_windows_services_registry_keys_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[reg_exe_used_to_hide_files_directories_via_registry_keys_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[registry_keys_used_for_persistence_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[registry_keys_used_for_privilege_escalation_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[registry_keys_for_creating_shim_databases_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[remote_desktop_network_bruteforce_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[remote_desktop_network_traffic_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[remote_desktop_process_running_on_system_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[remote_process_instantiation_via_wmi_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[remote_registry_key_modifications_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[remote_wmi_command_attempt_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[rundll_loading_dll_by_ordinal_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[smb_traffic_spike_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[smb_traffic_spike___mltk_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[sql_injection_with_long_urls_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[samsam_test_file_write_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[sc_exe_manipulating_windows_services_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[scheduled_task_name_used_by_dragonfly_threat_actors_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[scheduled_tasks_used_in_badrabbit_ransomware_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[schtasks_scheduling_job_on_remote_system_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[schtasks_used_for_forcing_a_reboot_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[script_execution_via_wmi_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[shim_database_file_creation_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[shim_database_installation_with_suspicious_parameters_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[short_lived_windows_accounts_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[single_letter_process_on_endpoint_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[spectre_and_meltdown_vulnerable_systems_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[spike_in_file_writes_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[splunk_enterprise_information_disclosure_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_changes_to_file_associations_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_email___uba_anomaly_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_email_attachment_extensions_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_file_write_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_java_classes_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_lnk_file_launching_a_process_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_reg_exe_process_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_wevtutil_usage_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_writes_to_system_volume_information_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[suspicious_writes_to_windows_recycle_bin_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[system_processes_run_from_unexpected_locations_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[tor_traffic_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[usn_journal_deletion_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[uncommon_processes_on_endpoint_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. [unload_sysmon_filter_driver_filter] definition = search * -description = Use this macro to add additional filter for Unload sysmon filter driver search to filter out the false positives +description = Update this macro to limit the output results to filter out false positives. -[unsigned_image_loaded_by_LSASS_filter] +[unsigned_image_loaded_by_lsass_filter] definition = search * -description = Use this macro to add additional filter for unsigned image loaded by LSASS +description = Update this macro to limit the output results to filter out false positives. -[unusually_long_commandlines_filter] +[unsuccessful_netbackup_backups_filter] definition = search * -description = Update this macro to limit the output results to filter out false positives. +description = Update this macro to limit the output results to filter out false positives. -[wineventlog_security] -definition = eventtype="wineventlog_security" -description = Customer specific splunk configurations(eg- index, source, sourcetype) for Windows Event Logs. Replace the macro definition with configurations for your Splunk Environmnent. - -[wmi_process_launch_filter] +[unusually_long_command_line_filter] definition = search * -description = Update this macro to limit the output results to filter out false positives. +description = Update this macro to limit the output results to filter out false positives. -[wmi_script_execution_filter] +[unusually_long_command_line___mltk_filter] definition = search * -description = Update this macro to limit the output results to filter out false positives. +description = Update this macro to limit the output results to filter out false positives. + +[unusually_long_content_type_length_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[wmi_permanent_event_subscription_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[wmi_permanent_event_subscription___sysmon_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[wmi_temporary_event_subscription_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[web_fraud___account_harvesting_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[web_fraud___anomalous_user_clickspeed_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[web_fraud___password_sharing_across_accounts_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[web_servers_executing_suspicious_processes_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[windows_event_log_cleared_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. + +[windows_hosts_file_modification_filter] +definition = search * +description = Update this macro to limit the output results to filter out false positives. diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 6b2ff03a98..12833ea6d5 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,582 +1,405 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-04-17T19:06:18 UTC +# On Date: 2020-05-06T14:58:49 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# ### ESCU DETECTIONS ### - [ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from cities that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new city is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. action.escu.creation_date = 2018-03-16 action.escu.modification_date = 2018-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen City +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, city -action.notable.param.rule_description = Your AWS infrastructure was provisioned from a city, $city$, which has never before been seen provisioning your infrastructure. -action.notable.param.rule_title = AWS Provision Activity From $city$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen City +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, errorCode +search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_city_filter` [ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each country. It returns only those events from countries that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new country is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. action.escu.creation_date = 2018-03-16 action.escu.modification_date = 2018-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen Country +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, country -action.notable.param.rule_description = Your AWS infrastructure was provisioned from a country, $country$, which has never before been seen provisioning your infrastructure. -action.notable.param.rule_title = AWS Provision Activity From $country$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Country +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCountry=1 | table Country] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Country, eventName, errorCode +search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Country | eval newCountry=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCountry=1 | table Country] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Country, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_country_filter` [ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from IP addresses that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new IP address is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. action.escu.creation_date = 2018-03-16 action.escu.modification_date = 2018-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen IP Address +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip -action.notable.param.rule_description = Your AWS infrastructure was provisioned from an IP, $src_ip$, which has never before been seen provisioning your infrastructure. -action.notable.param.rule_title = AWS Provision Activity From $src_ip$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen IP Address +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_ip -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | table sourceIPAddress] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, eventName, errorCode +search = `cloudtrail` (eventName=Run* OR eventName=Create*) [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Country=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | table sourceIPAddress] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_ip_address_filter` [ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from regions that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new region is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your region, there should be few false positives. If you are located in regions where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. action.escu.creation_date = 2018-03-16 action.escu.modification_date = 2018-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen Region +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, Region -action.notable.param.rule_description = Your AWS infrastructure was provisioned from a region, $Region$, which has never before been seen provisioning your infrastructure. -action.notable.param.rule_title = AWS Provision Activity From $region$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." +action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Region +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newRegion=1 | table Region] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Region, eventName, errorCode +search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* [search `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search Region=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by Region | eval newRegion=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newRegion=1 | table Region] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, Region, eventName, errorCode | `aws_cloud_provisioning_from_previously_unseen_region_filter` [ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} -action.escu.eli5 = This search\ -1. Retrieves the **AssumeRole** event\ -1. Verifies that the log entry contains a value for the account ID of the requesting account\ -1. Ensures that the requesting account ID does not match the account ID of the requested account\ -1. Pulls in the previously seen requesting and requested account IDs\ -1. Splits up and executes multiple search paths at the same.\ -1. The first path determines the **firstTime** and **lastTime** entries for the cache file\ -1. Outputs the data to the cache file.\ -1. Creates a conditional statement that is always false (both because we don't want these values to exit the search pipeline and because we think we're clever).The second pipeline adds the **firstTime** and **lastTime** entries to search results. Next, it filters out any account pairs that haven't been seen for the first time within the last hour. The `isnotnull(_time)` will remove the entries from the cache file.\ -The search finishes by gathering the data that it will display to the user. +action.escu.mappings = {"analytics_story": ["AWS Cross Account Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. action.escu.known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. -action.escu.creation_date = 2018-02-01 +action.escu.creation_date = 2018-11-02 action.escu.modification_date = 2018-11-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest_user"] -action.escu.entities = ["dest_user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Cross Account Activity"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = AWS Cross Account Activity From Previously Unseen Account +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = requestingAccountId, requestedAccountId, src_user, dest_user -action.notable.param.rule_description = Access to $dest_user$ was requested for the first time by $src_user$ -action.notable.param.rule_title = AWS Account $dest_user$ access by $src_user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. +action.notable.param.rule_title = AWS Cross Account Activity From Previously Unseen Account +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = requestingAccountId, requestedAccountId -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity | multireport [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as firstTime, max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime >= relative_time(now(), "-70m@m") AND isnotnull(_time) | spath output=accessKeyId path=responseElements.credentials.accessKeyId | spath output=requestingARN path=resources{}.ARN | stats values(awsRegion) as awsRegion values(firstTime) as firstTime values(lastTime) as lastTime values(sharedEventID) as sharedEventID, values(requestingARN) as src_user, values(responseElements.assumedRoleUser.arn) as dest_user by _time, requestingAccountId, requestedAccountId, accessKeyId] | table _time, firstTime, lastTime, src_user, requestingAccountId, dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID +search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity | multireport [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) as firstTime, max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime >= relative_time(now(), "-70m@m") AND isnotnull(_time) | spath output=accessKeyId path=responseElements.credentials.accessKeyId | spath output=requestingARN path=resources{}.ARN | stats values(awsRegion) as awsRegion values(firstTime) as firstTime values(lastTime) as lastTime values(sharedEventID) as sharedEventID, values(requestingARN) as src_user, values(responseElements.assumedRoleUser.arn) as dest_user by _time, requestingAccountId, requestedAccountId, accessKeyId] | table _time, firstTime, lastTime, src_user, requestingAccountId, dest_user, requestedAccountId, awsRegion, accessKeyId, sharedEventID | `aws_cross_account_activity_from_previously_unseen_account_filter` [ESCU - AWS Network Access Control List Created with All Open Ports - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. -action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = A network access control list (ACL) is a layer of security for your VPC that acts as a firewall for controlling traffic in and out of one or more subnets. Network ACLs with all open ports have a larger attack surface. This search looks for events within your CloudTrail logs to check if there were any Network ACLs created with ports ranging from 1024 to 65525. This search will create a table comprised of AWS account id, src, user and all parameters of the request made by the user and the server response. +action.escu.mappings = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. -action.escu.creation_date = 2017-01-08 +action.escu.creation_date = 2017-01-10 action.escu.modification_date = 2017-01-10 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Network Access Control List Created with All Open Ports - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Network ACL Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -1d@d -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = AWS Network Access Control List Created with All Open Ports +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = aws_account_id, src, arn -action.notable.param.rule_description = $src_user$ created a network access control list with all ports open. -action.notable.param.rule_title = Network ACL created with all ports open by $src_user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. +action.notable.param.rule_title = AWS Network Access Control List Created with All Open Ports +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = arn -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = arn -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=CreateNetworkAclEntry | mvexpand requestParameters | mvexpand responseElements | search requestParameters.portRange.from=1024 requestParameters.portRange.to=65535 requestParameters.ruleAction=allow | rename userIdentity.arn as arn | rename requestParameters.networkAclId as networkAclId | table _time aws_account_id src userName arn networkAclId requestParameters.* responseElements.* +search = `cloudtrail` eventName=CreateNetworkAclEntry | mvexpand requestParameters | mvexpand responseElements | search requestParameters.portRange.from=1024 requestParameters.portRange.to=65535 requestParameters.ruleAction=allow | rename userIdentity.arn as arn | rename requestParameters.networkAclId as networkAclId | table _time aws_account_id src userName arn networkAclId requestParameters.* responseElements.* | `aws_network_access_control_list_created_with_all_open_ports_filter` [ESCU - AWS Network Access Control List Deleted - Rule] action.escu = 0 action.escu.enabled = 1 description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. -action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = The search looks for CloudTrail events to detect whether any network ACLs have been deleted and gives you values of error messages and error codes (if any), user details, user source IP, the user who initiated this request, and the name of the event. +action.escu.mappings = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that a user has legitimately deleted a network ACL. -action.escu.creation_date = 2017-01-08 +action.escu.creation_date = 2017-01-10 action.escu.modification_date = 2017-01-10 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Network Access Control List Deleted - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["arn"] -action.escu.entities = ["arn"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Network ACL Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -1d@d -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = AWS Network Access Control List Deleted +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = arn, eventName -action.notable.param.rule_description = AWS network ACL has been deleted by $arn$. -action.notable.param.rule_title = AWS Network ACL deleted by $arn$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. +action.notable.param.rule_title = AWS Network Access Control List Deleted +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = arn -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = arn -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=DeleteNetworkAcl|rename userIdentity.arn as arn | stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) values(errorCode) values(userAgent) values(userIdentity.*) by src userName arn eventName | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` +search = `cloudtrail` eventName=DeleteNetworkAcl|rename userIdentity.arn as arn | stats count min(_time) as firstTime max(_time) as lastTime values(errorMessage) values(errorCode) values(userAgent) values(userIdentity.*) by src userName arn eventName | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `aws_network_access_control_list_deleted_filter` [ESCU - Abnormally High AWS Instances Launched by User - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events where an instance is successfully launched by a particular user. Since we want to detect a high number of instances launched within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances launched by a particular user, as well as the average and standard deviation values. Assign a `threshold_value` in the search. Start with 3 (but it will likely need to be tweaked for your environment). The `eval` function will set the outlier 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. For your reference, we then keep only the outliers and calculate the number of standard deviations away the value is from the average. +action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. action.escu.creation_date = 2018-02-26 action.escu.modification_date = 2018-02-26 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["userName"] -action.escu.entities = ["userName"] -action.escu.providing_technologies = ["AWS"] -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = */10 * * * * -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Abnormally High AWS Instances Launched by User +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = userName -action.notable.param.rule_description = An abnormally high number of instances were launched by a user within in a 10-minute window -action.notable.param.rule_title = High Number of instances launched by $userName$ -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. +action.notable.param.rule_title = Abnormally High AWS Instances Launched by User +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = userName -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = userName -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | bucket span=10m _time | stats count AS instances_launched by _time userName | eventstats avg(instances_launched) as total_launched_avg, stdev(instances_launched) as total_launched_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_launched > total_launched_avg+(total_launched_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m") | eval num_standard_deviations_away = round(abs(instances_launched - total_launched_avg) / total_launched_stdev, 2) | table _time, userName, instances_launched, num_standard_deviations_away, total_launched_avg, total_launched_stdev +search = `cloudtrail` eventName=RunInstances errorCode=success | bucket span=10m _time | stats count AS instances_launched by _time userName | eventstats avg(instances_launched) as total_launched_avg, stdev(instances_launched) as total_launched_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_launched > total_launched_avg+(total_launched_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m") | eval num_standard_deviations_away = round(abs(instances_launched - total_launched_avg) / total_launched_stdev, 2) | table _time, userName, instances_launched, num_standard_deviations_away, total_launched_avg, total_launched_stdev | `abnormally_high_aws_instances_launched_by_user_filter` [ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events where an instance is successfully launched by a particular user. Since we want to detect a high number of instances launched within a short period, we create event buckets for 10-minute windows. We then compare the total number of instances launched by a particular user against the saved baseline data in the model ec2_excessive_runinstances_v1. +action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. action.escu.creation_date = 2019-11-14 action.escu.modification_date = 2019-11-14 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] -action.escu.providing_technologies = ["AWS"] -action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = */10 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Abnormally High AWS Instances Launched by User - MLTK +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user -action.notable.param.rule_description = An abnormally high number of instances were launched by a user within in a 10-minute window -action.notable.param.rule_title = High Number of instances launched by $src_user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. +action.notable.param.rule_title = Abnormally High AWS Instances Launched by User - MLTK +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_user -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as isOutlier | where isOutlier=1 +search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as isOutlier | where isOutlier=1 [ESCU - Abnormally High AWS Instances Terminated by User - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events where an instance is successfully terminated by a particular user. Since we want to detect a high number of instances terminated within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances terminated by a particular user, as well as the average- and standard-deviation values. Assign a `threshold_value` in the search. Try starting with 3 (but it will likely need to be tweaked for your environment). The `eval` function will set the outlier to 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. We then filter out outliers with a value of 1 and show only those instance-termination events that happened within the previous 10 minutes. +action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. action.escu.creation_date = 2018-02-26 action.escu.modification_date = 2018-02-26 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["userName"] -action.escu.entities = ["userName"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] -cron_schedule = */10 * * * * -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Abnormally High AWS Instances Terminated by User +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = userName -action.notable.param.rule_description = An abnormally high number of instances were terminated by a user in a 10-minute window -action.notable.param.rule_title = High number of instances terminated by $userName$ -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window +action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = userName -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = userName -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success | bucket span=10m _time | stats count AS instances_terminated by _time userName | eventstats avg(instances_terminated) as total_terminations_avg, stdev(instances_terminated) as total_terminations_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_terminated > total_terminations_avg+(total_terminations_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m")| eval num_standard_deviations_away = round(abs(instances_terminated - total_terminations_avg) / total_terminations_stdev, 2) |table _time, userName, instances_terminated, num_standard_deviations_away, total_terminations_avg, total_terminations_stdev +search = `cloudtrail` eventName=TerminateInstances errorCode=success | bucket span=10m _time | stats count AS instances_terminated by _time userName | eventstats avg(instances_terminated) as total_terminations_avg, stdev(instances_terminated) as total_terminations_stdev | eval threshold_value = 4 | eval isOutlier=if(instances_terminated > total_terminations_avg+(total_terminations_stdev * threshold_value), 1, 0) | search isOutlier=1 AND _time >= relative_time(now(), "-10m@m")| eval num_standard_deviations_away = round(abs(instances_terminated - total_terminations_avg) / total_terminations_stdev, 2) |table _time, userName, instances_terminated, num_standard_deviations_away, total_terminations_avg, total_terminations_stdev | `abnormally_high_aws_instances_terminated_by_user_filter` [ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events where an instance is successfully terminated by a particular user. Since we want to detect a high number of instances terminated within a short period, we create event buckets for 10-minute windows. We then compare the total number of instances terminated by a particular user against the saved baseline data in the model ec2_excessive_terminateinstances_v1. +action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. action.escu.creation_date = 2019-11-14 action.escu.modification_date = 2019-11-14 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] -cron_schedule = */10 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Abnormally High AWS Instances Terminated by User - MLTK +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user -action.notable.param.rule_description = An abnormally high number of instances were terminated by a user within in a 10-minute window -action.notable.param.rule_title = High Number of instances terminated by $src_user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. +action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User - MLTK +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_user -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" as isOutlier | where isOutlier=1 +search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" as isOutlier | where isOutlier=1 [ESCU - Access LSASS Memory for Dump Creation - Rule] action.escu = 0 action.escu.enabled = 1 description = Detect memory dumping of the LSASS process. -action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.eli5 = dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = Detect memory dumping of the LSASS process. action.escu.how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. action.escu.creation_date = 2019-12-06 @@ -584,40 +407,23 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Access LSASS Memory for Dump Creation - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Access LSASS Memory for Dump Creation -action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = Possible attempt at credential dumping was detected on $dest$. -action.notable.param.rule_title = LSASS memory dump detected on $dest$. -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = `sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter` @@ -625,193 +431,139 @@ search = `sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR action.escu = 0 action.escu.enabled = 1 description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API -action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery"], "mitre_technique_id": ["T1190"]} -action.escu.eli5 = In this search we can detect unauthenticated web requests against an EKS cluster Pod, by looking at k8s authentication data, user agent and source IPs and API direct request. +action.escu.mappings = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster Pod", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +action.escu.eli5 = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. -action.escu.creation_date = 2020-03-24 +action.escu.creation_date = 2020-04-15 action.escu.modification_date = 2020-04-15 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Amazon EKS Kubernetes Pod scan detection - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Amazon EKS Kubernetes cluster Pod -action.escu.fields_required = ["cluster_name", "src_ip"] -action.escu.entities = ["cluster_name", "src_ip"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Amazon EKS Kubernetes Pod scan detection +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user.username, sourceIPs, verb, http_user_agent, group_name, requestURI action.notable.param.rule_description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.notable.param.rule_title = Amazon EKS Kubernetes Pod scan detection -action.notable.param.security_domain = threat +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = cluster_name -action.risk.param._risk_object_type = other -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" verb=list objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_detection` +search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_filter` [ESCU - Amazon EKS Kubernetes cluster scan detection - Rule] action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS -action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery"], "mitre_technique_id": ["T1190"]} -action.escu.eli5 = In this search we can detect unauthenticated web requests against an EKS cluster, by looking at k8s authentication data, user agent and source IPs. +action.escu.mappings = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. -action.escu.creation_date = 2020-03-24 +action.escu.creation_date = 2020-04-15 action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Amazon EKS Kubernetes cluster scan detection - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Amazon EKS Kubernetes cluster -action.escu.fields_required = ["cluster_name", "src_ip"] -action.escu.entities = ["cluster_name", "src_ip"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Amazon EKS Kubernetes cluster scan detection +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, cluster_name, http_user_agent action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.notable.param.rule_title = Amazon EKS Kubernetes cluster scan detection -action.notable.param.security_domain = threat -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = cluster_name -action.risk.param._risk_object_type = other -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="aws:cloudwatchlogs:eks" "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`kubernetes_aws_scan_fingerprint_detection` +search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`kubernetes_aws_scan_fingerprint_filter` [ESCU - Attempt To Add Certificate To Untrusted Store - Rule] action.escu = 0 action.escu.enabled = 1 description = Attempt to add a certificate to the untrusted certificate store -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Disabling Security Tools"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Attackers will often attempt to disable security tools in order to evade detection. It is also possible for end users to attempt to disable anti-virus or other security tools to circumvent restrictions they encounter while trying to execute other programs. One way malware may accomplish this is by adding the legitimate certificate used to sign the security software to the untrusted certificate store. This will cause the system to no longer trust the software signed with this certificate and disallow it from executing. This search simply looks for the execution of **certutil.exe** with the parameters `-addcert` and `disallowed`, which add a certification to the "untrusted" certificate store. +action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. -action.escu.creation_date = 2018-04-09 +action.escu.creation_date = 2018-11-15 action.escu.modification_date = 2018-11-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Add Certificate To Untrusted Store - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Disabling Security Tools"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Attempt To Add Certificate To Untrusted Store +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name +action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = Attempt to add a certificate to the untrusted certificate store -action.notable.param.rule_title = Attempt To Add Certificate to Untrusted Store -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = process, dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_title = Attempt To Add Certificate To Untrusted Store +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `attempt_to_add_certificate_to_untrusted_store_filter` [ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule] action.escu = 0 action.escu.enabled = 1 description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "mitre_technique_id": ["T1086", "T1064"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for changes of the ExecutionPolicy in the registry. The ExecutionPolicy is a safety feature that controls the conditions under which PowerShell loads configuration files and runs scripts. Usually, the ExecutionPolicy is "Restricted" for Windows clients and "RemoteSigned" for Windows Servers, allowing only certain scripts to run. This search detects when an attacker sets the ExecutionPolicy to "Unrestricted" or "Bypass." +action.escu.mappings = {"analytics_story": ["Credential Dumping", "Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. action.escu.known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. -action.escu.creation_date = 2018-08-28 +action.escu.creation_date = 2019-12-02 action.escu.modification_date = 2019-12-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Credential Dumping", "Malicious PowerShell"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, registry_path, registry_key_name, registry_value_name -action.notable.param.rule_description = An attempt to modify the default PowerShell execution policy in the registry to "Unrestricted" or "Bypass" was detected on $dest$. -action.notable.param.rule_title = Attempt To Set PowerShell Execution Policy To "Unrestricted" or "Bypass" On $dest$. -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = process_name, dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. +action.notable.param.rule_title = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` @@ -819,101 +571,69 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for attempts to stop security-related services on the endpoint. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Disabling Security Tools"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the processes **net.exe** and **sc.exe** with a parameter of `"stop"`. It then searches a list of security-related services included in a lookup file for matches on the command line. Results are subsequently returned in table format. The included lookup file can be modified to update the services to monitor. +action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., action.escu.known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. -action.escu.creation_date = 2018-04-09 +action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Stop Security Service - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Disabling Security Tools"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Attempt To Stop Security Service +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, user -action.notable.param.rule_description = Attempt to stop a security-related service on $dest$ -action.notable.param.rule_title = Attempt to Stop Security Service On $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for attempts to stop security-related services on the endpoint. +action.notable.param.rule_title = Attempt To Stop Security Service +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name = net.exe OR Processes.process_name = sc.exe) Processes.process="* stop *" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |lookup security_services_lookup service as process OUTPUTNEW category, description | search category=security +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name = net.exe OR Processes.process_name = sc.exe) Processes.process="* stop *" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` |lookup security_services_lookup service as process OUTPUTNEW category, description | search category=security | `attempt_to_stop_security_service_filter` -[ESCU - Attempted Credential Dump From Registry via Reg.exe - Rule] +[ESCU - Attempted Credential Dump From Registry via Reg exe - Rule] action.escu = 0 action.escu.enabled = 1 description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the process reg.exe with the "save" parameter, which specifies a binary export from the registry. In addition, it looks for the keys that contain the hashed credentials, which attackers may retrieve and use for brute-force attacks in order to harvest legitimate credentials. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. -action.escu.creation_date = 2018-08-28 +action.escu.creation_date = 2019-12-02 action.escu.modification_date = 2019-12-02 action.escu.confidence = high -action.escu.full_search_name = ESCU - Attempted Credential Dump From Registry via Reg.exe - Rule +action.escu.full_search_name = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Attempted Credential Dump From Registry via Reg.exe -action.notable = 1 -action.notable.param.nes_fields = user, process_name, process -action.notable.param.rule_description = An attempt to save registry keys holding credentials was identified by $user$. -action.notable.param.rule_title = Attempted Credential Dump From Registry from $user$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = process_name, dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.correlationsearch.label = Attempted Credential Dump From Registry via Reg exe +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=reg.exe OR Processes.process_name=cmd.exe) Processes.process=*save* (Processes.process=*HKEY_LOCAL_MACHINE\\Security* OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_filter` @@ -921,9 +641,9 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for a batch file (.bat) written to the Windows system directory tree. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks at file modifications across your hosts, as well as for evidence of batch files being written to paths that include "system32." This activity is consistent with some SamSam attacks and is, in general, suspicious. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. action.escu.creation_date = 2018-12-14 @@ -931,91 +651,61 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Batch File Write to System32 - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Batch File Write to System32 +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A batch file was written to the system directory on $dest$. -action.notable.param.rule_title = Batch file write to system32 detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for a batch file (.bat) written to the Windows system directory tree. +action.notable.param.rule_title = Batch File Write to System32 +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name values(Filesystem.user) as user from datamodel=Endpoint.Filesystem by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_path=*system32* AND file_extension=.bat +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name values(Filesystem.user) as user from datamodel=Endpoint.Filesystem by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_path=*system32* AND file_extension=.bat | `batch_file_write_to_system32_filter` -[ESCU - Child Processes of Spoolsv.exe - Rule] +[ESCU - Child Processes of Spoolsv exe - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. -action.escu.mappings = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Privilege Escalation", "Exploitation for Privilege Escalation"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for child processes of spoolsv.exe, which is associated with the Print Spooler service on Windows. Children of this process typically run under the SYSTEM context. This search should address the POC developed for the Windows local-privilege-escalation exploit announced in September of 2018. The associated vulnerability was assigned CVE-2018-8440. More information is available at https://doublepulsar.com/task-scheduler-alpc-exploit-high-level-analysis-ff08cda6ad4f. +action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. action.escu.known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. -action.escu.creation_date = 2018-11-26 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Child Processes of Spoolsv.exe - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Child Processes of Spoolsv exe - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Windows Privilege Escalation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Child Processes of Spoolsv.exe +action.correlationsearch.label = Child Processes of Spoolsv exe +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process_name, parent_process_name -action.notable.param.rule_description = A child process of spoolsv.exe was detected on $dest$. -action.notable.param.rule_title = Spoolsv.exe spawned a child process on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. +action.notable.param.rule_title = Child Processes of Spoolsv exe +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, parent_process_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.process_name) as process_name values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `children_of_spoolsv_filter` @@ -1023,52 +713,37 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. -action.escu.mappings = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Exfiltration Over Alternative Protocol"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = DNS Queries with multiple DNS servers from a single client is unusual and may be indicative of malicious activity. This search works by performing a count by the source of the distinct destinations for the DNS traffic. The search uses the `Network_Resolution` data model. +action.escu.mappings = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2020-01-16 action.escu.modification_date = 2020-01-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Clients Connecting to Multiple DNS Servers - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "src"] -action.escu.entities = ["dest", "src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "DNS Hijacking", "Host Redirection", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Clients Connecting to Multiple DNS Servers +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, dest -action.notable.param.rule_description = This search allows you to identify the endpoints that have connected to more than five DNS servers over the time frame specified in the search. -action.notable.param.rule_title = Client $src$ Connecting to Multiple DNS Servers -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. +action.notable.param.rule_title = Clients Connecting to Multiple DNS Servers +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count > 5 | `clients_connecting_to_multiple_dns_servers_output_filter` @@ -1076,105 +751,71 @@ search = | tstats `security_content_summariesonly` count, values(DNS.dest) AS de action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances created by users who have not created them before. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = For each user, the search returns the first time seen, last time seen, and the systems. It then appends the historical data and merges it into the data. The search then splits and outputs the updated times for each user back to the lookup file and then clears out any output. The other part of the search limits the results to when the user was seen for the first time within the previous 70 minutes. It then displays the new user, the instances created by that user, and the associated times. +action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.data_models = Cloud_Infrastructure +action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. action.escu.known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. -action.escu.creation_date = 2019-10-03 +action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Cloud Compute Instance -action.escu.fields_required = ["dest", "src_user"] -action.escu.entities = ["dest", "src_user"] -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Cloud Compute Instance Created By Previously Unseen User +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user, dest -action.notable.param.rule_description = The compute instance $dest$ was created by $src_user$. This is the first time $src_user$ has created a compute instance. -action.notable.param.rule_title = Cloud Compute Instance Created By Previously Unseen User $src_user$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for cloud compute instances created by users who have not created them before. +action.notable.param.rule_title = Cloud Compute Instance Created By Previously Unseen User +action.notable.param.security_domain = action.notable.param.severity = medium -action.notable.param.drilldown_name = Show all instances created by $src_user$ -action.notable.param.drilldown_search = | from datamodel:Cloud_Infrastructure.Compute | action=run src_user=$src_user$ -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_user, dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run by Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_creations_by_user | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by src_user | multireport [| table src_user, firstTime, lastTime | outputlookup previously_seen_cloud_compute_creations_by_user | where fact=fiction][| eval new_user=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_creations_by_user_search_window_begin_offset`), 1, 0) | where new_user=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table src_user, dest, firstTime, lastTime +search = | tstats `security_content_summariesonly` earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run by Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_creations_by_user | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by src_user | multireport [| table src_user, firstTime, lastTime | outputlookup previously_seen_cloud_compute_creations_by_user | where fact=fiction][| eval new_user=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_creations_by_user_search_window_begin_offset`), 1, 0) | where new_user=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table src_user, dest, firstTime, lastTime | `cloud_compute_instance_created_by_previously_unseen_user_filter` [ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances being created with previously unseen image IDs. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = For each image ID and user, the search returns the first time seen, last time seen, and the systems. It then appends the historical data and merges it into the data. The search then splits and outputs the updated times for each image back to the lookup file and clears out any output. The other part of the search limits the results to when the image was seen for the first time within the previous 70 minutes. It then displays the new image, the instances created using it, the user who created it, and the associated times. +action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.data_models = Cloud_Infrastructure +action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. action.escu.known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. -action.escu.creation_date = 2019-10-03 +action.escu.creation_date = 2018-10-12 action.escu.modification_date = 2018-10-12 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Cloud Compute Instance -action.escu.fields_required = ["dest", "src_user"] -action.escu.entities = ["dest", "src_user"] -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Cloud Compute Instance Created With Previously Unseen Image +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = The cloud compute instance $dest$ was created with previously unused image $image_id$. -action.notable.param.rule_title = Cloud Compute Instances Created With New Image -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for cloud compute instances being created with previously unseen image IDs. +action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Image +action.notable.param.security_domain = action.notable.param.severity = medium -action.notable.param.drilldown_name = Show all instances created with image $image_id$ -action.notable.param.drilldown_search = | from datamodel:Cloud_Infrastructure.Compute | image_id=$image_id$ -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_images | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by image_id, src_user | multireport [| table image_id, firstTime, lastTime | outputlookup previously_seen_cloud_compute_images | where fact=fiction][| eval new_image=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_image_search_window_begin_offset`), 1, 0) | where new_image=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table image_id, dest, src_user, firstTime, lastTime @@ -1182,52 +823,35 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = Find EC2 instances being created with previously unseen instance types. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = For each instance type and user, the search returns the first time seen, last time seen, and the system. It then appends the historical data and merges it into the data. The search then splits and outputs the updated times for each instance type back to the lookup file and clears out any output. The other part of the search limits the results to when the instance type was seen for the first time within the previous 70 minutes. It then displays the new instance type, the instances created using it, the user who created them, and the times associated. +action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.data_models = Cloud_Infrastructure +action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. -action.escu.creation_date = 2019-10-03 +action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Cloud Compute Instance -action.escu.fields_required = ["dest", "src_user"] -action.escu.entities = ["dest", "src_user"] -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Cloud Compute Instance Created With Previously Unseen Instance Type +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = instance_type -action.notable.param.rule_description = The instance type $instance_type$ was used for the first time to create $dest$. -action.notable.param.rule_title = New Cloud Compute Instance Type $instance_type$ detected -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Find EC2 instances being created with previously unseen instance types. +action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Instance Type +action.notable.param.security_domain = action.notable.param.severity = medium -action.notable.param.drilldown_name = Find all compute instances of type $instance_type$ -action.notable.param.drilldown_search = | from datamodel:Cloud_Infrastructure.Compute | instance_type=$instance_type$ -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_instance_types | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by instance_type, src_user | multireport [| table instance_type, firstTime, lastTime | outputlookup previously_seen_cloud_compute_instance_types | where fact=fiction][| eval new_type=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), 1, 0) | where new_type=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table instance_type, dest, src_user, firstTime, lastTime @@ -1235,52 +859,35 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. -action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = In this search, we query cloud infrastructure compute logs to look for events that indicate that an instance was started in a particular region. Using the \"previously_seen_cloud_regions\" lookup file created using the support search, we compare the region where this instance was started to all previously observed regions. The \"eval\" and \"if\" functions determine that the earliest times seen for this region and instance were within the last day. If a new region is detected, it will alert you with \"Instance Started in a New Region.\" However, this region will be added to the list in \"previously_seen_cloud_regions.\" +action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.data_models = Cloud_Infrastructure +action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. action.escu.creation_date = 2019-10-02 action.escu.modification_date = 2019-10-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Cloud Compute Instance -action.escu.fields_required = ["dest", "region", "src_user"] -action.escu.entities = ["dest", "region", "src_user"] -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] action.escu.analytic_story = ["Cloud Cryptomining"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Cloud Compute Instance Started In Previously Unused Region +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest,region -action.notable.param.rule_description = A cloud compute instance, $dest$, is started in a new, previously unseen, region $region$ -action.notable.param.rule_title = Cloud instance $dest$ started in a new region $region$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. +action.notable.param.rule_title = Cloud Compute Instance Started In Previously Unused Region +action.notable.param.security_domain = action.notable.param.severity = medium -action.notable.param.drilldown_name = See all activity in $region$ -action.notable.param.drilldown_search = | from datamodel:Cloud_Infrastructure.Compute | search region="$region$" -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,region -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `previously_seen_cloud_regions_input_filter` by Compute.region, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by region, src_user | multireport [| table region, firstTime, lastTime | outputlookup previously_seen_cloud_regions | where fact=fiction][| eval new_region=if(firstTime >= relative_time(now(), `previously_seen_cloud_regions_search_window_begin_offset`), 1, 0) | where new_region=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table region, dest, src_user, firstTime, lastTime @@ -1288,54 +895,39 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = The search looks for file modifications with extensions commonly used by Ransomware -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks at file modifications across your hosts and identifies files with extensions that are commonly associated with the encrypted files generated by ransomware. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ 1. \ 1. **Label:** File Extension, **Field:** file_extension\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions. -action.escu.creation_date = 2017-08-21 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Common Ransomware Extensions - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] -action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Common Ransomware Extensions +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A file modification was detected on $dest$ with an extension commonly used by ransomware. -action.notable.param.rule_title = Ransomware Extension detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for file modifications with extensions commonly used by Ransomware +action.notable.param.rule_title = Common Ransomware Extensions +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | `ransomware_extensions` | `common_ransomware_extensions_filter` @@ -1343,50 +935,35 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks at file modifications in the Change Analysis data model. It checks modified file names against an included lookup file, which contains the names of note files left behind by ransomware (to inform the victim how they can pay the ransom and retrieve their files). The search returns a list of files with matching names. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. -action.escu.creation_date = 2017-08-21 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Common Ransomware Notes - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] -action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Common Ransomware Notes +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A file modification associated with a ransomware victim notification file detected on $dest$ -action.notable.param.rule_title = Ransomware Note File detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. +action.notable.param.rule_title = Common Ransomware Notes +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`|`ransomware_notes`| `common_ransomware_notes_filter` @@ -1394,8 +971,8 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Detect remote thread creation into LSASS consistent with credential dumping. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.eli5 = This search detects the creation of a remote thread into LSASS (Local Security Authority Subsystem Service). This technique can be used by attackers to inject code into LSASS and dump the memory in order to obtain credentials. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = Detect remote thread creation into LSASS consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. action.escu.creation_date = 2019-12-06 @@ -1403,142 +980,95 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Create Remote Thread into LSASS - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Create Remote Thread into LSASS -action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = Possible attempt at credential dumping was detected on $dest$. -action.notable.param.rule_title = remote thread creation into LSASS on $dest$. -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, TargetProcessId -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = `sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as firstTime max(_time) as lastTime by Computer, EventCode, TargetImage, TargetProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`create_remote_thread_into_lsass_filter` -[ESCU - Create local admin accounts using net.exe - Rule] +[ESCU - Create local admin accounts using net exe - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of local administrator accounts using net.exe. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Net.exe is a built-in Windows command-line tool that can be used to add, display, or modify user accounts. While Microsoft administrators use this tool to manage user groups, threat actors often leverage it to create local admin accounts to maintain persistence. In this search, we are looking for the execution of process net.exe with command-line parameters such as `localgroup`, `add`, or `user` that may correspond to the creation of local admin accounts or setting user/group properties. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create admin accounts. -action.escu.creation_date = 2018-03-28 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Create local admin accounts using net.exe - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Create local admin accounts using net exe - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = 0 8 * * * -dispatch.earliest_time = -1440m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Create local admin accounts using net.exe +action.correlationsearch.label = Create local admin accounts using net exe +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = Net.exe was used to create local administrator accounts on $dest$. -action.notable.param.rule_title = Local administrator account created on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the creation of local administrator accounts using net.exe. +action.notable.param.rule_title = Create local admin accounts using net exe +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* OR process=*user*) |`create_local_admin_via_net_filter` -[ESCU - Create or delete windows shares using net.exe - Rule] +[ESCU - Create or delete windows shares using net exe - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation or deletion of hidden shares using net.exe. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement"], "mitre_technique_id": ["T1077", "T1126"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = In this search, we are looking for the command-line execution of net.exe with command-line parameters such as `net`, `share`, or `delete` that may correspond to the creation/deletion of windows drive shares. Net.exe is a built-in command-line tool on Windows that can be used to create, delete, and manage shared resources on the computer, both locally and remotely. Though this tool is used by Microsoft administrators to manage the network shares, attackers also leverage it to create and delete (hidden) file shares by appending "$" after the name of the share. Since the creation/deletion of hidden shares is a special case of detecting share creation/deletion we have commented out the regex that adds that additional matching criteria. If only hidden share detection is desired add `| regex process="\S+[$]"` before the last pipe in the search. +action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. -action.escu.creation_date = 2018-06-14 +action.escu.creation_date = 2020-01-20 action.escu.modification_date = 2020-01-20 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Create or delete windows shares using net.exe - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Create or delete windows shares using net exe - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Hidden Cobra Malware"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Create or delete windows shares using net.exe +action.correlationsearch.label = Create or delete windows shares using net exe +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest,process_name -action.notable.param.rule_description = Net.exe was used to create or delete hidden network shares by $user$ on $dest$ -action.notable.param.rule_title = Hidden File shares created/deleted on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the creation or deletion of hidden shares using net.exe. +action.notable.param.rule_title = Create or delete windows shares using net exe +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) | `create_or_delete_windows_shares_filter` @@ -1546,9 +1076,9 @@ search = | tstats `security_content_summariesonly` count values(Processes.user) action.escu = 0 action.escu.enabled = 1 description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The ntds.dit file contains the Active Directory (AD) database. This file can't be copied directly. That's why attackers will first create a shadow copy before exfiltrating the file. This search detects the creation of a shadow copy using Ntdsutil, Vssadmin, or Wmic. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. action.escu.creation_date = 2019-12-10 @@ -1556,40 +1086,23 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Creation of Shadow Copy - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Creation of Shadow Copy -action.notable = 1 -action.notable.param.nes_fields = user, dest, process_name, process -action.notable.param.rule_description = An attempt to create a shadow copy with Ntdsutil, Vssadmin, or Wmic was detected on $dest$. -action.notable.param.rule_title = Attempted Credential Dump of ntds.dit from $user$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = process_name, dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=ntdsutil.exe Processes.process=*ntds* Processes.process=*create*) OR (Processes.process_name=vssadmin.exe Processes.process=*create* Processes.process=*shadow*) OR (Processes.process_name=wmic.exe Processes.process=*shadowcopy* Processes.process=*create*) by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `creation_of_shadow_copy_filter` @@ -1597,49 +1110,32 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects the use of wmic and Powershell to create a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.eli5 = The ntds.dit file contains the Active Directory (AD) database. This file can't be copied directly. That's why attackers create a shadow copy before exfiltrating the file. This search detects the creation of a shadow copy using wmic, which is executed by Powershell. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search detects the use of wmic and Powershell to create a shadow copy. action.escu.how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Creation of Shadow Copy with wmic and powershell - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Creation of Shadow Copy with wmic and powershell -action.notable = 1 -action.notable.param.nes_fields = user, dest -action.notable.param.rule_description = An attempt to create a shadow copy with wmic and Powershell was detected on $dest$. -action.notable.param.rule_title = Attempted Credential Dump of ntds.dit on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = `sysmon` Message=*win32_shadowcopy* Message=*Create* | stats count min(_time) as firstTime max(_time) as lastTime by dvc User EventCode Message | rename User as user, dvc as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `creation_of_shadow_copy_with_wmic_and_powershell_filter` @@ -1647,9 +1143,9 @@ search = `sysmon` Message=*win32_shadowcopy* Message=*Create* | stats count min( action.escu = 0 action.escu.enabled = 1 description = This search detects credential dumping using copy command from a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The file system, security, sam and ntds.dit containing sensitive credentials. Normally, the files can't be easily copied. But it is possible by creating first a shadow copy and then copy it from the shadow copy. This search will detect this attack of credential dumping. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown action.escu.creation_date = 2019-12-10 @@ -1657,40 +1153,23 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Credential Dumping via Copy Command from Shadow Copy -action.notable = 1 -action.notable.param.nes_fields = user, dest, process_name, process -action.notable.param.rule_description = credential dumping using copy command was detected on $dest$. -action.notable.param.rule_title = Attempted Credential Dump using copy command from $user$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user, dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe (Processes.process=*\\system32\\config\\sam* OR Processes.process=*\\system32\\config\\security* OR Processes.process=*\\system32\\config\\system* OR Processes.process=*\\windows\\ntds\\ntds.dit*) by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_copy_from_shadowcopy_filter` @@ -1698,9 +1177,9 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects the creation of a symlink to a shadow copy. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The file system, security, sam, and ntds.dit containing sensitive credentials. Normally, the files can't be easily copied, but it can be done by creating shadow copy and then create a symlink to the shadow copy. This search will detect this attack of credential dumping. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown action.escu.creation_date = 2019-12-10 @@ -1708,40 +1187,23 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Credential Dumping via Symlink to Shadow Copy -action.notable = 1 -action.notable.param.nes_fields = user, dest, process_name, process -action.notable.param.rule_description = credential dumping using symlink on $dest$. -action.notable.param.rule_title = Attempted Credential Dump using symlink from $user$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user, dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe Processes.process=*mklink* Processes.process=*HarddiskVolumeShadowCopy* by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_symlink_shadowcopy_filter` @@ -1749,9 +1211,9 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "mitre_technique_id": ["T1071"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = Attackers often use random, long domain names for components of their attack infrastructure. This search leverages the probability distribution function algorithm provided by the Machine Learning Toolkit (MLTK) to identify outliers in the length of the DNS query for each record type observed. The companion search "Baseline of DNS Query Length - MLTK" creates a machine-learning (ML) model built over the historical data used by this search. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ 1. \ @@ -1760,45 +1222,30 @@ This search produces fields (`query`,`query_length`,`count`) that are not yet su 1. **Label:** Number of events, **Field:** count\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. -action.escu.creation_date = 2019-05-08 +action.escu.creation_date = 2020-01-22 action.escu.modification_date = 2020-01-22 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length Outliers - MLTK - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = DNS Query Length Outliers - MLTK +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src -action.notable.param.rule_description = Identify DNS traffic with unusual query lengths by record type -action.notable.param.rule_title = DNS query length outliers -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. +action.notable.param.rule_title = DNS Query Length Outliers - MLTK +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = query -alert.suppress.period = 43200s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename "IsOutlier(query_length)" as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time query record_type count src dest query_length | `dns_query_length_mltk_filter` @@ -1806,50 +1253,34 @@ search = | tstats `security_content_summariesonly` count min(_time) as start_tim action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "mitre_technique_id": ["T1071"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = Attackers often use random, long domain names for their attack infrastructure. This search looks at all the queries observed over the search time frame, and identifies any domains being resolved with names that are greater that 2 times the standard deviation. +action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It's possible there can be long domain names that are legitimate. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2020-01-22 action.escu.modification_date = 2020-01-22 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length With High Standard Deviation - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = DNS Query Length With High Standard Deviation +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src -action.notable.param.rule_description = Filter DNS requests and compute the standard deviation then filter on 2 times the standard deviation -action.notable.param.rule_title = DNS query length with high standard deviation -action.notable.param.security_domain = network +action.notable.param.rule_description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. +action.notable.param.rule_title = DNS Query Length With High Standard Deviation +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = query -alert.suppress.period = 43200s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | `drop_dm_object_name("DNS")` | eval query_length = len(query) | table query query_length record_type count | eventstats stdev(query_length) AS stdev avg(query_length) AS avg p50(query_length) AS p50| where query_length>(avg+stdev*2) | eval z_score=(query_length-avg)/stdev | `dns_query_length_with_high_standard_deviation_filter` @@ -1857,50 +1288,35 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. -action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Exfiltration", "Defense Evasion"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = Clients should be resolving their DNS requests via a trusted DNS server. This search will identify DNS queries being sent to unauthorized DNS servers by comparing the destination and source of the traffic with assets marked as DNS servers. +action.escu.mappings = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. action.escu.known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. -action.escu.creation_date = 2017-07-08 +action.escu.creation_date = 2020-01-17 action.escu.modification_date = 2020-01-17 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "src"] -action.escu.entities = ["dest", "src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "DNS Hijacking", "Host Redirection", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = DNS Query Requests Resolved by Unauthorized DNS Servers +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, src -action.notable.param.rule_description = The table represents a list of unauthorized DNS servers interacting with hosts in your network -action.notable.param.rule_title = DNS requests resolved by unauthorized DNS servers -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. +action.notable.param.rule_title = DNS Query Requests Resolved by Unauthorized DNS Servers +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,src -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src DNS.dest | `drop_dm_object_name("DNS")` | `unauthorized_dns_servers_filter` @@ -1908,54 +1324,39 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. -action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Exfiltration", "Command and Control", "Defense Evasion"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = Using a lookup `discover_dns_records` generated by support search "Discover DNS records" we check previous network traffic and make sure the responses have not changed. +action.escu.mappings = {"analytics_story": ["DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ **Splunk>Phantom Playbook Integration**\ If Splunk>Phantom is also configured in your environment, a Playbook called "DNS Hijack Enrichment" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\ action.escu.known_false_positives = Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate. -action.escu.creation_date = 2019-02-14 +action.escu.creation_date = 2020-01-16 action.escu.modification_date = 2020-01-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - DNS record changed - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src", "dest"] -action.escu.entities = ["src", "dest"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] action.escu.analytic_story = ["DNS Hijacking"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = DNS record changed +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src -action.notable.param.rule_description = The table represents a list of DNS records and their responses for corporate domains that have recently changed +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.notable.param.rule_title = DNS record changed -action.notable.param.security_domain = network +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | inputlookup discovered_dns_records.csv | rename answer as discovered_answer | join domain[|tstats `security_content_summariesonly` count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n) | `dns_record_changed_filter` @@ -1963,59 +1364,44 @@ search = | inputlookup discovered_dns_records.csv | rename answer as discovered_ action.escu = 0 action.escu.enabled = 1 description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Impact"], "mitre_technique_id": ["T1490"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for execution of vssadmin or wmic with both the "delete" and "shadows" parameters passed on the command-line. The two arguments are searched for separately because we can't predict the number of spaces between the words on the command-line. The search will return the number of times this activity was observed, and the times of the first and last event. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. -action.escu.creation_date = 2017-02-17 +action.escu.creation_date = 2020-04-17 action.escu.modification_date = 2020-04-17 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Deleting Shadow Copies - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Ransomware", "SamSam Ransomware", "Windows Log Manipulation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Deleting Shadow Copies +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = Using $process_name$ to delete shadow copies is common behavior by ransomware. This activity was observed on $dest$ -action.notable.param.rule_title = Deleting Shadow Copies on $dest$ with $process_name$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. +action.notable.param.rule_title = Deleting Shadow Copies +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 75 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=vssadmin.exe OR Processes.process_name=wmic.exe) by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*delete* AND process=*shadow* +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=vssadmin.exe OR Processes.process_name=wmic.exe) by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*delete* AND process=*shadow* | `deleting_shadow_copies_filter` [ESCU - Detect API activity from users without MFA - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "PR.AC"]} -action.escu.eli5 = In this search, we query CloudTrail logs and specifically look for events where the multi factor authentication context of the user's session is false which basically means, that the user does not have MFA enabled on AWS. We then filter out all the known AWS service accounts since service accounts typically do not have MFA enabled. The search then creates a table of the first and last time a user without MFA was detected, the values and count of the API calls made, the type of user identity, ARN and the name of the user. +action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ 1. \ @@ -2026,52 +1412,37 @@ Detailed documentation on how to create a new field within Incident Review may b action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure do not have multi factor authentication enabled. Please ignore the service accounts, if triggered and instead add them to the aws_service_accounts.csv file to fine tune the detection. It is also possible that the search detects users in your environment using Single Sign-On systems, since the MFA is not handled by AWS. action.escu.creation_date = 2018-05-17 action.escu.modification_date = 2018-05-17 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect API activity from users without MFA - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = 0 8 * * * -dispatch.earliest_time = -1d@d -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect API activity from users without MFA +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = API Activity detected from $user$ without MFA enabled. -action.notable.param.rule_title = API Activity detected from $user$ without MFA enabled -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. +action.notable.param.rule_title = Detect API activity from users without MFA +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 84600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail userIdentity.sessionContext.attributes.mfaAuthenticated=false | search NOT [| inputlookup aws_service_accounts | fields identity | rename identity as user]| stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by userIdentity.arn userIdentity.type user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = `cloudtrail` userIdentity.sessionContext.attributes.mfaAuthenticated=false | search NOT [| inputlookup aws_service_accounts | fields identity | rename identity as user]| stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by userIdentity.arn userIdentity.type user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_api_activity_from_users_without_mfa_filter` [ESCU - Detect AWS API Activities From Unapproved Accounts - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} -action.escu.eli5 = In this search, we are looking for successful API calls via CloudTrail. We filter out events triggered by known users listed in the `identity_lookup_expanded` lookup file and the service accounts. Once filtered out, we output a table with the event names and count, as well as the first and last time a specific user or service is detected. +action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"], "security_domain": "access"} +action.escu.eli5 = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ 1. \ @@ -2080,245 +1451,170 @@ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not ye 1. **Label:** Last Time, **Field:** lastTime\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` file. If the user is a legitimate service account, update the `aws_service_accounts.csv` table with that entry. -action.escu.creation_date = 2018-03-12 +action.escu.creation_date = 2018-03-13 action.escu.modification_date = 2018-03-13 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS API Activities From Unapproved Accounts - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect AWS API Activities From Unapproved Accounts +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A successful API activity was invoked by $user$, an unapproved/unknown account. -action.notable.param.rule_title = Successful API activity by a non-approved account: $user$ -action.notable.param.security_domain = access +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. +action.notable.param.rule_title = Detect AWS API Activities From Unapproved Accounts +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail errorCode=success | rename userName as identity | search NOT [| inputlookup identity_lookup_expanded | fields identity] | search NOT [| inputlookup aws_service_accounts | fields identity] | rename identity as user | stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = `cloudtrail` errorCode=success | rename userName as identity | search NOT [| inputlookup identity_lookup_expanded | fields identity] | search NOT [| inputlookup aws_service_accounts | fields identity] | rename identity as user | stats count min(_time) as firstTime max(_time) as lastTime values(eventName) as eventName by user | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_aws_api_activities_from_unapproved_accounts_filter` [ESCU - Detect AWS Console Login by User from New City - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new city and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and city combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-04-24 +action.escu.creation_date = 2018-04-30 action.escu.modification_date = 2018-04-30 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New City - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect AWS Console Login by User from New City +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A user has logged into the AWS console from a new city. -action.notable.param.rule_title = AWS Console Login by User from New City -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour +action.notable.param.rule_title = Detect AWS Console Login by User from New City +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user City | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New City","Previously Seen City") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New City" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `security_content_ctime(earliestseen)` | table user City userStatus firstTime lastTime earliestseen +search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user City | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New City","Previously Seen City") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New City" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `security_content_ctime(earliestseen)` | table user City userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_city_filter` [ESCU - Detect AWS Console Login by User from New Country - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new country and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and country combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-04-24 +action.escu.creation_date = 2018-04-30 action.escu.modification_date = 2018-04-30 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Country - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect AWS Console Login by User from New Country +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A user has logged into the AWS console from a new country. -action.notable.param.rule_title = AWS Console Login by User from New Country -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour +action.notable.param.rule_title = Detect AWS Console Login by User from New Country +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user Country | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New Country","Previously Seen Country") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Country" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`security_content_ctime(earliestseen)` | table user Country userStatus firstTime lastTime earliestseen +search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user Country | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New Country","Previously Seen Country") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Country" AND UserData="Old User" | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`security_content_ctime(earliestseen)` | table user Country userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_country_filter` [ESCU - Detect AWS Console Login by User from New Region - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new region and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and region combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-04-24 +action.escu.creation_date = 2018-04-30 action.escu.modification_date = 2018-04-30 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Region - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect AWS Console Login by User from New Region +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A user has logged into the AWS console from a new region. -action.notable.param.rule_title = AWS Console Login by User from New Region -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour +action.notable.param.rule_title = Detect AWS Console Login by User from New Region +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user Region | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New Region","Previously Seen Region") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Region" AND UserData="Old User" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `security_content_ctime(earliestseen)` | table user Region userStatus firstTime lastTime earliestseen +search = | inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user Region | join user type=outer [| inputlookup previously_seen_users_console_logins.csv | stats min(firstTime) AS earliestseen by user | fields earliestseen user] | eval userStatus=if(firstTime >= relative_time(now(), "@d"), "New Region","Previously Seen Region") | eval UserData=if(earliestseen >= relative_time(now(), "@d") OR isnull(earliestseen), "New User","Old User") | where userStatus="New Region" AND UserData="Old User" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `security_content_ctime(earliestseen)` | table user Region userStatus firstTime lastTime earliestseen | `detect_aws_console_login_by_user_from_new_region_filter` [ESCU - Detect Activity Related to Pass the Hash Attacks - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Pass the Hash"], "mitre_technique_id": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.eli5 = To detect pass the hash activity, we look at all events with event code 4624 that specify a logon type 3 (network logons) for remote pass the hash attacks and logon type 9 for local pass the hash attacks. The search also filters out events with an account name of 'Anonymous' to help reduce false positives. +action.escu.mappings = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "access"} +action.escu.eli5 = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. action.escu.how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. action.escu.known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2020-01-09 action.escu.modification_date = 2020-01-09 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Activity Related to Pass the Hash Attacks - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Lateral Movement"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Activity Related to Pass the Hash Attacks +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, dest, user -action.notable.param.rule_description = This search looks for Authentication log events from the Windows Security Audit logs to detect potential attempts for Passing the Hash -action.notable.param.rule_title = Detect Activity Related to Pass the Hash -action.notable.param.security_domain = access -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 10 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. +action.notable.param.rule_title = Detect Activity Related to Pass the Hash Attacks +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = `wineventlog_security` EventCode=4624 (Logon_Type=3 LogonProcessName=NtLmSsp WorkstationName=WORKSTATION NOT AccountName="ANONYMOUS LOGON") OR (EventCode=4624 Logon_Type=9 LogonProcessName=seclogo) | stats count min(_time) as firstTime max(_time) as lastTime by EventCode, Logon_Type, WorkstationName, user, dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_activity_related_to_pass_the_hash_attacks_filter` @@ -2326,49 +1622,32 @@ search = `wineventlog_security` EventCode=4624 (Logon_Type=3 LogonProcessName=Nt action.escu = 0 action.escu.enabled = 1 description = This search looks for reading lsass memory consistent with credential dumping. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} -action.escu.eli5 = This search looks for LSASS access using Credential Dumping tools by detecting Process access with Sysmon logs (EventCode 10), TargetImage lsass.exe and GrantedAccess 0x1410 or 0x1010. This will for example detect the use of sekurlsa::logonpasswords in Mimikatz. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for reading lsass memory consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -action.escu.creation_date = 2018-08-28 +action.escu.creation_date = 2019-12-03 action.escu.modification_date = 2019-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Credential Dumping through LSASS access - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Credential Dumping through LSASS access -action.notable = 1 -action.notable.param.nes_fields = user, dest -action.notable.param.rule_description = Possible attempt at credential dumping was detected on $dest$. -action.notable.param.rule_title = Detect reading lsass memory on $dest$. -action.notable.param.security_domain = endpoint -action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user, dest, ProcessName -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_LSASS_access_filter` @@ -2376,9 +1655,9 @@ search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR G action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["Spearphishing Link", "Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution", "Web"] -action.escu.eli5 = This search gathers all the answers to each system's DNS query, then filters for queries that have subdomains extracted from the EvilGinx toolkit. It will then run a regex to extract `legit_domains` from the query and remove that from the detection if it is listed in the `legit_domains.csv` +action.escu.mappings = {"analytics_story": ["Common Phishing Frameworks"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ **Splunk>Phantom Playbook Integration**\ If Splunk>Phantom is also configured in your environment, a Playbook called `Lets Encrypt Domain Investigate` can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ @@ -2390,257 +1669,181 @@ action.escu.modification_date = 2019-04-29 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] action.escu.analytic_story = ["Common Phishing Frameworks"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect DNS requests to Phishing Sites leveraging EvilGinx2 +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, query -action.notable.param.rule_description = The host $src$ issued a DNS request for a domain that could be a phishing site leverating EvilGinx toolkit. -action.notable.param.rule_title = DNS request for EvilGinx subdomain detected on $src$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src, query -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. +action.notable.param.rule_title = Detect DNS requests to Phishing Sites leveraging EvilGinx2 +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(DNS.answer) as answer from datamodel=Network_Resolution.DNS by DNS.dest DNS.src DNS.query host | `drop_dm_object_name(DNS)`| rex field=query ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | stats count values(query) as query by domain dest src answer| search `evilginx_phishlets_amazon` OR `evilginx_phishlets_facebook` OR `evilginx_phishlets_github` OR `evilginx_phishlets_0365` OR `evilginx_phishlets_outlook` OR `evilginx_phishlets_aws` OR `evilginx_phishlets_google` | search NOT [ inputlookup legit_domains.csv | fields domain]| join domain type=outer [| tstats count `security_content_summariesonly` values(Web.url) as url from datamodel=Web.Web by Web.dest Web.site | rename "Web.*" as * | rex field=site ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | table dest domain url] | table count src dest query answer domain url +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(DNS.answer) as answer from datamodel=Network_Resolution.DNS by DNS.dest DNS.src DNS.query host | `drop_dm_object_name(DNS)`| rex field=query ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | stats count values(query) as query by domain dest src answer| search `evilginx_phishlets_amazon` OR `evilginx_phishlets_facebook` OR `evilginx_phishlets_github` OR `evilginx_phishlets_0365` OR `evilginx_phishlets_outlook` OR `evilginx_phishlets_aws` OR `evilginx_phishlets_google` | search NOT [ inputlookup legit_domains.csv | fields domain]| join domain type=outer [| tstats count `security_content_summariesonly` values(Web.url) as url from datamodel=Web.Web by Web.dest Web.site | rename "Web.*" as * | rex field=site ".*?(?[^./:]+\.(\S{2,3}|\S{2,3}.\S{2,3}))$" | table dest domain url] | table count src dest query answer domain url | `detect_dns_requests_to_phishing_sites_leveraging_evilginx2_filter` [ESCU - Detect Excessive Account Lockouts From Endpoint - Rule] action.escu = 0 action.escu.enabled = 1 description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Initial Access", "Valid Accounts"], "nist": ["PR.IP"]} -action.escu.data_models = ["Change"] -action.escu.eli5 = This search queries the `Change.All_Changes` datamodel under the nodename is `Account_Management` , where the result is "lockout", which indicates that an account has been locked out. It then counts the number of times an endpoint has caused an account lockout within a four hour window and displays those hosts with a count greater than or equal to five. +action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.data_models = Change +action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ **Splunk>Phantom Playbook Integration**\ If Splunk>Phantom is also configured in your environment, a Playbook called "Excessive Account Lockouts Enrichment and Response" can be configured to run when any results are found by this detection search. The Playbook executes the Contextual and Investigative searches in this Story, conducts additional information gathering on Windows endpoints, and takes a response action to shut down the affected endpoint. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook Link:`https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\ action.escu.known_false_positives = It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts. -action.escu.creation_date = 2017-08-17 +action.escu.creation_date = 2019-04-18 action.escu.modification_date = 2019-04-18 -action.escu.confidence = low +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Excessive Account Lockouts From Endpoint - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -5m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Excessive Account Lockouts From Endpoint +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = The system $dest$ has generated a high number of account lockouts. -action.notable.param.rule_title = $dest$ has generated a high number of account lockouts -action.notable.param.security_domain = access -action.notable.param.severity = low -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. +action.notable.param.rule_title = Detect Excessive Account Lockouts From Endpoint +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.dest All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search count > 5 +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.dest All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search count > 5 | `detect_excessive_account_lockouts_from_endpoint_filter` [ESCU - Detect Excessive User Account Lockouts - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects user accounts that have been locked out a relatively high number of times in a short period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Initial Access", "Valid Accounts"], "nist": ["PR.IP"]} -action.escu.data_models = ["Change"] -action.escu.eli5 = This search queries the `Change.All_Changes` datamodel under the nodename is `Account_Management` , where the result is "lockout", which indicates that an account has been locked out. It then counts the number of times a user has caused an account lockout within a four hour window and displays those users with a count greater than or equal to five. +action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.data_models = Change +action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. action.escu.known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. -action.escu.creation_date = 2017-08-17 +action.escu.creation_date = 2019-03-01 action.escu.modification_date = 2019-03-01 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Excessive User Account Lockouts - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Excessive User Account Lockouts +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = The account $user$ has been locked out an excessive number of times -action.notable.param.rule_title = $user$ locked account an excessive number of times -action.notable.param.security_domain = access +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects user accounts that have been locked out a relatively high number of times in a short period. +action.notable.param.rule_title = Detect Excessive User Account Lockouts +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.user All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search count > 5 +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Change.All_Changes where nodename=All_Changes.Account_Management All_Changes.result="lockout" by All_Changes.user All_Changes.result |`drop_dm_object_name("All_Changes")` |`drop_dm_object_name("Account_Management")`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search count > 5 | `detect_excessive_user_account_lockouts_filter` [ESCU - Detect Large Outbound ICMP Packets - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. -action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Standard Non-Application Layer Protocol"], "nist": ["DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search works by looking at fields in the Network_Traffic data model, which is populated by various firewalls and passive networking monitoring technologies. Specifically, the search looks for ICMP packets larger than 1,000 bytes with a destination that is external to your organization. +action.escu.mappings = {"analytics_story": ["Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1095"], "nist": ["DE.AE"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. action.escu.creation_date = 2018-06-01 action.escu.modification_date = 2018-06-01 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Large Outbound ICMP Packets - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["Bro", "Splunk Stream", "Palo Alto Firewall"] action.escu.analytic_story = ["Command and Control"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Large Outbound ICMP Packets +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, dest_ip -action.notable.param.rule_description = Large outbound ICMP packet detected. -action.notable.param.rule_title = Large ICMP packet from $src_ip$ to $dest_ip$ detected -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. +action.notable.param.rule_title = Detect Large Outbound ICMP Packets +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_ip -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count earliest(_time) as firstTime latest(_time) as lastTime values(All_Traffic.action) values(All_Traffic.bytes) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.protocol=icmp OR All_Traffic.transport=icmp) All_Traffic.bytes > 1000 by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count earliest(_time) as firstTime latest(_time) as lastTime values(All_Traffic.action) values(All_Traffic.bytes) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.protocol=icmp OR All_Traffic.transport=icmp) All_Traffic.bytes > 1000 by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `detect_large_outbound_icmp_packets_filter` [ESCU - Detect Long DNS TXT Record Response - Rule] action.escu = 0 action.escu.enabled = 1 description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = This search uses the Network_Resolution data model and gathers all the answers to DNS queries for TXT records. The query then looks at the answer section and calculates the length of the answer. The search will then return information for those responses that exceed 100 characters in length. +action.escu.mappings = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. action.escu.known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. -action.escu.creation_date = 2017-06-18 +action.escu.creation_date = 2017-09-18 action.escu.modification_date = 2017-09-18 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Long DNS TXT Record Response - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Long DNS TXT Record Response +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, query -action.notable.param.rule_description = A DNS TXT record response of over 100 characters was detected. -action.notable.param.rule_title = Long DNS TXT Record Response -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. +action.notable.param.rule_title = Detect Long DNS TXT Record Response +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Resolution where DNS.message_type=response AND DNS.record_type=TXT by DNS.src DNS.dest DNS.answer DNS.record_type | `drop_dm_object_name("DNS")` | eval anslen=len(answer) | search anslen>100 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename src as "Source IP", dest as "Destination IP", answer as "DNS Answer" anslen as "Answer Length" record_type as "DNS Record Type" firstTime as "First Time" lastTime as "Last Time" count as Count | table "Source IP" "Destination IP" "DNS Answer" "DNS Record Type" "Answer Length" Count "First Time" "Last Time" +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Resolution where DNS.message_type=response AND DNS.record_type=TXT by DNS.src DNS.dest DNS.answer DNS.record_type | `drop_dm_object_name("DNS")` | eval anslen=len(answer) | search anslen>100 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename src as "Source IP", dest as "Destination IP", answer as "DNS Answer" anslen as "Answer Length" record_type as "DNS Record Type" firstTime as "First Time" lastTime as "Last Time" count as Count | table "Source IP" "Destination IP" "DNS Answer" "DNS Record Type" "Answer Length" Count "First Time" "Last Time" | `detect_long_dns_txt_record_response_filter` [ESCU - Detect Mimikatz Using Loaded Images - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. -action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.AE", "DE.CM"]} -action.escu.eli5 = This search looks for loaded images (dll) unique for Mimikatz using Sysmon EventCode 7 logs. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.AE", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for reading loaded Images unique to credential dumping with Mimikatz. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. action.escu.creation_date = 2019-12-03 @@ -2648,40 +1851,23 @@ action.escu.modification_date = 2019-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Mimikatz Using Loaded Images - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Mimikatz Using Loaded Images -action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = Possible attempt at credential dumping was detected on $dest$. -action.notable.param.rule_title = Detect Mimikatz using loaded images on $dest$. -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, Image -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = `sysmon` EventCode=7 | stats values(ImageLoaded) as ImageLoaded values(ProcessId) as ProcessId by Computer, Image | search ImageLoaded=*WinSCard.dll ImageLoaded=*cryptdll.dll ImageLoaded=*hid.dll ImageLoaded=*samlib.dll ImageLoaded=*vaultcli.dll | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_mimikatz_using_loaded_images_filter` @@ -2689,58 +1875,40 @@ search = `sysmon` EventCode=7 | stats values(ImageLoaded) as ImageLoaded values( action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell requesting privileges consistent with credential dumping. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} -action.escu.eli5 = This search looks for Windows Event Code(signature_id) 4703 (token right adjusted), where the process requesting the token change is PowerShell.exe and the requested privilege is "SeDebugPrivilege". This is consistent with the use of PowerShell to execute Mimikatz using sekurlsa::logonpasswords. It will return the host where the activity occurred, the process and associated id, the enabled privilege, and the message in the event. +action.escu.mappings = {"asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "access"} +action.escu.eli5 = This search looks for PowerShell requesting privileges consistent with credential dumping. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. action.escu.known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -action.escu.creation_date = 2018-08-28 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.analytic_story = [] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Mimikatz Via PowerShell And EventCode 4703 -action.notable = 1 -action.notable.param.nes_fields = user, dest -action.notable.param.rule_description = Possible attempt at credential dumping via PowerShell was detected on $dest$ by $user$. -action.notable.param.rule_title = Event Code 4703 Specifying PowerShell Acquiring A Token with SeDebugPrivilege Identified on $dest$. -action.notable.param.security_domain = access -action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user, dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = eventtype=wineventlog_security signature_id=4703 Process_Name=*powershell.exe | rex field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs as "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search = `wineventlog_security` signature_id=4703 Process_Name=*powershell.exe | rex field=Message "Enabled Privileges:\s+(?\w+)\s+Disabled Privileges:" | where privs="SeDebugPrivilege" | stats count min(_time) as firstTime max(_time) as lastTime by dest, Process_Name, privs, Process_ID, Message | rename privs as "Enabled Privilege" | rename Process_Name as process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_mimikatz_via_powershell_and_eventcode_4703_filter` [ESCU - Detect New Local Admin account - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for newly created accounts that have been elevated to local administrators. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Valid Accounts", "Defense Evasion", "Persistence"], "nist": ["PR.AC", "DE.CM"]} -action.escu.eli5 = This search looks for Windows Event Code 4720 (account creation) and 4732 (account added to a security-enabled local group), where the group name is "Administrators", and determines whether they are generated for the same user's Security ID within three hours of each other. It will return the user account that was added, the Security ID, the group name to which the user was added, the account name of the user who initiated the action, and the subsequent message returned. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Windows", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1078"], "nist": ["PR.AC", "DE.CM"], "security_domain": "access"} +action.escu.eli5 = This search looks for newly created accounts that have been elevated to local administrators. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ 1. \ @@ -2749,197 +1917,136 @@ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not 1. **Label:** Message, **Field:** Message\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not "Administrators", this search may generate an excessive number of false positives -action.escu.creation_date = 2018-03-26 +action.escu.creation_date = 2019-02-28 action.escu.modification_date = 2019-02-28 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Local Admin account - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = 0 9 * * * -dispatch.earliest_time = -1440m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect New Local Admin account +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user,src_user, dest -action.notable.param.rule_description = The new user account $user$ was created on $dest$ by $src_user$. -action.notable.param.rule_title = New local admin account $user$ created by $src_user$. -action.notable.param.security_domain = access +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for newly created accounts that have been elevated to local administrators. +action.notable.param.rule_title = Detect New Local Admin account +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = eventtype = wineventlog_security signature_id=4720 OR (signature_id=4732 Group_Name= Administrators) | transaction Security_ID connected=false maxspan=180m | search signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID Group_Name src_user Message +search = `wineventlog_security` signature_id=4720 OR (signature_id=4732 Group_Name= Administrators) | transaction Security_ID connected=false maxspan=180m | search signature_id=4720 signature_id=4732 | table _time user dest signature_id Security_ID Group_Name src_user Message | `detect_new_local_admin_account_filter` [ESCU - Detect New Login Attempts to Routers - Rule] action.escu = 0 action.escu.enabled = 1 description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. -action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Authentication"] -action.escu.eli5 = Attackers will often attempt to compromise network devices such as routers for a variety of nefarious purposes, including modifying VPN settings or re-routing network traffic. Typically, only a relatively small number of user accounts log into these devices on a regular basis. This search identifies 'new' connections to your routers by checking to see if a similar login was made in the last 30 days. Routers are identified by checking the IP address against those categorized as a "router" in the ES assets and identity framework. +action.escu.mappings = {"analytics_story": ["Router and Infrastructure Security"], "asset_type": "Endpoint", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"], "security_domain": "network"} +action.escu.data_models = Authentication +action.escu.eli5 = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. action.escu.known_false_positives = Legitimate router connections may appear as new connections -action.escu.creation_date = 2017-07-18 +action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Login Attempts to Routers - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Active Directory", "Palo Alto Firewall"] -action.escu.analytic_story = ["Router & Infrastructure Security"] -cron_schedule = 0 0 * * * -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Router and Infrastructure Security"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect New Login Attempts to Routers +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user -action.notable.param.rule_description = This search detects new connections made to the router devices at $dest$ -action.notable.param.rule_title = Detected a New Router Login -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. +action.notable.param.rule_title = Detect New Login Attempts to Routers +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count earliest(_time) as earliest latest(_time) as latest from datamodel=Authentication where Authentication.dest_category=router by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= relative_time(now(), "-30d@d"), 1, 0) | where isOutlier=1| `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `drop_dm_object_name("Authentication")` +search = | tstats `security_content_summariesonly` count earliest(_time) as earliest latest(_time) as latest from datamodel=Authentication where Authentication.dest_category=router by Authentication.dest Authentication.user| eval isOutlier=if(earliest >= relative_time(now(), "-30d@d"), 1, 0) | where isOutlier=1| `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `drop_dm_object_name("Authentication")` | `detect_new_login_attempts_to_routers_filter` [ESCU - Detect New Open S3 buckets - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Initial Access", "Exfiltration"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} -action.escu.eli5 = This search queries CloudTrail logs for events with S3 bucket access controls given to the "All Users" group, which allows anyone in the world access to the resource. This search generates a table displaying the time when the bucket was made public, the permission of the S3 bucket, the bucket name, and the ARN of the user who created the bucket. +action.escu.mappings = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events where a user has created an open/public S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. action.escu.creation_date = 2018-07-25 action.escu.modification_date = 2018-07-25 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Open S3 buckets - Rule action.escu.search_type = detection -action.escu.asset_at_risk = S3 Bucket -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect New Open S3 buckets +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = An open/public S3 bucket, $bucketName$, was created by $user$. -action.notable.param.rule_title = Public S3 bucket $bucketName$ created by $user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. +action.notable.param.rule_title = Detect New Open S3 buckets +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user,bucketName -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail AllUsers eventName=PutBucketAcl | spath output=userIdentityArn path=userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | spath output=aclControlList path=requestParameters.AccessControlPolicy.AccessControlList | spath input=aclControlList output=grantee path=Grant{} | mvexpand grantee | spath input=grantee | search Grantee.URI=*AllUsers | rename userIdentityArn as user| table _time, src,awsRegion Permission, Grantee.URI, bucketName, user +search = `cloudtrail` AllUsers eventName=PutBucketAcl | spath output=userIdentityArn path=userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | spath output=aclControlList path=requestParameters.AccessControlPolicy.AccessControlList | spath input=aclControlList output=grantee path=Grant{} | mvexpand grantee | spath input=grantee | search Grantee.URI=*AllUsers | rename userIdentityArn as user| table _time, src,awsRegion Permission, Grantee.URI, bucketName, user | `detect_new_open_s3_buckets_filter` -[ESCU - Detect Oulook.exe writing a .zip file - Rule] +[ESCU - Detect Oulook exe writing a zip file - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. -action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Initial Access", "Spearphishing Attachment"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = In this search, we are essentially trying to detect if outlook.exe is writing a `.zip` file to the disk. The way this search would run is, it will execute the the subsearch first which looks for all .zip files being written to the disk and outputs a crucial field "process_id", that we use the main search to check if that process\_id belongs to a process_name of outlook.exe. The search uses a join command to essentially give you an end result of the first and last time that zip file was written by outlook.exe, the dest and user logged on the system, the hash value and the complete path to the zip file on disk +action.escu.mappings = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +action.escu.eli5 = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. -action.escu.creation_date = 2019-04-29 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 action.escu.confidence = high -action.escu.full_search_name = ESCU - Detect Oulook.exe writing a .zip file - Rule +action.escu.full_search_name = ESCU - Detect Oulook exe writing a zip file - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Phishing Payloads"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Oulook.exe writing a .zip file +action.correlationsearch.label = Detect Oulook exe writing a zip file +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process_name, file_name -action.notable.param.rule_description = Outlook.exe is writing a zip file $file_name$ on $dest$ -action.notable.param.rule_title = Outlook.exe is writing a zip file $file_name$ on $dest$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. +action.notable.param.rule_title = Detect Oulook exe writing a zip file +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name=outlook.exe OR Processes.process_name=explorer.exe by _time span=5m Processes.parent_process_id Processes.process_id Processes.dest Processes.process_name Processes.parent_process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| rename parent_process_id as outlook_id| join malicious_id type=inner[| tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where (Filesystem.file_path=*zip* OR Filesystem.file_name=*.lnk ) AND (Filesystem.file_path=C:\\Users* OR Filesystem.file_path=*Local\\Temp*) by _time span=5m Filesystem.process_id Filesystem.file_hash Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| fields malicious_id outlook_id dest file_path file_name file_hash count file_id] | table firstTime lastTime user malicious_id outlook_id process_name parent_process_name file_name file_path | where file_name != "" | `outlook_writing_zip_filter` @@ -2947,254 +2054,178 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max( action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. -action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Commonly Used Port", "Credential Access", "Lateral Movement"], "mitre_technique_id": ["T1110", "T1135", "T1210"], "nist": ["DE.CM"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = In this search, we are looking for the network connections that were not blocked by the firewall and that are destined for destination port 139 or 445. We then filter out events that have Classless Inter-Domain Routing (CIDR) blocks categorized as internal in the `assets_by_cidr.csv` lookup file which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. Since we are only looking for outbound traffic from the hosts made to the Internet, we filter out traffic whose destination IP address is private. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. -action.escu.creation_date = 2018-03-20 +action.escu.creation_date = 2020-01-22 action.escu.modification_date = 2020-01-22 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Outbound SMB Traffic - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["Bro", "Splunk Stream"] action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Outbound SMB Traffic +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, dest_ip -action.notable.param.rule_description = Outbound SMB network traffic detected. -action.notable.param.rule_title = Outbound SMB traffic from $src_ip$ to $dest_ip$ detected -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. +action.notable.param.rule_title = Detect Outbound SMB Traffic +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_ip -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `outbound_smb_connections_filter` -[ESCU - Detect Path Interception By Creation Of program.exe - Rule] +[ESCU - Detect Path Interception By Creation Of program exe - Rule] action.escu = 0 action.escu.enabled = 1 description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Privilege Escalation", "Persistence"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search queries the Endpoint file-system data model node to list out all the values of destination machines, as well as the values of file hashes and file paths that have the file "program.exe" in the C: drive. Path interception occurs when an executable is placed in a specific path so that it is executed by an application instead of by the intended target. In this case, applications vulnerable to path interception (because of unquoted service paths with spaces in Windows registry) allow attackers to execute maliciously crafted program.exes. +action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. action.escu.known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. -action.escu.creation_date = 2017-11-16 +action.escu.creation_date = 2018-11-15 action.escu.modification_date = 2018-11-15 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Detect Path Interception By Creation Of program.exe - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Detect Path Interception By Creation Of program exe - Rule action.escu.search_type = detection -action.escu.asset_at_risk = -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Tanium", "Ziften"] action.escu.analytic_story = ["Windows Persistence Techniques"] -cron_schedule = 30 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Path Interception By Creation Of program.exe +action.correlationsearch.label = Detect Path Interception By Creation Of program exe +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_path, file_name -action.notable.param.rule_description = A potentially malicious file program.exe was detected on the C: drive. The creation of this file is often associated with a motive to perform a path interception attack. -action.notable.param.rule_title = Path Interception attempt discovered $dest$ via creation of program.exe -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. +action.notable.param.rule_title = Detect Path Interception By Creation Of program exe +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, file_path, file_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where Filesystem.file_path="C:\\program.exe" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where Filesystem.file_path="C:\\program.exe" by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `detect_path_interception_by_creation_of_program_exe_filter` -[ESCU - Detect Prohibited Applications Spawning cmd.exe - Rule] +[ESCU - Detect Prohibited Applications Spawning cmd exe - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution", "Command-Line Interface"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Obtaining access to the Command-Line Interface (CLI) is typically a primary attacker goal. Once an attacker has obtained the ability to execute code on a target system, they will often further manipulate the system via commands passed to the CLI. It is also unusual for many applications to spawn a command shell during normal operation, while it is often observed if an application has been compromised in some way. As such, it is often beneficial to look for cmd.exe being executed by processes that are often targeted for exploitation, or that would not spawn cmd.exe in any other circumstances. A lookup file is provided to easily modify the processes that are being watched for execution of cmd.exe. +action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. action.escu.known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. -action.escu.creation_date = 2017-10-07 +action.escu.creation_date = 2020-02-03 action.escu.modification_date = 2020-02-03 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Detect Prohibited Applications Spawning cmd.exe - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "parent_process_name", "user"] -action.escu.entities = ["dest", "parent_process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Prohibited Applications Spawning cmd.exe +action.correlationsearch.label = Detect Prohibited Applications Spawning cmd exe +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, parent_process -action.notable.param.rule_description = A prohibited application from prohibited_apps_launching_cmd.csv was leveraged to launch cmd.exe -action.notable.param.rule_title = Prohibited application($parent_process_name$) used to launch cmd.exe on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. +action.notable.param.rule_title = Detect Prohibited Applications Spawning cmd exe +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, parent_process, user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`] +search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe by Processes.parent_process_name Processes.process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |search [`prohibited_apps_launching_cmd`] | `detect_prohibited_applications_spawning_cmd_exe_filter` [ESCU - Detect PsExec With accepteula Flag - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = In this search, we are looking for the PsExec process with `accepteula` on the command line. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine -action.escu.creation_date = 2018-03-28 +action.escu.creation_date = 2019-02-26 action.escu.modification_date = 2019-02-26 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect PsExec With accepteula Flag - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["DHS Report TA18-074A", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect PsExec With accepteula Flag +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest,process_name -action.notable.param.rule_description = The process pssxec.exe was run with the -accepteula flag on $dest$ by $user$. -action.notable.param.rule_title = PsExec executed with accepteula flag on $dest$. -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. +action.notable.param.rule_title = Detect PsExec With accepteula Flag +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 75 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = PsExec.exe Processes.process = "*accepteula*" by Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = PsExec.exe Processes.process = "*accepteula*" by Processes.process_name Processes.dest Processes.parent_process_name | `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_psexec_with_accepteula_flag_filter` [ESCU - Detect Rare Executables - Rule] action.escu = 0 action.escu.enabled = 1 description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. -action.escu.mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search first executes the subsearch and counts all of your processes to determine the 10 most rare (the limit set is 10). It then filters out whitelisted processes and outputs the first and last time a rare process was encountered, the destination where the process is running, the count of occurrences, and the users who initiated the processes. +action.escu.mappings = {"analytics_story": ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. action.escu.known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. -action.escu.creation_date = 2016-08-09 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Rare Executables - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Unusual Processes"] -cron_schedule = 10 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Rare Executables +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process -action.notable.param.rule_description = The process $process$ was detected running on $dest. This process is rare in your environment. -action.notable.param.rule_title = Rare Process $process$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. +action.notable.param.rule_title = Detect Rare Executables +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.dest) as dest values(Processes.user) as user min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.process_name | rename Processes.process_name as process | rex field=user "(?.*)\\\\(?.*)" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name as process| `filter_rare_process_whitelist`| table process ] | `rare_executables_on_endpoint_filter` @@ -3202,69 +2233,42 @@ search = | tstats `security_content_summariesonly` count values(Processes.dest) action.escu = 0 action.escu.enabled = 1 description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. -action.escu.mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Exfiltration"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} -action.escu.eli5 = Here the subsearch executes first and returns all successful S3 bucket-access attempts (HTTP code "200") within the last hour. It groups the results by the earliest and latest times it has seen a remote IP accessing a particular bucket. It appends this information to the historical data from the lookup file and then recalculates the `firstTime` and `lastTime` field for each remote IP accessing an S3 bucket. Next, it returns only those remote IP addresses that have first been seen accessing a specific bucket within the past hour. This is combined with the main search to return the time, bucket name, source IP, city, and country operations performed, as well as the requested URI of the resource +action.escu.mappings = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} +action.escu.eli5 = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access logs' inputs. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. action.escu.known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour -action.escu.creation_date = 2018-06-25 +action.escu.creation_date = 2018-06-28 action.escu.modification_date = 2018-06-28 -action.escu.confidence = low +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect S3 access from a new IP - Rule action.escu.search_type = detection -action.escu.asset_at_risk = S3 Bucket -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect S3 access from a new IP +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = bucket_name, src_ip -action.notable.param.rule_description = A remote IP, $src_ip$, has made a successful connection with an S3 $bucket_name$. -action.notable.param.rule_title = S3 bucket $bucketName$ was accessed by a new $src_ip$ -action.notable.param.security_domain = network -action.notable.param.severity = low -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = bucket_name, src_ip -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. +action.notable.param.rule_title = Detect S3 access from a new IP +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:s3:accesslogs http_status=200 [search sourcetype=aws:s3:accesslogs http_status=200 | stats earliest(_time) as firstTime latest(_time) as lastTime by bucket_name remote_ip | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip.csv | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | table bucket_name remote_ip]| iplocation remote_ip |rename remote_ip as src_ip | table _time bucket_name src_ip City Country operation request_uri +search = `aws_s3_accesslogs` http_status=200 [search `aws_s3_accesslogs` http_status=200 | stats earliest(_time) as firstTime latest(_time) as lastTime by bucket_name remote_ip | inputlookup append=t previously_seen_S3_access_from_remote_ip.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip.csv | eval newIP=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newIP=1 | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | table bucket_name remote_ip]| iplocation remote_ip |rename remote_ip as src_ip | table _time bucket_name src_ip City Country operation request_uri | `detect_s3_access_from_a_new_ip_filter` [ESCU - Detect Spike in AWS API Activity - Rule] action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.eli5 = This search and its corresponding subsearch run through a series of steps, as per the following: \ -1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls.\ -1. Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.\ -1. Counts the number of API calls per ARN.\ -1. Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command. \ -1. Renames `apiCalls` as `latestCount`.\ -1. Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.\ -1. Updates the cache file with the latest results.\ -1. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filters out anything that it determines is not a spike and returns the list of ARNs to the main search. The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.eli5 = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ 1. \ @@ -3273,501 +2277,322 @@ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) 1. **Label:** Unique API Calls, **Field:** uniqueApisCalled\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = -action.escu.creation_date = 2018-03-12 +action.escu.creation_date = 2018-04-09 action.escu.modification_date = 2018-04-09 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in AWS API Activity - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Spike in AWS API Activity +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A spike in the number of AWS API calls by $user$ was detected. -action.notable.param.rule_title = Spike in AWS API activity detected by $user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. +action.notable.param.rule_title = Detect Spike in AWS API Activity +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventType=AwsApiCall [search sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user +search = `cloudtrail` eventType=AwsApiCall [search `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup api_call_by_user_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_aws_api_activity_filter` [ESCU - Detect Spike in Network ACL Activity - Rule] action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. -action.escu.mappings = {"cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Exfiltration"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.eli5 = This search and its corresponding subsearch run through the following series of steps: \ -1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for creating/modifying/replacing network Access Control Lists (ACLs).\ -1. Kick off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.\ -1. Count the number of API calls per Amazon Resource Name (ARN).\ -1. Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drop the count from the latest hour, since it is not necessary, and merge the rest of the data with the results of the stats command. \ -1. Rename `apiCalls` as `latestCount`.\ -1. Calculate the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. They do the same for the standard deviation--weighting the past more heavily than the current.\ -1. Update the cache file with the latest results.\ -1. Set the minimum threshold for the number of data points and set the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filter out anything that it determines is not a spike and return the list of ARNs to the main search. The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +action.escu.mappings = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.eli5 = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. -action.escu.creation_date = 2018-05-17 +action.escu.creation_date = 2018-05-21 action.escu.modification_date = 2018-05-21 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in Network ACL Activity - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Network ACL Activity"] -cron_schedule = 10 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Spike in Network ACL Activity +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A spike in the number of AWS API calls related to network ACLs by $user$ was detected. -action.notable.param.rule_title = Spike in AWS Network ACL activity detected by $user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. +action.notable.param.rule_title = Detect Spike in Network ACL Activity +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail `network_acl_events` [search sourcetype=aws:cloudtrail `network_acl_events` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup network_acl_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user +search = `cloudtrail` `network_acl_events` [search `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup network_acl_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_network_acl_activity_filter` [ESCU - Detect Spike in S3 Bucket deletion - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.eli5 = This search and its corresponding subsearch run through the following series of steps: \ -1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for deletion of S3 buckets.\ -1. Kick off a subsearch that retrieves the same data and pulls out and converts the ARN into a more friendly format.\ -1. Count the number of API calls per ARN.\ -1. Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drop the count from the latest hour, since it is unnecessary, and merge the rest of the data with the results of the `stats` command. \ -1. Rename `apiCalls` as `latestCount`.\ -1. Calculate the new average value for each ARN with the latest count, weighting the past more heavily than the current hour. It does the same for the standard deviation—weighting the past more heavily than the current.\ -1. Update the cache file with the latest results.\ -1. Set the minimum threshold for the number of data points and the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and if the count is a sufficient number of standard deviations away from the average.\ -1. Filter out anything that it determines is not a spike and returns the list of ARNs to the main search. The main search subsequently gets the names of the deleted S3 buckets, the number of unique API calls, and the total number of API calls for each of these user ARNs. +action.escu.mappings = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.eli5 = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -action.escu.creation_date = 2018-07-17 +action.escu.creation_date = 2018-11-27 action.escu.modification_date = 2018-11-27 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in S3 Bucket deletion - Rule action.escu.search_type = detection -action.escu.asset_at_risk = S3 Bucket -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Spike in S3 Bucket deletion +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A spike in the number of S3 buckets deleted by $user$ was detected. -action.notable.param.rule_title = Spike detected in S3 bucket deletion activity by $user$. -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. +action.notable.param.rule_title = Detect Spike in S3 Bucket deletion +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=DeleteBucket [search sourcetype=aws:cloudtrail eventName=DeleteBucket | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup s3_deletion_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | stats values(bucketName) as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user +search = `cloudtrail` eventName=DeleteBucket [search `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup s3_deletion_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | spath output=bucketName path=requestParameters.bucketName | stats values(bucketName) as bucketName, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_s3_bucket_deletion_filter` [ESCU - Detect Spike in Security Group Activity - Rule] action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} -action.escu.eli5 = This search and its corresponding subsearch run through the following series of steps: \ -1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls specifically for security groups.\ -1. Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.\ -1. Counts the number of API calls per ARN.\ -1. Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command. \ -1. Renames `apiCalls` as `latestCount`.\ -1. Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.\ -1. Updates the cache file with the latest results.\ -1. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filters out anything that it determines is not a spike and returns the list of ARNs to the main search. The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.eli5 = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -action.escu.creation_date = 2018-04-17 +action.escu.creation_date = 2018-04-18 action.escu.modification_date = 2018-04-18 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in Security Group Activity - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Spike in Security Group Activity +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A spike in the number of AWS API calls related to security groups by $user$ was detected. -action.notable.param.rule_title = Spike in AWS Security Group activity detected by $user$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. +action.notable.param.rule_title = Detect Spike in Security Group Activity +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail `security_group_api_calls` [search sourcetype=aws:cloudtrail `security_group_api_calls` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup security_group_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user +search = `cloudtrail` `security_group_api_calls` [search `cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | stats count as apiCalls by arn | inputlookup security_group_activity_baseline append=t | fields - latestCount | stats values(*) as * by arn | rename apiCalls as latestCount | eval newAvgApiCalls=avgApiCalls + (latestCount-avgApiCalls)/720 | eval newStdevApiCalls=sqrt(((pow(stdevApiCalls, 2)*719 + (latestCount-newAvgApiCalls)*(latestCount-avgApiCalls))/720)) | eval avgApiCalls=coalesce(newAvgApiCalls, avgApiCalls), stdevApiCalls=coalesce(newStdevApiCalls, stdevApiCalls), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | eval dataPointThreshold = 15, deviationThreshold = 3 | eval isSpike=if((latestCount > avgApiCalls+deviationThreshold*stdevApiCalls) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=user userIdentity.arn | stats values(eventName) as eventNames, count as numberOfApiCalls, dc(eventName) as uniqueApisCalled by user | `detect_spike_in_security_group_activity_filter` [ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule] action.escu = 0 action.escu.enabled = 1 description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Exfiltration", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -action.escu.eli5 = This search retrieves all the VPC Flow log entries that have recorded a blocked outbound network connection originating from your AWS environment. Then it kicks off a subsearch, which looks at the same data and performs the following series of steps: \ -1. Counts the number of blocked outbound connections by each source IP\ -1. Loads the cache file that contains the number of data points, the count from the latest hour, the average blocked connections, and the standard deviation for each source IP.\ -1. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command. \ -1. Renames `numberOfBlockedConnections` as `latestCount`.\ -1. Calculates the new average value for each source IP with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation, weighting the past more heavily than the current.\ -1. Updates the cache file with the latest results.\ -1. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filters out anything that it determines is not a spike and returns the list of source IPs to the main search. The main search subsequently gets the list of all destination IPs for which the traffic was blocked, the network interface ID, the number of unique destination IP, and the total number of blocked connections for each of these source IP addresses. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +action.escu.mappings = {"analytics_story": ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.eli5 = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. -action.escu.creation_date = 2018-04-26 +action.escu.creation_date = 2018-05-07 action.escu.modification_date = 2018-05-07 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["AWS"] -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Spike in blocked Outbound Traffic from your AWS +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip -action.notable.param.rule_description = A spike in the blocked outbound connection is detected from source $src_ip$. -action.notable.param.rule_title = Spike in blocked outbound network connections from $src_ip$ detected. -action.notable.param.security_domain = network +action.notable.param.rule_description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. +action.notable.param.rule_title = Detect Spike in blocked Outbound Traffic from your AWS +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_ip -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) [search sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | stats count as numberOfBlockedConnections by src_ip | inputlookup baseline_blocked_outbound_connections append=t | fields - latestCount | stats values(*) as * by src_ip | rename numberOfBlockedConnections as latestCount | eval newAvgBlockedConnections=avgBlockedConnections + (latestCount-avgBlockedConnections)/720 | eval newStdevBlockedConnections=sqrt(((pow(stdevBlockedConnections, 2)*719 + (latestCount-newAvgBlockedConnections)*(latestCount-avgBlockedConnections))/720)) | eval avgBlockedConnections=coalesce(newAvgBlockedConnections, avgBlockedConnections), stdevBlockedConnections=coalesce(newStdevBlockedConnections, stdevBlockedConnections), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | eval dataPointThreshold = 5, deviationThreshold = 3 | eval isSpike=if((latestCount > avgBlockedConnections+deviationThreshold*stdevBlockedConnections) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | table src_ip] | stats values(dest_ip) as "Blocked Destination IPs", values(interface_id) as "resourceId" count as numberOfBlockedConnections, dc(dest_ip) as uniqueDestConnections by src_ip +search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) [search `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | stats count as numberOfBlockedConnections by src_ip | inputlookup baseline_blocked_outbound_connections append=t | fields - latestCount | stats values(*) as * by src_ip | rename numberOfBlockedConnections as latestCount | eval newAvgBlockedConnections=avgBlockedConnections + (latestCount-avgBlockedConnections)/720 | eval newStdevBlockedConnections=sqrt(((pow(stdevBlockedConnections, 2)*719 + (latestCount-newAvgBlockedConnections)*(latestCount-avgBlockedConnections))/720)) | eval avgBlockedConnections=coalesce(newAvgBlockedConnections, avgBlockedConnections), stdevBlockedConnections=coalesce(newStdevBlockedConnections, stdevBlockedConnections), numDataPoints=if(isnull(latestCount), numDataPoints, numDataPoints+1) | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | eval dataPointThreshold = 5, deviationThreshold = 3 | eval isSpike=if((latestCount > avgBlockedConnections+deviationThreshold*stdevBlockedConnections) AND numDataPoints > dataPointThreshold, 1, 0) | where isSpike=1 | table src_ip] | stats values(dest_ip) as "Blocked Destination IPs", values(interface_id) as "resourceId" count as numberOfBlockedConnections, dc(dest_ip) as uniqueDestConnections by src_ip | `detect_spike_in_blocked_outbound_traffic_from_your_aws_filter` [ESCU - Detect USB device insertion - Rule] action.escu = 0 action.escu.enabled = 1 description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Exfiltration"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = ["Change_Analysis"] -action.escu.eli5 = USB is a common attack vector for delivering or propagating malicious code, or the exfiltration of data. Your corporation may have a policy of not allowing removable media at all, or may only allow approved media to be used on specific hosts by specific users. By logging USB activity from Windows and other endpoints gathered using the Universal Forwarder, you can gain an understanding of what systems might be vulnerable to attack via removable media, or what users might need additional security training. This search is looking for event_id 4656 for failure and 4663 for successful USB read/write attempts from Windows Security Event logs, which is the event code generated when a files are read from and written to a removable storage device +action.escu.mappings = {"analytics_story": ["Data Protection"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"], "security_domain": "endpoint"} +action.escu.data_models = Change_Analysis +action.escu.eli5 = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. action.escu.known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. -action.escu.creation_date = 2017-08-03 +action.escu.creation_date = 2017-11-27 action.escu.modification_date = 2017-11-27 -action.escu.confidence = low +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect USB device insertion - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Data Protection"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect USB device insertion +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = Read/Write attempt to a USB was detected on this host -action.notable.param.rule_title = Read/Write attempt to a USB detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = low -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. +action.notable.param.rule_title = Detect USB device insertion +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count earliest(_time) AS earliest latest(_time) AS latest from datamodel=Change_Analysis where (nodename = All_Changes) All_Changes.result="Removable Storage device" (All_Changes.result_id=4663 OR All_Changes.result_id=4656) (All_Changes.src_priority=high) by All_Changes.dest | `drop_dm_object_name("All_Changes")`| `security_content_ctime(earliest)`| `security_content_ctime(latest)` +search = | tstats `security_content_summariesonly` count earliest(_time) AS earliest latest(_time) AS latest from datamodel=Change_Analysis where (nodename = All_Changes) All_Changes.result="Removable Storage device" (All_Changes.result_id=4663 OR All_Changes.result_id=4656) (All_Changes.src_priority=high) by All_Changes.dest | `drop_dm_object_name("All_Changes")`| `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `detect_usb_device_insertion_filter` [ESCU - Detect Unauthorized Assets by MAC address - Rule] action.escu = 0 action.escu.enabled = 1 description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. -action.escu.mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "mitre_attack": ["Defense Evasion"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Network_Sessions"] -action.escu.eli5 = This search requires you to leverage the Enterprise Security Assets and Identity framework to populate assets_by_str.csv. Once the assets_by_str.csv is populated, we then query your DHCP logs to detect unknown systems connecting to your network. More documentation is available at: http://docs.splunk.com/Documentation/ES/4.7.1/Admin/Verifyassetandidentitydata. +action.escu.mappings = {"analytics_story": ["Asset Tracking"], "asset_type": "Infrastructure", "cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +action.escu.data_models = Network_Sessions +action.escu.eli5 = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. action.escu.known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. -action.escu.creation_date = 2017-06-11 +action.escu.creation_date = 2017-09-13 action.escu.modification_date = 2017-09-13 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Unauthorized Assets by MAC address - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Infrastructure -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] action.escu.analytic_story = ["Asset Tracking"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect Unauthorized Assets by MAC address +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, query -action.notable.param.rule_description = The host $src$ issued a DHCP request to connect with your network that does not belong to the list of authorized devices -action.notable.param.rule_title = Unauthorized Asset found with mac address: $src_mac$ -action.notable.param.security_domain = network +action.notable.param.rule_description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. +action.notable.param.rule_title = Detect Unauthorized Assets by MAC address +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_mac,src_ip -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST by All_Sessions.src_ip All_Sessions.src_mac | dedup All_Sessions.src_mac| `drop_dm_object_name("Network_Sessions")`|`drop_dm_object_name("All_Sessions")` | search NOT [| inputlookup asset_lookup_by_str |rename mac as src_mac | fields + src_mac] +search = | tstats `security_content_summariesonly` count from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST by All_Sessions.src_ip All_Sessions.src_mac | dedup All_Sessions.src_mac| `drop_dm_object_name("Network_Sessions")`|`drop_dm_object_name("All_Sessions")` | search NOT [| inputlookup asset_lookup_by_str |rename mac as src_mac | fields + src_mac] | `detect_unauthorized_assets_by_mac_address_filter` -[ESCU - Detect Use of cmd.exe to Launch Script Interpreters - Rule] +[ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution", "Command-Line Interface"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Attackers often leverage various scripting languages to execute their attacks. In a Windows environment, the Windows Script Host is the tool that interprets the scripts and is included in all modern versions of Windows. The Windows Script Host is available as a command-line tool called "cscript.exe" or "wscript.exe." To detect this behavior, the search looks for process-creation events for cscript.exe or wscript.exe with a parent process of cmd.exe. The search will return the count, the first and last times this behavior was seen on a destination machine, and user and process information. +action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Some legitimate applications may exhibit this behavior. -action.escu.creation_date = 2017-10-09 +action.escu.creation_date = 2020-03-02 action.escu.modification_date = 2020-03-02 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Detect Use of cmd.exe to Launch Script Interpreters - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "process_name", "user"] -action.escu.entities = ["dest", "process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Suspicious Command-Line Executions"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Use of cmd.exe to Launch Script Interpreters +action.correlationsearch.label = Detect Use of cmd exe to Launch Script Interpreters +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process_name, parent_process -action.notable.param.rule_description = Potentially malicious script execution detected. -action.notable.param.rule_title = Command prompt is executing scripts on $dest$ using $process_name$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine +action.notable.param.rule_title = Detect Use of cmd exe to Launch Script Interpreters +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name="cmd.exe" (Processes.process_name=cscript.exe OR Processes.process_name =wscript.exe) by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name="cmd.exe" (Processes.process_name=cscript.exe OR Processes.process_name =wscript.exe) by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `detect_use_of_cmd_exe_to_launch_script_interpreters_filter` [ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. -action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery", "System Information Discovery"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search returns the number of times a URL associated with this type of JexBoss probe is observed. +action.escu.mappings = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "kill_chain_phases": ["Reconnaissance"], "mitre_attack_id": ["T1082"], "security_domain": "network"} +action.escu.data_models = Web +action.escu.eli5 = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. action.escu.known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. -action.escu.creation_date = 2016-10-04 +action.escu.creation_date = 2017-09-23 action.escu.modification_date = 2017-09-23 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Web Server -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Splunk Stream", "Palo Alto Firewall", "Apache", "Bro"] action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect attackers scanning for vulnerable JBoss servers +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = -action.notable.param.rule_description = This search looks for specific GET/HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.notable.param.rule_title = Detect attackers scanning for vulnerable JBoss servers -action.notable.param.security_domain = network +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,url -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") AND (Web.url="*/web-console/ServerInfo.jsp*" OR Web.url="*web-console*" OR Web.url="*jmx-console*" OR Web.url = "*invoker*") by Web.http_method, Web.url, Web.src, Web.dest | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") AND (Web.url="*/web-console/ServerInfo.jsp*" OR Web.url="*web-console*" OR Web.url="*jmx-console*" OR Web.url = "*invoker*") by Web.http_method, Web.url, Web.src, Web.dest | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `detect_attackers_scanning_for_vulnerable_jboss_servers_filter` [ESCU - Detect hosts connecting to dynamic domain providers - Rule] action.escu = 0 action.escu.enabled = 1 description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Exfiltration", "Defense Evasion"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = The search leverages an accelerated `Network_Resolution` data model to count and list the values of resolved domains for each DNS query. It checks the results against the list of Dynamic DNS providers in the lookup `dynamic_dns_providers` by each host (DNS.src). +action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ 1. \ @@ -3776,308 +2601,217 @@ This search produces fields (query, answer, isDynDNS) that are not yet supported 1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified. -action.escu.creation_date = 2017-11-17 +action.escu.creation_date = 2020-01-16 action.escu.modification_date = 2020-01-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect hosts connecting to dynamic domain providers - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "DNS Hijacking", "Data Protection", "Dynamic DNS", "Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect hosts connecting to dynamic domain providers +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = answer, src, query -action.notable.param.rule_description = The search has detected a host making outbound queries to Dynamic DNS providers -action.notable.param.rule_title = Host $src$ detected to make a query to a Dynamic DNS provider -action.notable.param.security_domain = network +action.notable.param.rule_description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. +action.notable.param.rule_title = Detect hosts connecting to dynamic domain providers +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src, query -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(DNS.answer) as answer min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)` | `dynamic_dns_providers` +search = | tstats `security_content_summariesonly` count values(DNS.answer) as answer min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)` | `dynamic_dns_providers` | `detect_hosts_connecting_to_dynamic_domain_providers_filter` [ESCU - Detect malicious requests to exploit JBoss servers - Rule] action.escu = 0 action.escu.enabled = 1 description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. -action.escu.mappings = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search looks for HTTP requests for a URL that has been used to exploit JBoss servers. +action.escu.mappings = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Web +action.escu.eli5 = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model action.escu.known_false_positives = No known false positives for this detection. -action.escu.creation_date = 2016-10-04 +action.escu.creation_date = 2017-09-23 action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect malicious requests to exploit JBoss servers - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Web Server -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Splunk Stream", "Palo Alto Firewall", "Apache", "Bro"] action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect malicious requests to exploit JBoss servers +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, dest_ip -action.notable.param.rule_description = A search for detecting malicious requests made to exploit jmx-console in JBoss servers. The bad requests have a long url length since it serves the payload via the url -action.notable.param.rule_title = Detected malicious requests to exploit JBoss servers -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,url,src -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. +action.notable.param.rule_title = Detect malicious requests to exploit JBoss servers +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") by Web.http_method, Web.url,Web.url_length Web.src, Web.dest | search Web.url="*jmx-console/HtmlAdaptor?action=invokeOpByName&name=jboss.admin*import*" AND Web.url_length > 200 | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table src, dest_ip, http_method, url, firstTime, lastTime +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Web where (Web.http_method="GET" OR Web.http_method="HEAD") by Web.http_method, Web.url,Web.url_length Web.src, Web.dest | search Web.url="*jmx-console/HtmlAdaptor?action=invokeOpByName&name=jboss.admin*import*" AND Web.url_length > 200 | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table src, dest_ip, http_method, url, firstTime, lastTime | `detect_malicious_requests_to_exploit_jboss_servers_filter` -[ESCU - Detect mshta.exe running scripts in command-line arguments - Rule] +[ESCU - Detect mshta exe running scripts in command-line arguments - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Mshta.exe is a built-in Windows utility that can launch HTML files with .hta extensions (HTML applications), javascript, or VBScript. The search detects this behavior by looking for events where the process mshta.exe is executed with command-line arguments that indicate that a script is invoked +action.escu.mappings = {"analytics_story": ["Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. -action.escu.creation_date = 2018-08-07 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Detect mshta.exe running scripts in command-line arguments - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Detect mshta exe running scripts in command-line arguments - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Suspicious MSHTA Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect mshta.exe running scripts in command-line arguments +action.correlationsearch.label = Detect mshta exe running scripts in command-line arguments +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, parent_process_name -action.notable.param.rule_description = Mshta.exe is seen to be executing scripts via the command-line arguments -action.notable.param.rule_title = Mshta.exe is executing scripts on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. +action.notable.param.rule_title = Detect mshta exe running scripts in command-line arguments +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process, parent_process_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=mshta.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search (process=*vbscript* OR process=*javascript*) +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=mshta.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search (process=*vbscript* OR process=*javascript*) | `detect_mshta_exe_running_scripts_in_command_line_arguments_filter` [ESCU - Detect new API calls from user roles - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch will execute first and return the user roles and names of the API calls completed within the last hour, where the type of user identity is `AssumedRole`. It then appends the historical data to those results in the lookup file. Next, it recalculates the `earliest` and `latest` fields for each user role, as well as the name of the API call, and returns only those roles and API calls that have first been seen in the past hour. This is combined with the main search to return the values of API calls, name of the user role, and the earliest and latest time of this activity. It is worth noting that the name of the role of a particular user is parsed as "userName" in the CloudTrail logs. +action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. action.escu.known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. -action.escu.creation_date = 2018-04-01 +action.escu.creation_date = 2018-04-16 action.escu.modification_date = 2018-04-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect new API calls from user roles - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS User Monitoring"] -cron_schedule = 30 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect new API calls from user roles +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A new API call made by $user$ has been detected. This API activity has either never been seen before or has not been seen within the last hour. -action.notable.param.rule_title = New API call by $user$ detected -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. +action.notable.param.rule_title = Detect new API calls from user roles +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 10 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole [search sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | inputlookup append=t previously_seen_api_calls_from_user_roles | stats min(earliest) as earliest, max(latest) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles| eval newApiCallfromUserRole=if(earliest>=relative_time(now(), "-70m@m"), 1, 0) | where newApiCallfromUserRole=1 | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | table eventName userName] |rename userName as user| stats values(eventName) earliest(_time) as earliest latest(_time) as latest by user | `security_content_ctime(earliest)` | `security_content_ctime(latest)` +search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole [search `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | inputlookup append=t previously_seen_api_calls_from_user_roles | stats min(earliest) as earliest, max(latest) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles| eval newApiCallfromUserRole=if(earliest>=relative_time(now(), "-70m@m"), 1, 0) | where newApiCallfromUserRole=1 | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | table eventName userName] |rename userName as user| stats values(eventName) earliest(_time) as earliest latest(_time) as latest by user | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | `detect_new_api_calls_from_user_roles_filter` [ESCU - Detect new user AWS Console Login - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen users logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -action.escu.creation_date = 2018-02-26 +action.escu.creation_date = 2018-04-30 action.escu.modification_date = 2018-04-30 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detect new user AWS Console Login - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Suspicious AWS Login Activities"] -cron_schedule = 5 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect new user AWS Console Login +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = A new user has logged into the AWS console -action.notable.param.rule_title = AWS Console Login by New User -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour +action.notable.param.rule_title = Detect new user AWS Console Login +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user | stats earliest(_time) as firstTime latest(_time) as lastTime by user | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user | eval userStatus=if(firstTime >= relative_time(now(), "-70m@m"), "First Time Logging into AWS Console","Previously Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| where userStatus ="First Time Logging into AWS Console" +search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | stats earliest(_time) as firstTime latest(_time) as lastTime by user | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user | eval userStatus=if(firstTime >= relative_time(now(), "-70m@m"), "First Time Logging into AWS Console","Previously Seen User") | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| where userStatus ="First Time Logging into AWS Console" | `detect_new_user_aws_console_login_filter` [ESCU - Detect processes used for System Network Configuration Discovery - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Attackers have a range of built-in Windows tools they leverage to ascertain the topography of a network from the point of view of a compromised machine. It is uncommon to see these commands execute quickly within short periods of time. This search returns the number of times, as well as the first time and last times, that every process has run for each endpoint. It then executes the macro `system_network_configuration_discovery_tools`, which looks for processes that are typically used for network configuration discovery. Once you have a list of suspicious process launches for each destination, you can leverage the transaction command to see what processes are fired within a five-minute span on an endpoint and detect only those events where the count of these processes is greater than five. +action.escu.mappings = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. action.escu.known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. -action.escu.creation_date = 2018-11-04 +action.escu.creation_date = 2018-11-20 action.escu.modification_date = 2018-11-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect processes used for System Network Configuration Discovery - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Unusual Processes"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect processes used for System Network Configuration Discovery +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, user -action.notable.param.rule_description = Fast execution of processes $related to network system configuration discovery seen on $dest$. -action.notable.param.rule_title = Fast execution of processes $process_name$ related to network discovery seen on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. +action.notable.param.rule_title = Detect processes used for System Network Configuration Discovery +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.process_name Processes.user _time | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` | transaction dest connected=false maxpause=5m |where eventcount>=5 | table firstTime lastTime dest user process_name process parent_process eventcount +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.process_name Processes.user _time | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | search `system_network_configuration_discovery_tools` | transaction dest connected=false maxpause=5m |where eventcount>=5 | table firstTime lastTime dest user process_name process parent_process eventcount | `detect_processes_used_for_system_network_configuration_discovery_filter` [ESCU - Detect web traffic to dynamic domain providers - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for web connections to dynamic DNS providers. -action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Command and Control", "Web Service", "Exfiltration Over Command and Control Channel", "Defense Evasion"], "nist": ["PR.IP", "DE.DP"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search looks for hosts in your environment that may be communicating with a dynamic DNS provider. It checks each URL an endpoint is connecting to against a list of dynamic DNS providers. It returns the source and destination IP address of the web request, the URL requested, and the first time the event occurred. +action.escu.mappings = {"analytics_story": ["Dynamic DNS"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"], "security_domain": "network"} +action.escu.data_models = Web +action.escu.eli5 = This search looks for web connections to dynamic DNS providers. action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` @@ -4087,203 +2821,142 @@ action.escu.modification_date = 2018-09-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect web traffic to dynamic domain providers - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] action.escu.analytic_story = ["Dynamic DNS"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detect web traffic to dynamic domain providers +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, url, dest -action.notable.param.rule_description = The host $src$ has been detected making a web request to $url$, which is a listed as a dynamic DNS provider. -action.notable.param.rule_title = Dynamic DNS web traffic detected on $src$. -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src, url , dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for web connections to dynamic DNS providers. +action.notable.param.rule_title = Detect web traffic to dynamic domain providers +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Web.url) as url min(_time) as firstTime from datamodel=Web where Web.status=200 by Web.src Web.dest Web.status | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `dynamic_dns_web_traffic` +search = | tstats `security_content_summariesonly` count values(Web.url) as url min(_time) as firstTime from datamodel=Web where Web.status=200 by Web.src Web.dest Web.status | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `dynamic_dns_web_traffic` | `detect_web_traffic_to_dynamic_domain_providers_filter` [ESCU - Detection of DNS Tunnels - Rule] action.escu = 0 action.escu.enabled = 1 description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. -action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = The search will calculate the distinct count and sum of the length of DNS queries made and DNS answers received by a particular host to alert the analyst if the combined length is greater than 10000, which is not typical behavior. +action.escu.mappings = {"analytics_story": ["Data Protection", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "PR.DS"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. action.escu.known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. -action.escu.creation_date = 2017-07-19 +action.escu.creation_date = 2017-09-18 action.escu.modification_date = 2017-09-18 -action.escu.confidence = low +action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of DNS Tunnels - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "Data Protection", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Data Protection", "Suspicious DNS Traffic", "Command and Control"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detection of DNS Tunnels +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src -action.notable.param.rule_description = Potential DNS tunnel detected from $src$ which may be exfiltrating large data -action.notable.param.rule_title = DNS tunnel detected on $src$ -action.notable.param.security_domain = network -action.notable.param.severity = low -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src, query -alert.suppress.period = 43200s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. +action.notable.param.rule_title = Detection of DNS Tunnels +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` dc("DNS.query") as count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.query" | rename "DNS.src" as src "DNS.query" as message | eval length=len(message) | stats sum(length) as length by src | append [ tstats `security_content_summariesonly` dc("DNS.answer") as count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.answer" | rename "DNS.src" as src "DNS.answer" as message | eval message=if(message=="unknown","", message) | eval length=len(message) | stats sum(length) as length by src ] | stats sum(length) as length by src | where length > 10000 +search = | tstats `security_content_summariesonly` dc("DNS.query") as count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.query" | rename "DNS.src" as src "DNS.query" as message | eval length=len(message) | stats sum(length) as length by src | append [ tstats `security_content_summariesonly` dc("DNS.answer") as count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" NOT (`cim_corporate_web_domain_search("DNS.query")`) NOT "DNS.query"="*.in-addr.arpa" NOT ("DNS.src_category"="svc_infra_dns" OR "DNS.src_category"="svc_infra_webproxy" OR "DNS.src_category"="svc_infra_email*" ) by "DNS.src","DNS.answer" | rename "DNS.src" as src "DNS.answer" as message | eval message=if(message=="unknown","", message) | eval length=len(message) | stats sum(length) as length by src ] | stats sum(length) as length by src | where length > 10000 | `detection_of_dns_tunnels_filter` [ESCU - Detection of tools built by NirSoft - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Discovery", "Execution", "Lateral Movement", "Third-party Software", "Account Discovery"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for process-creation events accompanied by specific command-line arguments ("scomma" and "stext"). These parameters may be leveraged by a set of free, legitimate tools built by NirSoft. Attackers have been seen abusing the tools' capabilities to steal passwords, set up key loggers, recover account information from mail clients, and conduct other nefarious activities. The search will identify the count, the first and last times a process is executed, the command-line arguments, and the parent process. +action.escu.mappings = {"analytics_story": ["Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1072", "T1087"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. -action.escu.creation_date = 2018-09-11 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of tools built by NirSoft - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A "] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Detection of tools built by NirSoft +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = This search looks for specific arguments passed via the command line and detects execution of tools built by NirSoft, which are often abused by attackers. -action.notable.param.rule_title = Potential abuse of NirSoft tools on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. +action.notable.param.rule_title = Detection of tools built by NirSoft +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process="* /stext *" OR Processes.process="* /scomma *" ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process="* /stext *" OR Processes.process="* /scomma *" ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `detection_of_tools_built_by_nirsoft_filter` [ESCU - Disabling Remote User Account Control - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Modify Registry"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search checks to see if the registry key SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\LocalAccountTokenFilterPolicy was modified. This registry key can be used to disable remote User Account Control. The search returns the count, the first time activity was seen, last time activity was seen, the registry path that was modified, the host where the modification took place and the user that performed the modification. +action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. -action.escu.creation_date = 2017-10-12 +action.escu.creation_date = 2020-03-02 action.escu.modification_date = 2020-03-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Disabling Remote User Account Control - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Disabling Remote User Account Control +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, registry_path -action.notable.param.rule_description = The registry key SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\LocalAccountTokenFilterPolicy was modified. This registry key is associated with disabling remote UAC on Windows. -action.notable.param.rule_title = Registry Key Associated With Disabling Remote UAC Modified on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). +action.notable.param.rule_title = Disabling Remote User Account Control +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user, registry_path -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="*Windows\\CurrentVersion\\Policies\\System\\LocalAccountTokenFilterPolicy" by Registry.dest, Registry.registry_key_name Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="*Windows\\CurrentVersion\\Policies\\System\\LocalAccountTokenFilterPolicy" by Registry.dest, Registry.registry_key_name Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)` | `disabling_remote_user_account_control_filter` [ESCU - Dump LSASS via comsvcs DLL - Rule] action.escu = 0 action.escu.enabled = 1 description = Detect the usage of comsvcs.dll for dumping the lsass process. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = LSASS is the Local Security Authority Subsystem Service, which is responsible for storing the user credentials. There are multiple ways to attack LSASS. This search detects the usage of comsvcs.dll for dumping the LSASS process. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. action.escu.creation_date = 2020-02-21 @@ -4291,40 +2964,23 @@ action.escu.modification_date = 2020-02-21 action.escu.confidence = high action.escu.full_search_name = ESCU - Dump LSASS via comsvcs DLL - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Dump LSASS via comsvcs DLL -action.notable = 1 -action.notable.param.nes_fields = user, process_name, process -action.notable.param.rule_description = An attempt to dump credentials of lsass by $user$ was detected. -action.notable.param.rule_title = Dump LSASS via comsvcs DLL -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = process_name, dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=rundll32.exe Processes.process=*comsvcs.dll* Processes.process=*MiniDump* by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `dump_lsass_via_comsvcs_dll_filter` @@ -4332,353 +2988,245 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being modified by users who have not previously modified them. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns the ARNs of all successful EC2 instance modifications within the last hour and then appends the historical data in the lookup file to those results. EC2 modification APIs are defined by the macro `ec2_modification_api_calls`. The search then recalculates the `firstTime` and `lastTime` field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance ID of those systems. +action.escu.mappings = {"analytics_story": ["Unusual AWS EC2 Modifications"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for EC2 instances being modified by users who have not previously modified them. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. action.escu.known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. action.escu.creation_date = 2018-04-09 action.escu.modification_date = 2018-04-09 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Modified With Previously Unseen User - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = EC2 Instance Modified With Previously Unseen User +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user, dest -action.notable.param.rule_description = The EC2 instance $dest$ was modified by $user$. This user has never modified an EC2 instance before. -action.notable.param.rule_title = EC2 Instance Modified By Previously Unseen User $user$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for EC2 instances being modified by users who have not previously modified them. +action.notable.param.rule_title = EC2 Instance Modified With Previously Unseen User +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user, dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail `ec2_modification_api_calls` [search sourcetype=aws:cloudtrail `ec2_modification_api_calls` errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId | spath output=user userIdentity.arn | table _time, user, dest +search = `cloudtrail` `ec2_modification_api_calls` [search `cloudtrail` `ec2_modification_api_calls` errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_modifications_by_user | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | spath output=dest responseElements.instancesSet.items{}.instanceId | spath output=user userIdentity.arn | table _time, user, dest | `ec2_instance_modified_with_previously_unseen_user_filter` [ESCU - EC2 Instance Started In Previously Unseen Region - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started -action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion"], "nist": ["DE.DP", "DE.AE"]} -action.escu.eli5 = In this search, we query CloudTrail logs to look for events that indicate that an instance was started in a particular region. Using the `previously_seen_aws_regions.csv` lookup file created using the support search, we compare the region where this instance was started to all previously observed regions. The `eval` and `if` functions determine that the earliest times seen for this region and instance were within the last day. If a new region is detected, it will alert you with "Instance Started in a New Region". However, this region will be added to the list of `previously_seen_aws_regions.csv`. Please maintain `previously_seen_aws_regions.csv` +action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.eli5 = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. -action.escu.creation_date = 2018-02-01 +action.escu.creation_date = 2018-02-23 action.escu.modification_date = 2018-02-23 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started In Previously Unseen Region - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["awsRegion"] -action.escu.entities = ["awsRegion"] -action.escu.providing_technologies = ["AWS"] -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = EC2 Instance Started In Previously Unseen Region +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = awsRegion -action.notable.param.rule_description = An AWS instance is started in a new, previously unseen, region -action.notable.param.rule_title = AWS instance is started in a new region -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started +action.notable.param.rule_title = EC2 Instance Started In Previously Unseen Region +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = awsRegion -action.risk.param._risk_object_type = other -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = awsRegion -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail earliest=-1h StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | inputlookup append=t previously_seen_aws_regions.csv | stats min(earliest) as earliest max(latest) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | eval regionStatus=if(earliest >= relative_time(now(),"-1d@d"), "Instance Started in a New Region","Previously Seen Region") | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | where regionStatus="Instance Started in a New Region" +search = `cloudtrail` earliest=-1h StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | inputlookup append=t previously_seen_aws_regions.csv | stats min(earliest) as earliest max(latest) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | eval regionStatus=if(earliest >= relative_time(now(),"-1d@d"), "Instance Started in a New Region","Previously Seen Region") | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | where regionStatus="Instance Started in a New Region" | `ec2_instance_started_in_previously_unseen_region_filter` [ESCU - EC2 Instance Started With Previously Unseen AMI - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen AMIs. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns the AMI image ID of all successful EC2 instance launches within the last hour and then appends the historical data from the lookup file to those results. It then recalculates the earliest and latest seen time field for each AMI image ID and returns only those AMI image IDs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems. +action.escu.mappings = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for EC2 instances being created with previously unseen AMIs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. action.escu.known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen AMI - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Cryptomining"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = EC2 Instance Started With Previously Unseen AMI +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = The EC2 instance $dest$ was created with previously unused AMI $amiID$ -action.notable.param.rule_title = EC2 Instance Type $dest$ Created With New AMI -action.notable.param.security_domain = endpoint +action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen AMIs. +action.notable.param.rule_title = EC2 Instance Started With Previously Unseen AMI +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by requestParameters.instancesSet.items{}.imageId | rename requestParameters.instancesSet.items{}.imageId as amiID | inputlookup append=t previously_seen_ec2_amis.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | eval newAMI=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | where newAMI=1 | rename amiID as requestParameters.instancesSet.items{}.imageId | table requestParameters.instancesSet.items{}.imageId] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as arn, requestParameters.instancesSet.items{}.imageId as amiID | table firstTime, lastTime, arn, amiID, dest, instanceType +search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by requestParameters.instancesSet.items{}.imageId | rename requestParameters.instancesSet.items{}.imageId as amiID | inputlookup append=t previously_seen_ec2_amis.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | eval newAMI=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | where newAMI=1 | rename amiID as requestParameters.instancesSet.items{}.imageId | table requestParameters.instancesSet.items{}.imageId] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as arn, requestParameters.instancesSet.items{}.imageId as amiID | table firstTime, lastTime, arn, amiID, dest, instanceType | `ec2_instance_started_with_previously_unseen_ami_filter` [ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen instance types. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns the instance types of all successful EC2 instance launches within the last hour and then appends the historical data in the lookup file to those results. It then recalculates the earliest seen time field for each instance type and returns only those instance types that has first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems. +action.escu.mappings = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. -action.escu.creation_date = 2018-03-12 +action.escu.creation_date = 2020-02-07 action.escu.modification_date = 2020-02-07 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["AWS"] action.escu.analytic_story = ["AWS Cryptomining"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = EC2 Instance Started With Previously Unseen Instance Type +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = instanceType -action.notable.param.rule_description = The EC2 instance type $instanceType$ was used for the first time to create $dest$. -action.notable.param.rule_title = New EC2 Instance Type $instanceType$ detected -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen instance types. +action.notable.param.rule_title = EC2 Instance Started With Previously Unseen Instance Type +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | fillnull value="m1.small" requestParameters.instanceType | stats earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType | rename requestParameters.instanceType as instanceType | inputlookup append=t previously_seen_ec2_instance_types.csv | stats min(earliest) as earliest max(latest) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | eval newType=if(earliest >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | where newType=1 | rename instanceType as requestParameters.instanceType | table requestParameters.instanceType] | spath output=user userIdentity.arn | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest | table _time, user, dest, instanceType +search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | fillnull value="m1.small" requestParameters.instanceType | stats earliest(_time) as earliest latest(_time) as latest by requestParameters.instanceType | rename requestParameters.instanceType as instanceType | inputlookup append=t previously_seen_ec2_instance_types.csv | stats min(earliest) as earliest max(latest) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | eval newType=if(earliest >= relative_time(now(), "-70m@m"), 1, 0) | `security_content_ctime(earliest)` | `security_content_ctime(latest)` | where newType=1 | rename instanceType as requestParameters.instanceType | table requestParameters.instanceType] | spath output=user userIdentity.arn | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest | table _time, user, dest, instanceType | `ec2_instance_started_with_previously_unseen_instance_type_filter` [ESCU - EC2 Instance Started With Previously Unseen User - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created by users who have not created them before. -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns the ARNs of all successful EC2 instance launches within the last hour and then appends the historical data in the lookup file to those results. It then recalculates the `firstTime` and `lastTime` field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems. +action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for EC2 instances being created by users who have not created them before. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. action.escu.known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. -action.escu.creation_date = 2018-03-15 +action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen User - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["AWS"] -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = EC2 Instance Started With Previously Unseen User +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user, dest -action.notable.param.rule_description = The EC2 instance $dest$ was created by $user$. This user has never created an EC2 instance before. -action.notable.param.rule_title = EC2 Instance Created By Previously Unseen User $user$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for EC2 instances being created by users who have not created them before. +action.notable.param.rule_title = EC2 Instance Started With Previously Unseen User +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user, dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances [search sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as user | table _time, user, dest, instanceType +search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunInstances errorCode=success | stats earliest(_time) as firstTime latest(_time) as lastTime by userIdentity.arn | rename userIdentity.arn as arn | inputlookup append=t previously_seen_ec2_launches_by_user.csv | stats min(firstTime) as firstTime, max(lastTime) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | eval newUser=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newUser=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename arn as userIdentity.arn | table userIdentity.arn] | rename requestParameters.instanceType as instanceType, responseElements.instancesSet.items{}.instanceId as dest, userIdentity.arn as user | table _time, user, dest, instanceType | `ec2_instance_started_with_previously_unseen_user_filter` [ESCU - Email Attachments With Lots Of Spaces - Rule] action.escu = 0 action.escu.enabled = 1 description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. -action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.IP"]} -action.escu.data_models = ["Email"] -action.escu.eli5 = This search looks at any emails with file attachment names that contain many spaces, relative to the length of the file name. Specifically, it checks to see whether spaces make up more than 10% of the number of characters in the file name. This percentage can be tuned for each environment. The search will output the message ID of the email, the count, the sender and recipient addresses, the first and last time this event was seen, and the space ratio of the file attachment name. +action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +action.escu.data_models = Email +action.escu.eli5 = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ **Splunk Phantom Playbook Integration**\ If Splunk Phantom is also configured in your environment, a playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-04-21 +action.escu.creation_date = 2017-09-19 action.escu.modification_date = 2017-09-19 action.escu.confidence = high action.escu.full_search_name = ESCU - Email Attachments With Lots Of Spaces - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src", "message_id"] -action.escu.entities = ["src", "message_id"] -action.escu.providing_technologies = ["Microsoft Exchange"] -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Suspicious Emails"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Email Attachments With Lots Of Spaces +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user, file_name -action.notable.param.rule_description = The sender $src_user$ has sent an email with a suspicious amount of spaces in the file name: $file_name$ -action.notable.param.rule_title = Suspicious Email Attachment from $src_user$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. +action.notable.param.rule_title = Email Attachments With Lots Of Spaces +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(All_Email.recipient) as recipient_address min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | eval space_ratio = (mvcount(split(file_name," "))-1)/len(file_name) | search space_ratio >= 0.1 | rex field=recipient_address "(?.*)@" +search = | tstats `security_content_summariesonly` count values(All_Email.recipient) as recipient_address min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | eval space_ratio = (mvcount(split(file_name," "))-1)/len(file_name) | search space_ratio >= 0.1 | rex field=recipient_address "(?.*)@" | `email_attachments_with_lots_of_spaces_filter` [ESCU - Email files written outside of the Outlook directory - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Collection", "Email Collection"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = In this search, we are looking for activities consistent with an adversary collecting email data from local machines. The search will detect email files (files with .pst or .ost extensions) created in directories other than the standard Outlook directory (c:\users\username\My Documents\Outlook Files\. +action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. -action.escu.creation_date = 2017-12-13 +action.escu.creation_date = 2020-03-23 action.escu.modification_date = 2020-03-23 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Email files written outside of the Outlook directory - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Email files written outside of the Outlook directory +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_path, action, file_name -action.notable.param.rule_description = The system $dest$ has email files outside of the normal Outlook directory -action.notable.param.rule_title = Email files created or modified on $dest$ that are not in the normal Outlook directory -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. +action.notable.param.rule_title = Email files written outside of the Outlook directory +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, file_path -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name=*.pst OR Filesystem.file_name=*.ost) Filesystem.file_path != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name("Filesystem")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `email_files_not_in_outlook_directory_filter` @@ -4686,263 +3234,186 @@ search = | tstats `security_content_summariesonly` count values(Filesystem.file_ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. -action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Collection", "Email Collection", "Commonly Used Port"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search may look complex, but it's a neat representation of how statistics can help you understand your dataset to bubble up events that are not normal compared to its behavior. The search consists of three parts. The first part of the SPL fetches the data you want to work on. In this search, we calculate the sum of bytes sent and bytes_out from systems categorized as email_server to each host. We then calculate the average and standard deviation for the bytes sent to all the hosts combined and on a per-host basis. Then we set threshold values to deviation_threshold and minimum_data_samples using eval statements. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. We then check for byte transfers that are statistically significantly higher than normal. The search then gives IP address of the host, the time of the increased byte transfer, how much data was transferred, and the average amount of data transfer the email server normally sends to all hosts and to this specific host. Finally, it includes the number of standard deviations away the byte count was from these averages. +action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. action.escu.creation_date = 2017-12-20 action.escu.modification_date = 2017-12-20 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Email servers sending high volume traffic to hosts - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest_ip"] -action.escu.entities = ["dest_ip"] -action.escu.providing_technologies = ["Bro", "Splunk Stream"] action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = 0 0 * * * -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Email servers sending high volume traffic to hosts +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest_ip -action.notable.param.rule_description = High volume of traffic that originated from an email server is being sent to $dest_ip$ -action.notable.param.rule_title = High volume of traffic from an email server sent to $dest_ip$ -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. +action.notable.param.rule_title = Email servers sending high volume traffic to hosts +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest_ip -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as bytes_out from datamodel=Network_Traffic where All_Traffic.src_category=email_server by All_Traffic.dest_ip _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_out) as avg_bytes_out stdev(bytes_out) as stdev_bytes_out | eventstats count as num_data_samples avg(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_avg_bytes_out stdev(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_stdev_bytes_out by dest_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples >= minimum_data_samples AND bytes_out > (avg_bytes_out + (deviation_threshold * stdev_bytes_out)) AND bytes_out > (per_source_avg_bytes_out + (deviation_threshold * per_source_stdev_bytes_out)) AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average = round(abs(bytes_out - avg_bytes_out) / stdev_bytes_out, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_out - per_source_avg_bytes_out) / per_source_stdev_bytes_out, 2) | table dest_ip, _time, bytes_out, avg_bytes_out, per_source_avg_bytes_out, num_standard_deviations_away_from_server_average, num_standard_deviations_away_from_client_average +search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as bytes_out from datamodel=Network_Traffic where All_Traffic.src_category=email_server by All_Traffic.dest_ip _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_out) as avg_bytes_out stdev(bytes_out) as stdev_bytes_out | eventstats count as num_data_samples avg(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_avg_bytes_out stdev(eval(if(_time < relative_time(now(), "@d"), bytes_out, null))) as per_source_stdev_bytes_out by dest_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples >= minimum_data_samples AND bytes_out > (avg_bytes_out + (deviation_threshold * stdev_bytes_out)) AND bytes_out > (per_source_avg_bytes_out + (deviation_threshold * per_source_stdev_bytes_out)) AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average = round(abs(bytes_out - avg_bytes_out) / stdev_bytes_out, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_out - per_source_avg_bytes_out) / per_source_stdev_bytes_out, 2) | table dest_ip, _time, bytes_out, avg_bytes_out, per_source_avg_bytes_out, num_standard_deviations_away_from_server_average, num_standard_deviations_away_from_client_average | `email_servers_sending_high_volume_traffic_to_hosts_filter` [ESCU - Excessive DNS Failures - Rule] action.escu = 0 action.escu.enabled = 1 description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Exfiltration", "Exfiltration Over Alternative Protocol", "Command and Control", "Commonly Used Port"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = This search looks at DNS traffic with a reply code that is NOT indicative of a successful response. Numerous unsuccessful replies may be indicative of DNS protocol tampering or other malicious activity. If more than 50 of these unsuccessful responses are observed over the time frame of the search, a notable event will be generated. +action.escu.mappings = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2017-09-18 action.escu.modification_date = 2017-09-18 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Excessive DNS Failures - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Excessive DNS Failures +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, query -action.notable.param.rule_description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success and triggers on more than 50 occurrences. +action.notable.param.rule_description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.notable.param.rule_title = Excessive DNS Failures -action.notable.param.security_domain = network +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src,query -alert.suppress.period = 43200s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values("DNS.query") as queries from datamodel=Network_Resolution where nodename=DNS "DNS.reply_code"!="No Error" "DNS.reply_code"!="NoError" DNS.reply_code!="unknown" NOT "DNS.query"="*.arpa" "DNS.query"="*.*" by "DNS.src","DNS.query"| `drop_dm_object_name("DNS")`| lookup cim_corporate_web_domain_lookup domain as query OUTPUT domain| where isnull(domain)| lookup update=true alexa_lookup_by_str domain as query OUTPUT rank| where isnull(rank)| stats sum(count) as count mode(queries) as queries by src| `get_asset(src)`| where count>50 +search = | tstats `security_content_summariesonly` count values("DNS.query") as queries from datamodel=Network_Resolution where nodename=DNS "DNS.reply_code"!="No Error" "DNS.reply_code"!="NoError" DNS.reply_code!="unknown" NOT "DNS.query"="*.arpa" "DNS.query"="*.*" by "DNS.src","DNS.query"| `drop_dm_object_name("DNS")`| lookup cim_corporate_web_domain_lookup domain as query OUTPUT domain| where isnull(domain)| lookup update=true alexa_lookup_by_str domain as query OUTPUT rank| where isnull(rank)| stats sum(count) as count mode(queries) as queries by src| `get_asset(src)`| where count>50 | `excessive_dns_failures_filter` [ESCU - Execution of File With Spaces Before Extension - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Persistence", "Change Default File Association"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search uses the endpoint data model to look for process names with at least five spaces between the file name and its extension. +action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = None identified. action.escu.creation_date = 2018-01-26 action.escu.modification_date = 2018-01-26 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Execution of File With Spaces Before Extension - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Windows File Extension and Association Abuse"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Execution of File With Spaces Before Extension +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = The system $dest$ executed a file with spaces before its extension. -action.notable.param.rule_title = Process $process$ with spaces before extension Launched on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. +action.notable.param.rule_title = Execution of File With Spaces Before Extension +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process_path) as process_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "* .*" by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` +search = | tstats `security_content_summariesonly` count values(Processes.process_path) as process_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = "* .*" by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `execution_of_file_with_spaces_before_extension_filter` [ESCU - Execution of File with Multiple Extensions - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Persistence", "Change Default File Association"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search uses the "Application State" data model to look for process names with specific combinations of double extensions. Relatively straightforward, the search looks for strings in the "process" field that match what you're looking for. +action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. action.escu.known_false_positives = None identified. -action.escu.creation_date = 2018-01-26 +action.escu.creation_date = 2018-11-02 action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Execution of File with Multiple Extensions - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Windows File Extension and Association Abuse"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Execution of File with Multiple Extensions +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process -action.notable.param.rule_description = The system $dest$ executed a file with a double extension. -action.notable.param.rule_title = Process With Multiple Extensions Launched on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. +action.notable.param.rule_title = Execution of File with Multiple Extensions +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = *.doc.exe OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe by Processes.dest Processes.user Processes.process Processes.parent_process | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process = *.doc.exe OR Processes.process = *.htm.exe OR Processes.process = *.html.exe OR Processes.process = *.txt.exe OR Processes.process = *.pdf.exe OR Processes.process = *.doc.exe by Processes.dest Processes.user Processes.process Processes.parent_process | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `execution_of_file_with_multiple_extensions_filter` [ESCU - Extended Period Without Successful Netbackup Backups - Rule] action.escu = 0 action.escu.enabled = 1 description = This search returns a list of hosts that have not successfully completed a backup in over a week. -action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -action.escu.eli5 = This search finds all the successful backup messages in your logs, and then looks for the most recent backup time for each system. It then identifies those systems where the most recent successful backup time is over a week ago, and reports on them. +action.escu.mappings = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search returns a list of hosts that have not successfully completed a backup in over a week. action.escu.how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-06-15 +action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Extended Period Without Successful Netbackup Backups - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Netbackup"] action.escu.analytic_story = ["Monitor Backup Solution"] -cron_schedule = 0 0 1 * * -dispatch.earliest_time = -7d@d -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Extended Period Without Successful Netbackup Backups +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = The system $dest$ has not had a successful backup for an extended period. -action.notable.param.rule_title = Extended period of no successful backups by $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 10 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search returns a list of hosts that have not successfully completed a backup in over a week. +action.notable.param.rule_title = Extended Period Without Successful Netbackup Backups +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="netbackup_logs" MESSAGE="Disk/Partition backup completed successfully." | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest +search = `netbackup` MESSAGE="Disk/Partition backup completed successfully." | stats latest(_time) as latestTime by COMPUTERNAME | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest | eval isOutlier=if(latestTime <= relative_time(now(), "-7d@d"), 1, 0) | search isOutlier=1 | table latestTime, dest | `extended_period_without_successful_netbackup_backups_filter` [ESCU - File with Samsam Extension - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks at file modifications across your hosts and creates notable events when it identifies files with extensions associated with the SamSam ransomware, including `.stubbin`, `.berkshire`, `.satoshi`, `.sophos`, or `.keyxml`. Files with these extensions have been observed in SamSam attacks consisting of payload data or keying material. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. action.escu.creation_date = 2018-12-14 @@ -4950,141 +3421,95 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - File with Samsam Extension - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = File with Samsam Extension +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A file with an extension associated with SamSam ransomware was written on $dest$. -action.notable.param.rule_title = File with known SamSam extension detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. +action.notable.param.rule_title = File with Samsam Extension +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_extension=.stubbin OR file_extension=.berkshire OR file_extension=.satoshi OR file_extension=.sophos OR file_extension=.keyxml +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`| rex field=file_name "(?\.[^\.]+)$" | search file_extension=.stubbin OR file_extension=.berkshire OR file_extension=.satoshi OR file_extension=.sophos OR file_extension=.keyxml | `file_with_samsam_extension_filter` [ESCU - First Time Seen Running Windows Service - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the first time a Windows service is seen running in your environment. -action.escu.mappings = {"cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Execution", "New Service"], "mitre_technique_id": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} -action.escu.eli5 = This search looks for a change in the status of a Windows service and extracts the name of the service and the action taken by the service. Then the cache file of previously seen Windows services is added to the search. At this point, the search takes two different paths: the first updates the cache file with the latest information and the second searches for services that have never before been seen. It returns the time, the Windows host name, and the service name. +action.escu.mappings = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for the first time a Windows service is seen running in your environment. action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. action.escu.known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. -action.escu.creation_date = 2018-07-22 +action.escu.creation_date = 2020-01-13 action.escu.modification_date = 2020-01-13 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - First Time Seen Running Windows Service - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse"] -cron_schedule = 30 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = First Time Seen Running Windows Service +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = service_name -action.notable.param.rule_description = The service $service_name$ is running on $dest$. This is the first time this service has been run on any system. -action.notable.param.rule_title = First Time Seen Windows Service $service_name$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for the first time a Windows service is seen running in your environment. +action.notable.param.rule_title = First Time Seen Running Windows Service +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = service_name, dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" [ search eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | inputlookup append=t previously_seen_running_windows_services | stats min(firstTime) as firstTime max(lastTime) as lastTime by service_name | outputlookup previously_seen_running_windows_services| eval serviceStatus=if(firstTime >= relative_time(now(),"-60m@m"), "First time seen Windows service","Previously seen Windows service") | where serviceStatus="First time seen Windows service"| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table service_name]| table _time dest service_name +search = `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" [ search `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | inputlookup append=t previously_seen_running_windows_services | stats min(firstTime) as firstTime max(lastTime) as lastTime by service_name | outputlookup previously_seen_running_windows_services| eval serviceStatus=if(firstTime >= relative_time(now(),"-60m@m"), "First time seen Windows service","Previously seen Windows service") | where serviceStatus="First time seen Windows service"| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table service_name]| table _time dest service_name | `first_time_seen_running_windows_service_filter` [ESCU - First time seen command line argument - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "Scripting", "Persistence", "Command-Line Interface"], "mitre_technique_id": ["T1059", "T1117", "T1202"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The subsearch returns all events where `cmd.exe` was used with a `/c` parameter in the command-line arguments to execute other commands/programs. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for command-line execution and outputs this data to the lookup file to update the local cache. It returns only those events that have first been seen in the past one hour. This is combined with the main search to return the time, user, destination, process, parent process, and value of the command-line argument. +action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. action.escu.known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name -action.escu.creation_date = 2018-04-09 +action.escu.creation_date = 2020-03-02 action.escu.modification_date = 2020-03-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - First time seen command line argument - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "process_name", "user"] -action.escu.entities = ["dest", "process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions"] -cron_schedule = 30 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = First time seen command line argument +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = The system $dest$ executed a command-line argument, $process$, that has not previously been seen. -action.notable.param.rule_title = First-time seen command-line argument was detected on $dest$. -action.notable.param.security_domain = endpoint +action.notable.param.rule_description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. +action.notable.param.rule_title = First time seen command line argument +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process Processes.process_name Processes.parent_process_name Processes.dest| `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process | `drop_dm_object_name(Processes)` | inputlookup append=t previously_seen_cmd_line_arguments | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCmdLineArgument=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table process] | `first_time_seen_cmd_line_filter` @@ -5092,46 +3517,34 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_ action.escu = 0 action.escu.enabled = 1 description = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. -action.escu.mappings = {"mitre_attack": ["Persistence"], "mitre_technique_id": ["T1525"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = In this search we can detect if a new container has been uploaded to Google Container Registry, operator can monitor users uploading containers, object paths of new uploaded containers. +action.escu.mappings = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "GCP GCR Container", "security_domain": "threat"} +action.escu.eli5 = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. action.escu.creation_date = 2020-02-20 action.escu.modification_date = 2020-02-20 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - GCP GCR container uploaded - Rule action.escu.search_type = detection -action.escu.asset_at_risk = GCP GCR Container -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] -action.escu.providing_technologies = ["GCP"] -action.escu.analytic_story = ["Container Implantation Monitoring & Investigation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = GCP GCR container uploaded +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user, account, bucket_name, event_name -action.notable.param.rule_description = An GCP GCR container uploaded by $src_user$ +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. action.notable.param.rule_title = GCP GCR container uploaded -action.notable.param.security_domain = threat +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Storage where Storage.event_name=storage.objects.create by Storage.src_user Storage.account Storage.action Storage.bucket_name Storage.event_name Storage.http_user_agent Storage.msg Storage.object_path | `drop_dm_object_name("Storage")` | `container_implant_gcp_detection_filter` @@ -5139,96 +3552,69 @@ search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM data action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster -action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery"], "mitre_technique_id": ["T1190"]} -action.escu.eli5 = In this search we can detect unauthenticated web requests and possible attack against a GCP cluster, by looking at k8s authentication data, user agent, source IPs and destionation +action.escu.mappings = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "GCP Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. -action.escu.creation_date = 2020-03-24 +action.escu.creation_date = 2020-04-15 action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - GCP Kubernetes cluster scan detection - Rule action.escu.search_type = detection -action.escu.asset_at_risk = GCP Kubernetes cluster -action.escu.fields_required = ["cluster_name", "src_ip"] -action.escu.entities = ["cluster_name", "src_ip"] -action.escu.providing_technologies = ["GCP"] action.escu.analytic_story = ["Kubernetes Scanning Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = GCP Kubernetes cluster scan detection +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, -action.notable.param.rule_description = Detect scanning attempts against a GCP Kubernetes cluster +action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.notable.param.rule_title = GCP Kubernetes cluster scan detection -action.notable.param.security_domain = threat -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = cluster_name -action.risk.param._risk_object_type = other -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_name values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_gcp_scan_fingerprint_detection` +search = `google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_name values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_gcp_scan_fingerprint_filter` -[ESCU - Hiding Files And Directories With Attrib.exe - Rule] +[ESCU - Hiding Files And Directories With Attrib exe - Rule] action.escu = 0 action.escu.enabled = 1 description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Persistence"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search is looking to detect command-line execution with of attrib.exe binary with the +h flag set. The +h flag is used to hide a file. +action.escu.mappings = {"analytics_story": ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. -action.escu.creation_date = 2017-10-23 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Hiding Files And Directories With Attrib.exe - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Hiding Files And Directories With Attrib exe - Rule action.escu.search_type = detection -action.escu.asset_at_risk = -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"] -cron_schedule = 30 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Hiding Files And Directories With Attrib.exe +action.correlationsearch.label = Hiding Files And Directories With Attrib exe +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = Attrib.exe is often used by attackers to hide malware files and directories in windows environments. This rule detects command-line arguments used to hide a file/directory -action.notable.param.rule_title = Suspicious usage of attrib.exe on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. +action.notable.param.rule_title = Hiding Files And Directories With Attrib exe +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `attrib_to_hide_files_filter` @@ -5236,460 +3622,318 @@ search = | tstats `security_content_summariesonly` count min(_time) values(Proce action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. -action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Collection", "Commonly Used Port"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search may look complex, but it's a neat representation of how statistics can help you understand your dataset to bubble up events that are not normal compared to its behavior. The search consists of three parts. The first part of the SPL fetches the data you want to work on. In this search, we calculate the sum of bytes sent and bytes_out from systems categorized as email_server to each host. We then calculate the average and standard deviation for the bytes sent to all the hosts combined and on a per-host basis. Then we set threshold values to deviation_threshold and minimum_data_samples using eval statements. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. We then check for byte transfers that are statistically significantly higher than normal. The search then gives IP address of the host, the time of the increased byte transfer, how much data was transferred, and the average amount of data transfer the email server normally sends to all hosts and to this specific host. Finally, it includes the number of standard deviations away the byte count was from these averages. +action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. action.escu.creation_date = 2017-12-20 action.escu.modification_date = 2017-12-20 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Hosts receiving high volume of network traffic from email server - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["Bro", "Splunk Stream"] action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = 0 0 * * * -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Hosts receiving high volume of network traffic from email server +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip -action.notable.param.rule_description = $src_ip$ receiving high volume of traffic that originated from an email server -action.notable.param.rule_title = High volume traffic from email server received by $src_ip$ -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. +action.notable.param.rule_title = Hosts receiving high volume of network traffic from email server +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_ip -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as bytes_in from datamodel=Network_Traffic where All_Traffic.dest_category=email_server by All_Traffic.src_ip _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_in) as avg_bytes_in stdev(bytes_in) as stdev_bytes_in | eventstats count as num_data_samples avg(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_avg_bytes_in stdev(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_stdev_bytes_in by src_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples >= minimum_data_samples AND bytes_in > (avg_bytes_in + (deviation_threshold * stdev_bytes_in)) AND bytes_in > (per_source_avg_bytes_in + (deviation_threshold * per_source_stdev_bytes_in)) AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average = round(abs(bytes_in - avg_bytes_in) / stdev_bytes_in, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_in - per_source_avg_bytes_in) / per_source_stdev_bytes_in, 2) | table src_ip, _time, bytes_in, avg_bytes_in, per_source_avg_bytes_in, num_standard_deviations_away_from_server_average, num_standard_deviations_away_from_client_average +search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as bytes_in from datamodel=Network_Traffic where All_Traffic.dest_category=email_server by All_Traffic.src_ip _time span=1d | `drop_dm_object_name("All_Traffic")` | eventstats avg(bytes_in) as avg_bytes_in stdev(bytes_in) as stdev_bytes_in | eventstats count as num_data_samples avg(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_avg_bytes_in stdev(eval(if(_time < relative_time(now(), "@d"), bytes_in, null))) as per_source_stdev_bytes_in by src_ip | eval minimum_data_samples = 4, deviation_threshold = 3 | where num_data_samples >= minimum_data_samples AND bytes_in > (avg_bytes_in + (deviation_threshold * stdev_bytes_in)) AND bytes_in > (per_source_avg_bytes_in + (deviation_threshold * per_source_stdev_bytes_in)) AND _time >= relative_time(now(), "@d") | eval num_standard_deviations_away_from_server_average = round(abs(bytes_in - avg_bytes_in) / stdev_bytes_in, 2), num_standard_deviations_away_from_client_average = round(abs(bytes_in - per_source_avg_bytes_in) / per_source_stdev_bytes_in, 2) | table src_ip, _time, bytes_in, avg_bytes_in, per_source_avg_bytes_in, num_standard_deviations_away_from_server_average, num_standard_deviations_away_from_client_average | `hosts_receiving_high_volume_of_network_traffic_from_email_server_filter` [ESCU - Identify New User Accounts - Rule] action.escu = 0 action.escu.enabled = 1 description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Persistence", "Create Account"], "nist": ["PR.IP"]} -action.escu.data_models = ["Identity_Management"] -action.escu.eli5 = Adversaries will often seek to create new user accounts as a means of maintaining access to a target environment. Using this search, we identify accounts created in the last week by comparing the start date in the Identity_Management data model against the current time. +action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Domain Server", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.eli5 = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. action.escu.how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. action.escu.known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. -action.escu.creation_date = 2017-08-05 +action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Identify New User Accounts - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Domain Server -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Active Directory"] action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = 0 0 * * * -dispatch.earliest_time = -24h@h -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Identify New User Accounts +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = Using the identities lookup and macro from Enterprise Security to identify (report) new users (6 month period) and temp users (3 months until account expiration) -action.notable.param.rule_title = Identify Temporary Users -action.notable.param.security_domain = access +action.notable.param.rule_description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. +action.notable.param.rule_title = Identify New User Accounts +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = identity -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | from datamodel Identity_Management.All_Identities | eval empStatus=case((now()-startDate)<604800, "Accounts created in last week") | search empStatus="Accounts created in last week"| `security_content_ctime(endDate)` | `security_content_ctime(startDate)`| table identity empStatus endDate startDate +search = | from datamodel Identity_Management.All_Identities | eval empStatus=case((now()-startDate)<604800, "Accounts created in last week") | search empStatus="Accounts created in last week"| `security_content_ctime(endDate)` | `security_content_ctime(startDate)`| table identity empStatus endDate startDate | `identify_new_user_accounts_filter` [ESCU - Large Volume of DNS ANY Queries - Rule] action.escu = 0 action.escu.enabled = 1 description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. -action.escu.mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = This search counts the number of DNS ANY queries received in 5 minutes, and generates a Notable Event if the count exceeds a predefined threshold. The search returns the count, the first time, and the last time a DNS packet was observed with the ANY flag set. +action.escu.mappings = {"analytics_story": ["DNS Amplification Attacks"], "asset_type": "DNS Servers", "cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. -action.escu.creation_date = 2016-08-24 +action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Large Volume of DNS ANY Queries - Rule action.escu.search_type = detection -action.escu.asset_at_risk = DNS Servers -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] action.escu.analytic_story = ["DNS Amplification Attacks"] -cron_schedule = */5 * * * * -dispatch.earliest_time = -15m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Large Volume of DNS ANY Queries +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest action.notable.param.rule_description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.notable.param.rule_title = Large Volume of DNS ANY Queries -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 7200s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" "DNS.record_type"="ANY" by "DNS.dest" | `drop_dm_object_name("DNS")` | where count>200 +search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution where nodename=DNS "DNS.message_type"="QUERY" "DNS.record_type"="ANY" by "DNS.dest" | `drop_dm_object_name("DNS")` | where count>200 | `large_volume_of_dns_any_queries_filter` [ESCU - MacOS - Re-opened Applications - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "mitre_attack": ["Persistence"], "mitre_technique_id": ["T1164"], "nist": ["DE.DP", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks at the Endpoint data model to identify any MacOS process events referencing a property list file which determines which applications are "re-opened" during startup. This could indicate a malicious attempt to establish persistence on the system. +action.escu.mappings = {"asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"], "security_domain": "threat"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. action.escu.known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. action.escu.creation_date = 2020-02-07 action.escu.modification_date = 2020-02-07 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - MacOS - Re-opened Applications - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["host"] -action.escu.entities = ["host"] -action.escu.providing_technologies = ["OSquery"] -action.escu.analytic_story = [] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = MacOS - Re-opened Applications +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = host -action.notable.param.rule_description = Observed process referencing MacOS com.apple.loginwindow.plist files for Host $host$ -action.notable.param.rule_title = Possible attempt to establish persistence on $host$ -action.notable.param.security_domain = threat +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. +action.notable.param.rule_title = MacOS - Re-opened Applications +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = host -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = host -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process="*com.apple.loginwindow*" by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process="*com.apple.loginwindow*" by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `macos___re_opened_applications_filter` [ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for PowerShell processes running with specific command-line arguments that indicate that the process will download a file from the Internet without display anything to the user. The search for "*-Exec*" is to check and see if the default execution policy for PowerShell is being overridden on the command-line. The search for "*-WindowStyle*" and "*hidden*" are to see if the window that would normally be displayed will be hidden from the user instead. Finally, the search for "*New-Object*" and "*System.Net.WebClient*" are there to check to see if a PowerShell object that can be used to download files will be created. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process. +action.escu.mappings = {"analytics_story": ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -action.escu.creation_date = 2016-09-18 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "process_name", "user"] -action.escu.entities = ["dest", "process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Malicious PowerShell Process - Connect To Internet With Hidden Window +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = The system $dest$ executed a PowerShell process that connects to the Internet with a hidden window. -action.notable.param.rule_title = Malicious PowerShell Process detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. +action.notable.param.rule_title = Malicious PowerShell Process - Connect To Internet With Hidden Window +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 75 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = process_name, dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process="*-Exec*" process="*-WindowStyle*" process="*hidden*" process="*New-Object*" process="*System.Net.WebClient*" +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process="*-Exec*" process="*-WindowStyle*" process="*hidden*" process="*New-Object*" process="*System.Net.WebClient*" | `malicious_powershell_process___connect_to_internet_with_hidden_window_filter` [ESCU - Malicious PowerShell Process - Encoded Command - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for PowerShell processes that are passing encoded commands on the command-line. The flags "-EncodedCommand" and "-enc" are two different possible flags that can be used to pass base64 encoded commands to PowerShell. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process. +action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = System administrators may use this option, but it's not common. -action.escu.creation_date = 2016-09-18 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Encoded Command - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "process_name", "user"] -action.escu.entities = ["dest", "process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Malicious PowerShell"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Malicious PowerShell Process - Encoded Command +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = The system $dest$ executed a PowerShell process that has an encoded command on the command-line -action.notable.param.rule_title = PowerShell process with an encoded command detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. +action.notable.param.rule_title = Malicious PowerShell Process - Encoded Command +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user, process_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*-EncodedCommand* OR process=*-enc* +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*-EncodedCommand* OR process=*-enc* | `malicious_powershell_process___encoded_command_filter` [ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for PowerShell processes that were launched using a parameter designed to bypass the local PowerShell execution policy. By default, the policy is set to "Restricted," which disables the execution of PowerShell scripts. In environments that make heavy use of PowerShell, the policy can be set to allow only scripts signed by a trusted publisher. Malicious PowerShell use almost always includes the parameter `-ExecutionPolicy bypass`. PowerShell is very liberal when it comes to interpreting command-line parameters passed to it. For example, the parameter we look for, `-ExecutionPolicy`, can be abbreviated to `-Execution`, `-Exec`, or even `-ex`. As such, we look for `* -ex*`, which should catch all variations of this parameter, followed by the keyword `bypass`. This search will return the host, the user the process ran under, the process and its command-line arguments, the number of times it has seen this process, and the first and last times it saw this process. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. -action.escu.creation_date = 2018-03-19 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "process_id", "process", "parent_process_id"] -action.escu.entities = ["dest", "process_id", "process", "parent_process_id"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = 50 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Malicious PowerShell Process - Execution Policy Bypass +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = The system $dest$ executed a PowerShell process with parameters to bypass the local execution policy. -action.notable.param.rule_title = PowerShell process with -executionpolicy bypass detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. +action.notable.param.rule_title = Malicious PowerShell Process - Execution Policy Bypass +action.notable.param.security_domain = action.notable.param.severity = medium -action.notable.param.drilldown_name = View powershell process information on $dest$ -action.notable.param.drilldown_search = | from datamodel:Endpoint.Processes | search dest="$dest$" process_id=$process_id$ -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process_id) as process_id, values(Processes.parent_process_id) as parent_process_id values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe AND (Processes.process="* -ex*" OR Processes.process="* bypass *") by Processes.process_id, Processes.user, Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process_id) as process_id, values(Processes.parent_process_id) as parent_process_id values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe AND (Processes.process="* -ex*" OR Processes.process="* bypass *") by Processes.process_id, Processes.user, Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `malicious_powershell_process___execution_policy_bypass_filter` [ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for PowerShell processes that have a number of suspicious flags on the command-line. It is looking for flags are passing encoded commands on the command-line. The flags `-EncodedCommand` and `-enc` are two different possible flags that can be used to pass base64 encoded commands to PowerShell. The `*-Exec*` flag looks to see it the default execution policy of PowerShell is being overridden, while the `*-NonI*` flag tells the PowerShell process that this will be a noninteractive process, so the user doesn't know about the process. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process. +action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -action.escu.creation_date = 2016-09-18 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest", "process_name", "user"] -action.escu.entities = ["dest", "process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Malicious PowerShell"] -cron_schedule = 50 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process, process_name -action.notable.param.rule_description = The system $dest$ executed a PowerShell that had an encoded command on the command-line, attempted to bypass local execution policy, and prevented the display of an interactive prompt to the user. -action.notable.param.rule_title = PowerShell process with multiple suspicious command-line arguments detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. +action.notable.param.rule_title = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI* +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search (process=*-EncodedCommand* OR process=*-enc*) process=*-Exec* AND process=*-NonI* | `malicious_powershell_process___multiple_suspicious_command_line_arguments_filter` [ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for PowerShell processes that are passing command-line arguments with unusual characters (backticks and carets) that are PowerShell specific escape characters. Attackers use this obfuscation technique since it does not affect the functionality of PowerShell and it will bypass standard security controls that look for straight up malicious strings and commands. The search counts the occurrence of these obfuscation characters and lists out destination IPs running these PowerShell commands. +action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = These characters might be legitimately on the command-line, but it is not common. -action.escu.creation_date = 2017-04-25 +action.escu.creation_date = 2020-01-17 action.escu.modification_date = 2020-01-17 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Malicious PowerShell"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Malicious PowerShell Process With Obfuscation Techniques +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name, process -action.notable.param.rule_description = The system $dest$ executed a PowerShell process that has evidence of obfuscation on the command-line -action.notable.param.rule_title = PowerShell process with an obfuscation techniques detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. +action.notable.param.rule_title = Malicious PowerShell Process With Obfuscation Techniques +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process_name,process -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process, "`"))-1) + (mvcount(split(process, "^"))-1) | `malicious_powershell_process_obfuscation_techniques_output_filter` | search num_obfuscation > 0 @@ -5697,212 +3941,149 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. -action.escu.mappings = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} -action.escu.data_models = ["Network_Resolution"] -action.escu.eli5 = This search gathers all the answers to each system's DNS query, then filters out all queries that do not appear on the list of faux "look-a-like" domains that have been generated from the brand abuse domains you are monitoring. +action.escu.mappings = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "kill_chain_phases": ["Delivery", "Actions on Objectives"], "security_domain": "network"} +action.escu.data_models = Network_Resolution +action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-06-01 +action.escu.creation_date = 2017-09-23 action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor DNS For Brand Abuse - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] action.escu.analytic_story = ["Brand Monitoring"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Monitor DNS For Brand Abuse +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, query -action.notable.param.rule_description = The host $src$ issued a DNS request for a domain to that which you are monitoring for brand abuse. -action.notable.param.rule_title = DNS Query Brand Abuse from $src$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src,query -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. +action.notable.param.rule_title = Monitor DNS For Brand Abuse +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(DNS.answer) as IPs min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)`| `brand_abuse_dns` +search = | tstats `security_content_summariesonly` values(DNS.answer) as IPs min(_time) as firstTime from datamodel=Network_Resolution by DNS.src, DNS.query | `drop_dm_object_name("DNS")` | `security_content_ctime(firstTime)`| `brand_abuse_dns` | `monitor_dns_for_brand_abuse_filter` [ESCU - Monitor Email For Brand Abuse - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. -action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = ["Email"] -action.escu.eli5 = This search looks at the sender address in email headers, and identifies those with a sender address using a domain name that matches the list of permutations generated for the domain you want to monitor. +action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +action.escu.data_models = Email +action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-06-01 +action.escu.creation_date = 2018-01-05 action.escu.modification_date = 2018-01-05 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Email For Brand Abuse - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] -action.escu.providing_technologies = ["Microsoft Exchange", "Bro", "Splunk Stream"] -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Emails", "Brand Monitoring"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Monitor Email For Brand Abuse +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user, message_id -action.notable.param.rule_description = The sender $src_user$ has sent an email from a similar domain to that which you are monitoring for brand abuse. -action.notable.param.rule_title = Possible Brand Abuse from $src_user$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = message_id, src_user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. +action.notable.param.rule_title = Monitor Email For Brand Abuse +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(All_Email.recipient) as recipients, min(_time) as firstTime, max(_time) as lastTime from datamodel=Email by All_Email.src_user, All_Email.message_id | `drop_dm_object_name("All_Email")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval temp=split(src_user, "@") | eval email_domain=mvindex(temp, 1) | lookup update=true brandMonitoring_lookup domain as email_domain OUTPUT domain_abuse | search domain_abuse=true | table message_id, src_user, email_domain, recipients, firstTime, lastTime +search = | tstats `security_content_summariesonly` values(All_Email.recipient) as recipients, min(_time) as firstTime, max(_time) as lastTime from datamodel=Email by All_Email.src_user, All_Email.message_id | `drop_dm_object_name("All_Email")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval temp=split(src_user, "@") | eval email_domain=mvindex(temp, 1) | lookup update=true brandMonitoring_lookup domain as email_domain OUTPUT domain_abuse | search domain_abuse=true | table message_id, src_user, email_domain, recipients, firstTime, lastTime | `monitor_email_for_brand_abuse_filter` [ESCU - Monitor Registry Keys for Print Monitors - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Privilege Escalation", "Local Port Monitor"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = In this search, we look for modifications to registry keys used for adding print-monitor entries on Microsoft platforms via the `registry_path` field in the endpoint data model. It then provides the destination, command used to initiate the change, the user who conducted this activity, the resource affected (registry_key_name), and the entire path of the registry. +action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = You will encounter noise from legitimate print-monitor registry entries. -action.escu.creation_date = 2017-12-01 +action.escu.creation_date = 2018-11-02 action.escu.modification_date = 2018-11-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Registry Keys for Print Monitors - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Monitor Registry Keys for Print Monitors +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, registry_path -action.notable.param.rule_description = A registry key associated with adding print monitors can potentially be misused by giving it a path of a malicious .dll in the registry. -action.notable.param.rule_title = Registry Key changes for Print Monitors detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. +action.notable.param.rule_title = Monitor Registry Keys for Print Monitors +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, registry_path -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.action=modified AND Registry.registry_path="*CurrentControlSet\\Control\\Print\\Monitors*" by Registry.dest, Registry.registry_key_name Registry.status Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.action=modified AND Registry.registry_path="*CurrentControlSet\\Control\\Print\\Monitors*" by Registry.dest, Registry.registry_key_name Registry.status Registry.user Registry.registry_path Registry.action | `drop_dm_object_name(Registry)` | `monitor_registry_keys_for_print_monitors_filter` [ESCU - Monitor Web Traffic For Brand Abuse - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. -action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.IP"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search looks at all the URLs an endpoint is connecting to and then checks the URL against a list of faux domains that could be indicative of brand abuse. +action.escu.mappings = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +action.escu.data_models = Web +action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-06-01 +action.escu.creation_date = 2017-09-23 action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Web Traffic For Brand Abuse - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] action.escu.analytic_story = ["Brand Monitoring"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Monitor Web Traffic For Brand Abuse +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, url -action.notable.param.rule_description = The host $src$ connected to a web site with a domain similar to that which you are monitoring for brand abuse. -action.notable.param.rule_title = Web URL Brand Abuse from $src$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. +action.notable.param.rule_title = Monitor Web Traffic For Brand Abuse +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Web.url) as urls min(_time) as firstTime from datamodel=Web by Web.src | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `brand_abuse_web` +search = | tstats `security_content_summariesonly` values(Web.url) as urls min(_time) as firstTime from datamodel=Web by Web.src | `drop_dm_object_name("Web")` | `security_content_ctime(firstTime)` | `brand_abuse_web` | `monitor_web_traffic_for_brand_abuse_filter` [ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} -action.escu.eli5 = This search detects instances when there are more than 5 distinct users failing Okta logins due to invalid credentails from the same IP address. This may be indicative of attack techniques such as credential stuffing or password spraying, where an attacker attempts to login using common or found passwords and attempts to authenticate with them. +action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.eli5 = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. action.escu.creation_date = 2020-04-01 @@ -5910,87 +4091,59 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Infrastructure -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["Okta"] action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Multiple Okta Users With Invalid Credentails From The Same IP +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip -action.notable.param.rule_description = Multiple Users Failing Authenticaiton From $src_ip$ -action.notable.param.rule_title = Multiple Okta Users With Authentication Failures From a Single IP -action.notable.param.security_domain = access -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = system -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_ip -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. +action.notable.param.rule_title = Multiple Okta Users With Invalid Credentails From The Same IP +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = eventtype=okta_log outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter` +search = `okta` outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter` [ESCU - New container uploaded to AWS ECR - Rule] action.escu = 0 action.escu.enabled = 1 description = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. -action.escu.mappings = {"mitre_attack": ["Persistence"], "mitre_technique_id": ["T1525"]} -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.eli5 = In this search we can detect if a new container has been uploaded to Amazon Elastic Container Registry, operator can monitor users uploading containers, image ids of new uploaded containers. +action.escu.mappings = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "AWS ECR container", "security_domain": "threat"} +action.escu.eli5 = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. action.escu.creation_date = 2020-02-20 action.escu.modification_date = 2020-02-20 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - New container uploaded to AWS ECR - Rule action.escu.search_type = detection -action.escu.asset_at_risk = AWS ECR container -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] -action.escu.providing_technologies = ["AWS"] -action.escu.analytic_story = ["Container Implantation Monitoring & Investigation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = New container uploaded to AWS ECR +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = image_id, src_user, region, user_type -action.notable.param.rule_description = A new container with image id $image_id$ uploaded to AWS ECR by user $src_user$ +action.notable.param.nes_fields = ['user', 'src'] +action.notable.param.rule_description = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. action.notable.param.rule_title = New container uploaded to AWS ECR -action.notable.param.security_domain = threat +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.http_user_agent="AWS Internal" AND Compute.event_name="PutImage" by Compute.image_id Compute.src_user Compute.src Compute.region Compute.msg Compute.user_type | `drop_dm_object_name("Compute")` | `container_implant_aws_detection_filter` @@ -5998,59 +4151,44 @@ search = | tstats count min(_time) as firstTime max(_time) as lastTime FROM data action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. -action.escu.mappings = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} -action.escu.data_models = ["Updates"] -action.escu.eli5 = Keeping your systems up-to-date with the latest patches is an important step in keeping your systems secured. For Windows endpoints, Microsoft typically releases patches on the second Tuesday of every month. These patches contain fixes for vulnerabilities in the system that could potentially be exploited by malicious actors. This search checks for messages regarding Windows updates in the 'Update' data model. If a message indicating a successful update has not been observed in 60 days, a notable event will be generated. These systems should be checked to determine why it has not been updated in that time frame. +action.escu.mappings = {"analytics_story": ["Monitor for Updates"], "asset_type": "Endpoint", "cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"], "security_domain": "endpoint"} +action.escu.data_models = Updates +action.escu.eli5 = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-08-15 +action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - No Windows Updates in a time frame - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Monitor for Updates"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = No Windows Updates in a time frame +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, user -action.notable.param.rule_description = The system $src$ has not generated a successful Windows Update event in 60 days or more. -action.notable.param.rule_title = No Windows updates in last 60 days on $src$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. +action.notable.param.rule_title = No Windows Updates in a time frame +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` max(_time) as lastTime from datamodel=Updates where Updates.status=Installed Updates.vendor_product="Microsoft Windows" by Updates.dest Updates.status Updates.vendor_product | rename Updates.dest as Host | rename Updates.status as "Update Status" | rename Updates.vendor_product as Product | eval isOutlier=if(lastTime <= relative_time(now(), "-60d@d"), 1, 0) | `security_content_ctime(lastTime)` | search isOutlier=1 | rename lastTime as "Last Update Time", | table Host, "Update Status", Product, "Last Update Time" +search = | tstats `security_content_summariesonly` max(_time) as lastTime from datamodel=Updates where Updates.status=Installed Updates.vendor_product="Microsoft Windows" by Updates.dest Updates.status Updates.vendor_product | rename Updates.dest as Host | rename Updates.status as "Update Status" | rename Updates.vendor_product as Product | eval isOutlier=if(lastTime <= relative_time(now(), "-60d@d"), 1, 0) | `security_content_ctime(lastTime)` | search isOutlier=1 | rename lastTime as "Last Update Time", | table Host, "Update Status", Product, "Last Update Time" | `no_windows_updates_in_a_time_frame_filter` [ESCU - Okta Account Lockout Events - Rule] action.escu = 0 action.escu.enabled = 1 description = Detect Okta user lockout events -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} -action.escu.eli5 = This search detects when a user exceeds the maximum configured Okta login attempts and the account is subsequently locked out. This is often indicative of brtue force attempts against a user account. +action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.eli5 = Detect Okta user lockout events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. action.escu.creation_date = 2020-04-01 @@ -6058,49 +4196,33 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta Account Lockout Events - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Infrastructure -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Okta"] action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Okta Account Lockout Events +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = User $user$ locked out of Okta - too many attempts -action.notable.param.rule_title = Okta user lockout events -action.notable.param.security_domain = access -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = Detect Okta user lockout events +action.notable.param.rule_title = Okta Account Lockout Events +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = eventtype=okta_log displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip |`okta_user_lockouts_filter` +search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip |`okta_user_lockouts_filter` [ESCU - Okta Failed SSO Attempts - Rule] action.escu = 0 action.escu.enabled = 1 description = Detect failed Okta SSO events -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} -action.escu.eli5 = This search looks for events that indicate a user attempted to access an app they did not have permissions to access. This could indicate attempts to access prohibited applications. Please leverage the `okta_failed_sso_attempt_filter` macro to filter out false positives +action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.eli5 = Detect failed Okta SSO events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. action.escu.creation_date = 2020-04-01 @@ -6108,49 +4230,33 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta Failed SSO Attempts - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Infrastructure -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Okta"] action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Okta Failed SSO Attempts +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = Okta user $user$ attempted to access unauthorized app -action.notable.param.rule_title = Okta user SSO attempt to unauthorized app -action.notable.param.security_domain = access -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = Detect failed Okta SSO events +action.notable.param.rule_title = Okta Failed SSO Attempts +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = eventtype=okta_log displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter` +search = `okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter` [ESCU - Okta User Logins From Multiple Cities - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects logins from the same user from different states in a 24 hour period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} -action.escu.eli5 = This search detects users logging in from multiple states in the last 24 hours. This can be indicative of an attacker using compromised credentials to log in to Okta. The efficacy of this search is highly dependant on the mobility of the users using Okta. It is particularly useful in situations where users should explicitly *not* be travelling, such as during the COVID-19 pandemic. +action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.eli5 = This search detects logins from the same user from different states in a 24 hour period. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. action.escu.creation_date = 2020-04-01 @@ -6158,244 +4264,164 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta User Logins From Multiple Cities - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Infrastructure -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Okta"] action.escu.analytic_story = ["Suspicious Okta Activity"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -24h@h -dispatch.latest_time = -5m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Okta User Logins From Multiple Cities +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = User $user$ logged into Okta from different cities -action.notable.param.rule_title = Okta user login from different cities -action.notable.param.security_domain = access -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search detects logins from the same user from different states in a 24 hour period. +action.notable.param.rule_title = Okta User Logins From Multiple Cities +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = eventtype=okta_log displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`okta_user_logins_from_multiple_cities_filter`| search locations > 1 +search = `okta` displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`okta_user_logins_from_multiple_cities_filter`| search locations > 1 [ESCU - Open Redirect in Splunk Web - Rule] action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} -action.escu.data_models = [] -action.escu.eli5 = This search looks within Splunk's internal logs for evidence of CVE-2016-4859 open redirect exploitation attempts. +action.escu.mappings = {"analytics_story": ["Splunk Enterprise Vulnerability"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} +action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.escu.how_to_implement = No extra steps needed to implement this search. action.escu.known_false_positives = None identified -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2017-09-19 action.escu.modification_date = 2017-09-19 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Open Redirect in Splunk Web - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Splunk Server -action.escu.fields_required = ["host"] -action.escu.entities = ["host"] -action.escu.providing_technologies = ["Splunk Enterprise"] action.escu.analytic_story = ["Splunk Enterprise Vulnerability"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Open Redirect in Splunk Web +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = host -action.notable.param.rule_description = Search for exploitation of the Splunk Open Redirect Vulnerability +action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.notable.param.rule_title = Open Redirect in Splunk Web -action.notable.param.security_domain = network +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = host -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = host -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = index=_internal sourcetype=splunk_web_access return_to="/%09/*" +search = index=_internal sourcetype=splunk_web_access return_to="/%09/*" | `open_redirect_in_splunk_web_filter` [ESCU - Osquery pack - ColdRoot detection - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for ColdRoot events from the osx-attacks osquery pack. -action.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "mitre_attack": ["Execution", "Persistence", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} -action.escu.data_models = ["Alerts"] -action.escu.eli5 = The search looks at the Alerts data model to identify those generated from the osquery osx-attacks.conf pack, which search for the ColdRoot RAT. +action.escu.mappings = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"], "security_domain": "threat"} +action.escu.eli5 = This search looks for ColdRoot events from the osx-attacks osquery pack. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model action.escu.known_false_positives = There are no known false positives. action.escu.creation_date = 2019-01-29 action.escu.modification_date = 2019-01-29 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Osquery pack - ColdRoot detection - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["host"] -action.escu.entities = ["host"] -action.escu.providing_technologies = ["OSquery"] action.escu.analytic_story = ["ColdRoot MacOS RAT"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Osquery pack - ColdRoot detection +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = host, user -action.notable.param.rule_description = Host $host$ generated an alert for the macOS RAT ColdRoot -action.notable.param.rule_title = Osquery ColdRoot alert for $host$ -action.notable.param.security_domain = threat +action.notable.param.rule_description = This search looks for ColdRoot events from the osx-attacks osquery pack. +action.notable.param.rule_title = Osquery pack - ColdRoot detection +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = host -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = host -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | from datamodel Alerts.Alerts | search app=osquery:results (name=pack_osx-attacks_OSX_ColdRoot_RAT_Launchd OR name=pack_osx-attacks_OSX_ColdRoot_RAT_Files) | rename columns.path as path | bucket _time span=30s | stats count(path) by _time, host, user, path +search = | from datamodel Alerts.Alerts | search app=osquery:results (name=pack_osx-attacks_OSX_ColdRoot_RAT_Launchd OR name=pack_osx-attacks_OSX_ColdRoot_RAT_Files) | rename columns.path as path | bucket _time span=30s | stats count(path) by _time, host, user, path | `osquery_pack___coldroot_detection_filter` [ESCU - Overwriting Accessibility Binaries - Rule] action.escu = 0 action.escu.enabled = 1 description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Accessibility Features"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search returns all the different accessibility binaries that have been modified for each Windows host. +action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. -action.escu.creation_date = 2017-12-07 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Overwriting Accessibility Binaries - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Windows Privilege Escalation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Overwriting Accessibility Binaries +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A file, $file_name$, was created in the default shim database directory on $dest. -action.notable.param.rule_title = Modification to accessibility binary, $file_path$, was detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. +action.notable.param.rule_title = Overwriting Accessibility Binaries +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where (Filesystem.file_path=*\\Windows\\System32\\sethc.exe* OR Filesystem.file_path=*\\Windows\\System32\\utilman.exe* OR Filesystem.file_path=*\\Windows\\System32\\osk.exe* OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) by Filesystem.file_name Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem where (Filesystem.file_path=*\\Windows\\System32\\sethc.exe* OR Filesystem.file_path=*\\Windows\\System32\\utilman.exe* OR Filesystem.file_path=*\\Windows\\System32\\osk.exe* OR Filesystem.file_path=*\\Windows\\System32\\Magnify.exe* OR Filesystem.file_path=*\\Windows\\System32\\Narrator.exe* OR Filesystem.file_path=*\\Windows\\System32\\DisplaySwitch.exe* OR Filesystem.file_path=*\\Windows\\System32\\AtBroker.exe*) by Filesystem.file_name Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `overwriting_accessibility_binaries_filter` [ESCU - Process Execution via WMI - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched via WMI. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for processes launched via WMI, either remotely or locally, by looking for processes launched by WmiPrvSE.exe, which is the process WMI uses to execute new processes and commands. +action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for processes launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. -action.escu.creation_date = 2018-10-23 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Process Execution via WMI - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Process Execution via WMI +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = This search looks for child processes of WmiPrvSE.exe, which indicates that a process was launched via WMI. -action.notable.param.rule_title = Process launched via WMI on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launched via WMI. +action.notable.param.rule_title = Process Execution via WMI +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name = *WmiPrvSE.exe by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `wmi_process_launch_filter` @@ -6403,713 +4429,494 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input -action.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Collection"], "nist": ["DE.DP"]} -action.escu.data_models = ["Alerts"] -action.escu.eli5 = The search leverages Alerts generated from the osquery osx-attacks.conf pack search `Keyboard_Event_Taps` to detect when a process is monitoring the keystrokes of a machine, This is a common technique used by macOS remote access trojans to log keystrokes from a machine +action.escu.mappings = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"], "security_domain": "threat"} +action.escu.eli5 = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. action.escu.known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. action.escu.creation_date = 2019-01-25 action.escu.modification_date = 2019-01-25 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Processes Tapping Keyboard Events - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["host"] -action.escu.entities = ["host"] -action.escu.providing_technologies = ["OSquery"] action.escu.analytic_story = ["ColdRoot MacOS RAT"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Processes Tapping Keyboard Events +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = host, cmd, process_id -action.notable.param.rule_description = Host $host$ has process $process_id$ tapping keyboard events with command $cmd$ -action.notable.param.rule_title = Host $host has process $process_id$ monitoring its keystrokes -action.notable.param.security_domain = threat +action.notable.param.rule_description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input +action.notable.param.rule_title = Processes Tapping Keyboard Events +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = host -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = host -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | from datamodel Alerts.Alerts | search app=osquery:results name=pack_osx-attacks_Keyboard_Event_Taps | rename columns.cmdline as cmd, columns.name as process_name, columns.pid as process_id| dedup host,process_name | table host,process_name, cmd, process_id +search = | from datamodel Alerts.Alerts | search app=osquery:results name=pack_osx-attacks_Keyboard_Event_Taps | rename columns.cmdline as cmd, columns.name as process_name, columns.pid as process_id| dedup host,process_name | table host,process_name, cmd, process_id | `processes_tapping_keyboard_events_filter` [ESCU - Processes created by netsh - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for all processes with the parent process "c:\Windows\System32\netsh.exe" and returns the process, the command line used to execute it, the host name, and the user context under which it ran. +action.escu.mappings = {"analytics_story": ["Netsh Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. -action.escu.creation_date = 2018-01-04 +action.escu.creation_date = 2020-03-02 action.escu.modification_date = 2020-03-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Processes created by netsh - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Netsh Abuse"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Processes created by netsh +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, parent_process -action.notable.param.rule_description = A process, $process$, is spawned by netsh.exe. It is highly unlikely for netsh to have any child processes. -action.notable.param.rule_title = Process spawned by netsh.exe detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. +action.notable.param.rule_title = Processes created by netsh +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process="*C:\\Windows\\System32\\netsh.exe*" by Processes.user Processes.dest Processes.parent_process Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process="*C:\\Windows\\System32\\netsh.exe*" by Processes.user Processes.dest Processes.parent_process Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `processes_created_by_netsh_filter` [ESCU - Processes launching netsh - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence", "Defense Evasion", "Disabling Security Tools"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for all the parent processes of netsh.exe and returns that process, the command-line used to execute it, the host name, and the user context under which it ran. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model action.escu.known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. -action.escu.creation_date = 2017-01-08 +action.escu.creation_date = 2018-11-02 action.escu.modification_date = 2018-11-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Processes launching netsh - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Netsh Abuse"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Processes launching netsh +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, parent_process, cmdline -action.notable.param.rule_description = A process detected on $dest$ is launching netsh.exe. -action.notable.param.rule_title = Process launching netsh.exe detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. +action.notable.param.rule_title = Processes launching netsh +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, parent_process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=netsh.exe by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count values(Processes.process) min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=netsh.exe by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `processes_launching_netsh_filter` [ESCU - Prohibited Network Traffic Allowed - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. -action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Exfiltration", "Exfiltration Over Alternative Protocol"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = The search looks for traffic marked 'is_prohibited' in the Enterprise Security lookup table 'interesting_ports_lookup', and then determines if any network devices have an associated 'allow' action on that traffic by checking the Network_Traffic data model. +action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-04-18 +action.escu.creation_date = 2017-09-11 action.escu.modification_date = 2017-09-11 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Network Traffic Allowed - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["Palo Alto Firewall", "Bro", "Splunk Stream"] -action.escu.analytic_story = ["Command and Control", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Prohibited Network Traffic Allowed +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, dest_ip -action.notable.param.rule_description = This search looks for network traffic defined by port and transport in the ES lookup table "lookup_interesting_ports", that is marked as prohibited, and yet has an 'allow' action in the Network_Traffic data model. This should help to identify areas where a network device is not properly configured. -action.notable.param.rule_title = Prohibited Network Traffic Allowed from $src_ip$ -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. +action.notable.param.rule_title = Prohibited Network Traffic Allowed +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest_ip,src_ip -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.action = allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action | lookup update=true interesting_ports_lookup dest_port as All_Traffic.dest_port OUTPUT app is_prohibited note transport | search is_prohibited=true | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.action = allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action | lookup update=true interesting_ports_lookup dest_port as All_Traffic.dest_port OUTPUT app is_prohibited note transport | search is_prohibited=true | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `prohibited_network_traffic_allowed_filter` [ESCU - Prohibited Software On Endpoint - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as prohibited. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search returns the number of times, as well as the first and last time, every process has run for each endpoint and user. It then displays only those processes that you have marked as "prohibited" in the Enterprise Security "Interesting Processes" table. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-06-26 +action.escu.creation_date = 2019-10-11 action.escu.modification_date = 2019-10-11 action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Software On Endpoint - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Monitor for Unauthorized Software", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Prohibited Software On Endpoint +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process_name, user -action.notable.param.rule_description = Prohibited software $process_name$ has been detected on $dest$. -action.notable.param.rule_title = Prohibited Software Detected On $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as prohibited. +action.notable.param.rule_title = Prohibited Software On Endpoint +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `prohibited_softwares` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `prohibited_softwares` | `prohibited_software_on_endpoint_filter` [ESCU - Protocol or Port Mismatch - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. -action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Commonly Used Port"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search looks for instances in which the protocol observed is not consistent with the port and transport protocol typically used for that protocol. For example, looking for network traffic other than HTTP running over TCP port 80. Such behavior could indicate a misconfiguration or a custom command and control protocol that has been designed to look like ordinary web traffic. The search will also identify if HTTP traffic is observed running on unexpected ports. This can be common in many environments. +action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-04-18 +action.escu.creation_date = 2017-09-11 action.escu.modification_date = 2017-09-11 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Protocol or Port Mismatch - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["Palo Alto Firewall", "Bro", "Splunk Stream"] -action.escu.analytic_story = ["Command and Control", "Prohibited Traffic Allowed or Protocol Mismatch"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Protocol or Port Mismatch +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest_ip, src_ip -action.notable.param.rule_description = This search looks for network traffic on common ports where the underlying protocol does not match the port being used. For example, this search should identify cases where protocols other than HTTP are running on port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications in traffic that is typically allowed and not well inspected. -action.notable.param.rule_title = Protocol / Port Mismatch from $src_ip$ -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. +action.notable.param.rule_title = Protocol or Port Mismatch +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest_ip, dest_port -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where (All_Traffic.app=dns NOT All_Traffic.dest_port=53) OR ((All_Traffic.app=web-browsing OR All_Traffic.app=http) NOT (All_Traffic.dest_port=80 OR All_Traffic.dest_port=8080 OR All_Traffic.dest_port=8000)) OR (All_Traffic.app=ssl NOT (All_Traffic.dest_port=443 OR All_Traffic.dest_port=8443)) OR (All_Traffic.app=smtp NOT All_Traffic.dest_port=25) by All_Traffic.src_ip, All_Traffic.dest_ip, All_Traffic.app, All_Traffic.dest_port |`security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where (All_Traffic.app=dns NOT All_Traffic.dest_port=53) OR ((All_Traffic.app=web-browsing OR All_Traffic.app=http) NOT (All_Traffic.dest_port=80 OR All_Traffic.dest_port=8080 OR All_Traffic.dest_port=8000)) OR (All_Traffic.app=ssl NOT (All_Traffic.dest_port=443 OR All_Traffic.dest_port=8443)) OR (All_Traffic.app=smtp NOT All_Traffic.dest_port=25) by All_Traffic.src_ip, All_Traffic.dest_ip, All_Traffic.app, All_Traffic.dest_port |`security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `protocol_or_port_mismatch_filter` [ESCU - Protocols passing authentication in cleartext - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. -action.escu.mappings = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "mitre_attack": ["Credential Access", "Lateral Movement", "Collection"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search is checking for traffic on well-known ports that are associated with protocols that pass authentication in cleartext. +action.escu.mappings = {"analytics_story": ["Use of Cleartext Protocols"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. action.escu.known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. -action.escu.creation_date = 2017-08-03 +action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Protocols passing authentication in cleartext - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] action.escu.analytic_story = ["Use of Cleartext Protocols"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Protocols passing authentication in cleartext +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, dest, user -action.notable.param.rule_description = This search looks for the use of cleartext protocols that are known to pass authentication information in the clear. The cleartext credentials are typically passed at the beginning of the session. -action.notable.param.rule_title = Possible credential leak over cleartext protocol -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user', 'dest', 'src'] +action.notable.param.rule_description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. +action.notable.param.rule_title = Protocols passing authentication in cleartext +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.protocol="tcp" AND (All_Traffic.dest_port="23" OR All_Traffic.dest_port="143" OR All_Traffic.dest_port="110" OR (All_Traffic.dest_port="21" AND All_Traffic.user != "anonymous")) groupby All_Traffic.user All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.protocol="tcp" AND (All_Traffic.dest_port="23" OR All_Traffic.dest_port="143" OR All_Traffic.dest_port="110" OR (All_Traffic.dest_port="21" AND All_Traffic.user != "anonymous")) groupby All_Traffic.user All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `protocols_passing_authentication_in_cleartext_filter` -[ESCU - Reg.exe Manipulating Windows Services Registry Keys - Rule] +[ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["Persistence", "Privilege Escalation", "New Service", "Modify Existing Service", "Defense Evasion", "Disabling Security Tools"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for modifications to registry paths that specify the definition and configuration of Windows services by reg.exe. Reg.exe is a Windows utility that allows for manipulation of the registry via the command line. Malware often uses the Windows services architecture to persist, hide in plain sight, and gain the ability to interact with the Windows kernel. While it is common to modify the configuration of Windows services (and new services may be created with software installs), the use of reg.exe to create or modify a service configuration is unusual and a technique commonly used by attackers. The search returns the count, the first time the activity was seen, the last time activity was seen, the registry path that was modified, the host where the modification took place, and the user that performed the modification. +action.escu.mappings = {"analytics_story": ["Windows Service Abuse", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. -action.escu.creation_date = 2018-6-29 +action.escu.creation_date = 2019-03-01 action.escu.modification_date = 2019-03-01 action.escu.confidence = high -action.escu.full_search_name = ESCU - Reg.exe Manipulating Windows Services Registry Keys - Rule +action.escu.full_search_name = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Service Abuse"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows Service Abuse", "Windows Persistence Techniques"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Reg.exe Manipulating Windows Services Registry Keys +action.correlationsearch.label = Reg exe Manipulating Windows Services Registry Keys +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process -action.notable.param.rule_description = A registry key associated with Windows services was modified via reg.exe on $dest$ by $src_user$. -action.notable.param.rule_title = Modification of Windows Services Via Reg.exe on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. +action.notable.param.rule_title = Reg exe Manipulating Windows Services Registry Keys +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path] +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path] | `reg_exe_manipulating_windows_services_registry_keys_filter` -[ESCU - Reg.exe used to hide files/directories via registry keys - Rule] +[ESCU - Reg exe used to hide files directories via registry keys - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for command-line arguments used to hide a file or directory using the reg add command. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Persistence"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Reg.exe is a binary native to Windows platform used to edit the registry hives of the system. Attackers can leverage this binary to hide files by passing in arguments that are used to hide the files. In the search, we first gather results with keywords, add, Hidden, and REG_DWORD, that will be in the raw event and filter by process and the command-line. We then leverage regular expressions on the command-line field to look for /d value as 2 which is responsible for hiding a file or directory. +action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None at the moment -action.escu.creation_date = 2017-10-27 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Reg.exe used to hide files/directories via registry keys - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Reg exe used to hide files directories via registry keys - Rule action.escu.search_type = detection -action.escu.asset_at_risk = -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Reg.exe used to hide files/directories via registry keys +action.correlationsearch.label = Reg exe used to hide files directories via registry keys +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process -action.notable.param.rule_description = Regedit.exe is used by attackers to hide malware files/directories in windows environments via registry key settings. This rule detects command-line arguments used to hide a file/directory -action.notable.param.rule_title = Regedit.exe used to hide a file/directory on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for command-line arguments used to hide a file or directory using the reg add command. +action.notable.param.rule_title = Reg exe used to hide files directories via registry keys +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)" +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = reg.exe Processes.process="*add*" Processes.process="*Hidden*" Processes.process="*REG_DWORD*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)`| regex process = "(/d\s+2)" | `reg_exe_used_to_hide_files_directories_via_registry_keys_filter` [ESCU - Registry Keys Used For Persistence - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Registry Run Keys / Start Folder", "AppInit DLLs", "Authentication Package"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for specific registry paths that malware often uses to ensure survivability and persistence on system startup. The search returns the count, the first time the activity was seen, the last time the activity was seen, the registry path that was modified, the host where the modification took place and the user that performed the modification. +action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "endpoint"} +action.escu.eli5 = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. -action.escu.creation_date = 2017-08-23 +action.escu.creation_date = 2017-10-10 action.escu.modification_date = 2017-10-10 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Persistence - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] -action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware (DHS Report TA18-201A)", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Registry Keys Used For Persistence +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, registry_path -action.notable.param.rule_description = A registry key that is used for persistence on Windows was modified on $dest$ by $src_user$. -action.notable.param.rule_title = Registry Key Associated With Persistence Modified on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. +action.notable.param.rule_title = Registry Keys Used For Persistence +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user,registry_path -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path=*currentversion\\run* OR Registry.registry_path=*currentVersion\\Windows\\Appinit_Dlls* OR Registry.registry_path=CurrentVersion\\Winlogon\\Shell* OR Registry.registry_path=*CurrentVersion\\Winlogon\\Userinit* OR Registry.registry_path=*CurrentVersion\\Winlogon\\VmApplet* OR Registry.registry_path=*currentversion\\policies\\explorer\\run* OR Registry.registry_path=*currentversion\\runservices* OR Registry.registry_path=*\\CurrentControlSet\\Control\\Lsa\\* OR Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*" OR Registry.registry_path=HKLM\\SOFTWARE\\Microsoft\\Netsh\\*) by Registry.dest , Registry.status, Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` +search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path=*currentversion\\run* OR Registry.registry_path=*currentVersion\\Windows\\Appinit_Dlls* OR Registry.registry_path=CurrentVersion\\Winlogon\\Shell* OR Registry.registry_path=*CurrentVersion\\Winlogon\\Userinit* OR Registry.registry_path=*CurrentVersion\\Winlogon\\VmApplet* OR Registry.registry_path=*currentversion\\policies\\explorer\\run* OR Registry.registry_path=*currentversion\\runservices* OR Registry.registry_path=*\\CurrentControlSet\\Control\\Lsa\\* OR Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*" OR Registry.registry_path=HKLM\\SOFTWARE\\Microsoft\\Netsh\\*) by Registry.dest , Registry.status, Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `registry_keys_used_for_persistence_filter` [ESCU - Registry Keys Used For Privilege Escalation - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Privilege Escalation", "Persistence", "Accessibility Features"], "mitre_technique_id": ["T1183"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for specific registry paths that malware often uses to elevate privileges. The search returns the count, the first time the activity was seen, the last time the activity was seen, the registry path that was modified, the host where the modification took place, and the user who performed the modification. +action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. -action.escu.creation_date = 2017-12-07 +action.escu.creation_date = 2020-03-02 action.escu.modification_date = 2020-03-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Privilege Escalation - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Registry Keys Used For Privilege Escalation +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, registry_path -action.notable.param.rule_description = A registry key used for privilege escalation was modified on $dest$ by $user$. -action.notable.param.rule_title = Registry Key Associated With Privilege Escalation Modified on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. +action.notable.param.rule_title = Registry Keys Used For Privilege Escalation +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user, registry_path -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*") AND (Registry.registry_key_name=GlobalFlag OR Registry.registry_key_name=Debugger) by Registry.dest Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` +search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where (Registry.registry_path="*Microsoft\\Windows NT\\CurrentVersion\\Image File Execution Options*") AND (Registry.registry_key_name=GlobalFlag OR Registry.registry_key_name=Debugger) by Registry.dest Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `registry_keys_used_for_privilege_escalation_filter` [ESCU - Registry Keys for Creating SHIM Databases - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Application Shimming"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Change_Analysis"] -action.escu.eli5 = In this search, we look for modifications to registry keys used for shim databases on Microsoft platforms via the object_category and object_path field in the Change_Analysis data model and give you the destination, command used to initiate the change, the user who conducted this activity, the resource affected(object), and the whole path of the object. An application compatibility shim is a small library that transparently intercepts an API (via hooking), changes the parameters passed, handles the operation itself, or redirects the operation elsewhere, such as additional code stored on a system. This capability can be also leveraged by attackers to create and store malicious files in a shim database as observed in CARBANAK backdoor. +action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. action.escu.how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications -action.escu.creation_date = 2017-08-27 +action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys for Creating SHIM Databases - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Registry Keys for Creating SHIM Databases +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user -action.notable.param.rule_description = A registry key that is used for persistence on Windows was modified on $dest$ by $user$ -action.notable.param.rule_title = Registry Key Associated With SHIM databases on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.rule_description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. +action.notable.param.rule_title = Registry Keys for Creating SHIM Databases +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,object_path -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\Custom*" OR All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\InstalledSDB*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `drop_dm_object_name("All_Changes")` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\Custom*" OR All_Changes.object_path="*CurrentVersion\\AppCompatFlags\\InstalledSDB*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `drop_dm_object_name("All_Changes")` | `registry_keys_for_creating_shim_databases_filter` [ESCU - Remote Desktop Network Bruteforce - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. -action.escu.mappings = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["Credential Access", "Remote Desktop Protocol", "Lateral Movement"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search monitors for abnormal amounts of remote-desktop (RDP) traffic from a source to a destination that may be indicative of a brute-force attack. It does this by filtering out RDP traffic from the Network_Traffic.All_Traffic data model, using twice the standard deviation of all source-to-destination connections. If any tuple is within more than two standard deviations of all other usual RDP traffic flows, it is indicative of a brute-force attack. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. action.escu.known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. action.escu.creation_date = 2018-12-14 action.escu.modification_date = 2018-12-14 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Bruteforce - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Bro", "Splunk Stream"] action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Remote Desktop Network Bruteforce +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, src -action.notable.param.rule_description = Remote-desktop traffic detected from $src$ to $dest$. This activity is consistent with a brute-force attack. -action.notable.param.rule_title = Bruteforce Remote Desktop Network Traffic detected from $src$ to $dest$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. +action.notable.param.rule_title = Remote Desktop Network Bruteforce +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 75 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,src -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.app=rdp by All_Traffic.src All_Traffic.dest All_Traffic.dest_port | eventstats stdev(count) AS stdev avg(count) AS avg p50(count) AS p50 | where count>(avg + stdev*2) | rename All_Traffic.src AS src All_Traffic.dest AS dest | table firstTime lastTime src dest count avg p50 stdev +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.app=rdp by All_Traffic.src All_Traffic.dest All_Traffic.dest_port | eventstats stdev(count) AS stdev avg(count) AS avg p50(count) AS p50 | where count>(avg + stdev*2) | rename All_Traffic.src AS src All_Traffic.dest AS dest | table firstTime lastTime src dest count avg p50 stdev | `remote_desktop_network_bruteforce_filter` [ESCU - Remote Desktop Network Traffic - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Remote Desktop Protocol"], "mitre_technique_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = This search finds systems that do not commonly communicate use remote desktop. It does this by filtering out all systems that have the "common_rdp_source" or "common_rdp_destination" category applied to that system. Categories are applied to systems using the Assets and Identity framework. +action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2020-01-10 action.escu.modification_date = 2020-01-10 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Traffic - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Bro", "Splunk Stream"] -action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Remote Desktop Network Traffic +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, src -action.notable.param.rule_description = Remote Desktop Traffic detected between $src$ and $dest$. These two systems typically do not communicate with RDP -action.notable.param.rule_title = Uncommon Remote Desktop Network Traffic between $src$ and $dest$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. +action.notable.param.rule_title = Remote Desktop Network Traffic +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,src -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.dest_port=3389 AND All_Traffic.dest_category!=common_rdp_destination AND All_Traffic.src_category!=common_rdp_source by All_Traffic.src All_Traffic.dest All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `remote_desktop_network_traffic_filter` @@ -7117,50 +4924,35 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Remote Desktop Protocol"], "mitre_technique_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search finds systems that do not commonly use remote desktop, but which begin using it. It filters out all systems that have the "common_rdp_source" category applied. Categories are applied to systems using the Assets and Identity framework. +action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2020-01-13 action.escu.modification_date = 2020-01-13 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Process Running On System - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Remote Desktop Process Running On System +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = The system $dest$ is running the remote desktop process, mstsc.exe. This system does not commonly run this application. -action.notable.param.rule_title = Remote Desktop Process Running On $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. +action.notable.param.rule_title = Remote Desktop Process Running On System +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process=*mstsc.exe AND Processes.dest_category!=common_rdp_source by Processes.dest Processes.user Processes.process | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `remote_desktop_process_running_on_system_filter` @@ -7168,254 +4960,178 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Attackers are increasingly abusing native Windows utilities such as wmic.exe as a means to "live off the land", and avoid introducing new executables to the target system. In this search, we are looking for instances of wmic.exe being run with various parameters that are not typically used by administrators. +action.escu.mappings = {"analytics_story": ["Suspicious WMI Use", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. -action.escu.creation_date = 2017-01-13 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Process Instantiation via WMI - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious WMI Use", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Remote Process Instantiation via WMI +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process +action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. -action.notable.param.rule_title = Remote process instantiation via WMI on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.rule_title = Remote Process Instantiation via WMI +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user,process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = wmic.exe Processes.process="*/node*" Processes.process="*process*" Processes.process="*call*" Processes.process="*create*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = wmic.exe Processes.process="*/node*" Processes.process="*process*" Processes.process="*call*" Processes.process="*create*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `remote_process_instantiation_via_wmi_filter` [ESCU - Remote Registry Key modifications - Rule] action.escu = 0 action.escu.enabled = 1 description = This search monitors for remote modifications to registry keys. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Persistence", "Lateral Movement"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for modifications made to the Windows registry from remote locations using reg.exe—a tool used to create/update/delete/modify Windows registry keys. It is accomplished through specifying the machine names in the registry path, by entering double backslashes, followed by a computer name. In this search, we look for registry changes where the registry path contains the name of a remote computer. The search returns the number of times the remote server has been accessed, the first and last times the activity occurred, the name of the modified registry path, the host on which the modification took place, and the name of the user that performed the modification. +action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search monitors for remote modifications to registry keys. action.escu.how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. -action.escu.creation_date = 2018-05-31 +action.escu.creation_date = 2020-03-02 action.escu.modification_date = 2020-03-02 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Registry Key modifications - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Remote Registry Key modifications +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user -action.notable.param.rule_description = A registry key was modified remotely using the machine $dest$ by $user$. -action.notable.param.rule_title = Remote Registry Key Modification detection on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search monitors for remote modifications to registry keys. +action.notable.param.rule_title = Remote Registry Key modifications +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user,registry_path -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="\\\\*" by Registry.dest , Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` +search = | tstats `security_content_summariesonly` count values(Registry.registry_key_name) as registry_key_name values(Registry.registry_path) as registry_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path="\\\\*" by Registry.dest , Registry.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Registry)` | `remote_registry_key_modifications_filter` [ESCU - Remote WMI Command Attempt - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to operate on remote systems. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Many a times, attackers leverage native Windows utilities that are designed to help administrators better manage their systems, infrastructure, and auditing, but are instead leveraged for malicious purposes. In this case, we are looking for instances of wmic.exe being run with various parameters that are not typically used by administrators. +action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may use this legitimately to gather info from remote systems. -action.escu.creation_date = 2017-01-13 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Remote WMI Command Attempt - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = 50 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Remote WMI Command Attempt +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest,user,process_name +action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to operate on remote systems. -action.notable.param.rule_title = Endpoint - Remote WMI command attempt -action.notable.param.security_domain = endpoint +action.notable.param.rule_title = Remote WMI Command Attempt +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user,process_name -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=wmic.exe AND Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=wmic.exe AND Processes.process= */node* by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `remote_wmi_command_attempt_filter` [ESCU - RunDLL Loading DLL By Ordinal - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["Execution", "Rundll32"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for rundll32.exe being run, loading a DLL out of a directory or subdirectory of AppData, and specifying the function at ordinal 2 be run. +action.escu.mappings = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1085"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process -action.escu.creation_date = 2016-08-09 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - RunDLL Loading DLL By Ordinal - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Unusual Processes"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = RunDLL Loading DLL By Ordinal +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions with no names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -action.notable.param.rule_title = Endpoint - Suspicious RunDLL usage -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. +action.notable.param.rule_title = RunDLL Loading DLL By Ordinal +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = rundll32.exe Processes.process="*AppData*" Processes.process="*,#2" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = rundll32.exe Processes.process="*AppData*" Processes.process="*,#2" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `rundll_loading_dll_by_ordinal_filter` [ESCU - SMB Traffic Spike - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Execution", "Command and Control", "Commonly Used Port"], "mitre_technique_id": ["T1110", "T1135", "T1210"], "nist": ["DE.CM"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = Server Message Block (SMB) traffic, a protocol used for Windows file sharing-activity, is often leveraged by attackers. One example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search looks for a traffic spike in SMB traffic from a particular system. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. action.escu.known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. -action.escu.creation_date = 2017-08-20 +action.escu.creation_date = 2020-01-22 action.escu.modification_date = 2020-01-22 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Bro", "Splunk Stream"] -action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -7d@d -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = SMB Traffic Spike +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src -action.notable.param.rule_description = There was a spike in SMB traffic from $src$. -action.notable.param.rule_title = SMB Traffic Spike from $src$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['src'] +action.notable.param.rule_description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. +action.notable.param.rule_title = SMB Traffic Spike +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | `drop_dm_object_name("All_Traffic")` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, "-70m@m"), count, null))) as count avg(eval(if(_time upperBound AND num_data_samples >=50, 1, 0) | where isOutlier=1 | table src count | `smb_traffic_spike_filter` @@ -7423,53 +5139,38 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Execution", "Command and Control", "Commonly Used Port"], "mitre_technique_id": ["T1110", "T1135", "T1210"], "nist": ["DE.CM"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = Attackers often leverage Server Message Block (SMB) traffic, a protocol used for Windows file-sharing activity. A high-profile example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search leverages Splunk's Machine Learning Toolkit (MLTK) to identify spikes in SMB traffic that are unusual for a given hour of day/day of week combination. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ 1. **Label:** Number of events, **Field:** count\ Detailed documentation on how to create a new field within Incident Review is found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` action.escu.known_false_positives = If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. Please update the `smb_traffic_spike_mltk_filter` macro to filter out false positive results -action.escu.creation_date = 2019-05-08 +action.escu.creation_date = 2020-01-22 action.escu.modification_date = 2020-01-22 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - MLTK - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Bro", "Splunk Stream"] -action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = SMB Traffic Spike - MLTK +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src -action.notable.param.rule_description = There was a spike in SMB traffic from $src$ -action.notable.param.rule_title = SMB Traffic Spike from $src$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. +action.notable.param.rule_title = SMB Traffic Spike - MLTK +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(All_Traffic.dest_ip) as dest values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 | rename "IsOutlier(count)" as isOutlier | search isOutlier > 0 | sort -count | table _time src dest port count | `smb_traffic_spike_mltk_filter` @@ -7477,60 +5178,45 @@ search = | tstats `security_content_summariesonly` count values(All_Traffic.dest action.escu = 0 action.escu.enabled = 1 description = This search looks for long URLs that have several SQL commands visible within them. -action.escu.mappings = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability", "Execution", "Commonly Used Port"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} -action.escu.data_models = ["Web"] -action.escu.eli5 = This search looks only at your web servers and returns the source, the web server, the URL and its length, and the user agent associated with HTTP GET requests for extremely long URLs or user agent lengths with more than three common SQL commands found within the URL. +action.escu.mappings = {"analytics_story": ["SQL Injection"], "asset_type": "Database Server", "cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"], "security_domain": "network"} +action.escu.data_models = Web +action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. action.escu.known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2017-09-19 action.escu.modification_date = 2017-09-19 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - SQL Injection with Long URLs - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Database Server -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] action.escu.analytic_story = ["SQL Injection"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = SQL Injection with Long URLs +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, src, url -action.notable.param.rule_description = Using the length of url or user agent to identify SQL injection +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for long URLs that have several SQL commands visible within them. action.notable.param.rule_title = SQL Injection with Long URLs -action.notable.param.security_domain = network +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,src,url -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Web where Web.dest_category=web_server AND (Web.url_length > 1024 OR Web.http_user_agent_length > 200) by Web.src Web.dest Web.url Web.url_length Web.http_user_agent | `drop_dm_object_name("Web")` | eval num_sql_cmds=mvcount(split(url, "alter%20table")) + mvcount(split(url, "between")) + mvcount(split(url, "create%20table")) + mvcount(split(url, "create%20database")) + mvcount(split(url, "create%20index")) + mvcount(split(url, "create%20view")) + mvcount(split(url, "delete")) + mvcount(split(url, "drop%20database")) + mvcount(split(url, "drop%20index")) + mvcount(split(url, "drop%20table")) + mvcount(split(url, "exists")) + mvcount(split(url, "exec")) + mvcount(split(url, "group%20by")) + mvcount(split(url, "having")) + mvcount(split(url, "insert%20into")) + mvcount(split(url, "inner%20join")) + mvcount(split(url, "left%20join")) + mvcount(split(url, "right%20join")) + mvcount(split(url, "full%20join")) + mvcount(split(url, "select")) + mvcount(split(url, "distinct")) + mvcount(split(url, "select%20top")) + mvcount(split(url, "union")) + mvcount(split(url, "xp_cmdshell")) - 24 | where num_sql_cmds > 3 +search = | tstats `security_content_summariesonly` count from datamodel=Web where Web.dest_category=web_server AND (Web.url_length > 1024 OR Web.http_user_agent_length > 200) by Web.src Web.dest Web.url Web.url_length Web.http_user_agent | `drop_dm_object_name("Web")` | eval num_sql_cmds=mvcount(split(url, "alter%20table")) + mvcount(split(url, "between")) + mvcount(split(url, "create%20table")) + mvcount(split(url, "create%20database")) + mvcount(split(url, "create%20index")) + mvcount(split(url, "create%20view")) + mvcount(split(url, "delete")) + mvcount(split(url, "drop%20database")) + mvcount(split(url, "drop%20index")) + mvcount(split(url, "drop%20table")) + mvcount(split(url, "exists")) + mvcount(split(url, "exec")) + mvcount(split(url, "group%20by")) + mvcount(split(url, "having")) + mvcount(split(url, "insert%20into")) + mvcount(split(url, "inner%20join")) + mvcount(split(url, "left%20join")) + mvcount(split(url, "right%20join")) + mvcount(split(url, "full%20join")) + mvcount(split(url, "select")) + mvcount(split(url, "distinct")) + mvcount(split(url, "select%20top")) + mvcount(split(url, "union")) + mvcount(split(url, "xp_cmdshell")) - 24 | where num_sql_cmds > 3 | `sql_injection_with_long_urls_filter` [ESCU - Samsam Test File Write - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks at file modifications across your hosts and monitors for a file named "test.txt" written to "windows\system32". This file is copied to potential targets during SamSam ransomware attacks to test the attacker's ability to access remote systems. If the file is successfully copied to the system, the system is added to a list of targets on which to deploy ransomware. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = No false positives have been identified. action.escu.creation_date = 2018-12-14 @@ -7538,142 +5224,97 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Samsam Test File Write - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Samsam Test File Write +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A file named "test.txt," which is indicative of a SamSam ransomware attack, was written to system32 on $dest$. -action.notable.param.rule_title = File consistent with SamSam probes detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. +action.notable.param.rule_title = Samsam Test File Write +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name from datamodel=Endpoint.Filesystem where Filesystem.file_path=*\\windows\\system32\\test.txt by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_name) as file_name from datamodel=Endpoint.Filesystem where Filesystem.file_path=*\\windows\\system32\\test.txt by Filesystem.file_path | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `samsam_test_file_write_filter` -[ESCU - Sc.exe Manipulating Windows Services - Rule] +[ESCU - Sc exe Manipulating Windows Services - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["Persistence", "Privilege Escalation", "New Service", "Modify Existing Service", "Defense Evasion", "Disabling Security Tools"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the execution of sc.exe with parameters that indicate the utility is being used to create a new Windows service, or modify an existing one. Attackers often create a new service to host their malicious code, or they may take a non-critical service or one that is disabled, and modify it to point to their malware and enable the service if necessary. It is unusual for a service to be created or modified using the sc.exe utility. +action.escu.mappings = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. -action.escu.creation_date = 2017-11-03 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Sc.exe Manipulating Windows Services - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Sc exe Manipulating Windows Services - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Orangeworm Attack Group", "Windows Persistence Techniques", "Windows Service Abuse"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Sc.exe Manipulating Windows Services +action.correlationsearch.label = Sc exe Manipulating Windows Services +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process +action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. -action.notable.param.rule_title = Sc.exe Manipulating Windows Services on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.rule_title = Sc exe Manipulating Windows Services +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sc.exe (Processes.process="* create *" OR Processes.process="* config *") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sc.exe (Processes.process="* create *" OR Processes.process="* config *") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `sc_exe_manipulating_windows_services_filter` [ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Scheduled Task"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for execution of schtasks.exe with parameters that indicate that a specific task "reset," whose name is associated with the Dragonfly threat actor--has been created or deleted. Schtasks.exe is a native Windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or establish persistence. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives -action.escu.creation_date = 2018-03-19 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Scheduled Task Name Used by Dragonfly Threat Actors +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command line that indicate that a task--whose name is associated with the Dragonfly threat actor--has been created or deleted -action.notable.param.rule_title = Scheduled task used by Dragonfly threat actor detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. +action.notable.param.rule_title = Scheduled Task Name Used by Dragonfly Threat Actors +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process_name, process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*delete* OR process=*create*) process=*reset* | `dragonfly_schtasks_filter` @@ -7681,101 +5322,71 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Lateral Movement", "Execution", "Scheduled Task"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for execution of schtasks.exe with parameters that indicate that specific task names related to the Bad Rabbit ransomware were created or deleted. The specific task name used are rhaegal, drogon and viserion_. Schtasks.exe is a native windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or establish persistence. +action.escu.mappings = {"analytics_story": ["Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives -action.escu.creation_date = 2017-11-03 +action.escu.creation_date = 2019-02-28 action.escu.modification_date = 2019-02-28 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Scheduled tasks used in BadRabbit ransomware - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Scheduled tasks used in BadRabbit ransomware +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names specific to Bad Rabbit ransomware has been created or deleted -action.notable.param.rule_title = Scheduled tasks used in BadRabbit ransomware detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. +action.notable.param.rule_title = Scheduled tasks used in BadRabbit ransomware +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process_name -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process) as process from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe (Processes.process= "*create*" OR Processes.process= "*delete*") by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search (process=*rhaegal* OR process=*drogon* OR *viserion_*) +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process) as process from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe (Processes.process= "*create*" OR Processes.process= "*delete*") by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search (process=*rhaegal* OR process=*drogon* OR *viserion_*) | `scheduled_tasks_used_in_badrabbit_ransomware_filter` [ESCU - Schtasks scheduling job on remote system - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Privilege Escalation", "Execution", "Scheduled Task"], "mitre_technique_id": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for execution of schtasks.exe with parameters that indicate a task is being scheduled on a remote host. Schtasks.exe is a native windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or malicious executables on remote systems. +action.escu.mappings = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. -action.escu.creation_date = 2016-09-13 +action.escu.creation_date = 2020-01-10 action.escu.modification_date = 2020-01-10 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Schtasks scheduling job on remote system - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Lateral Movement"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Schtasks scheduling job on remote system +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process +action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.notable.param.rule_title = Schtasks scheduling job on remote system -action.notable.param.security_domain = endpoint +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = schtasks.exe Processes.process="*/create*" Processes.process="* /s *" by Processes.process_name Processes.process Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `schtasks_scheduling_job_on_remote_system_filter` @@ -7783,101 +5394,70 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Execution", "Scheduled Task"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The search looks for execution of schtasks.exe with parameters that indicate a task is being scheduled that would cause a forced reboot on the host. Schtasks.exe is a native windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or establish persistence. This tactic is leveraged by the Bad Rabbit Ransomware. +action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. -action.escu.creation_date = 2017-11-03 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Schtasks used for forcing a reboot - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Ransomware", "Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -5h@h -dispatch.latest_time = -1h@h +action.escu.analytic_story = ["Windows Persistence Techniques", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Schtasks used for forcing a reboot +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is scheduled to force a reboot -action.notable.param.rule_title = Schtasks used for scheduling a force reboot -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. +action.notable.param.rule_title = Schtasks used for forcing a reboot +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = schtasks.exe Processes.process="*shutdown*" Processes.process="*/r*" Processes.process="*/f*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = schtasks.exe Processes.process="*shutdown*" Processes.process="*/r*" Processes.process="*/f*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `schtasks_used_for_forcing_a_reboot_filter` [ESCU - Script Execution via WMI - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for scripts launched via WMI. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = Attackers are increasingly abusing Windows Management Infrastructure for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for scripts launched via WMI, either remotely or locally, by looking for the execution of scrcons.exe, which is the scripting host used by WMI, similar to wscript or cscript. +action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for scripts launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. -action.escu.creation_date = 2018-10-23 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Script Execution via WMI - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Script Execution via WMI +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = This search looks for scrcons.exe, which indicates that a script was launched via WMI. -action.notable.param.rule_title = Script execution via WMI on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for scripts launched via WMI. +action.notable.param.rule_title = Script Execution via WMI +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = "scrcons.exe" by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `wmi_script_execution_filter` @@ -7885,305 +5465,211 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Application Shimming"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for files being created in `Windows\AppPatch\Custom and Windows\AppPatch\Custom64`, the location where shim databases are installed. It will return all the files created, as well as the time of creation for the first and last file for each endpoint. +action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. -action.escu.creation_date = 2017-10-03 +action.escu.creation_date = 2018-11-02 action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Shim Database File Creation - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Shim Database File Creation +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A file, $file_name$, was created in the default shim database directory on $dest. -action.notable.param.rule_title = Shim database file created on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. +action.notable.param.rule_title = Shim Database File Creation +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Filesystem.action) values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\AppPatch\Custom* by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`drop_dm_object_name(Filesystem)` +search = | tstats `security_content_summariesonly` count values(Filesystem.action) values(Filesystem.file_hash) as file_hash values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_path=*Windows\AppPatch\Custom* by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`drop_dm_object_name(Filesystem)` | `shim_database_file_creation_filter` [ESCU - Shim Database Installation With Suspicious Parameters - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Application Shimming"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the execution of sdbinst.exe with command-line arguments of -q and -p. The -q option performs a silent installation with no visible window, status, or warning information. The -p option allows the shim database to contain patches. It will return the count, the first time, and the last time these command-line arguments were seen on each endpoint and by each user. +action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-10-03 +action.escu.creation_date = 2019-03-01 action.escu.modification_date = 2019-03-01 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Shim Database Installation With Suspicious Parameters - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Windows Persistence Techniques"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Shim Database Installation With Suspicious Parameters +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = The system $dest$ had a shim database installed. -action.notable.param.rule_title = Shim Database Installation on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. +action.notable.param.rule_title = Shim Database Installation With Suspicious Parameters +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 20 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sdbinst.exe Processes.process="*-p*" Processes.process="*-q*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = sdbinst.exe Processes.process="*-p*" Processes.process="*-q*" by Processes.process_name Processes.parent_process_name Processes.dest Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `shim_database_installation_with_suspicious_parameters_filter` [ESCU - Short Lived Windows Accounts - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects accounts that were created and deleted in a short time period. -action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["Persistence", "Create Account"], "nist": ["PR.IP"]} -action.escu.data_models = ["Change"] -action.escu.eli5 = This search looks for Windows Event Logs 4720 (account creation) and 4726 (account deletion) and determines if they happen for the same user within 4 hours of each other. It will report the user and machine that reported the events and the time it first and last saw this activity. +action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.data_models = Change +action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ action.escu.known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. action.escu.creation_date = 2018-01-05 action.escu.modification_date = 2018-01-05 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Short Lived Windows Accounts - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Account Monitoring and Controls"] -cron_schedule = 0 0,4,8,12,16,20 * * * -dispatch.earliest_time = -245m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Short Lived Windows Accounts +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = The account $user$ was created and deleted in a short amount of time. -action.notable.param.rule_title = Short lived account $user$ on $dest -action.notable.param.security_domain = access +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects accounts that were created and deleted in a short time period. +action.notable.param.rule_title = Short Lived Windows Accounts +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(All_Changes.result_id) as result_id count min(_time) as firstTime max(_time) as lastTime from datamodel=Change where All_Changes.result_id=4720 OR All_Changes.result_id=4726 by _time span=4h All_Changes.user All_Changes.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` | search result_id = 4720 result_id=4726 | transaction user connected=false maxspan=240m | table firstTime lastTime count user dest result_id +search = | tstats `security_content_summariesonly` values(All_Changes.result_id) as result_id count min(_time) as firstTime max(_time) as lastTime from datamodel=Change where All_Changes.result_id=4720 OR All_Changes.result_id=4726 by _time span=4h All_Changes.user All_Changes.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` | search result_id = 4720 result_id=4726 | transaction user connected=false maxspan=240m | table firstTime lastTime count user dest result_id | `short_lived_windows_accounts_filter` [ESCU - Single Letter Process On Endpoint - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for process names that consist only of a single letter. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search returns all the processes for each endpoint and user and filters out any process that isn't 5 characters long and ends with .exe. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for process names that consist only of a single letter. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. -action.escu.creation_date = 2018-03-22 +action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Single Letter Process On Endpoint - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["DHS Report TA18-074A"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Single Letter Process On Endpoint +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, user -action.notable.param.rule_description = A process with a single letter, $process_name$ was detected on $dest$ -action.notable.param.rule_title = Single-letter executable $process_name$ on $dest$. -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = This search looks for process names that consist only of a single letter. +action.notable.param.rule_title = Single Letter Process On Endpoint +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest, Processes.user, Processes.process, Processes.process_name | `drop_dm_object_name(Processes)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | eval process_name_length = len(process_name), endExe = if(substr(process_name, -4) == ".exe", 1, 0) | search process_name_length=5 AND endExe=1 | table count, firstTime, lastTime, dest, user, process, process_name +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest, Processes.user, Processes.process, Processes.process_name | `drop_dm_object_name(Processes)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | eval process_name_length = len(process_name), endExe = if(substr(process_name, -4) == ".exe", 1, 0) | search process_name_length=5 AND endExe=1 | table count, firstTime, lastTime, dest, user, process, process_name | `single_letter_process_on_endpoint_filter` [ESCU - Spectre and Meltdown Vulnerable Systems - Rule] action.escu = 0 action.escu.enabled = 1 description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. -action.escu.mappings = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} -action.escu.data_models = ["Vulnerabilities"] -action.escu.eli5 = This search looks for the three CVEs associated with the Spectre and Meltdown vulnerabilities. +action.escu.mappings = {"analytics_story": ["Spectre And Meltdown Vulnerabilities"], "asset_type": "Endpoint", "cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Vulnerabilities +action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. action.escu.known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. -action.escu.creation_date = 2018-01-07 +action.escu.creation_date = 2017-01-07 action.escu.modification_date = 2017-01-07 action.escu.confidence = high action.escu.full_search_name = ESCU - Spectre and Meltdown Vulnerable Systems - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Nessus", "Qualys"] action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] -cron_schedule = 0 6 * * * -dispatch.earliest_time = -25h@h -dispatch.latest_time = -1h@h +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Spectre and Meltdown Vulnerable Systems +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = $dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities. -action.notable.param.rule_title = $dest is vulnerable to the Spectre or Meltdown CPU vulnerabilities -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 100 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. +action.notable.param.rule_title = Spectre and Meltdown Vulnerable Systems +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Vulnerabilities where Vulnerabilities.cve ="CVE-2017-5753" OR Vulnerabilities.cve ="CVE-2017-5715" OR Vulnerabilities.cve ="CVE-2017-5754" by Vulnerabilities.dest| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Vulnerabilities where Vulnerabilities.cve ="CVE-2017-5753" OR Vulnerabilities.cve ="CVE-2017-5715" OR Vulnerabilities.cve ="CVE-2017-5754" by Vulnerabilities.dest| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `spectre_and_meltdown_vulnerable_systems_filter` [ESCU - Spike in File Writes - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for a sharp increase in the number of files written to a particular host -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search calculates counts the number of file modification events per hour per host in your environment. It then takes the average and standard deviations of those numbers and displays any hosts with more than 20 events that have over four times the standard deviation more than the average number of file modifications. +action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = The search looks for a sharp increase in the number of files written to a particular host action.escu.how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, such as Carbon Black or endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the file system. action.escu.known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. -action.escu.creation_date = 2017-08-20 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = low +action.escu.confidence = high action.escu.full_search_name = ESCU - Spike in File Writes - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -7d@d -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Spike in File Writes +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = A sharp increase in file writes was detected on $dest -action.notable.param.rule_title = Spike in file writes on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = low -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 7200s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for a sharp increase in the number of files written to a particular host +action.notable.param.rule_title = Spike in File Writes +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Filesystem where Filesystem.action=created by _time span=1h, Filesystem.dest | `drop_dm_object_name(Filesystem)` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, "-1d@d"), count, null))) as "count" avg(eval(if(_time upperBound) AND num_data_samples >=20, 1, 0) | search isOutlier=1 | `file_write_spikes_filter` @@ -8191,100 +5677,69 @@ search = | tstats `security_content_summariesonly` count FROM datamodel=Endpoint action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} -action.escu.eli5 = This search searches Splunk's internal logs for evidence of CVE-2018-11409 exploitation attempts. +action.escu.mappings = {"analytics_story": ["Splunk Enterprise Vulnerability CVE-2018-11409"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} +action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. action.escu.how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. action.escu.known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. action.escu.creation_date = 2018-06-14 action.escu.modification_date = 2018-06-14 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Splunk Enterprise Information Disclosure - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Splunk Server -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Splunk Enterprise"] action.escu.analytic_story = ["Splunk Enterprise Vulnerability CVE-2018-11409"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Splunk Enterprise Information Disclosure +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, src_ip -action.notable.param.rule_description = The Splunk Server $dest$ had a possible Splunk information-disclosure possibility from $src_ip$ -action.notable.param.rule_title = Possible Splunk Information Disclosure Exploitation Attempt from $src_ip$ -action.notable.param.security_domain = network +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. +action.notable.param.rule_title = Splunk Enterprise Information Disclosure +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, src_ip -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = index=_internal sourcetype=splunkd_ui_access server-info | search clientip!=127.0.0.1 uri_path="*raw/services/server/info/server-info" | rename clientip as src_ip, splunk_server as dest | stats earliest(_time) as firstTime, latest(_time) as lastTime, values(uri) as uri, values(useragent) as http_user_agent, values(user) as user by src_ip, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = index=_internal sourcetype=splunkd_ui_access server-info | search clientip!=127.0.0.1 uri_path="*raw/services/server/info/server-info" | rename clientip as src_ip, splunk_server as dest | stats earliest(_time) as firstTime, latest(_time) as lastTime, values(uri) as uri, values(useragent) as http_user_agent, values(user) as user by src_ip, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `splunk_enterprise_information_disclosure_filter` [ESCU - Suspicious Changes to File Associations - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Change Default File Association"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for changes made to the registry that control Windows file associations. It is typical for users to change the file association to open certain types of files with specific applications. However, when these changes are legitimately performed, they are typically done via the processes explorer.exe or openwith.exe. The search first executes the subsearch that looks at the Registry node, which specifies setting a value in the registry and creates a table of process_id and dest. It then uses those arguments to find out what process and parent process were responsible for making those registry changes. +action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. -action.escu.creation_date = 2018-01-26 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Changes to File Associations - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows File Extension and Association Abuse"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious Changes to File Associations +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name, process -action.notable.param.rule_description = The system $dest$ had an unusual change to a file association -action.notable.param.rule_title = Suspicious File Association Change on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. +action.notable.param.rule_title = Suspicious Changes to File Associations +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name!=Explorer.exe AND Processes.process_name!=OpenWith.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path]| `change_file_association_filter` @@ -8292,103 +5747,72 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). -action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.IP"]} -action.escu.data_models = ["UEBA"] -action.escu.eli5 = This detection monitors for emails that are suspicious because of their sender, domain rareness, or behavior differences, as determined by Splunk UBA. In this search, we query the "UEBA" data model to look for anomalies that are raised by the "SuspiciousEmailDetectionModel" and will output the count, description of the anomaly, signature, the type of event in UBA, the severity, and the user who received a potentially suspicious email from a newly seen domain. It will also output all the categories associated with that anomaly. +action.escu.mappings = {"analytics_story": ["Suspicious Emails"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "threat"} +action.escu.data_models = UEBA +action.escu.eli5 = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. action.escu.known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. action.escu.creation_date = 2019-07-21 action.escu.modification_date = 2019-07-21 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Email - UBA Anomaly - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["user", "url"] -action.escu.entities = ["user", "url"] -action.escu.providing_technologies = ["Microsoft Exchange"] action.escu.analytic_story = ["Suspicious Emails"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious Email - UBA Anomaly +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user, url -action.notable.param.rule_description = Newly observed email domain $url$ sent an email to $user$. -action.notable.param.rule_title = Suspicious Email Anomaly -action.notable.param.security_domain = threat +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). +action.notable.param.rule_title = Suspicious Email - UBA Anomaly +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = |tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(All_UEBA_Events.category) as category from datamodel=UEBA where nodename=All_UEBA_Events.UEBA_Anomalies All_UEBA_Events.UEBA_Anomalies.uba_model = "SuspiciousEmailDetectionModel" by All_UEBA_Events.description All_UEBA_Events.severity All_UEBA_Events.user All_UEBA_Events.uba_event_type All_UEBA_Events.link All_UEBA_Events.signature All_UEBA_Events.url All_UEBA_Events.UEBA_Anomalies.uba_model | `drop_dm_object_name(All_UEBA_Events)` | `drop_dm_object_name(UEBA_Anomalies)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search = |tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(All_UEBA_Events.category) as category from datamodel=UEBA where nodename=All_UEBA_Events.UEBA_Anomalies All_UEBA_Events.UEBA_Anomalies.uba_model = "SuspiciousEmailDetectionModel" by All_UEBA_Events.description All_UEBA_Events.severity All_UEBA_Events.user All_UEBA_Events.uba_event_type All_UEBA_Events.link All_UEBA_Events.signature All_UEBA_Events.url All_UEBA_Events.UEBA_Anomalies.uba_model | `drop_dm_object_name(All_UEBA_Events)` | `drop_dm_object_name(UEBA_Anomalies)`| `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `suspicious_email___uba_anomaly_filter` [ESCU - Suspicious Email Attachment Extensions - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for emails that have attachments with suspicious file extensions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Execution", "Defense Evasion"], "mitre_technique_id": ["T1193"], "nist": ["DE.AE", "PR.IP"]} -action.escu.data_models = ["Email"] -action.escu.eli5 = This search looks at any email messages with attachments and checks the file names of those attachments against an included lookup file to see if it has a suspicious file extension. +action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"], "security_domain": "network"} +action.escu.data_models = Email +action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ **Splunk Phantom Playbook Integration**\ If Splunk Phantom is also configured in your environment, a Playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-04-20 +action.escu.creation_date = 2020-01-27 action.escu.modification_date = 2020-01-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Email Attachment Extensions - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_user", "message_id"] -action.escu.entities = ["src_user", "message_id"] -action.escu.providing_technologies = ["Microsoft Exchange"] -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Suspicious Emails"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious Email Attachment Extensions +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user, file_name -action.notable.param.rule_description = The sender $src_user$ has sent an email with a suspicious file named $file_name$ -action.notable.param.rule_title = Suspicious Email Attachment from $src_user$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_user,message_id -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = This search looks for emails that have attachments with suspicious file extensions. +action.notable.param.rule_title = Suspicious Email Attachment Extensions +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | `suspicious_email_attachments` | `suspicious_email_attachments_filter` @@ -8396,202 +5820,139 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names that have been linked to malicious activity. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks at files being created or modified in the Endpoint file-system data model. The names of those files are checked against an included lookup file, which contains the names of files associated with malware or attack activity. The search returns any files with matching names, along with a note (also specified in the lookup file) that gives or points to more information about the files. +action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = The search looks for files created with names that have been linked to malicious activity. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. action.escu.known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. -action.escu.creation_date = 2018-06-14 +action.escu.creation_date = 2019-04-25 action.escu.modification_date = 2019-04-25 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious File Write - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Hidden Cobra Malware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious File Write +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A write to a filename associated with malicious activity detected on $dest$. -action.notable.param.rule_title = Suspicious File Write Detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for files created with names that have been linked to malicious activity. +action.notable.param.rule_title = Suspicious File Write +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Filesystem.action) as action values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Filesystem)` | `suspicious_writes` +search = | tstats `security_content_summariesonly` count values(Filesystem.action) as action values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name(Filesystem)` | `suspicious_writes` | `suspicious_file_write_filter` [ESCU - Suspicious Java Classes - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. -action.escu.mappings = {"cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution"], "nist": ["DE.AE"]} -action.escu.eli5 = The search leverages HTTP form data from typically POST events that can be captured with Splunk streams or similar wire data capture tools. The search looks for java classes like `processbuilder` and `runtime` are used to create a new process and execute commands inside java, and are synonymous with spawning a shell. There are very exceptional reasons to ever these classes in Java via an HTTP API and hence when seen are highly suspicious. Also, this is a common vectors leverage to exploit Apache Struts. +action.escu.mappings = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"], "security_domain": "threat"} +action.escu.eli5 = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. action.escu.known_false_positives = There are no known false positives. action.escu.creation_date = 2018-12-06 action.escu.modification_date = 2018-12-06 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Java Classes - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Apache"] action.escu.analytic_story = ["Apache Struts Vulnerability"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious Java Classes +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src, url, http_user_agent -action.notable.param.rule_description = The host $src$ with user agent $http_user_agent$ is sending web traffic to $url$, which contains suspicious Java classes. These classes may be indicative of remote code execution in Java frameworks, such as Apache Struts. -action.notable.param.rule_title = Suspicious Java Classes: Possible RCE against Struts or similar Java framework from $src$ -action.notable.param.security_domain = threat +action.notable.param.nes_fields = ['dest', 'src'] +action.notable.param.rule_description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. +action.notable.param.rule_title = Suspicious Java Classes +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src, url, http_user_agent -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="stream:http" http_method=POST http_content_length>1 | regex form_data="(?i)java\.lang\.(?:runtime|processbuilder)" | rename src_ip as src | stats count earliest(_time) as firstTime, latest(_time) as lastTime, values(url) as uri, values(status) as status, values(http_user_agent) as http_user_agent by src, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = `stream_http` http_method=POST http_content_length>1 | regex form_data="(?i)java\.lang\.(?:runtime|processbuilder)" | rename src_ip as src | stats count earliest(_time) as firstTime, latest(_time) as lastTime, values(url) as uri, values(status) as status, values(http_user_agent) as http_user_agent by src, dest | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `suspicious_java_classes_filter` [ESCU - Suspicious LNK file launching a process - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. -action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Initial Access", "Spearphishing Attachment"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = In this search, we are essentially trying to detect if a LNK file created under the C:\User* or *\Local\Temp\* directory structures is launching a process with in 1 hour of its creation. LNK files or also known as Windows shortcut files are commonly associated with phishing and are a [preferred method used for exploitation](https://www.fireeye.com/blog/threat-research/2017/04/fin7-phishing-lnk.html). +action.escu.mappings = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +action.escu.eli5 = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. -action.escu.creation_date = 2019-04-29 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious LNK file launching a process - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Phishing Payloads"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious LNK file launching a process +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process_name, file_name -action.notable.param.rule_description = suspicious LNK file from $file_name$ is executing a process $process_name$ on $dest$ -action.notable.param.rule_title = LNK file $file_name$ is executing process $process_name$ on $dest$ -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,file_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. +action.notable.param.rule_title = Suspicious LNK file launching a process +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_name="*.lnk" AND (Filesystem.file_path="C:\\Users*" OR Filesystem.file_path="*Local\\Temp*") by _time span=1h Filesystem.process_id Filesystem.file_name Filesystem.file_path Filesystem.file_hash Filesystem.user | `drop_dm_object_name(Filesystem)` | rename process_id as lnk_pid | join lnk_pid, _time [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_name=* by _time span=1h Processes.parent_process_id Processes.process_id Processes.process_name Processes.dest Processes.process_path Processes.process | `drop_dm_object_name(Processes)` | rename parent_process_id as lnk_pid | fields _time lnk_pid process_id dest process_name process_path process] | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table firstTime, lastTime, lnk_pid, process_id, user, dest, file_name, file_path, process_name, process, process_path, file_hash | `lnk_executing_a_process_filter` -[ESCU - Suspicious Reg.exe Process - Rule] +[ESCU - Suspicious Reg exe Process - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Modify Registry", "Disabling Security Tools"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the execution of reg.exe with a parent process of cmd.exe. It then executes a subsearch looking for those cmd.exe processes with a parent that is not explorer.exe. It then joins those two searches to make sure that the reg.exe process is a grandchild of the non explorer.exe process. The search will return the number of such instances and the first and last time this activity has been seen on each endpoint and user. +action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112", "T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. -action.escu.creation_date = 2017-10-11 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - Suspicious Reg.exe Process - Rule +action.escu.confidence = high +action.escu.full_search_name = ESCU - Suspicious Reg exe Process - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Windows Defense Evasion Tactics"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious Reg.exe Process +action.correlationsearch.label = Suspicious Reg exe Process +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = The system $dest$ had reg.exe process run not initiated by a user. -action.notable.param.rule_title = Suspicious reg.exe process detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. +action.notable.param.rule_title = Suspicious Reg exe Process +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name != explorer.exe Processes.process_name =cmd.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process_id Processes.parent_process_id | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe by Processes.parent_process_id Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename parent_process_id as process_id |dedup process_id| table process_id dest] | `suspicious_reg_process_filter` @@ -8599,357 +5960,246 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Indicator Removal on Host"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for execution of wevtutil.exe with command-line arguments that indicate that it has been used to delete the setup, application, security, or system event logs. The search returns the number of times the behavior was observed, the first and last time it was seen, the host exhibiting the behavior and the user context of the process execution. +action.escu.mappings = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. -action.escu.creation_date = 2017-02-17 +action.escu.creation_date = 2019-02-28 action.escu.modification_date = 2019-02-28 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious wevtutil Usage - Rule action.escu.search_type = detection -action.escu.asset_at_risk = -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Ransomware", "Windows Log Manipulation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious wevtutil Usage +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, user -action.notable.param.rule_description = wevtutil is the windows event log tool. This searches for wevtutil clearing the security or system logs. +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.notable.param.rule_title = Suspicious wevtutil Usage -action.notable.param.security_domain = endpoint +action.notable.param.security_domain = action.notable.param.severity = medium -action.notable.param.drilldown_name = View wevtutil process information on $dest$ -action.notable.param.drilldown_search = | from datamodel:Endpoint.Processes | search dest="$dest$" process=*wevtutil* -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = wevtutil.exe Processes.process="*cl*" (Processes.process="*System*" OR Processes.process="*Security*" OR Processes.process="*Setup*" OR Processes.process="*Application*") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = wevtutil.exe Processes.process="*cl*" (Processes.process="*System*" OR Processes.process="*Security*" OR Processes.process="*Setup*" OR Processes.process="*Application*") by Processes.process_name Processes.parent_process_name Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `suspicious_wevtutil_usage_filter` [ESCU - Suspicious writes to System Volume Information - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the 'System Volume Information' folder by something other than the System process. -action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["Collection", "Data Staged"], "nist": ["DE.CM"]} -action.escu.eli5 = This search uses data on file writes captured via Sysmon to watch for writes to the "System Volume Information" folder by processes other than the system process. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. It then looks for a file created with a path that includes "System Volume Information" and a process ID (PID) other than 4. PID 4 is assigned to the System process on Windows systems. Excluding these writes allows us to filter out legitimate activity. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity. +action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search detects writes to the 'System Volume Information' folder by something other than the System process. action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. action.escu.creation_date = 2018-01-08 action.escu.modification_date = 2018-01-08 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious writes to System Volume Information - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious writes to System Volume Information +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name, process -action.notable.param.rule_description = The process $process$ on $dest$ wrote $file_name$ to 'System Volume Information'. -action.notable.param.rule_title = Suspicious process $process$ wrote to 'System Volume Information' on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.rule_description = This search detects writes to the 'System Volume Information' folder by something other than the System process. +action.notable.param.rule_title = Suspicious writes to System Volume Information +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = (sourcetype=XmlWinEventLog:Microsoft-Windows-Sysmon/Operational OR tag=process) EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search = (`sysmon` OR tag=process) EventCode=11 process_id!=4 file_path=*System\ Volume\ Information* | stats count min(_time) as firstTime max(_time) as lastTime by dest, Image, file_path | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `suspicious_writes_to_system_volume_information_filter` [ESCU - Suspicious writes to windows Recycle Bin - Rule] action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the recycle bin by a process other than explorer.exe. -action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["Collection", "Data Staged"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search uses data on file writes captured via Sysmon to watch for writes to the Recycle Bin by processes other than explorer.exe. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. Next, it looks for files created with a path that includes the string "$Recycle.Bin" by processes other than explorer.exe, which is the process responsible for copying files to the Recycle Bin on delete. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity. +action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search detects writes to the recycle bin by a process other than explorer.exe. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. action.escu.known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. -action.escu.creation_date = 2018-01-08 +action.escu.creation_date = 2020-02-03 action.escu.modification_date = 2020-02-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious writes to windows Recycle Bin - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Sysmon"] action.escu.analytic_story = ["Collection and Staging"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Suspicious writes to windows Recycle Bin +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name, process_name -action.notable.param.rule_description = The process $process_name$ on $dest$ wrote $file_name$ to the Recycle Bin. -action.notable.param.rule_title = Suspicious process $process_name$ wrote to the Recycle Bin on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects writes to the recycle bin by a process other than explorer.exe. +action.notable.param.rule_title = Suspicious writes to windows Recycle Bin +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where Filesystem.file_path = "*$Recycle.Bin*" by Filesystem.process_id Filesystem.dest | `drop_dm_object_name("Filesystem")`| search [| tstats `security_content_summariesonly` values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name != "explorer.exe" by Processes.process_id Processes.dest| `drop_dm_object_name("Processes")` | table process_id dest] +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where Filesystem.file_path = "*$Recycle.Bin*" by Filesystem.process_id Filesystem.dest | `drop_dm_object_name("Filesystem")`| search [| tstats `security_content_summariesonly` values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name != "explorer.exe" by Processes.process_id Processes.dest| `drop_dm_object_name("Processes")` | table process_id dest] | `suspicious_writes_to_windows_recycle_bin_filter` [ESCU - System Processes Run From Unexpected Locations - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Masquerading"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search returns all the processes that are not executing out of the C:\Windows\System32 or C:\Windows\SysWOW64 directories. Next, it takes the filename and looks it up in a table `is_windows_system_file` of files that should normally run out of the C:\Windows\System32 or C:\Windows\SysWOW64 directory. Any matches are then returned. +action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1036"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. action.escu.how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. action.escu.known_false_positives = None identified -action.escu.creation_date = 2016-08-24 +action.escu.creation_date = 2020-02-04 action.escu.modification_date = 2020-02-04 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - System Processes Run From Unexpected Locations - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Ransomware", "Suspicious Command-Line Executions", "Unusual Processes"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = System Processes Run From Unexpected Locations +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user, process_name, dest -action.notable.param.rule_description = The system $dest$ has a process that normally runs out of Windows\System32\ that is not being run from that location. -action.notable.param.rule_title = System Processes Run From Unexpected Location on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. +action.notable.param.rule_title = System Processes Run From Unexpected Locations +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,process_name -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_path !="C:\\Windows\\System32*" Processes.process_path !="C:\\Windows\\SysWOW64*" by Processes.user Processes.dest Processes.process_name Processes.process_id Processes.process_path Processes.parent_process_name Processes.process_hash| `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `is_windows_system_file` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_path !="C:\\Windows\\System32*" Processes.process_path !="C:\\Windows\\SysWOW64*" by Processes.user Processes.dest Processes.process_name Processes.process_id Processes.process_path Processes.parent_process_name Processes.process_hash| `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `is_windows_system_file` | `system_processes_run_from_unexpected_locations_filter` [ESCU - TOR Traffic - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. -action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Exfiltration"], "nist": ["DE.AE"]} -action.escu.data_models = ["Network_Traffic"] -action.escu.eli5 = The search leverages the Enterprise Security Network_Traffic data model to look for network traffic that has been identified as TOR and marked as 'allowed'. +action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE"], "security_domain": "network"} +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None at this time -action.escu.creation_date = 2017-08-21 +action.escu.creation_date = 2017-09-11 action.escu.modification_date = 2017-09-11 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - TOR Traffic - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] -action.escu.providing_technologies = ["Palo Alto Firewall", "Bro", "Splunk Stream"] -action.escu.analytic_story = ["Command and Control", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = TOR Traffic +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, dest_ip -action.notable.param.rule_description = Network traffic accessing TOR detected from $src_ip$ -action.notable.param.rule_title = TOR Network Traffic Allowed from $src_ip$ -action.notable.param.security_domain = network +action.notable.param.rule_description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. +action.notable.param.rule_title = TOR Traffic +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_ip -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = src_ip -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.app=tor AND All_Traffic.action=allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Traffic where All_Traffic.app=tor AND All_Traffic.action=allowed by All_Traffic.src_ip All_Traffic.dest_ip All_Traffic.dest_port All_Traffic.action | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Traffic")` | `tor_traffic_filter` [ESCU - USN Journal Deletion - Rule] action.escu = 0 action.escu.enabled = 1 description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. -action.escu.mappings = {"cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Indicator Removal on Host"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search looks for the execution of fsutil.exe with command-line arguments to delete the USN journal. The search returns the count of the number of times it's seen this process execution with these arguments, the first and last time it's seen this behavior, the hosts it was executed on, and the user context under which it was executed. +action.escu.mappings = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-06-27 +action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - USN Journal Deletion - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Ransomware", "Windows Log Manipulation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = USN Journal Deletion +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process_name -action.notable.param.rule_description = The system $dest$ deleted its NTFS journals. -action.notable.param.rule_title = File System Journal Deleted on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. +action.notable.param.rule_title = USN Journal Deletion +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user,process_name -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fsutil.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process="*deletejournal*" AND process="*usn*" +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fsutil.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process="*deletejournal*" AND process="*usn*" | `usn_journal_deletion_filter` [ESCU - Uncommon Processes On Endpoint - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as uncommon. -action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Accessibility Features"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search returns the number of times, as well as the first and last time, it has seen every process run for each endpoint and user, and then displays only those processes that you have marked as uncommon in the `uncommon_processes_default.csv` table. +action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-12-08 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Uncommon Processes On Endpoint - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Unusual Processes", "Windows Privilege Escalation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows Privilege Escalation", "Unusual Processes"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Uncommon Processes On Endpoint +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process_name, user -action.notable.param.rule_description = Prohibited software $process_name$ has been detected on $dest$ -action.notable.param.rule_title = Prohibited Software Detected On $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as uncommon. +action.notable.param.rule_title = Uncommon Processes On Endpoint +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_filter` @@ -8957,50 +6207,35 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Disabling Security Tools"], "mitre_technique_id": ["T1089"], "nist": ["DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search is looking to detect execution of `fltMC.exe` that specifically used for unloading the Sysmon Filter Driver +action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. action.escu.known_false_positives = -action.escu.creation_date = 2017-10-23 +action.escu.creation_date = 2020-01-13 action.escu.modification_date = 2020-01-13 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Unload Sysmon Filter Driver - Rule action.escu.search_type = detection -action.escu.asset_at_risk = -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Disabling Security Tools"] -cron_schedule = 30 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Unload Sysmon Filter Driver +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process +action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. -action.notable.param.rule_title = Unload Sysmon Filter Driver on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.rule_title = Unload Sysmon Filter Driver +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=fltMC.exe AND Processes.process=*unload* AND Processes.process=*SysmonDrv* by Processes.process_name Processes.process_id Processes.parent_process_name Processes.process Processes.dest Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` |`unload_sysmon_filter_driver_filter`| table firstTime lastTime dest user count process_name process_id parent_process_name process @@ -9008,49 +6243,32 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects loading of unsigned images by LSASS. -action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} -action.escu.eli5 = This search detects unsigned images loaded by LSASS (Local Security Authrity Subsystem Service). Normally, LSASS only loads signed images. Therefore, it is a malicious indicator when unsigned images are loaded by LSASS. This can be an indicator for credential dumping using tools like Windows Credential Editor. +action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = This search detects loading of unsigned images by LSASS. action.escu.how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. action.escu.creation_date = 2019-12-06 action.escu.modification_date = 2019-12-06 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Unsigned Image Loaded by LSASS - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Windows -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */60 * * * * +dispatch.earliest_time = -60m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Unsigned Image Loaded by LSASS -action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = Possible attempt at credential dumping was detected on $dest$. -action.notable.param.rule_title = unsigned images loaded by LSASS on $dest$. -action.notable.param.security_domain = endpoint -action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, ImageLoaded -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +schedule_window = auto +action.email.subject.alert = Splunk Alert: $name$ +action.email.to = test@test.de +action.email.message.alert = Splunk Alert $name$ triggered +action.email.useNSSubject = 1 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `unsigned_image_loaded_by_LSASS_filter` @@ -9058,100 +6276,68 @@ search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_tim action.escu = 0 action.escu.enabled = 1 description = This search gives you the hosts where a backup was attempted and then failed. -action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -action.escu.eli5 = This search looks across the most recent backup events for each host, and returns those messages that indicate there was a backup failure. +action.escu.mappings = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search gives you the hosts where a backup was attempted and then failed. action.escu.how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. action.escu.known_false_positives = None identified -action.escu.creation_date = 2017-06-15 +action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Unsuccessful Netbackup backups - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Netbackup"] action.escu.analytic_story = ["Monitor Backup Solution"] -cron_schedule = 0 7 * * * -dispatch.earliest_time = -24h@h -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Unsuccessful Netbackup backups +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = The system $dest$ attempted a backup but encountered an error. -action.notable.param.rule_title = Failed backup attempt by $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 10 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.rule_description = This search gives you the hosts where a backup was attempted and then failed. +action.notable.param.rule_title = Unsuccessful Netbackup backups +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="netbackup_logs" | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature +search = `netbackup` | stats latest(_time) as latestTime by COMPUTERNAME, MESSAGE | search MESSAGE="An error occurred, failed to backup." | `security_content_ctime(latestTime)` | rename COMPUTERNAME as dest, MESSAGE as signature | table latestTime, dest, signature | `unsuccessful_netbackup_backups_filter` [ESCU - Unusually Long Command Line - Rule] action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search calculates the average and standard deviation for the length of the command lines on each of your endpoints and alerts when it detects a command line with a length over 10 times the standard deviation larger than the average command line. +action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships, from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some legitimate applications start with long command lines. -action.escu.creation_date = 2017-08-23 +action.escu.creation_date = 2020-03-16 action.escu.modification_date = 2020-03-16 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - Rule action.escu.search_type = detection -action.escu.asset_at_risk = -action.escu.fields_required = ["dest", "process_name", "user"] -action.escu.entities = ["dest", "process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Unusual Processes"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -1d@d -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Unusually Long Command Line +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, user -action.notable.param.rule_description = An unusually long command line $cmdline$ was found on $dest$ -action.notable.param.rule_title = Unusually Long Command Line on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. +action.notable.param.rule_title = Unusually Long Command Line +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user,process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| `unusually_long_commandlines_filter`| eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost) @@ -9159,2807 +6345,2100 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. -action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This search leverages the Machine Learning Toolkit (MLTK) to identify outliers in the length of the command lines observed to be used by a specific user. The companion search, "Baseline of Command Line Length - MLTK," creates a machine-learning (ML) model built over the historical data used by this search. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. action.escu.how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. action.escu.known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. action.escu.creation_date = 2019-05-08 action.escu.modification_date = 2019-05-08 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - MLTK - Rule action.escu.search_type = detection -action.escu.asset_at_risk = -action.escu.fields_required = ["dest", "process_name", "user"] -action.escu.entities = ["dest", "process_name", "user"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Unusual Processes"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Unusually Long Command Line - MLTK +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, process, user -action.notable.param.rule_description = An unusually long command line $cmdline$ was found on $dest$ -action.notable.param.rule_title = Unusually Long Command Line on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. +action.notable.param.rule_title = Unusually Long Command Line - MLTK +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 50 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user,process_name -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | search user!=unknown | apply cmdline_pdfmodel threshold=0.01 | rename "IsOutlier(processlen)" as isOutlier | search isOutlier > 0 | table firstTime lastTime user dest process_name process processlen count +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | search user!=unknown | apply cmdline_pdfmodel threshold=0.01 | rename "IsOutlier(processlen)" as isOutlier | search isOutlier > 0 | table firstTime lastTime user dest process_name process processlen count | `unusually_long_command_line___mltk_filter` [ESCU - Unusually Long Content-Type Length - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -action.escu.eli5 = This detection search uses HTTP traffic data captured with Splunk Stream. The search is constructed to use "stream:http" sourcetype and counts of the number of times an HTTP request is received by a destination which the length of the Content-Type header value the client sends the server is greater than 100 characters long. We calculate this content_type_length field and output the results. +action.escu.mappings = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} +action.escu.eli5 = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.escu.how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. action.escu.known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. -action.escu.creation_date = 2017-03-14 +action.escu.creation_date = 2017-10-13 action.escu.modification_date = 2017-10-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Content-Type Length - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Web Server -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Splunk Stream"] action.escu.analytic_story = ["Apache Struts Vulnerability"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Unusually Long Content-Type Length +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_ip, dest_ip, url -action.notable.param.rule_description = This search looks for unusually long strings in the Content-Type http header +action.notable.param.rule_description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.notable.param.rule_title = Unusually Long Content-Type Length -action.notable.param.security_domain = network -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 75 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest_ip -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=stream:http | eval cs_content_type_length = len(cs_content_type) | where cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length cs_content_type url +search = `stream_http` | eval cs_content_type_length = len(cs_content_type) | where cs_content_type_length > 100 | table endtime src_ip dest_ip cs_content_type_length cs_content_type url | `unusually_long_content_type_length_filter` [ESCU - WMI Permanent Event Subscription - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI permanent event subscriptions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation", "Persistence", "Windows Management Instrumentation Event Subscription"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.eli5 = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Windows event ID 5861. +action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. action.escu.creation_date = 2018-10-23 action.escu.modification_date = 2018-10-23 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = WMI Permanent Event Subscription +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = This search looks for the creation of a permanent WMI event subscription via Windows event logs. -action.notable.param.rule_title = WMI Event Subscription Detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. +action.notable.param.rule_title = WMI Permanent Event Subscription +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" EventCode=5861 Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" | search consumer!="NTEventLogEventConsumer=\"SCM Event Log Consumer\"" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | rename ComputerName as dest +search = `wmi` EventCode=5861 Binding | rex field=Message "Consumer =\s+(?[^;|^$]+)" | search consumer!="NTEventLogEventConsumer=\"SCM Event Log Consumer\"" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, consumer, Message | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | rename ComputerName as dest | `wmi_permanent_event_subscription_filter` [ESCU - WMI Permanent Event Subscription - Sysmon - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI permanent event subscriptions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation", "Persistence", "Windows Management Instrumentation Event Subscription"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.eli5 = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Sysmon event ID 21. +action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. action.escu.creation_date = 2018-10-23 action.escu.modification_date = 2018-10-23 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Sysmon - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = WMI Permanent Event Subscription - Sysmon +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user -action.notable.param.rule_description = This search looks for the creation of a permanent WMI event subscription via Sysmon logs. -action.notable.param.rule_title = WMI Event Subscription Detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. +action.notable.param.rule_title = WMI Permanent Event Subscription - Sysmon +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode=21 | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, Filter +search = `sysmon` EventCode=21 | rename host as dest | table _time, dest, user, Operation, EventType, Query, Consumer, Filter | `wmi_permanent_event_subscription___sysmon_filter` [ESCU - WMI Temporary Event Subscription - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI temporary event subscriptions. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation", "Persistence", "Windows Management Instrumentation Event Subscription"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.eli5 = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI temporary event subscription by watching for Windows event ID 5860. +action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for the creation of WMI temporary event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. action.escu.known_false_positives = Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events. action.escu.creation_date = 2018-10-23 action.escu.modification_date = 2018-10-23 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Temporary Event Subscription - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] action.escu.analytic_story = ["Suspicious WMI Use"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = WMI Temporary Event Subscription +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = This search looks for the creation of a temporary WMI event subscription via Windows event logs. -action.notable.param.rule_title = Temporary WMI Event Subscription Detected on $dest$ -action.notable.param.security_domain = endpoint +action.notable.param.rule_description = This search looks for the creation of WMI temporary event subscriptions. +action.notable.param.rule_title = WMI Temporary Event Subscription +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 70 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype="wineventlog:microsoft-windows-wmi-activity/operational" EventCode=5860 Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" | search query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = 'wsmprovhost.exe'" AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search = `wmi` EventCode=5860 Temporary | rex field=Message "NotificationQuery =\s+(?[^;|^$]+)" | search query!="SELECT * FROM Win32_ProcessStartTrace WHERE ProcessName = 'wsmprovhost.exe'" AND query!="SELECT * FROM __InstanceOperationEvent WHERE TargetInstance ISA 'AntiVirusProduct' OR TargetInstance ISA 'FirewallProduct' OR TargetInstance ISA 'AntiSpywareProduct'" | stats count min(_time) as firstTime max(_time) as lastTime by ComputerName, query | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `wmi_temporary_event_subscription_filter` [ESCU - Web Fraud - Account Harvesting - Rule] action.escu = 0 action.escu.enabled = 1 description = This search is used to identify the creation of multiple user accounts using the same email domain name. -action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Create Account"], "nist": ["DE.CM", "DE.DP"]} -action.escu.eli5 = When a fraudster is setting the stage for a campaign, they will often create many user accounts on the website. This is a simple example of how to detect a many-account creation hosted on a Magento2 e-commerce platform, where the fraudster is using email addresses from a single email domain. +action.escu.mappings = {"analytics_story": ["Web Fraud Detection"], "asset_type": "Account", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1136"], "nist": ["DE.CM", "DE.DP"], "security_domain": "threat"} +action.escu.eli5 = This search is used to identify the creation of multiple user accounts using the same email domain name. action.escu.how_to_implement = We start with a dataset that provides visibility into the email address used for the account creation. In this example, we are narrowing our search down to the single web page that hosts the Magento2 e-commerce platform (via URI) used for account creation, the single http content-type to grab only the user's clicks, and the http field that provides the username (form_data), for performance reasons. After we have the username and email domain, we look for numerous account creations per email domain. Common data sources used for this detection are customized Apache logs or Splunk Stream. action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamolous behavior. This search will need to be customized to fit your environment—improving its fidelity by counting based on something much more specific, such as a device ID that may be present in your dataset. Consideration for whether the large number of registrations are occuring from a first-time seen domain may also be important. Extending the search window to look further back in time, or even calculating the average per hour/day for each email domain to look for an anomalous spikes, will improve this search. You can also use Shannon entropy or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness or similarity of the email name or email domain, as the names are often machine-generated. -action.escu.creation_date = 2018-07-12 +action.escu.creation_date = 2018-10-08 action.escu.modification_date = 2018-10-08 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Account Harvesting - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Account -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] -action.escu.providing_technologies = ["Splunk Stream"] action.escu.analytic_story = ["Web Fraud Detection"] -cron_schedule = 0 1 * * * -dispatch.earliest_time = -1445m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Web Fraud - Account Harvesting +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = src_user -action.notable.param.rule_description = This search is used to identify multiple created accounts tied to a specific email domain. Such activity is often indicative of account harvesting. A list of $src_user$ accounts were created. -action.notable.param.rule_title = Web Fraud Detection: Possible Account Harvesting -action.notable.param.security_domain = threat +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search is used to identify the creation of multiple user accounts using the same email domain name. +action.notable.param.rule_title = Web Fraud - Account Harvesting +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = src_user -action.risk.param._risk_object_type = user -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=stream:http http_content_type=text* uri="/magento2/customer/account/loginPost/" | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> 25 +search = `stream_http` http_content_type=text* uri="/magento2/customer/account/loginPost/" | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> 25 | `web_fraud___account_harvesting_filter` [ESCU - Web Fraud - Anomalous User Clickspeed - Rule] action.escu = 0 action.escu.enabled = 1 description = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. -action.escu.mappings = {"cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Initial Access", "Valid Accounts"], "nist": ["DE.AE", "DE.CM"]} -action.escu.eli5 = It's suspicious when someone or something is moving throughout your website too quickly or with a perfect click cadence. Fortunately, it's easy to detect by calculating the time between clicks for each session and highlighting the anomalous behavior. +action.escu.mappings = {"analytics_story": ["Web Fraud Detection"], "asset_type": "account", "cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1078"], "nist": ["DE.AE", "DE.CM"], "security_domain": "threat"} +action.escu.eli5 = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. action.escu.how_to_implement = Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior. -action.escu.creation_date = 2018-07-12 +action.escu.creation_date = 2018-10-08 action.escu.modification_date = 2018-10-08 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Anomalous User Clickspeed - Rule action.escu.search_type = detection -action.escu.asset_at_risk = account -action.escu.fields_required = ["session_id"] -action.escu.entities = ["session_id"] -action.escu.providing_technologies = ["Splunk Stream"] action.escu.analytic_story = ["Web Fraud Detection"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Web Fraud - Anomalous User Clickspeed +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = session_id -action.notable.param.rule_description = This search is used to examine web sessions in order to identify unnaturally rapid clicks with near-perfect cadence (high periodicity or low standard deviation), which resemble a script-driven session. -action.notable.param.rule_title = Web Fraud Detection: Anomalous User Clickspeed -action.notable.param.security_domain = threat +action.notable.param.rule_description = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. +action.notable.param.rule_title = Web Fraud - Anomalous User Clickspeed +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = session_id -action.risk.param._risk_object_type = other -action.risk.param._risk_score = 40 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = session_id -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=stream:http http_content_type=text* | rex field=cookie "form_key=(?\w+)" | streamstats window=2 current=1 range(_time) as TimeDelta by session_id | where TimeDelta>0 |stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) as ClickSpeedAvg by session_id | where count>5 AND (ClickSpeedStdDev<.5 OR ClickSpeedAvg<.5) +search = `stream_http` http_content_type=text* | rex field=cookie "form_key=(?\w+)" | streamstats window=2 current=1 range(_time) as TimeDelta by session_id | where TimeDelta>0 |stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) as ClickSpeedAvg by session_id | where count>5 AND (ClickSpeedStdDev<.5 OR ClickSpeedAvg<.5) | `web_fraud___anomalous_user_clickspeed_filter` [ESCU - Web Fraud - Password Sharing Across Accounts - Rule] action.escu = 0 action.escu.enabled = 1 description = This search is used to identify user accounts that share a common password. -action.escu.mappings = {"cis20": ["CIS 16"], "nist": ["DE.DP"]} -action.escu.eli5 = A common password across user accounts generally indicates that the users are choosing poor passwords or that a fraudster has a common password across multiple accounts embedded within a script. The search will extract the username and password information from the form_data field, then calculate the number and values for usernames that have the same passwords. Finally, it outputs the values where the unique usernames sharing passwords are greater than 5 +action.escu.mappings = {"analytics_story": ["Web Fraud Detection"], "asset_type": "account", "cis20": ["CIS 16"], "nist": ["DE.DP"], "security_domain": "threat"} +action.escu.eli5 = This search is used to identify user accounts that share a common password. action.escu.how_to_implement = We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior. -action.escu.creation_date = 2018-07-12 +action.escu.creation_date = 2018-10-08 action.escu.modification_date = 2018-10-08 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Password Sharing Across Accounts - Rule action.escu.search_type = detection -action.escu.asset_at_risk = account -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] -action.escu.providing_technologies = ["Splunk Stream"] action.escu.analytic_story = ["Web Fraud Detection"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Web Fraud - Password Sharing Across Accounts +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = user -action.notable.param.rule_description = This search is used to identify user accounts, $user$, that share common passwords -action.notable.param.rule_title = Web Fraud Detection: Password Sharing Across Accounts -action.notable.param.security_domain = threat +action.notable.param.nes_fields = ['user'] +action.notable.param.rule_description = This search is used to identify user accounts that share a common password. +action.notable.param.rule_title = Web Fraud - Password Sharing Across Accounts +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = user -action.risk.param._risk_object_type = other -action.risk.param._risk_score = 10 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = user -alert.suppress.period = 3600s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = sourcetype=stream:http http_content_type=text* uri=/magento2/customer/account/loginPost* | rex field=form_data "login\[username\]=(?[^&|^$]+)" | rex field=form_data "login\[password\]=(?[^&|^$]+)" | stats dc(Username) as UniqueUsernames values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5 +search = `stream_http` http_content_type=text* uri=/magento2/customer/account/loginPost* | rex field=form_data "login\[username\]=(?[^&|^$]+)" | rex field=form_data "login\[password\]=(?[^&|^$]+)" | stats dc(Username) as UniqueUsernames values(Username) as user list(src_ip) as src_ip by Password|where UniqueUsernames>5 | `web_fraud___password_sharing_across_accounts_filter` [ESCU - Web Servers Executing Suspicious Processes - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious processes on all systems labeled as web servers. -action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability", "Execution", "Discovery", "System Information Discovery"], "nist": ["PR.IP"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = This detection search uses the Enterprise Security Endpoint data model. The search uses tstats to search within an accelerated data model to find suspicious applications or processes such as whoami, ping, iptables, wget, service, or curl, running on hosts which are marked as web servers in the Assets and Identity Framework of ES. +action.escu.mappings = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1082"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.data_models = Endpoint +action.escu.eli5 = This search looks for suspicious processes on all systems labeled as web servers. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. action.escu.known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. -action.escu.creation_date = 2017-03-14 +action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 -action.escu.confidence = medium +action.escu.confidence = high action.escu.full_search_name = ESCU - Web Servers Executing Suspicious Processes - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Web Server -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] action.escu.analytic_story = ["Apache Struts Vulnerability"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Web Servers Executing Suspicious Processes +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, user, process -action.notable.param.rule_description = This search looks for suspicious processes on all systems labeled as web servers +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for suspicious processes on all systems labeled as web servers. action.notable.param.rule_title = Web Servers Executing Suspicious Processes -action.notable.param.security_domain = endpoint +action.notable.param.security_domain = action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 75 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, process -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest_category="web_server" AND (Processes.process="*whoami*" OR Processes.process="*ping*" OR Processes.process="*iptables*" OR Processes.process="*wget*" OR Processes.process="*service*" OR Processes.process="*curl*") by Processes.process Processes.process_name, Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest_category="web_server" AND (Processes.process="*whoami*" OR Processes.process="*ping*" OR Processes.process="*iptables*" OR Processes.process="*wget*" OR Processes.process="*service*" OR Processes.process="*curl*") by Processes.process Processes.process_name, Processes.dest Processes.user| `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `web_servers_executing_suspicious_processes_filter` [ESCU - Windows Event Log Cleared - Rule] action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows events that indicate one of the Windows event logs has been purged. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Indicator Removal on Host"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"]} -action.escu.eli5 = This search looks at the Windows security and system event logs. EventCode 1002 in the security log indicates that the log has been cleared, EventCode 1000 in the security log indicates the event logging service has been shut down, and EventCode 104 in the system log indicates the application log has been cleared. If any of these events are found, a notable will be generated. +action.escu.mappings = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} +action.escu.eli5 = This search looks for Windows events that indicate one of the Windows event logs has been purged. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting Windows event logs from your hosts. action.escu.known_false_positives = It is possible that these logs may be legitimately cleared by Administrators. -action.escu.creation_date = 2017-02-17 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Windows Event Log Cleared - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.analytic_story = ["Ransomware", "Windows Log Manipulation"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Windows Event Log Cleared +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest -action.notable.param.rule_description = The Event Logging System has been cleared or shutdown on $dest$ -action.notable.param.rule_title = Windows Event Log Cleared on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 60 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest, signature_id -alert.suppress.period = 28800s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for Windows events that indicate one of the Windows event logs has been purged. +action.notable.param.rule_title = Windows Event Log Cleared +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = ((eventtype=wineventlog_security) AND (signature_id=1102 OR signature_id=1100)) OR ((eventtype=wineventlog_system) AND signature_id=104) | stats count min(_time) as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = ((`wineventlog_security` AND (signature_id=1102 OR signature_id=1100)) OR ((`wineventlog_system` AND signature_id=104) | stats count min(_time) as firstTime max(_time) as lastTime by signature_id dest user| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_event_log_cleared_filter` [ESCU - Windows hosts file modification - Rule] action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to the hosts file on all Windows endpoints across your environment. -action.escu.mappings = {"cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"]} -action.escu.data_models = ["Endpoint"] -action.escu.eli5 = The hosts file is present on both Windows and Linux endpoints. The purpose of the hosts file is to provide a mapping between hostnames and IP addresses, the same way DNS is used to provide such a mapping. However, the information in the hosts file takes precedence over information received via DNS and a DNS query will not be issued if the hostname of interest is found in the hosts file. As such, attackers have been observed adding entries to the host file to override any DNS resolution. For this reason, it is useful to monitor for changes to this file, which typically do not occur very often in legitimate cases. +action.escu.mappings = {"analytics_story": ["Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"], "security_domain": "endpoint"} +action.escu.eli5 = The search looks for modifications to the hosts file on all Windows endpoints across your environment. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = There may be legitimate reasons for system administrators to add entries to this file. -action.escu.creation_date = 2017-06-07 +action.escu.creation_date = 2018-11-02 action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Windows hosts file modification - Rule action.escu.search_type = detection -action.escu.asset_at_risk = Endpoint -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] action.escu.analytic_story = ["Host Redirection"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m +dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = Windows hosts file modification +schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = dest, file_name -action.notable.param.rule_description = A file modification was noted for the hosts file on $dest$. -action.notable.param.rule_title = Modification of hosts file detected on $dest$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = high -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 80 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest,user -alert.suppress.period = 86400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = The search looks for modifications to the hosts file on all Windows endpoints across your environment. +action.notable.param.rule_title = Windows hosts file modification +action.notable.param.security_domain = +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events relation = greater than quantity = 0 realtime_schedule = 0 -schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.file_path Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | search Filesystem.file_name=hosts AND Filesystem.file_path=*Windows\\System32\\* | `drop_dm_object_name(Filesystem)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem by Filesystem.file_name Filesystem.file_path Filesystem.dest | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | search Filesystem.file_name=hosts AND Filesystem.file_path=*Windows\\System32\\* | `drop_dm_object_name(Filesystem)` | `windows_hosts_file_modification_filter` ### END ESCU DETECTIONS ### -### ESCU INVESTIGATIONS ### -[ESCU - AWS Investigate User Activities By ARN] +### ESCU BASELINES ### + +[ESCU - Add Prohibited Processes to Enterprise Security - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security - Baseline +description = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. +action.escu.creation_date = 2017-09-15 +action.escu.modification_date = 2017-09-15 +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "SamSam Ransomware"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. +action.escu.how_to_implement = This search should be run on each new install of ESCU. +disabled = true +is_visible = false +search = | inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count + +[ESCU - Baseline of API Calls per User ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of API Calls per User ARN - Baseline +description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-04-09 +action.escu.modification_date = 2018-04-09 +action.escu.analytic_story = ["AWS User Monitoring"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count + +[ESCU - Baseline of Command Line Length - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Command Line Length - MLTK - Baseline +description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. +action.escu.creation_date = 2019-05-08 +action.escu.modification_date = 2019-05-08 +action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Unusual Processes"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. +action.escu.how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search user!=unknown | `security_content_ctime(start_time)`| `security_content_ctime(end_time)`| eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel + +[ESCU - Baseline of DNS Query Length - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of DNS Query Length - MLTK - Baseline +description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. +action.escu.creation_date = 2019-05-08 +action.escu.modification_date = 2019-05-08 +action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] +action.escu.data_models = Network_Resolution +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. +action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name("DNS")` | eval query_length = len(query) | fit DensityFunction query_length by record_type into dns_query_pdfmodel + +[ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK - Baseline +description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. +action.escu.creation_date = 2019-11-14 +action.escu.modification_date = 2019-11-14 +action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ +In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ +More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 + +[ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK - Baseline +description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. +action.escu.creation_date = 2019-11-14 +action.escu.modification_date = 2019-11-14 +action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ +In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ +More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 + +[ESCU - Baseline of Network ACL Activity by ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Network ACL Activity by ARN - Baseline +description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-05-21 +action.escu.modification_date = 2018-05-21 +action.escu.analytic_story = ["AWS Network ACL Activity"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. +disabled = true +is_visible = false +search = `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats count + +[ESCU - Baseline of S3 Bucket deletion activity by ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of S3 Bucket deletion activity by ARN - Baseline +description = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-07-17 +action.escu.modification_date = 2018-07-17 +action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count + +[ESCU - Baseline of SMB Traffic - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of SMB Traffic - MLTK - Baseline +description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. +action.escu.creation_date = 2019-05-08 +action.escu.modification_date = 2019-05-08 +action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Netsh Abuse", "Ransomware"] +action.escu.data_models = Network_Traffic +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. +action.escu.how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name("All_Traffic")` | fit DensityFunction count by "HourOfDay,DayOfWeek" into smb_pdfmodel + +[ESCU - Baseline of Security Group Activity by ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Security Group Activity by ARN - Baseline +description = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-04-17 +action.escu.modification_date = 2018-04-17 +action.escu.analytic_story = ["AWS User Monitoring"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. +disabled = true +is_visible = false +search = `cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats count + +[ESCU - Baseline of blocked outbound traffic from AWS - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of blocked outbound traffic from AWS - Baseline +description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-05-07 +action.escu.modification_date = 2018-05-07 +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. +disabled = true +is_visible = false +search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | stats count + +[ESCU - Count of Unique IPs Connecting to Ports - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Count of Unique IPs Connecting to Ports - Baseline +description = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. +action.escu.creation_date = 2017-09-13 +action.escu.modification_date = 2017-09-13 +action.escu.data_models = Network_Traffic +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. +action.escu.how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` | sort - count + +[ESCU - Count of assets by category - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Count of assets by category - Baseline +description = This search shows you every asset category you have and the assets that belong to those categories. +action.escu.creation_date = 2017-09-13 +action.escu.modification_date = 2017-09-13 +action.escu.analytic_story = ["Asset Tracking"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search shows you every asset category you have and the assets that belong to those categories. +action.escu.how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. +disabled = true +is_visible = false +search = | from datamodel Identity_Management.All_Assets | stats count values(nt_host) by category | sort -count + +[ESCU - Create a list of approved AWS service accounts - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Create a list of approved AWS service accounts - Baseline +description = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. +action.escu.creation_date = 2018-12-03 +action.escu.modification_date = 2018-12-03 +action.escu.analytic_story = ["AWS User Monitoring"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. +disabled = true +is_visible = false +search = `cloudtrail` errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count by identity | table identity | outputlookup aws_service_accounts | stats count + +[ESCU - DNSTwist Domain Names - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - DNSTwist Domain Names - Baseline +description = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. +action.escu.creation_date = 2018-10-08 +action.escu.modification_date = 2018-10-08 +action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. +action.escu.how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. +disabled = true +is_visible = false +search = | dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse="true" | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count + +[ESCU - Discover DNS records - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Discover DNS records - Baseline +description = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup +action.escu.creation_date = 2019-02-14 +action.escu.modification_date = 2019-02-14 +action.escu.analytic_story = ["DNS Hijacking"] +action.escu.data_models = Network_Resolution +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup +action.escu.how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation +disabled = true +is_visible = false +search = | inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, "\*", "")) | join domain [|tstats `security_content_summariesonly` count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,domain,type,query,answer | outputlookup createinapp=true discovered_dns_records.csv + +[ESCU - Identify Systems Creating Remote Desktop Traffic - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Identify Systems Creating Remote Desktop Traffic - Baseline +description = This search counts the numbers of times the system has generated remote desktop traffic. +action.escu.creation_date = 2017-09-15 +action.escu.modification_date = 2017-09-15 +action.escu.data_models = Network_Traffic +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search counts the numbers of times the system has generated remote desktop traffic. +action.escu.how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name("All_Traffic")` | sort - count + +[ESCU - Identify Systems Receiving Remote Desktop Traffic - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Identify Systems Receiving Remote Desktop Traffic - Baseline +description = This search counts the numbers of times the system has created remote desktop traffic +action.escu.creation_date = 2017-09-15 +action.escu.modification_date = 2017-09-15 +action.escu.data_models = Network_Traffic +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search counts the numbers of times the system has created remote desktop traffic +action.escu.how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name("All_Traffic")` | sort - count + +[ESCU - Identify Systems Using Remote Desktop - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Identify Systems Using Remote Desktop - Baseline +description = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. +action.escu.creation_date = 2019-04-01 +action.escu.modification_date = 2019-04-01 +action.escu.data_models = Endpoint +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. +action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Endpoint.Processes where Processes.process_name="*mstsc.exe*" by Processes.dest Processes.process_name | `drop_dm_object_name(Processes)` | sort - count + +[ESCU - Monitor Successful Backups - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Monitor Successful Backups - Baseline +description = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.creation_date = 2017-09-12 +action.escu.modification_date = 2017-09-12 +action.escu.analytic_story = ["Monitor Backup Solution"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. +disabled = true +is_visible = false +search = `netbackup` "Disk/Partition backup completed successfully." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE + +[ESCU - Monitor Unsuccessful Backups - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Monitor Unsuccessful Backups - Baseline +description = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.creation_date = 2017-09-12 +action.escu.modification_date = 2017-09-12 +action.escu.analytic_story = ["Monitor Backup Solution"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. +disabled = true +is_visible = false +search = `netbackup` "An error occurred, failed to backup." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE + +[ESCU - Previously Seen AWS Cross Account Activity - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen AWS Cross Account Activity - Baseline +description = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. +action.escu.creation_date = 2018-06-04 +action.escu.modification_date = 2018-06-04 +action.escu.analytic_story = ["AWS Cross Account Activity"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats count + +[ESCU - Previously Seen AWS Provisioning Activity Sources - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen AWS Provisioning Activity Sources - Baseline +description = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. +action.escu.creation_date = 2018-03-16 +action.escu.modification_date = 2018-03-16 +action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count + +[ESCU - Previously Seen AWS Regions - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen AWS Regions - Baseline +description = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days +action.escu.creation_date = 2018-01-08 +action.escu.modification_date = 2018-01-08 +action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count + +[ESCU - Previously Seen Cloud Compute Creations By User - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Creations By User - Baseline +description = This search builds a table of previously seen users that have launched a cloud compute instance. +action.escu.creation_date = 2018-03-15 +action.escu.modification_date = 2018-03-15 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = Cloud_Infrastructure +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of previously seen users that have launched a cloud compute instance. +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_creations_by_user_input_filter` by Compute.src_user | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_creations_by_user | stats count + +[ESCU - Previously Seen Cloud Compute Images - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Images - Baseline +description = This search builds a table of previously seen images used to launch cloud compute instances +action.escu.creation_date = 2018-03-12 +action.escu.modification_date = 2018-03-12 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = Cloud_Infrastructure +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of previously seen images used to launch cloud compute instances +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_images | stats count + +[ESCU - Previously Seen Cloud Compute Instance Types - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Instance Types - Baseline +description = This search builds a table of previously seen cloud compute instance types +action.escu.creation_date = 2019-10-03 +action.escu.modification_date = 2019-10-03 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = Cloud_Infrastructure +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of previously seen cloud compute instance types +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_instance_types | stats count + +[ESCU - Previously Seen Cloud Regions - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Regions - Baseline +description = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days +action.escu.creation_date = 2019-10-02 +action.escu.modification_date = 2019-10-02 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = Cloud_Infrastructure +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=start `previously_seen_cloud_regions_input_filter` by Compute.region | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_regions | stats count + +[ESCU - Previously Seen EC2 AMIs - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 AMIs - Baseline +description = This search builds a table of previously seen AMIs used to launch EC2 instances +action.escu.creation_date = 2018-03-12 +action.escu.modification_date = 2018-03-12 +action.escu.analytic_story = ["AWS Cryptomining"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of previously seen AMIs used to launch EC2 instances +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | stats count + +[ESCU - Previously Seen EC2 Instance Types - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 Instance Types - Baseline +description = This search builds a table of previously seen EC2 instance types +action.escu.creation_date = 2018-03-08 +action.escu.modification_date = 2018-03-08 +action.escu.analytic_story = ["AWS Cryptomining"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of previously seen EC2 instance types +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | stats count + +[ESCU - Previously Seen EC2 Launches By User - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 Launches By User - Baseline +description = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.creation_date = 2018-03-15 +action.escu.modification_date = 2018-03-15 +action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count + +[ESCU - Previously Seen EC2 Modifications By User - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 Modifications By User - Baseline +description = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.creation_date = 2018-04-05 +action.escu.modification_date = 2018-04-05 +action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. +disabled = true +is_visible = false +search = `cloudtrail` `ec2_modification_api_calls` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count + +[ESCU - Previously Seen Running Windows Services - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Running Windows Services - Baseline +description = This collects the services that have been started across your entire enterprise. +action.escu.creation_date = 2020-01-13 +action.escu.modification_date = 2020-01-13 +action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This collects the services that have been started across your entire enterprise. +action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. +disabled = true +is_visible = false +search = `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services | stats count + +[ESCU - Previously seen API call per user roles in CloudTrail - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen API call per user roles in CloudTrail - Baseline +description = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. +action.escu.creation_date = 2018-04-16 +action.escu.modification_date = 2018-04-16 +action.escu.analytic_story = ["AWS User Monitoring"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles | stats count + +[ESCU - Previously seen S3 bucket access by remote IP - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen S3 bucket access by remote IP - Baseline +description = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" +action.escu.creation_date = 2018-06-28 +action.escu.modification_date = 2018-06-28 +action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `aws_s3_accesslogs` http_status=200 | stats earliest(_time) as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip | stats count + +[ESCU - Previously seen command line arguments - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen command line arguments - Baseline +description = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. +action.escu.creation_date = 2019-03-01 +action.escu.modification_date = 2019-03-01 +action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Hidden Cobra Malware", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] +action.escu.data_models = Endpoint +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. +action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe AND Processes.process="* /c *" by Processes.process | `drop_dm_object_name(Processes)` + +[ESCU - Previously seen users in CloudTrail - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen users in CloudTrail - Baseline +description = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. +action.escu.creation_date = 2018-04-30 +action.escu.modification_date = 2018-04-30 +action.escu.analytic_story = ["Suspicious AWS Login Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv | stats count + +[ESCU - Systems Ready for Spectre-Meltdown Windows Patch - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Systems Ready for Spectre-Meltdown Windows Patch - Baseline +description = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. +action.escu.creation_date = 2018-01-08 +action.escu.modification_date = 2018-01-08 +action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. +action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` + +[ESCU - Update previously seen users in CloudTrail - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Update previously seen users in CloudTrail - Baseline +description = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. +action.escu.creation_date = 2018-04-30 +action.escu.modification_date = 2018-04-30 +action.escu.analytic_story = ["Suspicious AWS Login Activities"] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv + +[ESCU - Windows Updates Install Failures - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Windows Updates Install Failures - Baseline +description = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.creation_date = 2017-09-14 +action.escu.modification_date = 2017-09-14 +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.how_to_implement = You must be ingesting your Windows Update Logs +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=failure by _time span=1d + +[ESCU - Windows Updates Install Successes - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Windows Updates Install Successes - Baseline +description = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.creation_date = 2017-09-14 +action.escu.modification_date = 2017-09-14 +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.eli5 = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.how_to_implement = You must be ingesting your Windows Update Logs +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=installed by _time span=1d + + + +### ESCU RESPONSE TASKS ### + +[ESCU - AWS Investigate User Activities By ARN - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN +action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN - Response Task description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. -action.escu.creation_date = 2018-01-22 +action.escu.creation_date = 2019-04-30 action.escu.modification_date = 2019-04-30 action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Cloud Cryptomining", "Command and Control", "Suspicious AWS EC2 Activities", "Suspicious AWS Login Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Unusual AWS EC2 Modifications"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] +action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType -[ESCU - AWS Investigate User Activities By AccessKeyId] +[ESCU - AWS Investigate User Activities By AccessKeyId - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By AccessKeyId +action.escu.full_search_name = ESCU - AWS Investigate User Activities By AccessKeyId - Response Task description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. action.escu.creation_date = 2018-06-08 action.escu.modification_date = 2018-06-08 action.escu.analytic_story = ["AWS Cross Account Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["accessKeyId"] -action.escu.entities = ["accessKeyId"] +action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage -[ESCU - AWS Investigate User Activities By Source User] +[ESCU - AWS Investigate User Activities By Source User - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By Source User +action.escu.full_search_name = ESCU - AWS Investigate User Activities By Source User - Response Task description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. action.escu.creation_date = 2018-06-08 action.escu.modification_date = 2018-06-08 action.escu.analytic_story = ["AWS Cross Account Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] +action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage -[ESCU - AWS Network ACL Details from ID] +[ESCU - AWS Network ACL Details from ID - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network ACL Details from ID +action.escu.full_search_name = ESCU - AWS Network ACL Details from ID - Response Task description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID -action.escu.creation_date = 2018-01-18 +action.escu.creation_date = 2017-01-22 action.escu.modification_date = 2017-01-22 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["networkAclId"] -action.escu.entities = ["networkAclId"] +action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:description id={networkAclId} | table id account_id vpc_id network_acl_entries{}.* -[ESCU - AWS Network Interface details via resourceId] +[ESCU - AWS Network Interface details via resourceId - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network Interface details via resourceId +action.escu.full_search_name = ESCU - AWS Network Interface details via resourceId - Response Task description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. action.escu.creation_date = 2018-05-07 action.escu.modification_date = 2018-05-07 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS configuration inputs -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["resourceId"] -action.escu.entities = ["resourceId"] +action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:config resourceId={resourceId} | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp -[ESCU - AWS S3 Bucket details via bucketName] +[ESCU - AWS S3 Bucket details via bucketName - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS S3 Bucket details via bucketName +action.escu.full_search_name = ESCU - AWS S3 Bucket details via bucketName - Response Task description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. action.escu.creation_date = 2018-06-26 action.escu.modification_date = 2018-06-26 action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = To implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later) and configure your AWS inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["bucketName"] -action.escu.entities = ["bucketName"] +action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList -[ESCU - All backup logs for host] +[ESCU - All backup logs for host - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - All backup logs for host +action.escu.full_search_name = ESCU - All backup logs for host - Response Task description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. -action.escu.creation_date = 2017-06-19 +action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.analytic_story = ["Monitor Backup Solution"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Netbackup"] -action.escu.eli5 = none -action.escu.how_to_implement = The successfully implement this search you must first send your backup logs to Splunk. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.eli5 = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. disabled = true schedule_window = auto is_visible = false search = | search sourcetype="netbackup_logs" dest={dest} -[ESCU - Amazon EKS Kubernetes activity by src_ip] +[ESCU - Amazon EKS Kubernetes activity by src ip - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Amazon EKS Kubernetes activity by src_ip +action.escu.full_search_name = ESCU - Amazon EKS Kubernetes activity by src ip - Response Task description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address -action.escu.creation_date = 2020-03-24 +action.escu.creation_date = 2020-04-13 action.escu.modification_date = 2020-04-13 action.escu.analytic_story = ["Kubernetes Scanning Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your Cloud Watch EKS inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] +action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address disabled = true schedule_window = auto is_visible = false search = sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip -[ESCU - GCP Kubernetes activity by src_ip] +[ESCU - GCP Kubernetes activity by src ip - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - GCP Kubernetes activity by src_ip +action.escu.full_search_name = ESCU - GCP Kubernetes activity by src ip - Response Task description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address -action.escu.creation_date = 2020-03-24 +action.escu.creation_date = 2020-04-13 action.escu.modification_date = 2020-04-13 action.escu.analytic_story = ["Kubernetes Scanning Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["GCP"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] +action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address disabled = true schedule_window = auto is_visible = false search = sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type -[ESCU - Get All AWS Activity From City] +[ESCU - Get All AWS Activity From City - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From City +action.escu.full_search_name = ESCU - Get All AWS Activity From City - Response Task description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["City"] -action.escu.entities = ["City"] +action.escu.eli5 = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode -[ESCU - Get All AWS Activity From Country] +[ESCU - Get All AWS Activity From Country - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Country +action.escu.full_search_name = ESCU - Get All AWS Activity From Country - Response Task description = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["Country"] -action.escu.entities = ["Country"] +action.escu.eli5 = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode -[ESCU - Get All AWS Activity From IP Address] +[ESCU - Get All AWS Activity From IP Address - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From IP Address +action.escu.full_search_name = ESCU - Get All AWS Activity From IP Address - Response Task description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Network ACL Activity", "AWS Suspicious Provisioning Activities", "Command and Control", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] +action.escu.eli5 = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode -[ESCU - Get All AWS Activity From Region] +[ESCU - Get All AWS Activity From Region - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Region +action.escu.full_search_name = ESCU - Get All AWS Activity From Region - Response Task description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["Region"] -action.escu.entities = ["Region"] +action.escu.eli5 = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode -[ESCU - Get Authentication Logs For Endpoint] +[ESCU - Get Authentication Logs For Endpoint - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Authentication Logs For Endpoint +action.escu.full_search_name = ESCU - Get Authentication Logs For Endpoint - Response Task description = This search returns all users that have attempted to access a particular endpoint. -action.escu.creation_date = 2017-04-10 +action.escu.creation_date = 2017-11-01 action.escu.modification_date = 2017-11-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router & Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Authentication"] -action.escu.providing_technologies = ["Microsoft Windows", "Linux", "macOS"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.data_models = Authentication +action.escu.eli5 = This search returns all users that have attempted to access a particular endpoint. disabled = true schedule_window = auto is_visible = false search = | tstats count from datamodel=Authentication where Authentication.dest={dest} by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` -[ESCU - Get Backup Logs For Endpoint] +[ESCU - Get Backup Logs For Endpoint - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Backup Logs For Endpoint +action.escu.full_search_name = ESCU - Get Backup Logs For Endpoint - Response Task description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. -action.escu.creation_date = 2017-08-24 +action.escu.creation_date = 2017-09-14 action.escu.modification_date = 2017-09-14 action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Netbackup"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting your backup logs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.eli5 = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. disabled = true schedule_window = auto is_visible = false search = | search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature -[ESCU - Get Certificate logs for a domain] +[ESCU - Get Certificate logs for a domain - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Certificate logs for a domain +action.escu.full_search_name = ESCU - Get Certificate logs for a domain - Response Task description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. action.escu.creation_date = 2019-04-29 action.escu.modification_date = 2019-04-29 action.escu.analytic_story = ["Common Phishing Frameworks"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Certificates"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting your certificates or SSL logs from your network traffic into your Certificates datamodel. Please note the wildcard(*) before domain in the search syntax, we use to match for all domain and subdomain combinations -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["domain"] -action.escu.entities = ["domain"] +action.escu.eli5 = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. disabled = true schedule_window = auto is_visible = false search = | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` -[ESCU - Get DNS Server History for a host] +[ESCU - Get DNS Server History for a host - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS Server History for a host +action.escu.full_search_name = ESCU - Get DNS Server History for a host - Response Task description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. -action.escu.creation_date = 2017-04-10 +action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DNS Hijacking", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Host Redirection", "Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search, you must be ingesting your DNS traffic -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] +action.escu.eli5 = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. disabled = true schedule_window = auto is_visible = false search = | search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count -[ESCU - Get DNS traffic ratio] +[ESCU - Get DNS traffic ratio - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS traffic ratio +action.escu.full_search_name = ESCU - Get DNS traffic ratio - Response Task description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. -action.escu.creation_date = 2017-04-10 +action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Network_Traffic"] -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting your network traffic -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip", "dest_ip"] -action.escu.entities = ["src_ip", "dest_ip"] +action.escu.data_models = Network_Traffic +action.escu.eli5 = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. disabled = true schedule_window = auto is_visible = false search = | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval ratio = (bytes_out/bytes_in) | table ratio -[ESCU - Get EC2 Instance Details by instanceId] +[ESCU - Get EC2 Instance Details by instanceId - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get EC2 Instance Details by instanceId +action.escu.full_search_name = ESCU - Get EC2 Instance Details by instanceId - Response Task description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field action.escu.creation_date = 2018-02-12 action.escu.modification_date = 2018-02-12 action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Unusual AWS EC2 Modifications"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["instanceId"] -action.escu.entities = ["instanceId"] +action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field disabled = true schedule_window = auto is_visible = false search = | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC -[ESCU - Get EC2 Launch Details] +[ESCU - Get EC2 Launch Details - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get EC2 Launch Details +action.escu.full_search_name = ESCU - Get EC2 Launch Details - Response Task description = This search returns some of the launch details for a EC2 instance. action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.eli5 = This search returns some of the launch details for a EC2 instance. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName -[ESCU - Get Email Info] +[ESCU - Get Email Info - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Email Info +action.escu.full_search_name = ESCU - Get Email Info - Response Task description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. -action.escu.creation_date = 2017-04-21 +action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Email"] -action.escu.providing_technologies = ["Microsoft Exchange"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting your email logs or capturing unencrypted network traffic which contains email communications. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["message_id"] -action.escu.entities = ["message_id"] +action.escu.eli5 = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. disabled = true schedule_window = auto is_visible = false search = | from datamodel Email.All_Email | search message_id={message_id} -[ESCU - Get Emails From Specific Sender] +[ESCU - Get Emails From Specific Sender - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Emails From Specific Sender +action.escu.full_search_name = ESCU - Get Emails From Specific Sender - Response Task description = This search returns all the emails from a specific sender over the last 24 and next hours. -action.escu.creation_date = 2017-04-21 +action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails", "Web Fraud Detection"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Email"] -action.escu.providing_technologies = ["Microsoft Exchange"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] +action.escu.eli5 = This search returns all the emails from a specific sender over the last 24 and next hours. disabled = true schedule_window = auto is_visible = false search = | from datamodel Email.All_Email | search src_user={src_user} -[ESCU - Get First Occurrence and Last Occurrence of a MAC Address] +[ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get First Occurrence and Last Occurrence of a MAC Address +action.escu.full_search_name = ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. -action.escu.creation_date = 2017-06-14 +action.escu.creation_date = 2017-09-13 action.escu.modification_date = 2017-09-13 action.escu.analytic_story = ["Asset Tracking"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Network_Sessions"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Microsoft Windows"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search, you must be ingesting the logs from your DHCP server. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_mac"] -action.escu.entities = ["src_mac"] +action.escu.data_models = Network_Sessions +action.escu.eli5 = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` -[ESCU - Get History Of Email Sources] +[ESCU - Get History Of Email Sources - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get History Of Email Sources +action.escu.full_search_name = ESCU - Get History Of Email Sources - Response Task description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. action.escu.creation_date = 2019-02-21 action.escu.modification_date = 2019-02-21 -action.escu.analytic_story = [] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Email"] -action.escu.providing_technologies = ["Microsoft Exchange"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] +action.escu.data_models = Email +action.escu.eli5 = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. disabled = true schedule_window = auto is_visible = false search = |tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` -[ESCU - Get Logon Rights Modifications For Endpoint] +[ESCU - Get Logon Rights Modifications For Endpoint - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For Endpoint +action.escu.full_search_name = ESCU - Get Logon Rights Modifications For Endpoint - Response Task description = This search allows you to retrieve any modifications to logon rights associated with a specific host. -action.escu.creation_date = 2017-08-16 +action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.analytic_story = ["Account Monitoring and Controls"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting your Windows event logs -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.eli5 = This search allows you to retrieve any modifications to logon rights associated with a specific host. disabled = true schedule_window = auto is_visible = false search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest={dest} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature -[ESCU - Get Logon Rights Modifications For User] +[ESCU - Get Logon Rights Modifications For User - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For User +action.escu.full_search_name = ESCU - Get Logon Rights Modifications For User - Response Task description = This search allows you to retrieve any modifications to logon rights for a specific user account. -action.escu.creation_date = 2017-08-16 +action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 action.escu.analytic_story = ["Account Monitoring and Controls"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting your Windows event logs -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] +action.escu.eli5 = This search allows you to retrieve any modifications to logon rights for a specific user account. disabled = true schedule_window = auto is_visible = false search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user={user} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature -[ESCU - Get Notable History] +[ESCU - Get Notable History - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable History +action.escu.full_search_name = ESCU - Get Notable History - Response Task description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. -action.escu.creation_date = 2017-03-15 +action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cross Account Activity", "AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router & Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual AWS EC2 Modifications", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = none -action.escu.how_to_implement = If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.analytic_story = ["AWS Cross Account Activity", "AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual AWS EC2 Modifications", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.eli5 = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. disabled = true schedule_window = auto is_visible = false search = | search `notable` | search dest={dest} | table _time, rule_name, owner, priority, severity, status_description -[ESCU - Get Notable Info] +[ESCU - Get Notable Info - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable Info +action.escu.full_search_name = ESCU - Get Notable Info - Response Task description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. -action.escu.creation_date = 2017-03-15 +action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router & Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = none -action.escu.how_to_implement = If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["event_id"] -action.escu.entities = ["event_id"] +action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.eli5 = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. disabled = true schedule_window = auto is_visible = false search = | search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description -[ESCU - Get Outbound Emails to Hidden Cobra Threat Actors] +[ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Outbound Emails to Hidden Cobra Threat Actors +action.escu.full_search_name = ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. action.escu.creation_date = 2018-06-14 action.escu.modification_date = 2018-06-14 -action.escu.analytic_story = [] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Email"] -action.escu.providing_technologies = ["Microsoft Exchange"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_user", "recipient"] -action.escu.entities = ["src_user", "recipient"] +action.escu.eli5 = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. disabled = true schedule_window = auto is_visible = false search = | from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` -[ESCU - Get Parent Process Info] +[ESCU - Get Parent Process Info - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Parent Process Info +action.escu.full_search_name = ESCU - Get Parent Process Info - Response Task description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest -action.escu.creation_date = 2017-08-22 +action.escu.creation_date = 2019-02-28 action.escu.modification_date = 2019-02-28 -action.escu.analytic_story = ["Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Phishing Payloads", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Endpoint"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["process_name", "dest"] -action.escu.entities = ["process_name", "dest"] +action.escu.analytic_story = ["Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Phishing Payloads", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.eli5 = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest disabled = true schedule_window = auto is_visible = false search = | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` -[ESCU - Get Process File Activity] +[ESCU - Get Process File Activity - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process File Activity +action.escu.full_search_name = ESCU - Get Process File Activity - Response Task description = This search returns the file activity for a specific process on a specific endpoint action.escu.creation_date = 2019-11-06 action.escu.modification_date = 2019-11-06 action.escu.analytic_story = ["DHS Report TA18-074A"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Endpoint"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["process_id", "dest"] -action.escu.entities = ["process_id", "dest"] +action.escu.data_models = Endpoint +action.escu.eli5 = This search returns the file activity for a specific process on a specific endpoint disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path -[ESCU - Get Process Info] +[ESCU - Get Process Info - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Info +action.escu.full_search_name = ESCU - Get Process Info - Response Task description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. -action.escu.creation_date = 2017-03-15 +action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Endpoint"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["process_name", "dest"] -action.escu.entities = ["process_name", "dest"] +action.escu.analytic_story = ["AWS Network ACL Activity", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.data_models = Endpoint +action.escu.eli5 = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` -[ESCU - Get Process Information For Port Activity] +[ESCU - Get Process Information For Port Activity - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Information For Port Activity +action.escu.full_search_name = ESCU - Get Process Information For Port Activity - Response Task description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. -action.escu.creation_date = 2017-06-25 +action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DHS Report TA18-074A", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Lateral Movement", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Use of Cleartext Protocols"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Endpoint"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data that associates processes with network events and populate the Endpoint Datamodel -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest_port", "dest"] -action.escu.entities = ["dest_port", "dest"] +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Use of Cleartext Protocols"] +action.escu.data_models = Endpoint +action.escu.eli5 = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] -[ESCU - Get Process Registry Activity] +[ESCU - Get Process Registry Activity - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Registry Activity +action.escu.full_search_name = ESCU - Get Process Registry Activity - Response Task description = This search returns the registry activity for a specific process on a specific endpoint action.escu.creation_date = 2019-11-06 action.escu.modification_date = 2019-11-06 action.escu.analytic_story = ["DHS Report TA18-074A"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Endpoint"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["process_id", "dest"] -action.escu.entities = ["process_id", "dest"] +action.escu.data_models = Endpoint +action.escu.eli5 = This search returns the registry activity for a specific process on a specific endpoint disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id={process_id} AND Registry.dest={dest} by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path -[ESCU - Get Process Responsible For The DNS Traffic] +[ESCU - Get Process Responsible For The DNS Traffic - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Responsible For The DNS Traffic +action.escu.full_search_name = ESCU - Get Process Responsible For The DNS Traffic - Response Task description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. -action.escu.creation_date = 2017-04-10 +action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 action.escu.analytic_story = ["AWS Network ACL Activity", "Brand Monitoring", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Endpoint"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting endpoint data that associates processes with network events into the Endpoint datamodel. This can come from endpoint protection products such as carbon black, or endpoint data sources such as Sysmon. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.data_models = Endpoint +action.escu.eli5 = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] -[ESCU - Get Registry Activities] +[ESCU - Get Registry Activities - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Registry Activities +action.escu.full_search_name = ESCU - Get Registry Activities - Response Task description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. -action.escu.creation_date = 2018-08-07 +action.escu.creation_date = 2019-03-01 action.escu.modification_date = 2019-03-01 -action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware (DHS Report TA18-201A)", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Persistence Techniques", "Windows Privilege Escalation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Endpoint"] -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Persistence Techniques", "Windows Privilege Escalation"] +action.escu.eli5 = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "{dest}" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] -[ESCU - Get Risk Modifiers For Endpoint] +[ESCU - Get Risk Modifiers For Endpoint - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For Endpoint +action.escu.full_search_name = ESCU - Get Risk Modifiers For Endpoint - Response Task description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) -action.escu.creation_date = 2017-10-14 +action.escu.creation_date = 2017-10-19 action.escu.modification_date = 2017-10-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router & Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Risk"] -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = none -action.escu.how_to_implement = Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) disabled = true schedule_window = auto is_visible = false search = | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` -[ESCU - Get Risk Modifiers For User] +[ESCU - Get Risk Modifiers For User - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For User +action.escu.full_search_name = ESCU - Get Risk Modifiers For User - Response Task description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user -action.escu.creation_date = 2017-10-14 +action.escu.creation_date = 2017-10-19 action.escu.modification_date = 2017-10-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router & Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Risk"] -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = none -action.escu.how_to_implement = Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] +action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user disabled = true schedule_window = auto is_visible = false search = | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` -[ESCU - Get Sysmon WMI Activity for Host] +[ESCU - Get Sysmon WMI Activity for Host - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Sysmon WMI Activity for Host +action.escu.full_search_name = ESCU - Get Sysmon WMI Activity for Host - Response Task description = This search queries Sysmon WMI events for the host of interest. action.escu.creation_date = 2018-10-23 action.escu.modification_date = 2018-10-23 action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Sysmon"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate events for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["process", "dest"] -action.escu.entities = ["process", "dest"] +action.escu.eli5 = This search queries Sysmon WMI events for the host of interest. disabled = true schedule_window = auto is_visible = false search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter -[ESCU - Get Update Logs For Endpoint] +[ESCU - Get Update Logs For Endpoint - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Update Logs For Endpoint +action.escu.full_search_name = ESCU - Get Update Logs For Endpoint - Response Task description = This search will tell you give you the update logs for a specific endpoint for the last week. action.escu.creation_date = 2017-08-24 action.escu.modification_date = 2017-08-24 -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Updates"] -action.escu.providing_technologies = ["Microsoft Windows", "Linux", "macOS"] -action.escu.eli5 = none -action.escu.how_to_implement = You need to be ingesting the update logs from your various systems. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware"] +action.escu.eli5 = This search will tell you give you the update logs for a specific endpoint for the last week. disabled = true schedule_window = auto is_visible = false search = | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest} -[ESCU - Get User Information from Identity Table] +[ESCU - Get User Information from Identity Table - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get User Information from Identity Table +action.escu.full_search_name = ESCU - Get User Information from Identity Table - Response Task description = Gather more information about the user identified in the Notable Event. -action.escu.creation_date = 2017-04-10 +action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router & Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must have populated the identity table with information about your users. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] +action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.eli5 = Gather more information about the user identified in the Notable Event. disabled = true schedule_window = auto is_visible = false search = | `identities` | search identity={user} | table _time, identity, first, last, email, category, watchlist -[ESCU - Get Vulnerability Logs For Endpoint] +[ESCU - Get Vulnerability Logs For Endpoint - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Vulnerability Logs For Endpoint +action.escu.full_search_name = ESCU - Get Vulnerability Logs For Endpoint - Response Task description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. -action.escu.creation_date = 2017-08-24 +action.escu.creation_date = 2017-09-10 action.escu.modification_date = 2017-09-10 -action.escu.analytic_story = ["ColdRoot MacOS RAT", "DHS Report TA18-074A", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware", "Windows Log Manipulation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Vulnerabilities"] -action.escu.providing_technologies = ["Nessus"] -action.escu.eli5 = none -action.escu.how_to_implement = You need to be ingesting the logs from your vulnerability scanner. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.analytic_story = ["ColdRoot MacOS RAT", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware", "Windows Log Manipulation"] +action.escu.eli5 = This search will show you any vulnerabilities noted for a specific endpoint for the last week. disabled = true schedule_window = auto is_visible = false search = | from datamodel Vulnerabilities.Vulnerabilities | search dest={dest} -[ESCU - Get Web Session Information via session_id] +[ESCU - Get Web Session Information via session id - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Web Session Information via session_id +action.escu.full_search_name = ESCU - Get Web Session Information via session id - Response Task description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. action.escu.creation_date = 2018-10-08 action.escu.modification_date = 2018-10-08 action.escu.analytic_story = ["Web Fraud Detection"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Splunk Stream"] -action.escu.eli5 = none -action.escu.how_to_implement = This search leverages data extracted from Stream:HTTP. You must configure the HTTP stream using the Splunk Stream App on your Splunk Stream deployment server. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["session_id"] -action.escu.entities = ["session_id"] +action.escu.eli5 = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) by src_ip status -[ESCU - Investigate AWS ECR container listing activity] +[ESCU - Investigate AWS ECR container listing activity - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS ECR container listing activity +action.escu.full_search_name = ESCU - Investigate AWS ECR container listing activity - Response Task description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. action.escu.creation_date = 2020-02-20 action.escu.modification_date = 2020-02-20 -action.escu.analytic_story = ["Container Implantation Monitoring & Investigation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.You must also install Cloud Infrastructure Data Model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_user"] -action.escu.entities = ["src_user"] +action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] +action.escu.eli5 = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. disabled = true schedule_window = auto is_visible = false search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1 -[ESCU - Investigate AWS User Activities by user field] +[ESCU - Investigate AWS User Activities by user field - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS User Activities by user field +action.escu.full_search_name = ESCU - Investigate AWS User Activities by user field - Response Task description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] +action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType -[ESCU - Investigate AWS activities via region name] +[ESCU - Investigate AWS activities via region name - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS activities via region name +action.escu.full_search_name = ESCU - Investigate AWS activities via region name - Response Task description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user action.escu.creation_date = 2018-02-09 action.escu.modification_date = 2018-02-09 action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["awsRegion"] -action.escu.entities = ["awsRegion"] +action.escu.eli5 = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user disabled = true schedule_window = auto is_visible = false search = | search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId -[ESCU - Investigate Cloud Compute Instance Activities] +[ESCU - Investigate Cloud Compute Instance Activities - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Cloud Compute Instance Activities +action.escu.full_search_name = ESCU - Investigate Cloud Compute Instance Activities - Response Task description = This search returns a logs of events that operated on the compute instance. -action.escu.creation_date = 2019-10-02 +action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.eli5 = This search returns a logs of events that operated on the compute instance. disabled = true schedule_window = auto is_visible = false search = | from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields - _* -[ESCU - Investigate Failed Logins for Multiple Destinations] +[ESCU - Investigate Failed Logins for Multiple Destinations - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Failed Logins for Multiple Destinations +action.escu.full_search_name = ESCU - Investigate Failed Logins for Multiple Destinations - Response Task description = This search returns failed logins to multiple destinations by user. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Authentication"] -action.escu.providing_technologies = ["Microsoft Windows", "Linux", "macOS"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.data_models = Authentication +action.escu.eli5 = This search returns failed logins to multiple destinations by user. disabled = true schedule_window = auto is_visible = false search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` -[ESCU - Investigate Network Traffic From src_ip] +[ESCU - Investigate Network Traffic From src ip - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Network Traffic From src_ip +action.escu.full_search_name = ESCU - Investigate Network Traffic From src ip - Response Task description = This search allows you to find all the network traffic from a specific IP address. action.escu.creation_date = 2018-06-15 action.escu.modification_date = 2018-06-15 action.escu.analytic_story = ["ColdRoot MacOS RAT", "Splunk Enterprise Vulnerability CVE-2018-11409"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Network_Traffic"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Palo Alto Firewall"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] +action.escu.eli5 = This search allows you to find all the network traffic from a specific IP address. disabled = true schedule_window = auto is_visible = false search = | from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip} -[ESCU - Investigate Okta Activity by IP Address] +[ESCU - Investigate Okta Activity by IP Address - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by IP Address +action.escu.full_search_name = ESCU - Investigate Okta Activity by IP Address - Response Task description = This search returns all okta events from a specific IP address. action.escu.creation_date = 2020-04-02 action.escu.modification_date = 2020-04-02 action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Okta"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting Okta logs -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] +action.escu.eli5 = This search returns all okta events from a specific IP address. disabled = true schedule_window = auto is_visible = false search = eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason -[ESCU - Investigate Okta Activity by app] +[ESCU - Investigate Okta Activity by app - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by app +action.escu.full_search_name = ESCU - Investigate Okta Activity by app - Response Task description = This search returns all okta events associated with a specific app action.escu.creation_date = 2020-04-02 action.escu.modification_date = 2020-04-02 action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Okta"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting Okta logs -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["app"] -action.escu.entities = ["app"] +action.escu.eli5 = This search returns all okta events associated with a specific app disabled = true schedule_window = auto is_visible = false search = eventtype=okta_log app={app} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason -[ESCU - Investigate Pass the Hash Attempts] +[ESCU - Investigate Pass the Hash Attempts - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Hash Attempts +action.escu.full_search_name = ESCU - Investigate Pass the Hash Attempts - Response Task description = This search hunts for dumped NTLM hashes used for pass the hash. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you need be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.eli5 = This search hunts for dumped NTLM hashes used for pass the hash. disabled = true schedule_window = auto is_visible = false search = `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` -[ESCU - Investigate Pass the Ticket Attempts] +[ESCU - Investigate Pass the Ticket Attempts - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Ticket Attempts +action.escu.full_search_name = ESCU - Investigate Pass the Ticket Attempts - Response Task description = This search hunts for dumped kerberos ticket from LSASS memory. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you need to be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.eli5 = This search hunts for dumped kerberos ticket from LSASS memory. disabled = true schedule_window = auto is_visible = false search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user -[ESCU - Investigate Previous Unseen User] +[ESCU - Investigate Previous Unseen User - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Previous Unseen User +action.escu.full_search_name = ESCU - Investigate Previous Unseen User - Response Task description = This search returns previous unseen user, which didn't log in for 30 days. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Authentication"] -action.escu.providing_technologies = ["Microsoft Windows", "Linux", "macOS"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.data_models = Authentication +action.escu.eli5 = This search returns previous unseen user, which didn't log in for 30 days. disabled = true schedule_window = auto is_visible = false search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` -[ESCU - Investigate Successful Remote Desktop Authentications] +[ESCU - Investigate Successful Remote Desktop Authentications - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Successful Remote Desktop Authentications +action.escu.full_search_name = ESCU - Investigate Successful Remote Desktop Authentications - Response Task description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. action.escu.creation_date = 2018-12-14 action.escu.modification_date = 2018-12-14 action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Authentication"] -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be populating the Authentication data model with security events from your Windows event logs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.data_models = Authentication +action.escu.eli5 = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| table firstTime lastTime src src_nt_domain dest user app count | sort count -[ESCU - Investigate Suspicious Strings in HTTP Header] +[ESCU - Investigate Suspicious Strings in HTTP Header - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Suspicious Strings in HTTP Header +action.escu.full_search_name = ESCU - Investigate Suspicious Strings in HTTP Header - Response Task description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. -action.escu.creation_date = 2017-06-26 +action.escu.creation_date = 2017-10-20 action.escu.modification_date = 2017-10-20 action.escu.analytic_story = ["Apache Struts Vulnerability"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Splunk Stream"] -action.escu.eli5 = none -action.escu.how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip", "dest_ip"] -action.escu.entities = ["src_ip", "dest_ip"] +action.escu.eli5 = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. disabled = true schedule_window = auto is_visible = false search = | search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url -[ESCU - Investigate User Activities In All Cloud Regions] +[ESCU - Investigate User Activities In All Cloud Regions - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In All Cloud Regions +action.escu.full_search_name = ESCU - Investigate User Activities In All Cloud Regions - Response Task description = This search lists all the logged cloud infrastructure activities by a specific cloud user -action.escu.creation_date = 2019-10-02 +action.escu.creation_date = 2019-04-30 action.escu.modification_date = 2019-04-30 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["region", "src_user"] -action.escu.entities = ["region", "src_user"] +action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user disabled = true schedule_window = auto is_visible = false search = | from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | fields - _* -[ESCU - Investigate User Activities In Okta] +[ESCU - Investigate User Activities In Okta - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Okta +action.escu.full_search_name = ESCU - Investigate User Activities In Okta - Response Task description = This search returns all okta events by a specific user action.escu.creation_date = 2020-04-02 action.escu.modification_date = 2020-04-02 action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["Okta"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting Okta logs -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["user"] -action.escu.entities = ["user"] +action.escu.eli5 = This search returns all okta events by a specific user disabled = true schedule_window = auto is_visible = false search = eventtype=okta_log user={user} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason -[ESCU - Investigate User Activities In Single Cloud Region] +[ESCU - Investigate User Activities In Single Cloud Region - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Single Cloud Region +action.escu.full_search_name = ESCU - Investigate User Activities In Single Cloud Region - Response Task description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region -action.escu.creation_date = 2019-10-02 +action.escu.creation_date = 2019-04-30 action.escu.modification_date = 2019-04-30 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Cloud_Infrastructure"] -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] -action.escu.eli5 = none -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["region", "src_user"] -action.escu.entities = ["region", "src_user"] +action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region disabled = true schedule_window = auto is_visible = false search = | from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} | fields - _* -[ESCU - Investigate Web Activity From Host] +[ESCU - Investigate Web Activity From Host - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From Host +action.escu.full_search_name = ESCU - Investigate Web Activity From Host - Response Task description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -action.escu.creation_date = 2017-04-21 +action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["Brand Monitoring", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Web"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search you must be ingesting your web traffic and populating the Web data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["dest"] -action.escu.entities = ["dest"] +action.escu.analytic_story = ["Brand Monitoring", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation"] +action.escu.eli5 = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. disabled = true schedule_window = auto is_visible = false search = | from datamodel Web.Web | search src={dest} -[ESCU - Investigate Web Activity From src_ip] +[ESCU - Investigate Web Activity From src ip - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From src_ip +action.escu.full_search_name = ESCU - Investigate Web Activity From src ip - Response Task description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. action.escu.creation_date = 2018-06-15 action.escu.modification_date = 2018-06-15 action.escu.analytic_story = ["ColdRoot MacOS RAT", "Dynamic DNS", "Splunk Enterprise Vulnerability CVE-2018-11409"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Web"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search, you must be ingesting your web traffic and populating the web data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src_ip"] -action.escu.entities = ["src_ip"] +action.escu.eli5 = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. disabled = true schedule_window = auto is_visible = false search = | from datamodel Web.Web | search src={src_ip} -[ESCU - Investigate Web POSTs From src] +[ESCU - Investigate Web POSTs From src - Response Task] action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web POSTs From src +action.escu.full_search_name = ESCU - Investigate Web POSTs From src - Response Task description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. action.escu.creation_date = 2018-12-06 action.escu.modification_date = 2018-12-06 action.escu.analytic_story = ["Apache Struts Vulnerability"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.data_models = ["Web"] -action.escu.providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] -action.escu.eli5 = none -action.escu.how_to_implement = To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["src"] -action.escu.entities = ["src"] +action.escu.data_models = Web +action.escu.eli5 = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. disabled = true schedule_window = auto is_visible = false search = | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "{src}") and like(http_method, "POST") - -### END ESCU INVESTIGATIONS ### - - -### ESCU BASELINES ### - -[ESCU - Add Prohibited Processes to Enterprise Security] +[ESCU - Process Chain Analysis - Response Task] action.escu = 0 action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security -description = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. -action.escu.creation_date = 2017-06-27 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Monitor for Unauthorized Software", "SamSam Ransomware"] -action.escu.data_models = [] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = This search outputs the interesting processes lookup table and filters out all processes in the table that haven't already been inserted by ESCU. It then appends to those results all the processes currently identified by ESCU that should be prohibited. Next, it fills in the required fields with processes identified by ESCU, and then writes the results back to the interesting process lookup table. This is done so any new processes identified that should be prohibited will be added to the lookup table without creating any duplicate entries. -action.escu.how_to_implement = This search should be run on each new install of ESCU. -action.escu.known_false_positives = +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Process Chain Analysis - Response Task +description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. +action.escu.creation_date = 2020-04-29 +action.escu.modification_date = 2020-04-29 +action.escu.eli5 = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. disabled = true schedule_window = auto is_visible = false -search = | inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count +search = `sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count -[ESCU - Baseline of API Calls per User ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of API Calls per User ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-04-09 -action.escu.modification_date = 2018-04-09 -action.escu.analytic_story = ["AWS User Monitoring"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = This search returns all log events that are API calls, pulls out the ARN that initiated each call, and collects them in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each ARN had. This table is then stored in a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count -[ESCU - Baseline of Command Line Length - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Command Line Length - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Unusual Processes"] -action.escu.data_models = ["Endpoint"] -dispatch.earliest_time = -31d@d -dispatch.latest_time = -1d@d -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = Create a machine-learning (ML) model to characterize the length of the command lines used in your environment. This can help you identify unusually long ones that may indicate that attackers are executing commands on yout systems. -action.escu.how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search user!=unknown | `security_content_ctime(start_time)`| `security_content_ctime(end_time)`| eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel - -[ESCU - Baseline of DNS Query Length - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of DNS Query Length - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -action.escu.data_models = ["Network_Resolution"] -dispatch.earliest_time = -31d@d -dispatch.latest_time = -1d@d -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = Create a machine-learning (ML) model to characterize the length of DNS requests seen in your environment to help identify unusually long ones that may be indicative of attacker infrastrucutre or the use of DNS as a command-and-control channel in your environment. -action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name("DNS")` | eval query_length = len(query) | fit DensityFunction query_length by record_type into dns_query_pdfmodel - -[ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -dispatch.earliest_time = -91d@d -dispatch.latest_time = -1d@d -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = Create a machine-learning (ML) model to establish a baseline for how many RunInstances users do in the environment. This can help you identify excessive numbers of RunInstances which may warrant further investigation to determine if there is misuse or abuse. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 - -[ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] -dispatch.earliest_time = -91d@d -dispatch.latest_time = -1d@d -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = Create a machine-learning (ML) model to establish a baseline for how many TerminateInstances users do in the environment. This can help you identify excessive numbers of TerminateInstances which may warrant further investigation to determine if there is misuse or abuse. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 - -[ESCU - Baseline of Network ACL Activity by ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Network ACL Activity by ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-05-21 -action.escu.modification_date = 2018-05-21 -action.escu.analytic_story = ["AWS Network ACL Activity"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = Use this search to create a baseline for API calls related to network ACLs for the users who initiated this activity. It returns all logged API calls for network activity, pulls out the ARN that initiated each call, and collects the `eventNames` in one-hour groupings. Next, it calculates the number of API calls made per ARN per-hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail `network_acl_events` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats count - -[ESCU - Baseline of S3 Bucket deletion activity by ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of S3 Bucket deletion activity by ARN -description = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-07-17 -action.escu.modification_date = 2018-07-17 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = Use this search to create a baseline for API calls related to deleting an S3 bucket, grouped by the users who initiated this activity. It returns all logged API calls for S3 bucket-deletion activity and then pulls out the ARN that initiated each call. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count - -[ESCU - Baseline of SMB Traffic - MLTK] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of SMB Traffic - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware (DHS Report TA18-201A)", "Hidden Cobra Malware", "Netsh Abuse", "Ransomware"] -action.escu.data_models = ["Network_Traffic"] -dispatch.earliest_time = -31d@d -dispatch.latest_time = -1d@d -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = Create a machine-learning (ML) model to characterize the number of SMB connections observed in your environment. This may help identify spikes in SMB traffic that may be indicative of attackers scanning or attempting to propagate to other systems in your environment. By default, this model is built over 30 days of data and profiles the number of SMB connections in your environment by the hour of day/day of week that the connections occur. -action.escu.how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name("All_Traffic")` | fit DensityFunction count by "HourOfDay,DayOfWeek" into smb_pdfmodel - -[ESCU - Baseline of Security Group Activity by ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Security Group Activity by ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-04-17 -action.escu.modification_date = 2018-04-17 -action.escu.analytic_story = ["AWS User Monitoring"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = Use this search to create a baseline for API calls related to security groups by the users who initiated this activity. It returns all logged API calls for all security-group-related activity, pulls out the ARN that initiated each call, and collects the `eventNames` in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail `security_group_api_calls` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats count - -[ESCU - Baseline of blocked outbound traffic from AWS] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of blocked outbound traffic from AWS -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-04-26 -action.escu.modification_date = 2018-05-07 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = Use this search to create a baseline of blocked outbound network connections by each source IP in your AWS environment. This search returns all log events that correspond to a blocked outbound network connection, extracts the source IP from where the outbound connection was initiated, and collects the events in one-hour groupings. Next, it calculates the number of outbound connections blocked per hour. For each source IP, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each source IP had. This table is then stored in a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudwatchlogs:vpcflow action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | stats count - -[ESCU - Count of Unique IPs Connecting to Ports] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of Unique IPs Connecting to Ports -description = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. -action.escu.creation_date = 2017-06-24 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = [] -action.escu.data_models = ["Network_Traffic"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = For each port being accessed on the network, this search gives the total number of connections observed, and the number of unique IP addresses making those connections. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Count of assets by category] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of assets by category -description = This search shows you every asset category you have and the assets that belong to those categories. -action.escu.creation_date = 2017-06-11 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = ["Asset Tracking"] -action.escu.data_models = ["Identity_Management"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = This search gives you the number and the names of the hosts of each host in your environment by category. It will then sort them by the count. -action.escu.how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Identity_Management.All_Assets | stats count values(nt_host) by category | sort -count - -[ESCU - Create a list of approved AWS service accounts] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Create a list of approved AWS service accounts -description = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-12-03 -action.escu.analytic_story = ["AWS User Monitoring"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = We first look for all successful CloudTrail API activity caused by types of user accounts and then remove all the events caused by users in the Identity table. This generates a list of accounts--typically service accounts--configured in your AWS environment. We output this list of service accounts to `aws_service_accounts.csv`. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count by identity | table identity | outputlookup aws_service_accounts | stats count - -[ESCU - DNSTwist Domain Names] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - DNSTwist Domain Names -description = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. -action.escu.creation_date = 2017-06-01 -action.escu.modification_date = 2018-10-08 -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Enterprise"] -action.escu.eli5 = This search starts with the dnstwist command consuming domains from a file called domains.csv in the DA-ESS-SOC/lookups directory. This search then adds a domain\_abuse=true term to each permutation, removes all the valid domain names and stores all that information into a lookup file that is used in the associated detection search. Alternatively domain dnstwist permutations can be calculated from domains in the `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` lookups located in **Splunk\_SA\_CIM** using argument `populate_from_cim=true`. Also an individual domain can be passed using argument `domain=` -action.escu.how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse="true" | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count - -[ESCU - Discover DNS records] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Discover DNS records -description = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup -action.escu.creation_date = 2019-02-14 -action.escu.modification_date = 2019-02-14 -action.escu.analytic_story = ["DNS Hijacking"] -action.escu.data_models = ["Network_Resolution"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named `discovered_dns_records.csv` -action.escu.how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation -action.escu.known_false_positives = Please vet the lookup created by this baseline search -action.escu.fields_required = ["query", "answer"] -action.escu.entities = ["query", "answer"] -disabled = true -schedule_window = auto -is_visible = false -search = | inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, "\*", "")) | join domain [|tstats `security_content_summariesonly` count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,domain,type,query,answer | outputlookup createinapp=true discovered_dns_records.csv - -[ESCU - Identify Systems Creating Remote Desktop Traffic] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Creating Remote Desktop Traffic -description = This search counts the numbers of times the system has generated remote desktop traffic. -action.escu.creation_date = 2017-04-24 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = [] -action.escu.data_models = ["Network_Traffic"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = This search counts the numbers of times the system has tried to connect to another system on TCP/3389, the default port used for RDP traffic. -action.escu.how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Identify Systems Receiving Remote Desktop Traffic] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Receiving Remote Desktop Traffic -description = This search counts the numbers of times the system has created remote desktop traffic -action.escu.creation_date = 2017-04-24 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = [] -action.escu.data_models = ["Network_Traffic"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Stream", "Bro"] -action.escu.eli5 = This search counts the numbers of times the system has received a connection to TCP/ 3389, the default port used for RDP traffic. -action.escu.how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Identify Systems Using Remote Desktop] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Using Remote Desktop -description = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. -action.escu.creation_date = 2017-04-18 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = [] -action.escu.data_models = ["Endpoint"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. It does this by looking for the process name in the Endpoint data model. -action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Endpoint.Processes where Processes.process_name="*mstsc.exe*" by Processes.dest Processes.process_name | `drop_dm_object_name(Processes)` | sort - count - -[ESCU - Monitor Successful Backups] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Successful Backups -description = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.creation_date = 2017-08-24 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Netbackup"] -action.escu.eli5 = This search gives you the count and the hostname of all the systems that had a successful backup each day. -action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype="netbackup_logs" "Disk/Partition backup completed successfully." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE - -[ESCU - Monitor Unsuccessful Backups] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Unsuccessful Backups -description = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.creation_date = 2017-08-24 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Netbackup"] -action.escu.eli5 = This search gives you the count and hostname of all the systems that had a backup failure each day -action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype="netbackup_logs" "An error occurred, failed to backup." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE - -[ESCU - Previously Seen AWS Cross Account Activity] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Cross Account Activity -description = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. -action.escu.creation_date = 2018-06-04 -action.escu.modification_date = 2018-06-04 -action.escu.analytic_story = ["AWS Cross Account Activity"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we look for **AssumeRole** events where the requesting account is different from the requested account. The first and last times these events are seen are written to a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats count - -[ESCU - Previously Seen AWS Provisioning Activity Sources] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Provisioning Activity Sources -description = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = This search includes any event name that begins with "run" or "create," and then determines the first and last time these events were seen for each IP address that initiated the action. The search then consults a **GeoIP** database to determine the physical location of this IP address. This table outputs to a file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count - -[ESCU - Previously Seen AWS Regions] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Regions -description = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days -action.escu.creation_date = 2018-01-08 -action.escu.modification_date = 2018-01-08 -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we create a table of the first time (earliest) and most recent time (latest) that this region has been seen in our dataset, grouped by the value `awsRegion`. We only look for those events where an instance has been started. All of these entries will be added to the `previously_seen_aws_regions.csv` lookup file, which will act like a baseline for detections. Please validate the entries of region names in the lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count - -[ESCU - Previously Seen Cloud Compute Creations By User] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Creations By User -description = This search builds a table of previously seen users that have launched a cloud compute instance. -action.escu.creation_date = 2019-10-03 -action.escu.modification_date = 2018-03-15 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] -action.escu.eli5 = In this support search, we create a table of the earliest and latest time for each user that has created a cloud compute instance. -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_creations_by_user_input_filter` by Compute.src_user | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_creations_by_user | stats count - -[ESCU - Previously Seen Cloud Compute Images] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Images -description = This search builds a table of previously seen images used to launch cloud compute instances -action.escu.creation_date = 2019-10-03 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] -action.escu.eli5 = In this support search, we create a table of the earliest and latest time for each image id that has been seen. This table is then outputted to a csv file. -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_images | stats count - -[ESCU - Previously Seen Cloud Compute Instance Types] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Instance Types -description = This search builds a table of previously seen cloud compute instance types -action.escu.creation_date = 2019-10-03 -action.escu.modification_date = 2019-10-03 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] -action.escu.eli5 = In this support search, we create a table of the first time `firstTime` and most recent time `lastTime` that the compute type has been seen in our dataset. We only look for those events where an instance has been created. All of these entries will be added to the `previously_seen_cloud_compute_instance_types` lookup file, which will act as a baseline for detections. -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_instance_types | stats count - -[ESCU - Previously Seen Cloud Regions] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Regions -description = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days -action.escu.creation_date = 2019-10-02 -action.escu.modification_date = 2019-10-02 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = ["Cloud_Infrastructure"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS", "Azure", "GCP"] -action.escu.eli5 = In this support search, we create a table of the first time `firstTime` and most recent time `lastTime` that this region has been seen in our dataset, grouped by the region. We only look for those events where an instance has been started. All of these entries will be added to the `previously_seen_cloud_regions` lookup file, which will act like a baseline for detections. -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=start `previously_seen_cloud_regions_input_filter` by Compute.region | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_regions | stats count - -[ESCU - Previously Seen EC2 AMIs] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 AMIs -description = This search builds a table of previously seen AMIs used to launch EC2 instances -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["AWS Cryptomining"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we create a table of the earliest and latest time that a specific AMI ID has been seen. This table is then outputted to a csv file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | stats count - -[ESCU - Previously Seen EC2 Instance Types] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Instance Types -description = This search builds a table of previously seen EC2 instance types -action.escu.creation_date = 2018-03-08 -action.escu.modification_date = 2018-03-08 -action.escu.analytic_story = ["AWS Cryptomining"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we create a table of the earliest and latest time that a specific EC2 instance type has been seen. The instanceType request field is not required and defaults to m1.small, so any time this field is null, the search defaults the field to m1.small. This table is then outputted to a csv file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | stats count - -[ESCU - Previously Seen EC2 Launches By User] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Launches By User -description = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.creation_date = 2018-03-15 -action.escu.modification_date = 2018-03-15 -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we create a table of the earliest and latest times that an ARN has launched a EC2 instance. This table is then outputted to a csv file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count - -[ESCU - Previously Seen EC2 Modifications By User] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Modifications By User -description = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.creation_date = 2018-04-05 -action.escu.modification_date = 2018-04-05 -action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] -dispatch.earliest_time = -90d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we create a table of the earliest and latest times that an ARN has modified a EC2 instance. The list of APIs that modify an EC2 are defined in the `ec2_modification_api_calls` macro for ease of use. This table is then outputted to a file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail `ec2_modification_api_calls` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count - -[ESCU - Previously Seen Running Windows Services] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Running Windows Services -description = This collects the services that have been started across your entire enterprise. -action.escu.creation_date = 2018-07-20 -action.escu.modification_date = 2020-01-13 -action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = In this support search, we look for Windows system-event code that indicates a status change of a Windows service. In this specific log event, the `param1` field represents the "service_name" and the `param2` represents the action/status of the service. This search will create a table of the first and last time as particular Windows service was seen to be in the `running` status. -action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = eventtype=wineventlog_system signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services | stats count - -[ESCU - Previously seen API call per user roles in CloudTrail] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen API call per user roles in CloudTrail -description = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. -action.escu.creation_date = 2018-04-01 -action.escu.modification_date = 2018-04-16 -action.escu.analytic_story = ["AWS User Monitoring"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we are looking for successful API calls made by user roles within your AWS infrastructure. The intent is to create an initial baseline cache of names of the API calls per security role for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of user role and the name of the API call. It is also worth noting that the role of a particular user is parsed as "userName" in the CloudTrail logs. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles | stats count - -[ESCU - Previously seen S3 bucket access by remote IP] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen S3 bucket access by remote IP -description = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" -action.escu.creation_date = 2018-06-28 -action.escu.modification_date = 2018-06-28 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we are looking for successful S3 bucket-access attempts made from remote IPs. The intent is to create an initial baseline cache of remote IP addresses per bucket name for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of remote IP and the name of the S3 bucket. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:s3:accesslogs http_status=200 | stats earliest(_time) as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip | stats count - -[ESCU - Previously seen command line arguments] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen command line arguments -description = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. -action.escu.creation_date = 2018-04-09 -action.escu.modification_date = 2019-03-01 -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Hidden Cobra Malware", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] -action.escu.data_models = ["Endpoint"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = In this support search, we look for command-line arguments using the parameter `/c` to execute processes and create an initial baseline cache for the previous 30 days. This will include the earliest and latest times a particular command-line argument is seen in our dataset, grouped by the command-line value. -action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe AND Processes.process="* /c *" by Processes.process | `drop_dm_object_name(Processes)` - -[ESCU - Previously seen users in CloudTrail] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen users in CloudTrail -description = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. -action.escu.creation_date = 2018-02-23 -action.escu.modification_date = 2018-04-30 -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we look for console login events by a particular user and create an initial baseline cache for the previous 30 days, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. -action.escu.known_false_positives = n/a -action.escu.fields_required = ["user", "src"] -action.escu.entities = ["user", "src"] -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv | stats count - -[ESCU - Systems Ready for Spectre-Meltdown Windows Patch] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Systems Ready for Spectre-Meltdown Windows Patch -description = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. -action.escu.creation_date = 2018-01-08 -action.escu.modification_date = 2018-01-08 -action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] -action.escu.data_models = ["Change_Analysis"] -dispatch.earliest_time = -1d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] -action.escu.eli5 = This search looks to see if a registry key was created at `HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat`. It will tell you when it was created and, if possible, what process created it. -action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` - -[ESCU - Update previously seen users in CloudTrail] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Update previously seen users in CloudTrail -description = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. -action.escu.creation_date = 2019-04-25 -action.escu.modification_date = 2018-04-30 -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -dispatch.earliest_time = -60m@m -dispatch.latest_time = m@m -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = In this support search, we look for console login events by a particular user to update the baseline cache of users/arns making the accesses, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. -action.escu.known_false_positives = n/a -action.escu.fields_required = ["user", "src"] -action.escu.entities = ["user", "src"] -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv - -[ESCU - Windows Updates Install Failures] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Failures -description = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.creation_date = 2017-08-24 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = [] -action.escu.data_models = ["Updates"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = This search gives you the count of the number of systems that attempted and failed to install a Windows update each day. -action.escu.how_to_implement = You must be ingesting your Windows Update Logs -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=failure by _time span=1d - -[ESCU - Windows Updates Install Successes] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Successes -description = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.creation_date = 2017-08-24 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = [] -action.escu.data_models = ["Updates"] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Microsoft Windows"] -action.escu.eli5 = This search gives you the count and name of all the systems that had a successful update applied each day -action.escu.how_to_implement = You must be ingesting your Windows Update Logs -action.escu.known_false_positives = -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=installed by _time span=1d +### END ESCU RESPONSE TASKS ### ### USAGE DASHBOARD CONFIGURATIONS ### diff --git a/package/default/transforms.conf b/package/default/transforms.conf index e80f45becc..2e2a9467ec 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-04-17T19:06:18 UTC +# On Date: 2020-05-06T14:58:49 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index ace2c52f36..4d20e72ad4 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-04-17T19:06:18 UTC +# On Date: 2020-05-06T14:58:49 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -10,11 +10,11 @@ [analytic_story://AWS Cross Account Activity] category = Cloud Security last_updated = 2018-06-04 -version = 1.0 +version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - Previously Seen AWS Cross Account Activity"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["AWS Cross Account Activity From Previously Unseen Account"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -23,11 +23,11 @@ This Analytic Story includes searches that will help you monitor your AWS CloudT [analytic_story://AWS Cryptomining] category = Cloud Security last_updated = 2018-03-08 -version = 1.0 +version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started In Previously Unseen Region"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -37,22 +37,22 @@ This Analytic Story is focused on detecting suspicious new instances in your EC2 [analytic_story://AWS Network ACL Activity] category = Cloud Security last_updated = 2018-05-21 -version = 2.0 +version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Baseline of Network ACL Activity by ARN", "ESCU - Baseline of blocked outbound traffic from AWS"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["AWS Network Access Control List Deleted", "Detect Spike in blocked Outbound Traffic from your AWS", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in Network ACL Activity"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. [analytic_story://AWS Suspicious Provisioning Activities] category = Cloud Security last_updated = 2018-03-16 -version = 1.0 +version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Previously Seen AWS Provisioning Activity Sources"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region", "AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -60,11 +60,11 @@ This Analytic Story was designed to provide you with flexibility in the precisio [analytic_story://AWS User Monitoring] category = Cloud Security last_updated = 2018-03-12 -version = 1.0 +version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Baseline of API Calls per User ARN", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Create a list of approved AWS service accounts", "ESCU - Previously seen API call per user roles in CloudTrail"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect new API calls from user roles", "Detect Spike in Security Group Activity", "Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -74,22 +74,22 @@ The detection searches in this Analytic Story are designed to help you uncover A [analytic_story://Account Monitoring and Controls] category = Best Practices last_updated = 2017-09-06 -version = 1.0 +version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}, {"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Short Lived Windows Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint", "Identify New User Accounts"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. [analytic_story://Apache Struts Vulnerability] category = Vulnerability last_updated = 2018-12-06 -version = 1.0 +version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] -maintainers = [{"company": "Splunk", "email": "jhernandez@splunk.com", "name": "Jose Hernandez"}] -spec_version = 2 -searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -109,22 +109,22 @@ It can also be very helpful to examine various behaviors of the process of inter [analytic_story://Asset Tracking] category = Best Practices last_updated = 2017-09-13 -version = 1.0 +version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Count of assets by category"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect Unauthorized Assets by MAC address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. [analytic_story://Brand Monitoring] category = Abuse last_updated = 2017-12-19 -version = 1.0 +version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - DNSTwist Domain Names"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Monitor Web Traffic For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -133,11 +133,11 @@ Notable events will include IP addresses, URLs, and user data. Drilling down can [analytic_story://Cloud Cryptomining] category = Cloud Security last_updated = 2019-10-02 -version = 1.0 +version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Regions"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -147,11 +147,11 @@ This Analytic Story is focused on detecting suspicious new instances in your clo [analytic_story://ColdRoot MacOS RAT] category = Malware last_updated = 2019-01-09 -version = 1.0 +version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] -maintainers = [{"company": "Splunk", "email": "jhernandez@splunk.com", "name": "Jose Hernandez"}] -spec_version = 2 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src_ip", "ESCU - Investigate Web Activity From src_ip"] +maintainers = "Jose Hernandez, Splunk" +spec_version = 3 +searches = ["Processes Tapping Keyboard Events", "Osquery pack - ColdRoot detection"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -160,11 +160,11 @@ Searches in this Analytic Story leverage the capabilities of OSquery to address [analytic_story://Collection and Staging] category = Adversary Tactics last_updated = 2020-02-03 -version = 1.1 +version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Email files written outside of the Outlook directory", "Suspicious writes to windows Recycle Bin", "Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -173,11 +173,11 @@ Use the searches to detect and monitor suspicious behavior related to these acti [analytic_story://Command and Control] category = Adversary Tactics last_updated = 2018-06-01 -version = 1.0 +version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Long DNS TXT Record Response", "DNS Query Length Outliers - MLTK", "TOR Traffic", "Protocol or Port Mismatch", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Large Outbound ICMP Packets", "Prohibited Network Traffic Allowed", "Excessive DNS Failures"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -185,34 +185,34 @@ Because this communication is so critical for an adversary, they often use techn [analytic_story://Common Phishing Frameworks] category = Adversary Tactics last_updated = 2019-04-29 -version = 1.0 +version = 1 references = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] -maintainers = [{"company": "Splunk", "email": "research@splunk.com", "name": "Splunk Research Team"}] -spec_version = 2 -searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule", "ESCU - Get Certificate logs for a domain"] +maintainers = "Splunk Research Team, Splunk" +spec_version = 3 +searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. narrative = As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. -[analytic_story://Container Implantation Monitoring & Investigation] +[analytic_story://Container Implantation Monitoring and Investigation] category = Cloud Security -last_updated = -version = 1.0 +last_updated = 2020-02-20 +version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] -maintainers = [{"company": "Splunk", "email": "rsoto@splunk.com, rvaldez@splunk.com", "name": "Rod Soto, Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] +maintainers = "Rod Soto, Rico Valdez, Splunk" +spec_version = 3 +searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. [analytic_story://Credential Dumping] category = Adversary Tactics last_updated = 2020-02-04 -version = 3.0 +version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}, {"company": "Splunk", "email": "pbareiss@splunk.com", "name": "Patrick Bareiss"}] -spec_version = 2 -searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg.exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Detect Credential Dumping through LSASS access", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Access LSASS Memory for Dump Creation", "Create Remote Thread into LSASS", "Detect Mimikatz Using Loaded Images"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -221,11 +221,11 @@ The detection searches in this Analytic Story monitor access to the Local Securi [analytic_story://DHS Report TA18-074A] category = Malware last_updated = 2020-01-22 -version = 2.0 +version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Create local admin accounts using net.exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg.exe Process - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Processes launching netsh", "Registry Keys Used For Persistence", "Detect Outbound SMB Traffic", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Detect New Local Admin account", "Single Letter Process On Endpoint", "Detect PsExec With accepteula Flag", "Create local admin accounts using net exe", "First time seen command line argument", "Scheduled Task Name Used by Dragonfly Threat Actors", "Malicious PowerShell Process - Execution Policy Bypass"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -235,11 +235,11 @@ Suspicious activities--spikes in SMB traffic, processes that launch netsh (to mo [analytic_story://DNS Amplification Attacks] category = Abuse last_updated = 2016-09-13 -version = 1.0 +version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Large Volume of DNS ANY Queries"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -247,11 +247,11 @@ The search in this story can help you to detect if attackers are abusing your co [analytic_story://DNS Hijacking] category = Adversary Tactics last_updated = 2020-02-04 -version = 1.0 +version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Discover DNS records"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "DNS record changed"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -266,44 +266,44 @@ The searches in this Analytic Story help you detect and investigate activities t [analytic_story://Data Protection] category = Abuse last_updated = 2017-09-14 -version = 1.0 +version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Detection of DNS Tunnels"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. [analytic_story://Disabling Security Tools] category = Adversary Tactics last_updated = 2020-02-04 -version = 2.0 +version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg.exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Unload Sysmon Filter Driver", "Processes launching netsh", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). [analytic_story://Dynamic DNS] category = Malware last_updated = 2018-09-06 -version = 2.0 +version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src_ip"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. -[analytic_story://Emotet Malware (DHS Report TA18-201A)] +[analytic_story://Emotet Malware DHS Report TA18-201A ] category = Malware last_updated = 2020-01-27 -version = 1.0 +version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd.exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Add Prohibited Processes to Enterprise Security", "ESCU - Baseline of SMB Traffic - MLTK"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Prohibited Software On Endpoint", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Registry Keys Used For Persistence", "Detection of tools built by NirSoft", "Suspicious Email Attachment Extensions", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Rare Executables", "Email Attachments With Lots Of Spaces"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -312,11 +312,11 @@ The searches in this Analytic Story will help you find executables that are rare [analytic_story://Hidden Cobra Malware] category = Malware last_updated = 2020-01-22 -version = 2.0 +version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Create or delete windows shares using net.exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Create or delete windows shares using net exe", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Remote Desktop Network Traffic", "Detect Outbound SMB Traffic", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "First time seen command line argument", "Remote Desktop Process Running On System", "Suspicious File Write"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -326,22 +326,22 @@ Among other searches in this Analytic Story is a detection search that looks for [analytic_story://Host Redirection] category = Abuse last_updated = 2017-09-14 -version = 1.0 +version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Windows hosts file modification"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. [analytic_story://JBoss Vulnerability] category = Vulnerability last_updated = 2017-09-14 -version = 1.0 +version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -362,22 +362,22 @@ It can also be helpful to examine various behaviors of and the parent of the pro [analytic_story://Kubernetes Scanning Activity] category = Cloud Security last_updated = 2020-04-15 -version = 1.0 +version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] -maintainers = [{"company": "Splunk", "email": "rsoto@splunk.com", "name": "Rod Soto"}] -spec_version = 2 -searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src_ip", "ESCU - GCP Kubernetes activity by src_ip", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +maintainers = "Rod Soto, Splunk" +spec_version = 3 +searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. [analytic_story://Lateral Movement] category = Adversary Tactics last_updated = 2020-02-04 -version = 2.0 +version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks", "Schtasks scheduling job on remote system", "Remote Desktop Process Running On System"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -388,11 +388,11 @@ If there is evidence of lateral movement, it is imperative for analysts to colle [analytic_story://Malicious PowerShell] category = Adversary Tactics last_updated = 2017-08-23 -version = 4.0 +version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process With Obfuscation Techniques", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -408,22 +408,22 @@ In the event a system is suspected of having been compromised via a malicious we [analytic_story://Monitor Backup Solution] category = Best Practices last_updated = 2017-09-12 -version = 1.0 +version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. [analytic_story://Monitor for Unauthorized Software] category = Best Practices last_updated = 2017-09-15 -version = 1.0 +version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Add Prohibited Processes to Enterprise Security"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Prohibited Software On Endpoint"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -431,11 +431,11 @@ It is important to investigate any software identified as suspicious, in order t [analytic_story://Monitor for Updates] category = Best Practices last_updated = 2017-09-15 -version = 1.0 +version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["No Windows Updates in a time frame"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -444,11 +444,11 @@ Microsoft releases updates for Windows systems on a monthly cadence. They should [analytic_story://Netsh Abuse] category = Abuse last_updated = 2017-01-05 -version = 1.0 +version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Processes created by netsh", "Processes launching netsh"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -456,11 +456,11 @@ To get started, run the detection search to identify parent processes of `netsh. [analytic_story://Orangeworm Attack Group] category = Malware last_updated = 2020-01-22 -version = 2.0 +version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "First time seen command line argument"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -471,11 +471,11 @@ This Analytic Story is designed to help you detect and investigate suspicious ac [analytic_story://Phishing Payloads] category = Adversary Tactics last_updated = 2019-04-29 -version = 1.0 +version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] -maintainers = [{"company": "Splunk", "email": "research@splunk.com", "name": "Splunk Research Team"}] -spec_version = 2 -searches = ["ESCU - Detect Oulook.exe writing a .zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +maintainers = "Splunk Research Team, Splunk" +spec_version = 3 +searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -489,11 +489,11 @@ This Analytic Story focuses on detecting signs that a malicious payload has been [analytic_story://Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns] category = Adversary Tactics last_updated = 2020-01-22 -version = 1.0 +version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] -maintainers = [{"company": "iDefense", "email": "iDefense.IntelOps@accenture.com", "name": "iDefense Cyber Espionage Team"}] -spec_version = 2 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +maintainers = "iDefense Cyber Espionage Team, iDefense" +spec_version = 3 +searches = ["Registry Keys Used For Persistence", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -527,33 +527,33 @@ If behavioral searches included in this story yield positive hits, iDefense reco [analytic_story://Prohibited Traffic Allowed or Protocol Mismatch] category = Best Practices last_updated = 2017-09-11 -version = 1.0 +version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. [analytic_story://Ransomware] category = Malware last_updated = 2020-02-04 -version = 1.1 +version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Scheduled tasks used in BadRabbit ransomware", "Suspicious wevtutil Usage", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Registry Keys Used For Persistence", "Common Ransomware Notes", "Remote Process Instantiation via WMI", "USN Journal Deletion", "Common Ransomware Extensions", "System Processes Run From Unexpected Locations", "TOR Traffic", "Schtasks used for forcing a reboot", "Spike in File Writes", "Unusually Long Command Line", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Unusually Long Command Line - MLTK"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. -[analytic_story://Router & Infrastructure Security] +[analytic_story://Router and Infrastructure Security] category = Best Practices last_updated = 2017-09-12 -version = 1.0 +version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect New Login Attempts to Routers"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -561,11 +561,11 @@ This Analytic Story helps you gain a better understanding of how your network de [analytic_story://SQL Injection] category = Adversary Tactics last_updated = 2017-09-19 -version = 1.0 +version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["SQL Injection with Long URLs"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -573,11 +573,11 @@ This Analytic Story contains a search designed to identify attempts by attackers [analytic_story://SamSam Ransomware] category = Malware last_updated = 2018-12-13 -version = 1.0 +version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Add Prohibited Processes to Enterprise Security"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Detect malicious requests to exploit JBoss servers", "Prohibited Software On Endpoint", "Common Ransomware Notes", "Remote Desktop Network Traffic", "Common Ransomware Extensions", "Batch File Write to System32", "Spike in File Writes", "Samsam Test File Write", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Bruteforce", "File with Samsam Extension"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -589,22 +589,22 @@ This Analytic Story includes searches designed to help detect and investigate si [analytic_story://Spectre And Meltdown Vulnerabilities] category = Vulnerability last_updated = 2018-01-08 -version = 1.0 +version = 1 references = ["https://meltdownattack.com/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Spectre and Meltdown Vulnerable Systems"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. [analytic_story://Splunk Enterprise Vulnerability] category = Vulnerability last_updated = 2017-09-19 -version = 1.0 +version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Open Redirect in Splunk Web"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -620,11 +620,11 @@ It is important to ensure that your Splunk deployment is being kept up to date a [analytic_story://Splunk Enterprise Vulnerability CVE-2018-11409] category = Vulnerability last_updated = 2018-06-14 -version = 1.0 +version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src_ip", "ESCU - Investigate Web Activity From src_ip"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Splunk Enterprise Information Disclosure"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -634,33 +634,33 @@ A detection search within this Analytic Story looks for vulnerabilities describe [analytic_story://Suspicious AWS EC2 Activities] category = Cloud Security last_updated = 2018-02-09 -version = 1.0 +version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 Launches By User"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. [analytic_story://Suspicious AWS Login Activities] category = Cloud Security last_updated = 2019-05-01 -version = 1.0 +version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}, {"company": "Splunk", "email": "jbrewer@splunk.com", "name": "Jason Brewer"}] -spec_version = 2 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Previously seen users in CloudTrail", "ESCU - Update previously seen users in CloudTrail"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect new user AWS Console Login", "Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New Country"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. [analytic_story://Suspicious AWS S3 Activities] category = Cloud Security last_updated = 2018-07-24 -version = 2.0 +version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Baseline of S3 Bucket deletion activity by ARN", "ESCU - Previously seen S3 bucket access by remote IP"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets", "Detect S3 access from a new IP"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -669,11 +669,11 @@ Among things to look out for are S3 access from unfamiliar locations and by unfa [analytic_story://Suspicious AWS Traffic] category = Cloud Security last_updated = 2018-05-07 -version = 1.0 +version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Baseline of blocked outbound traffic from AWS"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -683,33 +683,33 @@ The searches in this Analytic Story will monitor your AWS network traffic for ev [analytic_story://Suspicious Command-Line Executions] category = Adversary Tactics last_updated = 2020-02-03 -version = 2.1 +version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd.exe - Rule", "ESCU - Detect Use of cmd.exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["System Processes Run From Unexpected Locations", "Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. [analytic_story://Suspicious DNS Traffic] category = Adversary Tactics last_updated = 2017-09-18 -version = 1.0 +version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Baseline of DNS Query Length - MLTK"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Excessive DNS Failures"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. [analytic_story://Suspicious Emails] category = Adversary Tactics last_updated = 2020-01-27 -version = 1.0 +version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - DNSTwist Domain Names"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -720,11 +720,11 @@ Once a phishing message has been detected, the next steps are to answer the foll [analytic_story://Suspicious MSHTA Activity] category = Adversary Tactics last_updated = 2020-02-03 -version = 1.1 +version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd.exe - Rule", "ESCU - Detect mshta.exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -733,11 +733,11 @@ The searches in this story help you detect and investigate suspicious activity t [analytic_story://Suspicious Okta Activity] category = Adversary Tactics last_updated = 2020-04-02 -version = 1.0 +version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Okta Account Lockout Events", "Okta Failed SSO Attempts", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta User Logins From Multiple Cities"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -746,11 +746,11 @@ With people moving quickly to adopt web-based applications and ways to manage th [analytic_story://Suspicious WMI Use] category = Adversary Tactics last_updated = 2018-10-23 -version = 2.0 +version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get User Information from Identity Table"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["WMI Permanent Event Subscription", "Remote Process Instantiation via WMI", "WMI Temporary Event Subscription", "Process Execution via WMI", "WMI Permanent Event Subscription - Sysmon", "Script Execution via WMI", "Remote WMI Command Attempt"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -759,11 +759,11 @@ In the event that unauthorized WMI execution occurs, it will be important for an [analytic_story://Suspicious Windows Registry Activities] category = Adversary Tactics last_updated = 2018-05-31 -version = 1.0 +version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg.exe used to hide files/directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Monitor Registry Keys for Print Monitors", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Suspicious Changes to File Associations"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -772,11 +772,11 @@ narrative = Attackers are developing increasingly sophisticated techniques for h [analytic_story://Unusual AWS EC2 Modifications] category = Cloud Security last_updated = 2018-04-09 -version = 1.0 +version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Previously Seen EC2 Modifications By User"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["EC2 Instance Modified With Previously Unseen User"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -784,11 +784,11 @@ narrative = A common attack technique is to infiltrate a cloud instance and make [analytic_story://Unusual Processes] category = Malware last_updated = 2020-02-04 -version = 2.1 +version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Baseline of Command Line Length - MLTK"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Uncommon Processes On Endpoint", "System Processes Run From Unexpected Locations", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Detect Rare Executables", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -797,22 +797,22 @@ In the event an unusual process is identified, it is imperative to better unders [analytic_story://Use of Cleartext Protocols] category = Best Practices last_updated = 2017-09-15 -version = 1.0 +version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] -maintainers = [{"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Protocols passing authentication in cleartext"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. [analytic_story://Web Fraud Detection] category = Abuse last_updated = 2018-10-08 -version = 1.0 +version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] -maintainers = [{"company": "Splunk", "email": "Mayhem@splunk.com", "name": "Jim Apger"}] -spec_version = 2 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session_id"] +maintainers = "Jim Apger, Splunk" +spec_version = 3 +searches = ["Web Fraud - Account Harvesting", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -824,22 +824,22 @@ Another search detects incidents wherein a single password is used across multip [analytic_story://Windows Defense Evasion Tactics] category = Adversary Tactics last_updated = 2018-05-31 -version = 1.0 +version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib.exe - Rule", "ESCU - Reg.exe used to hide files/directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg.exe Process - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Remote Registry Key modifications", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Suspicious Reg exe Process", "Hiding Files And Directories With Attrib exe"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. [analytic_story://Windows File Extension and Association Abuse] category = Malware last_updated = 2018-01-26 -version = 1.0 +version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Execution of File with Multiple Extensions", "Suspicious Changes to File Associations", "Execution of File With Spaces Before Extension"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -850,11 +850,11 @@ Run the searches in this story to detect and investigate suspicious behavior tha [analytic_story://Windows Log Manipulation] category = Adversary Tactics last_updated = 2017-09-12 -version = 2.0 +version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Suspicious wevtutil Usage", "Windows Event Log Cleared", "USN Journal Deletion", "Deleting Shadow Copies"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -862,33 +862,33 @@ The Analytic Story gives users two different ways to detect manipulation of Wind [analytic_story://Windows Persistence Techniques] category = Adversary Tactics last_updated = 2018-05-31 -version = 2.0 +version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}, {"company": "Splunk", "email": "bpatel@splunk.com", "name": "Bhavin Patel"}] -spec_version = 2 -searches = ["ESCU - Detect Path Interception By Creation Of program.exe - Rule", "ESCU - Hiding Files And Directories With Attrib.exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg.exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg.exe used to hide files/directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +maintainers = "Bhavin Patel, Splunk" +spec_version = 3 +searches = ["Monitor Registry Keys for Print Monitors", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters", "Reg exe used to hide files directories via registry keys", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Detect Path Interception By Creation Of program exe", "Reg exe Manipulating Windows Services Registry Keys"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. [analytic_story://Windows Privilege Escalation] category = Adversary Tactics last_updated = 2020-02-04 -version = 2.0 +version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] -maintainers = [{"company": "Splunk", "email": "davidd@splunk.com", "name": "David Dorsey"}] -spec_version = 2 -searches = ["ESCU - Child Processes of Spoolsv.exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +maintainers = "David Dorsey, Splunk" +spec_version = 3 +searches = ["Child Processes of Spoolsv exe", "Registry Keys Used For Privilege Escalation", "Overwriting Accessibility Binaries", "Uncommon Processes On Endpoint"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. [analytic_story://Windows Service Abuse] category = Malware last_updated = 2017-11-02 -version = 3.0 +version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] -maintainers = [{"company": "Splunk", "email": "rvaldez@splunk.com", "name": "Rico Valdez"}] -spec_version = 2 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg.exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc.exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Previously Seen Running Windows Services"] +maintainers = "Rico Valdez, Splunk" +spec_version = 3 +searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. @@ -898,368 +898,359 @@ narrative = The Windows operating system uses a services architecture to allow f [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from cities that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +explanation = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new city is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each country. It returns only those events from countries that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +explanation = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new country is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from IP addresses that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +explanation = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new IP address is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from regions that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. +explanation = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new region is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your region, there should be few false positives. If you are located in regions where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = This search\ -1. Retrieves the **AssumeRole** event\ -1. Verifies that the log entry contains a value for the account ID of the requesting account\ -1. Ensures that the requesting account ID does not match the account ID of the requested account\ -1. Pulls in the previously seen requesting and requested account IDs\ -1. Splits up and executes multiple search paths at the same.\ -1. The first path determines the **firstTime** and **lastTime** entries for the cache file\ -1. Outputs the data to the cache file.\ -1. Creates a conditional statement that is always false (both because we don't want these values to exit the search pipeline and because we think we're clever).The second pipeline adds the **firstTime** and **lastTime** entries to search results. Next, it filters out any account pairs that haven't been seen for the first time within the last hour. The `isnotnull(_time)` will remove the entries from the cache file.\ -The search finishes by gathering the data that it will display to the user. +explanation = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} +annotations = {"analytics_story": ["AWS Cross Account Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"], "security_domain": "network"} known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - AWS Network Access Control List Created with All Open Ports - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = A network access control list (ACL) is a layer of security for your VPC that acts as a firewall for controlling traffic in and out of one or more subnets. Network ACLs with all open ports have a larger attack surface. This search looks for events within your CloudTrail logs to check if there were any Network ACLs created with ports ranging from 1024 to 65525. This search will create a table comprised of AWS account id, src, user and all parameters of the request made by the user and the server response. +explanation = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail inputs. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - AWS Network Access Control List Deleted - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The search looks for CloudTrail events to detect whether any network ACLs have been deleted and gives you values of error messages and error codes (if any), user details, user source IP, the user who initiated this request, and the name of the event. +explanation = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = It's possible that a user has legitimately deleted a network ACL. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Launched by User - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events where an instance is successfully launched by a particular user. Since we want to detect a high number of instances launched within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances launched by a particular user, as well as the average and standard deviation values. Assign a `threshold_value` in the search. Start with 3 (but it will likely need to be tweaked for your environment). The `eval` function will set the outlier 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. For your reference, we then keep only the outliers and calculate the number of standard deviations away the value is from the average. +explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events where an instance is successfully launched by a particular user. Since we want to detect a high number of instances launched within a short period, we create event buckets for 10-minute windows. We then compare the total number of instances launched by a particular user against the saved baseline data in the model ec2_excessive_runinstances_v1. +explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Terminated by User - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events where an instance is successfully terminated by a particular user. Since we want to detect a high number of instances terminated within a short period, we create event buckets for 10-minute windows. We then calculate the total number of instances terminated by a particular user, as well as the average- and standard-deviation values. Assign a `threshold_value` in the search. Try starting with 3 (but it will likely need to be tweaked for your environment). The `eval` function will set the outlier to 1 if the number of instances is greater than the average number of instances terminated, added to the multiplied value of threshold and standard deviation. We then filter out outliers with a value of 1 and show only those instance-termination events that happened within the previous 10 minutes. +explanation = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events where an instance is successfully terminated by a particular user. Since we want to detect a high number of instances terminated within a short period, we create event buckets for 10-minute windows. We then compare the total number of instances terminated by a particular user against the saved baseline data in the model ec2_excessive_terminateinstances_v1. +explanation = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Access LSASS Memory for Dump Creation - Rule] type = detection -asset_type = Windows -confidence = high -explanation = dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump. +asset_type = +confidence = medium +explanation = Detect memory dumping of the LSASS process. how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Amazon EKS Kubernetes Pod scan detection - Rule] type = detection -asset_type = Amazon EKS Kubernetes cluster Pod +asset_type = confidence = medium -explanation = In this search we can detect unauthenticated web requests against an EKS cluster Pod, by looking at k8s authentication data, user agent and source IPs and API direct request. +explanation = This search provides detection information on unauthenticated requests against Kubernetes' Pods API how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. -annotations = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery"], "mitre_technique_id": ["T1190"]} +annotations = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster Pod", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Amazon EKS Kubernetes cluster scan detection - Rule] type = detection -asset_type = Amazon EKS Kubernetes cluster -confidence = high -explanation = In this search we can detect unauthenticated web requests against an EKS cluster, by looking at k8s authentication data, user agent and source IPs. +asset_type = +confidence = medium +explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs. -annotations = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery"], "mitre_technique_id": ["T1190"]} +annotations = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Attempt To Add Certificate To Untrusted Store - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = Attackers will often attempt to disable security tools in order to evade detection. It is also possible for end users to attempt to disable anti-virus or other security tools to circumvent restrictions they encounter while trying to execute other programs. One way malware may accomplish this is by adding the legitimate certificate used to sign the security software to the untrusted certificate store. This will cause the system to no longer trust the software signed with this certificate and disallow it from executing. This search simply looks for the execution of **certutil.exe** with the parameters `-addcert` and `disallowed`, which add a certification to the "untrusted" certificate store. +asset_type = +confidence = medium +explanation = Attempt to add a certificate to the untrusted certificate store how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Disabling Security Tools"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks for changes of the ExecutionPolicy in the registry. The ExecutionPolicy is a safety feature that controls the conditions under which PowerShell loads configuration files and runs scripts. Usually, the ExecutionPolicy is "Restricted" for Windows clients and "RemoteSigned" for Windows Servers, allowing only certain scripts to run. This search detects when an attacker sets the ExecutionPolicy to "Unrestricted" or "Bypass." +asset_type = +confidence = medium +explanation = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "mitre_technique_id": ["T1086", "T1064"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping", "Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Attempt To Stop Security Service - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks for the processes **net.exe** and **sc.exe** with a parameter of `"stop"`. It then searches a list of security-related services included in a lookup file for matches on the command line. Results are subsequently returned in table format. The included lookup file can be modified to update the services to monitor. +asset_type = +confidence = medium +explanation = This search looks for attempts to stop security-related services on the endpoint. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Disabling Security Tools"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none -[savedsearch://ESCU - Attempted Credential Dump From Registry via Reg.exe - Rule] +[savedsearch://ESCU - Attempted Credential Dump From Registry via Reg exe - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks for the process reg.exe with the "save" parameter, which specifies a binary export from the registry. In addition, it looks for the keys that contain the hashed credentials, which attackers may retrieve and use for brute-force attacks in order to harvest legitimate credentials. +asset_type = +confidence = medium +explanation = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = None identified. -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - Batch File Write to System32 - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at file modifications across your hosts, as well as for evidence of batch files being written to paths that include "system32." This activity is consistent with some SamSam attacks and is, in general, suspicious. -how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] - -[savedsearch://ESCU - Child Processes of Spoolsv.exe - Rule] -type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for child processes of spoolsv.exe, which is associated with the Print Spooler service on Windows. Children of this process typically run under the SYSTEM context. This search should address the POC developed for the Windows local-privilege-escalation exploit announced in September of 2018. The associated vulnerability was assigned CVE-2018-8440. More information is available at https://doublepulsar.com/task-scheduler-alpc-exploit-high-level-analysis-ff08cda6ad4f. +explanation = The search looks for a batch file (.bat) written to the Windows system directory tree. +how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. +annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. +providing_technologies = none + +[savedsearch://ESCU - Child Processes of Spoolsv exe - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. -annotations = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Privilege Escalation", "Exploitation for Privilege Escalation"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Clients Connecting to Multiple DNS Servers - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = DNS Queries with multiple DNS servers from a single client is unusual and may be indicative of malicious activity. This search works by performing a count by the source of the distinct destinations for the DNS traffic. The search uses the `Network_Resolution` data model. +explanation = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Exfiltration Over Alternative Protocol"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} +annotations = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"], "security_domain": "network"} known_false_positives = It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule] type = detection -asset_type = Cloud Compute Instance +asset_type = confidence = medium -explanation = For each user, the search returns the first time seen, last time seen, and the systems. It then appends the historical data and merges it into the data. The search then splits and outputs the updated times for each user back to the lookup file and then clears out any output. The other part of the search limits the results to when the user was seen for the first time within the previous 70 minutes. It then displays the new user, the instances created by that user, and the associated times. +explanation = This search looks for cloud compute instances created by users who have not created them before. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. -providing_technologies = ["AWS", "Azure", "GCP"] +providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule] type = detection -asset_type = Cloud Compute Instance +asset_type = confidence = medium -explanation = For each image ID and user, the search returns the first time seen, last time seen, and the systems. It then appends the historical data and merges it into the data. The search then splits and outputs the updated times for each image back to the lookup file and clears out any output. The other part of the search limits the results to when the image was seen for the first time within the previous 70 minutes. It then displays the new image, the instances created using it, the user who created it, and the associated times. +explanation = This search looks for cloud compute instances being created with previously unseen image IDs. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. -providing_technologies = ["AWS", "Azure", "GCP"] +providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule] type = detection -asset_type = Cloud Compute Instance +asset_type = confidence = medium -explanation = For each instance type and user, the search returns the first time seen, last time seen, and the system. It then appends the historical data and merges it into the data. The search then splits and outputs the updated times for each instance type back to the lookup file and clears out any output. The other part of the search limits the results to when the instance type was seen for the first time within the previous 70 minutes. It then displays the new instance type, the instances created using it, the user who created them, and the times associated. +explanation = Find EC2 instances being created with previously unseen instance types. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. -providing_technologies = ["AWS", "Azure", "GCP"] +providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule] type = detection -asset_type = Cloud Compute Instance +asset_type = confidence = medium -explanation = In this search, we query cloud infrastructure compute logs to look for events that indicate that an instance was started in a particular region. Using the \"previously_seen_cloud_regions\" lookup file created using the support search, we compare the region where this instance was started to all previously observed regions. The \"eval\" and \"if\" functions determine that the earliest times seen for this region and instance were within the last day. If a new region is detected, it will alert you with \"Instance Started in a New Region.\" However, this region will be added to the list in \"previously_seen_cloud_regions.\" +explanation = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. -annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. -providing_technologies = ["AWS", "Azure", "GCP"] +providing_technologies = none [savedsearch://ESCU - Common Ransomware Extensions - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at file modifications across your hosts and identifies files with extensions that are commonly associated with the encrypted files generated by ransomware. +asset_type = +confidence = medium +explanation = The search looks for file modifications with extensions commonly used by Ransomware how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ 1. \ 1. **Label:** File Extension, **Field:** file_extension\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Common Ransomware Notes - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at file modifications in the Change Analysis data model. It checks modified file names against an included lookup file, which contains the names of note files left behind by ransomware (to inform the victim how they can pay the ransom and retrieve their files). The search returns a list of files with matching names. +asset_type = +confidence = medium +explanation = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Create Remote Thread into LSASS - Rule] type = detection -asset_type = Windows -confidence = high -explanation = This search detects the creation of a remote thread into LSASS (Local Security Authority Subsystem Service). This technique can be used by attackers to inject code into LSASS and dump the memory in order to obtain credentials. +asset_type = +confidence = medium +explanation = Detect remote thread creation into LSASS consistent with credential dumping. how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none -[savedsearch://ESCU - Create local admin accounts using net.exe - Rule] +[savedsearch://ESCU - Create local admin accounts using net exe - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Net.exe is a built-in Windows command-line tool that can be used to add, display, or modify user accounts. While Microsoft administrators use this tool to manage user groups, threat actors often leverage it to create local admin accounts to maintain persistence. In this search, we are looking for the execution of process net.exe with command-line parameters such as `localgroup`, `add`, or `user` that may correspond to the creation of local admin accounts or setting user/group properties. +explanation = This search looks for the creation of local administrator accounts using net.exe. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Administrators often leverage net.exe to create admin accounts. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none -[savedsearch://ESCU - Create or delete windows shares using net.exe - Rule] +[savedsearch://ESCU - Create or delete windows shares using net exe - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = In this search, we are looking for the command-line execution of net.exe with command-line parameters such as `net`, `share`, or `delete` that may correspond to the creation/deletion of windows drive shares. Net.exe is a built-in command-line tool on Windows that can be used to create, delete, and manage shared resources on the computer, both locally and remotely. Though this tool is used by Microsoft administrators to manage the network shares, attackers also leverage it to create and delete (hidden) file shares by appending "$" after the name of the share. Since the creation/deletion of hidden shares is a special case of detecting share creation/deletion we have commented out the regex that adds that additional matching criteria. If only hidden share detection is desired add `| regex process="\S+[$]"` before the last pipe in the search. +explanation = This search looks for the creation or deletion of hidden shares using net.exe. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement"], "mitre_technique_id": ["T1077", "T1126"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Creation of Shadow Copy - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = The ntds.dit file contains the Active Directory (AD) database. This file can't be copied directly. That's why attackers will first create a shadow copy before exfiltrating the file. This search detects the creation of a shadow copy using Ntdsutil, Vssadmin, or Wmic. +asset_type = +confidence = medium +explanation = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - Creation of Shadow Copy with wmic and powershell - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The ntds.dit file contains the Active Directory (AD) database. This file can't be copied directly. That's why attackers create a shadow copy before exfiltrating the file. This search detects the creation of a shadow copy using wmic, which is executed by Powershell. +explanation = This search detects the use of wmic and Powershell to create a shadow copy. how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = The file system, security, sam and ntds.dit containing sensitive credentials. Normally, the files can't be easily copied. But it is possible by creating first a shadow copy and then copy it from the shadow copy. This search will detect this attack of credential dumping. +asset_type = +confidence = medium +explanation = This search detects credential dumping using copy command from a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = unknown -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - Credential Dumping via Symlink to Shadow Copy - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = The file system, security, sam, and ntds.dit containing sensitive credentials. Normally, the files can't be easily copied, but it can be done by creating shadow copy and then create a symlink to the shadow copy. This search will detect this attack of credential dumping. +asset_type = +confidence = medium +explanation = This search detects the creation of a symlink to a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = unknown -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - DNS Query Length Outliers - MLTK - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers often use random, long domain names for components of their attack infrastructure. This search leverages the probability distribution function algorithm provided by the Machine Learning Toolkit (MLTK) to identify outliers in the length of the DNS query for each record type observed. The companion search "Baseline of DNS Query Length - MLTK" creates a machine-learning (ML) model built over the historical data used by this search. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +explanation = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ 1. \ @@ -1267,59 +1258,59 @@ This search produces fields (`query`,`query_length`,`count`) that are not yet su 1. \ 1. **Label:** Number of events, **Field:** count\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "mitre_technique_id": ["T1071"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - DNS Query Length With High Standard Deviation - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers often use random, long domain names for their attack infrastructure. This search looks at all the queries observed over the search time frame, and identifies any domains being resolved with names that are greater that 2 times the standard deviation. +explanation = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. -annotations = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "mitre_technique_id": ["T1071"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = It's possible there can be long domain names that are legitimate. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Clients should be resolving their DNS requests via a trusted DNS server. This search will identify DNS queries being sent to unauthorized DNS servers by comparing the destination and source of the traffic with assets marked as DNS servers. +explanation = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. -annotations = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Exfiltration", "Defense Evasion"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - DNS record changed - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Using a lookup `discover_dns_records` generated by support search "Discover DNS records" we check previous network traffic and make sure the responses have not changed. +explanation = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ **Splunk>Phantom Playbook Integration**\ If Splunk>Phantom is also configured in your environment, a Playbook called "DNS Hijack Enrichment" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\ -annotations = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Exfiltration", "Command and Control", "Defense Evasion"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Deleting Shadow Copies - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for execution of vssadmin or wmic with both the "delete" and "shadows" parameters passed on the command-line. The two arguments are searched for separately because we can't predict the number of spaces between the words on the command-line. The search will return the number of times this activity was observed, and the times of the first and last event. +explanation = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Impact"], "mitre_technique_id": ["T1490"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Detect API activity from users without MFA - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs and specifically look for events where the multi factor authentication context of the user's session is false which basically means, that the user does not have MFA enabled on AWS. We then filter out all the known AWS service accounts since service accounts typically do not have MFA enabled. The search then creates a table of the first and last time a user without MFA was detected, the values and count of the API calls made, the type of user identity, ARN and the name of the user. +explanation = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ 1. \ @@ -1327,15 +1318,15 @@ This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) 1. \ 1. **Label:** AWS User Type, **Field:** userIdentity.type\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Execution"], "nist": ["DE.DP", "PR.AC"]} +annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"], "security_domain": "network"} known_false_positives = Many service accounts configured within an AWS infrastructure do not have multi factor authentication enabled. Please ignore the service accounts, if triggered and instead add them to the aws_service_accounts.csv file to fine tune the detection. It is also possible that the search detects users in your environment using Single Sign-On systems, since the MFA is not handled by AWS. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect AWS API Activities From Unapproved Accounts - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we are looking for successful API calls via CloudTrail. We filter out events triggered by known users listed in the `identity_lookup_expanded` lookup file and the service accounts. Once filtered out, we output a table with the event names and count, as well as the first and last time a specific user or service is detected. +explanation = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ 1. \ @@ -1343,143 +1334,143 @@ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not ye 1. \ 1. **Label:** Last Time, **Field:** lastTime\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} +annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"], "security_domain": "access"} known_false_positives = It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` file. If the user is a legitimate service account, update the `aws_service_accounts.csv` table with that entry. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect AWS Console Login by User from New City - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new city and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and city combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect AWS Console Login by User from New Country - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new country and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and country combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect AWS Console Login by User from New Region - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console from a new region and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen ARN and region combinations logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect Activity Related to Pass the Hash Attacks - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = To detect pass the hash activity, we look at all events with event code 4624 that specify a logon type 3 (network logons) for remote pass the hash attacks and logon type 9 for local pass the hash attacks. The search also filters out events with an account name of 'Anonymous' to help reduce false positives. +asset_type = +confidence = medium +explanation = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Pass the Hash"], "mitre_technique_id": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "access"} known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect Credential Dumping through LSASS access - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search looks for LSASS access using Credential Dumping tools by detecting Process access with Sysmon logs (EventCode 10), TargetImage lsass.exe and GrantedAccess 0x1410 or 0x1010. This will for example detect the use of sekurlsa::logonpasswords in Mimikatz. +explanation = This search looks for reading lsass memory consistent with credential dumping. how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "endpoint"} known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search gathers all the answers to each system's DNS query, then filters for queries that have subdomains extracted from the EvilGinx toolkit. It will then run a regex to extract `legit_domains` from the query and remove that from the detection if it is listed in the `legit_domains.csv` +asset_type = +confidence = medium +explanation = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ **Splunk>Phantom Playbook Integration**\ If Splunk>Phantom is also configured in your environment, a Playbook called `Lets Encrypt Domain Investigate` can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook link:`https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/`).\ -annotations = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["Spearphishing Link", "Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Common Phishing Frameworks"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = If a known good domain is not listed in the legit_domains.csv file, then the search could give you false postives. Please update that lookup file to filter out DNS requests to legitimate domains. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Detect Excessive Account Lockouts From Endpoint - Rule] type = detection -asset_type = Windows -confidence = low -explanation = This search queries the `Change.All_Changes` datamodel under the nodename is `Account_Management` , where the result is "lockout", which indicates that an account has been locked out. It then counts the number of times an endpoint has caused an account lockout within a four hour window and displays those hosts with a count greater than or equal to five. +asset_type = +confidence = medium +explanation = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ **Splunk>Phantom Playbook Integration**\ If Splunk>Phantom is also configured in your environment, a Playbook called "Excessive Account Lockouts Enrichment and Response" can be configured to run when any results are found by this detection search. The Playbook executes the Contextual and Investigative searches in this Story, conducts additional information gathering on Windows endpoints, and takes a response action to shut down the affected endpoint. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook Link:`https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\ -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Initial Access", "Valid Accounts"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} known_false_positives = It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect Excessive User Account Lockouts - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search queries the `Change.All_Changes` datamodel under the nodename is `Account_Management` , where the result is "lockout", which indicates that an account has been locked out. It then counts the number of times a user has caused an account lockout within a four hour window and displays those users with a count greater than or equal to five. +explanation = This search detects user accounts that have been locked out a relatively high number of times in a short period. how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Initial Access", "Valid Accounts"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect Large Outbound ICMP Packets - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search works by looking at fields in the Network_Traffic data model, which is populated by various firewalls and passive networking monitoring technologies. Specifically, the search looks for ICMP packets larger than 1,000 bytes with a destination that is external to your organization. +explanation = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Standard Non-Application Layer Protocol"], "nist": ["DE.AE"]} +annotations = {"analytics_story": ["Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1095"], "nist": ["DE.AE"], "security_domain": "network"} known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. -providing_technologies = ["Bro", "Splunk Stream", "Palo Alto Firewall"] +providing_technologies = none [savedsearch://ESCU - Detect Long DNS TXT Record Response - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search uses the Network_Resolution data model and gathers all the answers to DNS queries for TXT records. The query then looks at the answer section and calculates the length of the answer. The search will then return information for those responses that exceed 100 characters in length. +explanation = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. -annotations = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Detect Mimikatz Using Loaded Images - Rule] type = detection -asset_type = Windows -confidence = high -explanation = This search looks for loaded images (dll) unique for Mimikatz using Sysmon EventCode 7 logs. +asset_type = +confidence = medium +explanation = This search looks for reading loaded Images unique to credential dumping with Mimikatz. how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.AE", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search looks for Windows Event Code(signature_id) 4703 (token right adjusted), where the process requesting the token change is PowerShell.exe and the requested privilege is "SeDebugPrivilege". This is consistent with the use of PowerShell to execute Mimikatz using sekurlsa::logonpasswords. It will return the host where the activity occurred, the process and associated id, the enabled privilege, and the message in the event. +explanation = This search looks for PowerShell requesting privileges consistent with credential dumping. how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} +annotations = {"asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "access"} known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect New Local Admin account - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search looks for Windows Event Code 4720 (account creation) and 4732 (account added to a security-enabled local group), where the group name is "Administrators", and determines whether they are generated for the same user's Security ID within three hours of each other. It will return the user account that was added, the Security ID, the group name to which the user was added, the account name of the user who initiated the action, and the subsequent message returned. +explanation = This search looks for newly created accounts that have been elevated to local administrators. how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ 1. \ @@ -1487,116 +1478,105 @@ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not 1. \ 1. **Label:** Message, **Field:** Message\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Valid Accounts", "Defense Evasion", "Persistence"], "nist": ["PR.AC", "DE.CM"]} +annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Windows", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1078"], "nist": ["PR.AC", "DE.CM"], "security_domain": "access"} known_false_positives = The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not "Administrators", this search may generate an excessive number of false positives -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect New Login Attempts to Routers - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers will often attempt to compromise network devices such as routers for a variety of nefarious purposes, including modifying VPN settings or re-routing network traffic. Typically, only a relatively small number of user accounts log into these devices on a regular basis. This search identifies 'new' connections to your routers by checking to see if a similar login was made in the last 30 days. Routers are identified by checking the IP address against those categorized as a "router" in the ES assets and identity framework. +explanation = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Router and Infrastructure Security"], "asset_type": "Endpoint", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"], "security_domain": "network"} known_false_positives = Legitimate router connections may appear as new connections -providing_technologies = ["Active Directory", "Palo Alto Firewall"] +providing_technologies = none [savedsearch://ESCU - Detect New Open S3 buckets - Rule] type = detection -asset_type = S3 Bucket +asset_type = confidence = medium -explanation = This search queries CloudTrail logs for events with S3 bucket access controls given to the "All Users" group, which allows anyone in the world access to the resource. This search generates a table displaying the time when the bucket was made public, the permission of the S3 bucket, the bucket name, and the ARN of the user who created the bucket. +explanation = This search looks for CloudTrail events where a user has created an open/public S3 bucket. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Initial Access", "Exfiltration"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. -providing_technologies = ["AWS"] +providing_technologies = none -[savedsearch://ESCU - Detect Oulook.exe writing a .zip file - Rule] -type = detection -asset_type = Endpoint -confidence = high -explanation = In this search, we are essentially trying to detect if outlook.exe is writing a `.zip` file to the disk. The way this search would run is, it will execute the the subsearch first which looks for all .zip files being written to the disk and outputs a crucial field "process_id", that we use the main search to check if that process\_id belongs to a process_name of outlook.exe. The search uses a join command to essentially give you an end result of the first and last time that zip file was written by outlook.exe, the dest and user logged on the system, the hash value and the complete path to the zip file on disk -how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Initial Access", "Spearphishing Attachment"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] - -[savedsearch://ESCU - Detect Outbound SMB Traffic - Rule] -type = detection -asset_type = Endpoint -confidence = medium -explanation = In this search, we are looking for the network connections that were not blocked by the firewall and that are destined for destination port 139 or 445. We then filter out events that have Classless Inter-Domain Routing (CIDR) blocks categorized as internal in the `assets_by_cidr.csv` lookup file which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. Since we are only looking for outbound traffic from the hosts made to the Internet, we filter out traffic whose destination IP address is private. -how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Commonly Used Port", "Credential Access", "Lateral Movement"], "mitre_technique_id": ["T1110", "T1135", "T1210"], "nist": ["DE.CM"]} -known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. -providing_technologies = ["Bro", "Splunk Stream"] - -[savedsearch://ESCU - Detect Path Interception By Creation Of program.exe - Rule] +[savedsearch://ESCU - Detect Oulook exe writing a zip file - Rule] type = detection asset_type = confidence = medium -explanation = This search queries the Endpoint file-system data model node to list out all the values of destination machines, as well as the values of file hashes and file paths that have the file "program.exe" in the C: drive. Path interception occurs when an executable is placed in a specific path so that it is executed by an application instead of by the intended target. In this case, applications vulnerable to path interception (because of unquoted service paths with spaces in Windows registry) allow attackers to execute maliciously crafted program.exes. -how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Privilege Escalation", "Persistence"], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Tanium", "Ziften"] +explanation = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. +how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. +annotations = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. +providing_technologies = none -[savedsearch://ESCU - Detect Prohibited Applications Spawning cmd.exe - Rule] +[savedsearch://ESCU - Detect Outbound SMB Traffic - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Obtaining access to the Command-Line Interface (CLI) is typically a primary attacker goal. Once an attacker has obtained the ability to execute code on a target system, they will often further manipulate the system via commands passed to the CLI. It is also unusual for many applications to spawn a command shell during normal operation, while it is often observed if an application has been compromised in some way. As such, it is often beneficial to look for cmd.exe being executed by processes that are often targeted for exploitation, or that would not spawn cmd.exe in any other circumstances. A lookup file is provided to easily modify the processes that are being watched for execution of cmd.exe. +explanation = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. +how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model +annotations = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. +providing_technologies = none + +[savedsearch://ESCU - Detect Path Interception By Creation Of program exe - Rule] +type = detection +asset_type = +confidence = medium +explanation = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. +how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. +annotations = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. +providing_technologies = none + +[savedsearch://ESCU - Detect Prohibited Applications Spawning cmd exe - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution", "Command-Line Interface"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Detect PsExec With accepteula Flag - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = In this search, we are looking for the PsExec process with `accepteula` on the command line. +explanation = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["DHS Report TA18-074A", "SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - Detect Rare Executables - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search first executes the subsearch and counts all of your processes to determine the 10 most rare (the limit set is 10). It then filters out whitelisted processes and outputs the first and last time a rare process was encountered, the destination where the process is running, the count of occurrences, and the users who initiated the processes. +explanation = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. -annotations = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} +annotations = {"analytics_story": ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Detect S3 access from a new IP - Rule] type = detection -asset_type = S3 Bucket -confidence = low -explanation = Here the subsearch executes first and returns all successful S3 bucket-access attempts (HTTP code "200") within the last hour. It groups the results by the earliest and latest times it has seen a remote IP accessing a particular bucket. It appends this information to the historical data from the lookup file and then recalculates the `firstTime` and `lastTime` field for each remote IP accessing an S3 bucket. Next, it returns only those remote IP addresses that have first been seen accessing a specific bucket within the past hour. This is combined with the main search to return the time, bucket name, source IP, city, and country operations performed, as well as the requested URI of the resource +asset_type = +confidence = medium +explanation = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access logs' inputs. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. -annotations = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Exfiltration"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect Spike in AWS API Activity - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = This search and its corresponding subsearch run through a series of steps, as per the following: \ -1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls.\ -1. Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.\ -1. Counts the number of API calls per ARN.\ -1. Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command. \ -1. Renames `apiCalls` as `latestCount`.\ -1. Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.\ -1. Updates the cache file with the latest results.\ -1. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filters out anything that it determines is not a spike and returns the list of ARNs to the main search. The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +explanation = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ 1. \ @@ -1604,137 +1584,95 @@ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) 1. \ 1. **Label:** Unique API Calls, **Field:** uniqueApisCalled\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} known_false_positives = -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect Spike in Network ACL Activity - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = This search and its corresponding subsearch run through the following series of steps: \ -1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for creating/modifying/replacing network Access Control Lists (ACLs).\ -1. Kick off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.\ -1. Count the number of API calls per Amazon Resource Name (ARN).\ -1. Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drop the count from the latest hour, since it is not necessary, and merge the rest of the data with the results of the stats command. \ -1. Rename `apiCalls` as `latestCount`.\ -1. Calculate the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. They do the same for the standard deviation--weighting the past more heavily than the current.\ -1. Update the cache file with the latest results.\ -1. Set the minimum threshold for the number of data points and set the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filter out anything that it determines is not a spike and return the list of ARNs to the main search. The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +explanation = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. -annotations = {"cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Exfiltration"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +annotations = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect Spike in S3 Bucket deletion - Rule] type = detection -asset_type = S3 Bucket +asset_type = confidence = medium -explanation = This search and its corresponding subsearch run through the following series of steps: \ -1. Retrieve all the AWS CloudTrail log entries that have recorded AWS API calls specifically for deletion of S3 buckets.\ -1. Kick off a subsearch that retrieves the same data and pulls out and converts the ARN into a more friendly format.\ -1. Count the number of API calls per ARN.\ -1. Load the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drop the count from the latest hour, since it is unnecessary, and merge the rest of the data with the results of the `stats` command. \ -1. Rename `apiCalls` as `latestCount`.\ -1. Calculate the new average value for each ARN with the latest count, weighting the past more heavily than the current hour. It does the same for the standard deviation—weighting the past more heavily than the current.\ -1. Update the cache file with the latest results.\ -1. Set the minimum threshold for the number of data points and the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Make a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and if the count is a sufficient number of standard deviations away from the average.\ -1. Filter out anything that it determines is not a spike and returns the list of ARNs to the main search. The main search subsequently gets the names of the deleted S3 buckets, the number of unique API calls, and the total number of API calls for each of these user ARNs. +explanation = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +annotations = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect Spike in Security Group Activity - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = This search and its corresponding subsearch run through the following series of steps: \ -1. Retrieves all the AWS CloudTrail log entries that have recorded AWS API calls specifically for security groups.\ -1. Kicks off a subsearch that retrieves the same data and pulls out the ARN into a more friendly format.\ -1. Counts the number of API calls per ARN.\ -1. Loads the cache file that contains the number of data points, the count from the latest hour, the API call average, and the standard deviation for each ARN.\ -1. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command. \ -1. Renames `apiCalls` as `latestCount`.\ -1. Calculates the new average value for each ARN with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation--weighting the past more heavily than the current.\ -1. Updates the cache file with the latest results.\ -1. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filters out anything that it determines is not a spike and returns the list of ARNs to the main search. The main search subsequently gets the names of all the API calls, the number of unique API calls, and the total number of API calls for each of these ARNs. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +explanation = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Execution"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = This search retrieves all the VPC Flow log entries that have recorded a blocked outbound network connection originating from your AWS environment. Then it kicks off a subsearch, which looks at the same data and performs the following series of steps: \ -1. Counts the number of blocked outbound connections by each source IP\ -1. Loads the cache file that contains the number of data points, the count from the latest hour, the average blocked connections, and the standard deviation for each source IP.\ -1. Drops the count from the latest hour, since it is not necessary, and merges the rest of the data with the results of the stats command. \ -1. Renames `numberOfBlockedConnections` as `latestCount`.\ -1. Calculates the new average value for each source IP with the latest count, weighting the past much more heavily than the current hour. It does the same for the standard deviation, weighting the past more heavily than the current.\ -1. Updates the cache file with the latest results.\ -1. Sets the minimum threshold for the number of data points and sets the number of standard deviations away from the mean it must be to be considered a spike.\ -1. Makes a determination regarding whether or not the current count is a spike by checking to see if the minimum data-point threshold has been met and the count is a sufficient number of standard deviations away from the average.\ -1. Filters out anything that it determines is not a spike and returns the list of source IPs to the main search. The main search subsequently gets the list of all destination IPs for which the traffic was blocked, the network interface ID, the number of unique destination IP, and the total number of blocked connections for each of these source IP addresses. Finally, it looks up the average and standard deviation and returns both the average and the number of standard deviations the spike is from the average. +explanation = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. -annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["Exfiltration", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} +annotations = {"analytics_story": ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"], "security_domain": "network"} known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect USB device insertion - Rule] type = detection -asset_type = Endpoint -confidence = low -explanation = USB is a common attack vector for delivering or propagating malicious code, or the exfiltration of data. Your corporation may have a policy of not allowing removable media at all, or may only allow approved media to be used on specific hosts by specific users. By logging USB activity from Windows and other endpoints gathered using the Universal Forwarder, you can gain an understanding of what systems might be vulnerable to attack via removable media, or what users might need additional security training. This search is looking for event_id 4656 for failure and 4663 for successful USB read/write attempts from Windows Security Event logs, which is the event code generated when a files are read from and written to a removable storage device +asset_type = +confidence = medium +explanation = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Exfiltration"], "nist": ["PR.PT", "PR.DS"]} +annotations = {"analytics_story": ["Data Protection"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"], "security_domain": "endpoint"} known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Detect Unauthorized Assets by MAC address - Rule] type = detection -asset_type = Infrastructure +asset_type = confidence = medium -explanation = This search requires you to leverage the Enterprise Security Assets and Identity framework to populate assets_by_str.csv. Once the assets_by_str.csv is populated, we then query your DHCP logs to detect unknown systems connecting to your network. More documentation is available at: http://docs.splunk.com/Documentation/ES/4.7.1/Admin/Verifyassetandidentitydata. +explanation = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. -annotations = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "mitre_attack": ["Defense Evasion"], "nist": ["ID.AM", "PR.DS"]} +annotations = {"analytics_story": ["Asset Tracking"], "asset_type": "Infrastructure", "cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none -[savedsearch://ESCU - Detect Use of cmd.exe to Launch Script Interpreters - Rule] +[savedsearch://ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers often leverage various scripting languages to execute their attacks. In a Windows environment, the Windows Script Host is the tool that interprets the scripts and is included in all modern versions of Windows. The Windows Script Host is available as a command-line tool called "cscript.exe" or "wscript.exe." To detect this behavior, the search looks for process-creation events for cscript.exe or wscript.exe with a parent process of cmd.exe. The search will return the count, the first and last times this behavior was seen on a destination machine, and user and process information. +explanation = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution", "Command-Line Interface"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Some legitimate applications may exhibit this behavior. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule] type = detection -asset_type = Web Server +asset_type = confidence = medium -explanation = This search returns the number of times a URL associated with this type of JexBoss probe is observed. +explanation = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. -annotations = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery", "System Information Discovery"]} +annotations = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "kill_chain_phases": ["Reconnaissance"], "mitre_attack_id": ["T1082"], "security_domain": "network"} known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. -providing_technologies = ["Splunk Stream", "Palo Alto Firewall", "Apache", "Bro"] +providing_technologies = none [savedsearch://ESCU - Detect hosts connecting to dynamic domain providers - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search leverages an accelerated `Network_Resolution` data model to count and list the values of resolved domains for each DNS query. It checks the results against the list of Dynamic DNS providers in the lookup `dynamic_dns_providers` by each host (DNS.src). +explanation = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ 1. \ @@ -1742,1204 +1680,1204 @@ This search produces fields (query, answer, isDynDNS) that are not yet supported 1. \ 1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Exfiltration", "Defense Evasion"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Detect malicious requests to exploit JBoss servers - Rule] type = detection -asset_type = Web Server -confidence = high -explanation = This search looks for HTTP requests for a URL that has been used to exploit JBoss servers. -how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model -annotations = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -known_false_positives = No known false positives for this detection. -providing_technologies = ["Splunk Stream", "Palo Alto Firewall", "Apache", "Bro"] - -[savedsearch://ESCU - Detect mshta.exe running scripts in command-line arguments - Rule] -type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Mshta.exe is a built-in Windows utility that can launch HTML files with .hta extensions (HTML applications), javascript, or VBScript. The search detects this behavior by looking for events where the process mshta.exe is executed with command-line arguments that indicate that a script is invoked +explanation = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. +how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model +annotations = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} +known_false_positives = No known false positives for this detection. +providing_technologies = none + +[savedsearch://ESCU - Detect mshta exe running scripts in command-line arguments - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Detect new API calls from user roles - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch will execute first and return the user roles and names of the API calls completed within the last hour, where the type of user identity is `AssumedRole`. It then appends the historical data to those results in the lookup file. Next, it recalculates the `earliest` and `latest` fields for each user role, as well as the name of the API call, and returns only those roles and API calls that have first been seen in the past hour. This is combined with the main search to return the values of API calls, name of the user role, and the earliest and latest time of this activity. It is worth noting that the name of the role of a particular user is parsed as "userName" in the CloudTrail logs. +explanation = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect new user AWS Console Login - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events that indicate that a user has attempted to log in to the AWS console and group the events using ARN value. Using the `previously_seen_users_console_logins.csv` lookup file created using the support search, we compare the ARN to all the previously seen users logging into the AWS console. The `eval` and `if` functions determine whether the earliest time we see this user ARN was seen within the last hour. The alert will be fired only when a user is seen for first time in the last hour. +explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Detect processes used for System Network Configuration Discovery - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = Attackers have a range of built-in Windows tools they leverage to ascertain the topography of a network from the point of view of a compromised machine. It is uncommon to see these commands execute quickly within short periods of time. This search returns the number of times, as well as the first time and last times, that every process has run for each endpoint. It then executes the macro `system_network_configuration_discovery_tools`, which looks for processes that are typically used for network configuration discovery. Once you have a list of suspicious process launches for each destination, you can leverage the transaction command to see what processes are fired within a five-minute span on an endpoint and detect only those events where the count of these processes is greater than five. +asset_type = +confidence = medium +explanation = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.DS"]} +annotations = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Detect web traffic to dynamic domain providers - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks for hosts in your environment that may be communicating with a dynamic DNS provider. It checks each URL an endpoint is connecting to against a list of dynamic DNS providers. It returns the source and destination IP address of the web request, the URL requested, and the first time the event occurred. +asset_type = +confidence = medium +explanation = This search looks for web connections to dynamic DNS providers. how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Command and Control", "Web Service", "Exfiltration Over Command and Control Channel", "Defense Evasion"], "nist": ["PR.IP", "DE.DP"]} +annotations = {"analytics_story": ["Dynamic DNS"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"], "security_domain": "network"} known_false_positives = It is possible that list of dynamic DNS providers is outdated and/or that the URL being requested is legitimate. -providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] +providing_technologies = none [savedsearch://ESCU - Detection of DNS Tunnels - Rule] type = detection -asset_type = Endpoint -confidence = low -explanation = The search will calculate the distinct count and sum of the length of DNS queries made and DNS answers received by a particular host to alert the analyst if the combined length is greater than 10000, which is not typical behavior. +asset_type = +confidence = medium +explanation = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. -annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Command and Control", "Exfiltration", "Commonly Used Port"], "nist": ["PR.PT", "PR.DS"]} +annotations = {"analytics_story": ["Data Protection", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "PR.DS"], "security_domain": "network"} known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Detection of tools built by NirSoft - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks for process-creation events accompanied by specific command-line arguments ("scomma" and "stext"). These parameters may be leveraged by a set of free, legitimate tools built by NirSoft. Attackers have been seen abusing the tools' capabilities to steal passwords, set up key loggers, recover account information from mail clients, and conduct other nefarious activities. The search will identify the count, the first and last times a process is executed, the command-line arguments, and the parent process. +explanation = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Discovery", "Execution", "Lateral Movement", "Third-party Software", "Account Discovery"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1072", "T1087"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Disabling Remote User Account Control - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search checks to see if the registry key SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System\LocalAccountTokenFilterPolicy was modified. This registry key can be used to disable remote User Account Control. The search returns the count, the first time activity was seen, last time activity was seen, the registry path that was modified, the host where the modification took place and the user that performed the modification. +explanation = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Modify Registry"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Dump LSASS via comsvcs DLL - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = LSASS is the Local Security Authority Subsystem Service, which is responsible for storing the user credentials. There are multiple ways to attack LSASS. This search detects the usage of comsvcs.dll for dumping the LSASS process. +asset_type = +confidence = medium +explanation = Detect the usage of comsvcs.dll for dumping the lsass process. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = None identified. -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - EC2 Instance Modified With Previously Unseen User - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns the ARNs of all successful EC2 instance modifications within the last hour and then appends the historical data in the lookup file to those results. EC2 modification APIs are defined by the macro `ec2_modification_api_calls`. The search then recalculates the `firstTime` and `lastTime` field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance ID of those systems. +explanation = This search looks for EC2 instances being modified by users who have not previously modified them. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["Unusual AWS EC2 Modifications"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - EC2 Instance Started In Previously Unseen Region - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = In this search, we query CloudTrail logs to look for events that indicate that an instance was started in a particular region. Using the `previously_seen_aws_regions.csv` lookup file created using the support search, we compare the region where this instance was started to all previously observed regions. The `eval` and `if` functions determine that the earliest times seen for this region and instance were within the last day. If a new region is detected, it will alert you with "Instance Started in a New Region". However, this region will be added to the list of `previously_seen_aws_regions.csv`. Please maintain `previously_seen_aws_regions.csv` +explanation = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. -annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion"], "nist": ["DE.DP", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - EC2 Instance Started With Previously Unseen AMI - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns the AMI image ID of all successful EC2 instance launches within the last hour and then appends the historical data from the lookup file to those results. It then recalculates the earliest and latest seen time field for each AMI image ID and returns only those AMI image IDs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems. +explanation = This search looks for EC2 instances being created with previously unseen AMIs. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns the instance types of all successful EC2 instance launches within the last hour and then appends the historical data in the lookup file to those results. It then recalculates the earliest seen time field for each instance type and returns only those instance types that has first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems. +explanation = This search looks for EC2 instances being created with previously unseen instance types. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - EC2 Instance Started With Previously Unseen User - Rule] type = detection -asset_type = AWS Instance +asset_type = confidence = medium -explanation = The subsearch returns the ARNs of all successful EC2 instance launches within the last hour and then appends the historical data in the lookup file to those results. It then recalculates the `firstTime` and `lastTime` field for each ARN and returns only those ARNs that have first been seen in the past hour. This is combined with the main search to return the time, user, and instance id of those systems. +explanation = This search looks for EC2 instances being created by users who have not created them before. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. -annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - Email Attachments With Lots Of Spaces - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at any emails with file attachment names that contain many spaces, relative to the length of the file name. Specifically, it checks to see whether spaces make up more than 10% of the number of characters in the file name. This percentage can be tuned for each environment. The search will output the message ID of the email, the count, the sender and recipient addresses, the first and last time this event was seen, and the space ratio of the file attachment name. +asset_type = +confidence = medium +explanation = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ **Splunk Phantom Playbook Integration**\ If Splunk Phantom is also configured in your environment, a playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} known_false_positives = None at this time -providing_technologies = ["Microsoft Exchange"] +providing_technologies = none [savedsearch://ESCU - Email files written outside of the Outlook directory - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = In this search, we are looking for activities consistent with an adversary collecting email data from local machines. The search will detect email files (files with .pst or .ost extensions) created in directories other than the standard Outlook directory (c:\users\username\My Documents\Outlook Files\. +explanation = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Collection", "Email Collection"]} +annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114"], "security_domain": "endpoint"} known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Email servers sending high volume traffic to hosts - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search may look complex, but it's a neat representation of how statistics can help you understand your dataset to bubble up events that are not normal compared to its behavior. The search consists of three parts. The first part of the SPL fetches the data you want to work on. In this search, we calculate the sum of bytes sent and bytes_out from systems categorized as email_server to each host. We then calculate the average and standard deviation for the bytes sent to all the hosts combined and on a per-host basis. Then we set threshold values to deviation_threshold and minimum_data_samples using eval statements. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. We then check for byte transfers that are statistically significantly higher than normal. The search then gives IP address of the host, the time of the increased byte transfer, how much data was transferred, and the average amount of data transfer the email server normally sends to all hosts and to this specific host. Finally, it includes the number of standard deviations away the byte count was from these averages. +explanation = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Collection", "Email Collection", "Commonly Used Port"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} +annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. -providing_technologies = ["Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Excessive DNS Failures - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks at DNS traffic with a reply code that is NOT indicative of a successful response. Numerous unsuccessful replies may be indicative of DNS protocol tampering or other malicious activity. If more than 50 of these unsuccessful responses are observed over the time frame of the search, a notable event will be generated. +explanation = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -annotations = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Exfiltration", "Exfiltration Over Alternative Protocol", "Command and Control", "Commonly Used Port"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Execution of File With Spaces Before Extension - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search uses the endpoint data model to look for process names with at least five spaces between the file name and its extension. +explanation = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Persistence", "Change Default File Association"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} +annotations = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} known_false_positives = None identified. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Execution of File with Multiple Extensions - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search uses the "Application State" data model to look for process names with specific combinations of double extensions. Relatively straightforward, the search looks for strings in the "process" field that match what you're looking for. +asset_type = +confidence = medium +explanation = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Persistence", "Change Default File Association"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} +annotations = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} known_false_positives = None identified. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Extended Period Without Successful Netbackup Backups - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search finds all the successful backup messages in your logs, and then looks for the most recent backup time for each system. It then identifies those systems where the most recent successful backup time is over a week ago, and reports on them. +asset_type = +confidence = medium +explanation = This search returns a list of hosts that have not successfully completed a backup in over a week. how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. -annotations = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Netbackup"] +providing_technologies = none [savedsearch://ESCU - File with Samsam Extension - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at file modifications across your hosts and creates notable events when it identifies files with extensions associated with the SamSam ransomware, including `.stubbin`, `.berkshire`, `.satoshi`, `.sophos`, or `.keyxml`. Files with these extensions have been observed in SamSam attacks consisting of payload data or keying material. +asset_type = +confidence = medium +explanation = The search looks for file writes with extensions consistent with a SamSam ransomware attack. how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - First Time Seen Running Windows Service - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for a change in the status of a Windows service and extracts the name of the service and the action taken by the service. Then the cache file of previously seen Windows services is added to the search. At this point, the search takes two different paths: the first updates the cache file with the latest information and the second searches for services that have never before been seen. It returns the time, the Windows host name, and the service name. +explanation = This search looks for the first time a Windows service is seen running in your environment. how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -annotations = {"cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Execution", "New Service"], "mitre_technique_id": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} +annotations = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"], "security_domain": "endpoint"} known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - First time seen command line argument - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The subsearch returns all events where `cmd.exe` was used with a `/c` parameter in the command-line arguments to execute other commands/programs. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for command-line execution and outputs this data to the lookup file to update the local cache. It returns only those events that have first been seen in the past one hour. This is combined with the main search to return the time, user, destination, process, parent process, and value of the command-line argument. +explanation = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "Scripting", "Persistence", "Command-Line Interface"], "mitre_technique_id": ["T1059", "T1117", "T1202"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - GCP GCR container uploaded - Rule] type = detection -asset_type = GCP GCR Container +asset_type = confidence = medium -explanation = In this search we can detect if a new container has been uploaded to Google Container Registry, operator can monitor users uploading containers, object paths of new uploaded containers. +explanation = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. -annotations = {"mitre_attack": ["Persistence"], "mitre_technique_id": ["T1525"]} +annotations = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "GCP GCR Container", "security_domain": "threat"} known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. -providing_technologies = ["GCP"] +providing_technologies = none [savedsearch://ESCU - GCP Kubernetes cluster scan detection - Rule] type = detection -asset_type = GCP Kubernetes cluster -confidence = high -explanation = In this search we can detect unauthenticated web requests and possible attack against a GCP cluster, by looking at k8s authentication data, user agent, source IPs and destionation +asset_type = +confidence = medium +explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. -annotations = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["Discovery"], "mitre_technique_id": ["T1190"]} +annotations = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "GCP Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. -providing_technologies = ["GCP"] +providing_technologies = none -[savedsearch://ESCU - Hiding Files And Directories With Attrib.exe - Rule] +[savedsearch://ESCU - Hiding Files And Directories With Attrib exe - Rule] type = detection asset_type = confidence = medium -explanation = This search is looking to detect command-line execution with of attrib.exe binary with the +h flag set. The +h flag is used to hide a file. +explanation = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Persistence"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Hosts receiving high volume of network traffic from email server - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search may look complex, but it's a neat representation of how statistics can help you understand your dataset to bubble up events that are not normal compared to its behavior. The search consists of three parts. The first part of the SPL fetches the data you want to work on. In this search, we calculate the sum of bytes sent and bytes_out from systems categorized as email_server to each host. We then calculate the average and standard deviation for the bytes sent to all the hosts combined and on a per-host basis. Then we set threshold values to deviation_threshold and minimum_data_samples using eval statements. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. We then check for byte transfers that are statistically significantly higher than normal. The search then gives IP address of the host, the time of the increased byte transfer, how much data was transferred, and the average amount of data transfer the email server normally sends to all hosts and to this specific host. Finally, it includes the number of standard deviations away the byte count was from these averages. +explanation = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Collection", "Commonly Used Port"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} +annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. -providing_technologies = ["Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Identify New User Accounts - Rule] type = detection -asset_type = Domain Server +asset_type = confidence = medium -explanation = Adversaries will often seek to create new user accounts as a means of maintaining access to a target environment. Using this search, we identify accounts created in the last week by comparing the start date in the Identity_Management data model against the current time. +explanation = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Persistence", "Create Account"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Domain Server", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. -providing_technologies = ["Active Directory"] +providing_technologies = none [savedsearch://ESCU - Large Volume of DNS ANY Queries - Rule] type = detection -asset_type = DNS Servers -confidence = high -explanation = This search counts the number of DNS ANY queries received in 5 minutes, and generates a Notable Event if the count exceeds a predefined threshold. The search returns the count, the first time, and the last time a DNS packet was observed with the ANY flag set. +asset_type = +confidence = medium +explanation = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -annotations = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} +annotations = {"analytics_story": ["DNS Amplification Attacks"], "asset_type": "DNS Servers", "cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"], "security_domain": "network"} known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - MacOS - Re-opened Applications - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks at the Endpoint data model to identify any MacOS process events referencing a property list file which determines which applications are "re-opened" during startup. This could indicate a malicious attempt to establish persistence on the system. +explanation = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "mitre_attack": ["Persistence"], "mitre_technique_id": ["T1164"], "nist": ["DE.DP", "DE.CM"]} +annotations = {"asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"], "security_domain": "threat"} known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. -providing_technologies = ["OSquery"] +providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for PowerShell processes running with specific command-line arguments that indicate that the process will download a file from the Internet without display anything to the user. The search for "*-Exec*" is to check and see if the default execution policy for PowerShell is being overridden on the command-line. The search for "*-WindowStyle*" and "*hidden*" are to see if the window that would normally be displayed will be hidden from the user instead. Finally, the search for "*New-Object*" and "*System.Net.WebClient*" are there to check to see if a PowerShell object that can be used to download files will be created. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process. +explanation = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Encoded Command - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for PowerShell processes that are passing encoded commands on the command-line. The flags "-EncodedCommand" and "-enc" are two different possible flags that can be used to pass base64 encoded commands to PowerShell. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process. +explanation = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = System administrators may use this option, but it's not common. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for PowerShell processes that were launched using a parameter designed to bypass the local PowerShell execution policy. By default, the policy is set to "Restricted," which disables the execution of PowerShell scripts. In environments that make heavy use of PowerShell, the policy can be set to allow only scripts signed by a trusted publisher. Malicious PowerShell use almost always includes the parameter `-ExecutionPolicy bypass`. PowerShell is very liberal when it comes to interpreting command-line parameters passed to it. For example, the parameter we look for, `-ExecutionPolicy`, can be abbreviated to `-Execution`, `-Exec`, or even `-ex`. As such, we look for `* -ex*`, which should catch all variations of this parameter, followed by the keyword `bypass`. This search will return the host, the user the process ran under, the process and its command-line arguments, the number of times it has seen this process, and the first and last times it saw this process. +explanation = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for PowerShell processes that have a number of suspicious flags on the command-line. It is looking for flags are passing encoded commands on the command-line. The flags `-EncodedCommand` and `-enc` are two different possible flags that can be used to pass base64 encoded commands to PowerShell. The `*-Exec*` flag looks to see it the default execution policy of PowerShell is being overridden, while the `*-NonI*` flag tells the PowerShell process that this will be a noninteractive process, so the user doesn't know about the process. This search will return the host, the user the process ran under, the process and it's command-line arguments, the number of times it's seen this process, and the first and last times it saw this process. +explanation = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for PowerShell processes that are passing command-line arguments with unusual characters (backticks and carets) that are PowerShell specific escape characters. Attackers use this obfuscation technique since it does not affect the functionality of PowerShell and it will bypass standard security controls that look for straight up malicious strings and commands. The search counts the occurrence of these obfuscation characters and lists out destination IPs running these PowerShell commands. +explanation = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution", "PowerShell", "Scripting"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} +annotations = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} known_false_positives = These characters might be legitimately on the command-line, but it is not common. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Monitor DNS For Brand Abuse - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search gathers all the answers to each system's DNS query, then filters out all queries that do not appear on the list of faux "look-a-like" domains that have been generated from the brand abuse domains you are monitoring. +asset_type = +confidence = medium +explanation = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} +annotations = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "kill_chain_phases": ["Delivery", "Actions on Objectives"], "security_domain": "network"} known_false_positives = None at this time -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Monitor Email For Brand Abuse - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at the sender address in email headers, and identifies those with a sender address using a domain name that matches the list of permutations generated for the domain you want to monitor. +asset_type = +confidence = medium +explanation = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Suspicious Emails", "Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} known_false_positives = None at this time -providing_technologies = ["Microsoft Exchange", "Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Monitor Registry Keys for Print Monitors - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = In this search, we look for modifications to registry keys used for adding print-monitor entries on Microsoft platforms via the `registry_path` field in the endpoint data model. It then provides the destination, command used to initiate the change, the user who conducted this activity, the resource affected (registry_key_name), and the entire path of the registry. +explanation = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -annotations = {"cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Privilege Escalation", "Local Port Monitor"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} +annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"], "security_domain": "endpoint"} known_false_positives = You will encounter noise from legitimate print-monitor registry entries. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Monitor Web Traffic For Brand Abuse - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at all the URLs an endpoint is connecting to and then checks the URL against a list of faux domains that could be indicative of brand abuse. +asset_type = +confidence = medium +explanation = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} known_false_positives = None at this time -providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Palo Alto Firewall"] +providing_technologies = none [savedsearch://ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule] type = detection -asset_type = Infrastructure -confidence = high -explanation = This search detects instances when there are more than 5 distinct users failing Okta logins due to invalid credentails from the same IP address. This may be indicative of attack techniques such as credential stuffing or password spraying, where an attacker attempts to login using common or found passwords and attempts to authenticate with them. +asset_type = +confidence = medium +explanation = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. -providing_technologies = ["Okta"] +providing_technologies = none [savedsearch://ESCU - New container uploaded to AWS ECR - Rule] type = detection -asset_type = AWS ECR container +asset_type = confidence = medium -explanation = In this search we can detect if a new container has been uploaded to Amazon Elastic Container Registry, operator can monitor users uploading containers, image ids of new uploaded containers. +explanation = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. -annotations = {"mitre_attack": ["Persistence"], "mitre_technique_id": ["T1525"]} +annotations = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "AWS ECR container", "security_domain": "threat"} known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. -providing_technologies = ["AWS"] +providing_technologies = none [savedsearch://ESCU - No Windows Updates in a time frame - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Keeping your systems up-to-date with the latest patches is an important step in keeping your systems secured. For Windows endpoints, Microsoft typically releases patches on the second Tuesday of every month. These patches contain fixes for vulnerabilities in the system that could potentially be exploited by malicious actors. This search checks for messages regarding Windows updates in the 'Update' data model. If a message indicating a successful update has not been observed in 60 days, a notable event will be generated. These systems should be checked to determine why it has not been updated in that time frame. +explanation = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. -annotations = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} +annotations = {"analytics_story": ["Monitor for Updates"], "asset_type": "Endpoint", "cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Okta Account Lockout Events - Rule] type = detection -asset_type = Infrastructure -confidence = high -explanation = This search detects when a user exceeds the maximum configured Okta login attempts and the account is subsequently locked out. This is often indicative of brtue force attempts against a user account. +asset_type = +confidence = medium +explanation = Detect Okta user lockout events how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. -providing_technologies = ["Okta"] +providing_technologies = none [savedsearch://ESCU - Okta Failed SSO Attempts - Rule] type = detection -asset_type = Infrastructure -confidence = high -explanation = This search looks for events that indicate a user attempted to access an app they did not have permissions to access. This could indicate attempts to access prohibited applications. Please leverage the `okta_failed_sso_attempt_filter` macro to filter out false positives +asset_type = +confidence = medium +explanation = Detect failed Okta SSO events how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. -providing_technologies = ["Okta"] +providing_technologies = none [savedsearch://ESCU - Okta User Logins From Multiple Cities - Rule] type = detection -asset_type = Infrastructure -confidence = high -explanation = This search detects users logging in from multiple states in the last 24 hours. This can be indicative of an attacker using compromised credentials to log in to Okta. The efficacy of this search is highly dependant on the mobility of the users using Okta. It is particularly useful in situations where users should explicitly *not* be travelling, such as during the COVID-19 pandemic. +asset_type = +confidence = medium +explanation = This search detects logins from the same user from different states in a 24 hour period. how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Valid Accounts"], "mitre_technique_id": ["T1078"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. -providing_technologies = ["Okta"] +providing_technologies = none [savedsearch://ESCU - Open Redirect in Splunk Web - Rule] type = detection -asset_type = Splunk Server +asset_type = confidence = medium -explanation = This search looks within Splunk's internal logs for evidence of CVE-2016-4859 open redirect exploitation attempts. +explanation = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. how_to_implement = No extra steps needed to implement this search. -annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} +annotations = {"analytics_story": ["Splunk Enterprise Vulnerability"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} known_false_positives = None identified -providing_technologies = ["Splunk Enterprise"] +providing_technologies = none [savedsearch://ESCU - Osquery pack - ColdRoot detection - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks at the Alerts data model to identify those generated from the osquery osx-attacks.conf pack, which search for the ColdRoot RAT. +explanation = This search looks for ColdRoot events from the osx-attacks osquery pack. how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model -annotations = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "mitre_attack": ["Execution", "Persistence", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} +annotations = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"], "security_domain": "threat"} known_false_positives = There are no known false positives. -providing_technologies = ["OSquery"] +providing_technologies = none [savedsearch://ESCU - Overwriting Accessibility Binaries - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search returns all the different accessibility binaries that have been modified for each Windows host. +asset_type = +confidence = medium +explanation = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Accessibility Features"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Process Execution via WMI - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for processes launched via WMI, either remotely or locally, by looking for processes launched by WmiPrvSE.exe, which is the process WMI uses to execute new processes and commands. +explanation = This search looks for processes launched via WMI. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. -providing_technologies = ["Carbon Black Response", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Processes Tapping Keyboard Events - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search leverages Alerts generated from the osquery osx-attacks.conf pack search `Keyboard_Event_Taps` to detect when a process is monitoring the keystrokes of a machine, This is a common technique used by macOS remote access trojans to log keystrokes from a machine +explanation = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. -annotations = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Collection"], "nist": ["DE.DP"]} +annotations = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"], "security_domain": "threat"} known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. -providing_technologies = ["OSquery"] +providing_technologies = none [savedsearch://ESCU - Processes created by netsh - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for all processes with the parent process "c:\Windows\System32\netsh.exe" and returns the process, the command line used to execute it, the host name, and the user context under which it ran. +explanation = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Netsh Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Processes launching netsh - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for all the parent processes of netsh.exe and returns that process, the command-line used to execute it, the host name, and the user context under which it ran. +explanation = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Command-Line Interface", "Persistence", "Defense Evasion", "Disabling Security Tools"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Prohibited Network Traffic Allowed - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks for traffic marked 'is_prohibited' in the Enterprise Security lookup table 'interesting_ports_lookup', and then determines if any network devices have an associated 'allow' action on that traffic by checking the Network_Traffic data model. +explanation = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Exfiltration", "Exfiltration Over Alternative Protocol"], "nist": ["DE.AE", "PR.AC"]} +annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} known_false_positives = None identified -providing_technologies = ["Palo Alto Firewall", "Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Prohibited Software On Endpoint - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search returns the number of times, as well as the first and last time, every process has run for each endpoint and user. It then displays only those processes that you have marked as "prohibited" in the Enterprise Security "Interesting Processes" table. +asset_type = +confidence = medium +explanation = This search looks for applications on the endpoint that you have marked as prohibited. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.DS"]} +annotations = {"analytics_story": ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Protocol or Port Mismatch - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for instances in which the protocol observed is not consistent with the port and transport protocol typically used for that protocol. For example, looking for network traffic other than HTTP running over TCP port 80. Such behavior could indicate a misconfiguration or a custom command and control protocol that has been designed to look like ordinary web traffic. The search will also identify if HTTP traffic is observed running on unexpected ports. This can be common in many environments. +explanation = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Commonly Used Port"], "nist": ["DE.AE", "PR.AC"]} +annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} known_false_positives = None identified -providing_technologies = ["Palo Alto Firewall", "Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Protocols passing authentication in cleartext - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search is checking for traffic on well-known ports that are associated with protocols that pass authentication in cleartext. +explanation = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. -annotations = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "mitre_attack": ["Credential Access", "Lateral Movement", "Collection"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} +annotations = {"analytics_story": ["Use of Cleartext Protocols"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"], "security_domain": "network"} known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none -[savedsearch://ESCU - Reg.exe Manipulating Windows Services Registry Keys - Rule] -type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks for modifications to registry paths that specify the definition and configuration of Windows services by reg.exe. Reg.exe is a Windows utility that allows for manipulation of the registry via the command line. Malware often uses the Windows services architecture to persist, hide in plain sight, and gain the ability to interact with the Windows kernel. While it is common to modify the configuration of Windows services (and new services may be created with software installs), the use of reg.exe to create or modify a service configuration is unusual and a technique commonly used by attackers. The search returns the count, the first time the activity was seen, the last time activity was seen, the registry path that was modified, the host where the modification took place, and the user that performed the modification. -how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["Persistence", "Privilege Escalation", "New Service", "Modify Existing Service", "Defense Evasion", "Disabling Security Tools"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] - -[savedsearch://ESCU - Reg.exe used to hide files/directories via registry keys - Rule] +[savedsearch://ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule] type = detection asset_type = confidence = medium -explanation = Reg.exe is a binary native to Windows platform used to edit the registry hives of the system. Attackers can leverage this binary to hide files by passing in arguments that are used to hide the files. In the search, we first gather results with keywords, add, Hidden, and REG_DWORD, that will be in the raw event and filter by process and the command-line. We then leverage regular expressions on the command-line field to look for /d value as 2 which is responsible for hiding a file or directory. +explanation = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. +how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. +annotations = {"analytics_story": ["Windows Service Abuse", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} +known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. +providing_technologies = none + +[savedsearch://ESCU - Reg exe used to hide files directories via registry keys - Rule] +type = detection +asset_type = +confidence = medium +explanation = The search looks for command-line arguments used to hide a file or directory using the reg add command. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Persistence"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = None at the moment -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Registry Keys Used For Persistence - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for specific registry paths that malware often uses to ensure survivability and persistence on system startup. The search returns the count, the first time the activity was seen, the last time the activity was seen, the registry path that was modified, the host where the modification took place and the user that performed the modification. +explanation = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Registry Run Keys / Start Folder", "AppInit DLLs", "Authentication Package"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} +annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "endpoint"} known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Registry Keys Used For Privilege Escalation - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for specific registry paths that malware often uses to elevate privileges. The search returns the count, the first time the activity was seen, the last time the activity was seen, the registry path that was modified, the host where the modification took place, and the user who performed the modification. +explanation = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Privilege Escalation", "Persistence", "Accessibility Features"], "mitre_technique_id": ["T1183"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Registry Keys for Creating SHIM Databases - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = In this search, we look for modifications to registry keys used for shim databases on Microsoft platforms via the object_category and object_path field in the Change_Analysis data model and give you the destination, command used to initiate the change, the user who conducted this activity, the resource affected(object), and the whole path of the object. An application compatibility shim is a small library that transparently intercepts an API (via hooking), changes the parameters passed, handles the operation itself, or redirects the operation elsewhere, such as additional code stored on a system. This capability can be also leveraged by attackers to create and store malicious files in a shim database as observed in CARBANAK backdoor. +explanation = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Application Shimming"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Remote Desktop Network Bruteforce - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search monitors for abnormal amounts of remote-desktop (RDP) traffic from a source to a destination that may be indicative of a brute-force attack. It does this by filtering out RDP traffic from the Network_Traffic.All_Traffic data model, using twice the standard deviation of all source-to-destination connections. If any tuple is within more than two standard deviations of all other usual RDP traffic flows, it is indicative of a brute-force attack. +explanation = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. -annotations = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["Credential Access", "Remote Desktop Protocol", "Lateral Movement"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. -providing_technologies = ["Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Remote Desktop Network Traffic - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search finds systems that do not commonly communicate use remote desktop. It does this by filtering out all systems that have the "common_rdp_source" or "common_rdp_destination" category applied to that system. Categories are applied to systems using the Assets and Identity framework. +explanation = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. -annotations = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Remote Desktop Protocol"], "mitre_technique_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} known_false_positives = Remote Desktop may be used legitimately by users on the network. -providing_technologies = ["Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Remote Desktop Process Running On System - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search finds systems that do not commonly use remote desktop, but which begin using it. It filters out all systems that have the "common_rdp_source" category applied. Categories are applied to systems using the Assets and Identity framework. +explanation = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. -annotations = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Remote Desktop Protocol"], "mitre_technique_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Hidden Cobra Malware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Remote Desktop may be used legitimately by users on the network. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Remote Process Instantiation via WMI - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers are increasingly abusing native Windows utilities such as wmic.exe as a means to "live off the land", and avoid introducing new executables to the target system. In this search, we are looking for instances of wmic.exe being run with various parameters that are not typically used by administrators. +explanation = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious WMI Use", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. -providing_technologies = ["Carbon Black Response", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Remote Registry Key modifications - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for modifications made to the Windows registry from remote locations using reg.exe—a tool used to create/update/delete/modify Windows registry keys. It is accomplished through specifying the machine names in the registry path, by entering double backslashes, followed by a computer name. In this search, we look for registry changes where the registry path contains the name of a remote computer. The search returns the number of times the remote server has been accessed, the first and last times the activity occurred, the name of the modified registry path, the host on which the modification took place, and the name of the user that performed the modification. +explanation = This search monitors for remote modifications to registry keys. how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Persistence", "Lateral Movement"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Remote WMI Command Attempt - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Many a times, attackers leverage native Windows utilities that are designed to help administrators better manage their systems, infrastructure, and auditing, but are instead leveraged for malicious purposes. In this case, we are looking for instances of wmic.exe being run with various parameters that are not typically used by administrators. +explanation = This search looks for wmic.exe being launched with parameters to operate on remote systems. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Administrators may use this legitimately to gather info from remote systems. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - RunDLL Loading DLL By Ordinal - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for rundll32.exe being run, loading a DLL out of a directory or subdirectory of AppData, and specifying the function at ordinal 2 be run. +explanation = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["Execution", "Rundll32"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1085"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - SMB Traffic Spike - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Server Message Block (SMB) traffic, a protocol used for Windows file sharing-activity, is often leveraged by attackers. One example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search looks for a traffic spike in SMB traffic from a particular system. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic. +explanation = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Execution", "Command and Control", "Commonly Used Port"], "mitre_technique_id": ["T1110", "T1135", "T1210"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. -providing_technologies = ["Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - SMB Traffic Spike - MLTK - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers often leverage Server Message Block (SMB) traffic, a protocol used for Windows file-sharing activity. A high-profile example of SMB abuse was the WannaCry ransomware, which leveraged a vulnerability in the SMB protocol to propagate to other systems. Attackers have also used SMB for lateral movement with a target environment and to test credentials against target systems. While SMB is highly prevalent in Windows environments, a spike in SMB traffic may still be indicative of this type of malicious activity. This search leverages Splunk's Machine Learning Toolkit (MLTK) to identify spikes in SMB traffic that are unusual for a given hour of day/day of week combination. If such a spike is detected, you may want to investigate the source and analyze the cause of the abnormal traffic. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +explanation = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ 1. **Label:** Number of events, **Field:** count\ Detailed documentation on how to create a new field within Incident Review is found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Lateral Movement", "Execution", "Command and Control", "Commonly Used Port"], "mitre_technique_id": ["T1110", "T1135", "T1210"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} known_false_positives = If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. Please update the `smb_traffic_spike_mltk_filter` macro to filter out false positive results -providing_technologies = ["Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - SQL Injection with Long URLs - Rule] type = detection -asset_type = Database Server +asset_type = confidence = medium -explanation = This search looks only at your web servers and returns the source, the web server, the URL and its length, and the user agent associated with HTTP GET requests for extremely long URLs or user agent lengths with more than three common SQL commands found within the URL. +explanation = This search looks for long URLs that have several SQL commands visible within them. how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. -annotations = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability", "Execution", "Commonly Used Port"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} +annotations = {"analytics_story": ["SQL Injection"], "asset_type": "Database Server", "cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"], "security_domain": "network"} known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. -providing_technologies = ["Splunk Stream", "Bro"] +providing_technologies = none [savedsearch://ESCU - Samsam Test File Write - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at file modifications across your hosts and monitors for a file named "test.txt" written to "windows\system32". This file is copied to potential targets during SamSam ransomware attacks to test the attacker's ability to access remote systems. If the file is successfully copied to the system, the system is added to a list of targets on which to deploy ransomware. -how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} -known_false_positives = No false positives have been identified. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] - -[savedsearch://ESCU - Sc.exe Manipulating Windows Services - Rule] -type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for the execution of sc.exe with parameters that indicate the utility is being used to create a new Windows service, or modify an existing one. Attackers often create a new service to host their malicious code, or they may take a non-critical service or one that is disabled, and modify it to point to their malware and enable the service if necessary. It is unusual for a service to be created or modified using the sc.exe utility. +explanation = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. +how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. +annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +known_false_positives = No false positives have been identified. +providing_technologies = none + +[savedsearch://ESCU - Sc exe Manipulating Windows Services - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["Persistence", "Privilege Escalation", "New Service", "Modify Existing Service", "Defense Evasion", "Disabling Security Tools"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} +annotations = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks for execution of schtasks.exe with parameters that indicate that a specific task "reset," whose name is associated with the Dragonfly threat actor--has been created or deleted. Schtasks.exe is a native Windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or establish persistence. +explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Scheduled Task"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = No known false positives -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Scheduled tasks used in BadRabbit ransomware - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks for execution of schtasks.exe with parameters that indicate that specific task names related to the Bad Rabbit ransomware were created or deleted. The specific task name used are rhaegal, drogon and viserion_. Schtasks.exe is a native windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or establish persistence. +explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Lateral Movement", "Execution", "Scheduled Task"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = No known false positives -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Schtasks scheduling job on remote system - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks for execution of schtasks.exe with parameters that indicate a task is being scheduled on a remote host. Schtasks.exe is a native windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or malicious executables on remote systems. +explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Privilege Escalation", "Execution", "Scheduled Task"], "mitre_technique_id": ["T1053"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Schtasks used for forcing a reboot - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search looks for execution of schtasks.exe with parameters that indicate a task is being scheduled that would cause a forced reboot on the host. Schtasks.exe is a native windows program that is used to schedule tasks on local or remote systems. Attackers often leverage this capability to schedule the execution of commands or establish persistence. This tactic is leveraged by the Bad Rabbit Ransomware. +explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Execution", "Scheduled Task"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Windows Persistence Techniques", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Script Execution via WMI - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers are increasingly abusing Windows Management Infrastructure for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for scripts launched via WMI, either remotely or locally, by looking for the execution of scrcons.exe, which is the scripting host used by WMI, similar to wscript or cscript. +explanation = This search looks for scripts launched via WMI. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. -providing_technologies = ["Carbon Black Response", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Shim Database File Creation - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks for files being created in `Windows\AppPatch\Custom and Windows\AppPatch\Custom64`, the location where shim databases are installed. It will return all the files created, as well as the time of creation for the first and last file for each endpoint. +asset_type = +confidence = medium +explanation = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Application Shimming"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Shim Database Installation With Suspicious Parameters - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for the execution of sdbinst.exe with command-line arguments of -q and -p. The -q option performs a silent installation with no visible window, status, or warning information. The -p option allows the shim database to contain patches. It will return the count, the first time, and the last time these command-line arguments were seen on each endpoint and by each user. +explanation = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Application Shimming"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Short Lived Windows Accounts - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search looks for Windows Event Logs 4720 (account creation) and 4726 (account deletion) and determines if they happen for the same user within 4 hours of each other. It will report the user and machine that reported the events and the time it first and last saw this activity. +explanation = This search detects accounts that were created and deleted in a short time period. how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ -annotations = {"cis20": ["CIS 16"], "mitre_attack": ["Persistence", "Create Account"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Single Letter Process On Endpoint - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search returns all the processes for each endpoint and user and filters out any process that isn't 5 characters long and ends with .exe. +asset_type = +confidence = medium +explanation = This search looks for process names that consist only of a single letter. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["ID.AM", "PR.DS"]} +annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Spectre and Meltdown Vulnerable Systems - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks for the three CVEs associated with the Spectre and Meltdown vulnerabilities. +asset_type = +confidence = medium +explanation = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. -annotations = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} +annotations = {"analytics_story": ["Spectre And Meltdown Vulnerabilities"], "asset_type": "Endpoint", "cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"], "security_domain": "endpoint"} known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. -providing_technologies = ["Nessus", "Qualys"] +providing_technologies = none [savedsearch://ESCU - Spike in File Writes - Rule] type = detection -asset_type = Endpoint -confidence = low -explanation = This search calculates counts the number of file modification events per hour per host in your environment. It then takes the average and standard deviations of those numbers and displays any hosts with more than 20 events that have over four times the standard deviation more than the average number of file modifications. +asset_type = +confidence = medium +explanation = The search looks for a sharp increase in the number of files written to a particular host how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, such as Carbon Black or endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the file system. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Splunk Enterprise Information Disclosure - Rule] type = detection -asset_type = Splunk Server +asset_type = confidence = medium -explanation = This search searches Splunk's internal logs for evidence of CVE-2018-11409 exploitation attempts. +explanation = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. -annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} +annotations = {"analytics_story": ["Splunk Enterprise Vulnerability CVE-2018-11409"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. -providing_technologies = ["Splunk Enterprise"] +providing_technologies = none [savedsearch://ESCU - Suspicious Changes to File Associations - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for changes made to the registry that control Windows file associations. It is typical for users to change the file association to open certain types of files with specific applications. However, when these changes are legitimately performed, they are typically done via the processes explorer.exe or openwith.exe. The search first executes the subsearch that looks at the Registry node, which specifies setting a value in the registry and creates a table of process_id and dest. It then uses those arguments to find out what process and parent process were responsible for making those registry changes. +explanation = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. -annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Change Default File Association"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} +annotations = {"analytics_story": ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} known_false_positives = There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Suspicious Email - UBA Anomaly - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This detection monitors for emails that are suspicious because of their sender, domain rareness, or behavior differences, as determined by Splunk UBA. In this search, we query the "UEBA" data model to look for anomalies that are raised by the "SuspiciousEmailDetectionModel" and will output the count, description of the anomaly, signature, the type of event in UBA, the severity, and the user who received a potentially suspicious email from a newly seen domain. It will also output all the categories associated with that anomaly. +explanation = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. -annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "mitre_attack": [], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Suspicious Emails"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "threat"} known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. -providing_technologies = ["Microsoft Exchange"] +providing_technologies = none [savedsearch://ESCU - Suspicious Email Attachment Extensions - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at any email messages with attachments and checks the file names of those attachments against an included lookup file to see if it has a suspicious file extension. +asset_type = +confidence = medium +explanation = This search looks for emails that have attachments with suspicious file extensions. how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ **Splunk Phantom Playbook Integration**\ If Splunk Phantom is also configured in your environment, a Playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Execution", "Defense Evasion"], "mitre_technique_id": ["T1193"], "nist": ["DE.AE", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"], "security_domain": "network"} known_false_positives = None identified -providing_technologies = ["Microsoft Exchange"] +providing_technologies = none [savedsearch://ESCU - Suspicious File Write - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at files being created or modified in the Endpoint file-system data model. The names of those files are checked against an included lookup file, which contains the names of files associated with malware or attack activity. The search returns any files with matching names, along with a note (also specified in the lookup file) that gives or points to more information about the files. +asset_type = +confidence = medium +explanation = The search looks for files created with names that have been linked to malicious activity. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": [], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none [savedsearch://ESCU - Suspicious Java Classes - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search leverages HTTP form data from typically POST events that can be captured with Splunk streams or similar wire data capture tools. The search looks for java classes like `processbuilder` and `runtime` are used to create a new process and execute commands inside java, and are synonymous with spawning a shell. There are very exceptional reasons to ever these classes in Java via an HTTP API and hence when seen are highly suspicious. Also, this is a common vectors leverage to exploit Apache Struts. +explanation = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. -annotations = {"cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["Execution"], "nist": ["DE.AE"]} +annotations = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"], "security_domain": "threat"} known_false_positives = There are no known false positives. -providing_technologies = ["Splunk Stream", "Bro", "Bluecoat", "Apache"] +providing_technologies = none [savedsearch://ESCU - Suspicious LNK file launching a process - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = In this search, we are essentially trying to detect if a LNK file created under the C:\User* or *\Local\Temp\* directory structures is launching a process with in 1 hour of its creation. LNK files or also known as Windows shortcut files are commonly associated with phishing and are a [preferred method used for exploitation](https://www.fireeye.com/blog/threat-research/2017/04/fin7-phishing-lnk.html). -how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["Initial Access", "Spearphishing Attachment"], "nist": ["ID.AM", "PR.DS"]} -known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] - -[savedsearch://ESCU - Suspicious Reg.exe Process - Rule] -type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for the execution of reg.exe with a parent process of cmd.exe. It then executes a subsearch looking for those cmd.exe processes with a parent that is not explorer.exe. It then joins those two searches to make sure that the reg.exe process is a grandchild of the non explorer.exe process. The search will return the number of such instances and the first and last time this activity has been seen on each endpoint and user. +explanation = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. +how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. +annotations = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. +providing_technologies = none + +[savedsearch://ESCU - Suspicious Reg exe Process - Rule] +type = detection +asset_type = +confidence = medium +explanation = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Modify Registry", "Disabling Security Tools"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112", "T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Suspicious wevtutil Usage - Rule] type = detection asset_type = confidence = medium -explanation = This search looks for execution of wevtutil.exe with command-line arguments that indicate that it has been used to delete the setup, application, security, or system event logs. The search returns the number of times the behavior was observed, the first and last time it was seen, the host exhibiting the behavior and the user context of the process execution. +explanation = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Indicator Removal on Host"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} +annotations = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Suspicious writes to System Volume Information - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search uses data on file writes captured via Sysmon to watch for writes to the "System Volume Information" folder by processes other than the system process. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. It then looks for a file created with a path that includes "System Volume Information" and a process ID (PID) other than 4. PID 4 is assigned to the System process on Windows systems. Excluding these writes allows us to filter out legitimate activity. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity. +explanation = This search detects writes to the 'System Volume Information' folder by something other than the System process. how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"cis20": ["CIS 8"], "mitre_attack": ["Collection", "Data Staged"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - Suspicious writes to windows Recycle Bin - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search uses data on file writes captured via Sysmon to watch for writes to the Recycle Bin by processes other than explorer.exe. The search looks for event code 11 in the Sysmon events, which indicates a file-creation event. Next, it looks for files created with a path that includes the string "$Recycle.Bin" by processes other than explorer.exe, which is the process responsible for copying files to the Recycle Bin on delete. It will report the system where the activity occurred, the path to which the file was written, the process responsible for the write, and the times it first and last saw this activity. +explanation = This search detects writes to the recycle bin by a process other than explorer.exe. how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. -annotations = {"cis20": ["CIS 8"], "mitre_attack": ["Collection", "Data Staged"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. -providing_technologies = ["Sysmon"] +providing_technologies = none [savedsearch://ESCU - System Processes Run From Unexpected Locations - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search returns all the processes that are not executing out of the C:\Windows\System32 or C:\Windows\SysWOW64 directories. Next, it takes the filename and looks it up in a table `is_windows_system_file` of files that should normally run out of the C:\Windows\System32 or C:\Windows\SysWOW64 directory. Any matches are then returned. +explanation = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Masquerading"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1036"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - TOR Traffic - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = The search leverages the Enterprise Security Network_Traffic data model to look for network traffic that has been identified as TOR and marked as 'allowed'. +explanation = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Commonly Used Port", "Exfiltration"], "nist": ["DE.AE"]} +annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE"], "security_domain": "network"} known_false_positives = None at this time -providing_technologies = ["Palo Alto Firewall", "Bro", "Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - USN Journal Deletion - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = This search looks for the execution of fsutil.exe with command-line arguments to delete the USN journal. The search returns the count of the number of times it's seen this process execution with these arguments, the first and last time it's seen this behavior, the hosts it was executed on, and the user context under which it was executed. +explanation = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Indicator Removal on Host"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} +annotations = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Uncommon Processes On Endpoint - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search returns the number of times, as well as the first and last time, it has seen every process run for each endpoint and user, and then displays only those processes that you have marked as uncommon in the `uncommon_processes_default.csv` table. +asset_type = +confidence = medium +explanation = This search looks for applications on the endpoint that you have marked as uncommon. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. -annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Accessibility Features"], "nist": ["ID.AM", "PR.DS"]} +annotations = {"analytics_story": ["Windows Privilege Escalation", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Unload Sysmon Filter Driver - Rule] type = detection asset_type = confidence = medium -explanation = This search is looking to detect execution of `fltMC.exe` that specifically used for unloading the Sysmon Filter Driver +explanation = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Disabling Security Tools"], "mitre_technique_id": ["T1089"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Disabling Security Tools"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Unsigned Image Loaded by LSASS - Rule] type = detection -asset_type = Windows +asset_type = confidence = medium -explanation = This search detects unsigned images loaded by LSASS (Local Security Authrity Subsystem Service). Normally, LSASS only loads signed images. Therefore, it is a malicious indicator when unsigned images are loaded by LSASS. This can be an indicator for credential dumping using tools like Windows Credential Editor. +explanation = This search detects loading of unsigned images by LSASS. how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Credential Access", "Credential Dumping"], "mitre_technique_id": ["T1003"], "nist": ["DE.CM"]} +annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Unsuccessful Netbackup backups - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks across the most recent backup events for each host, and returns those messages that indicate there was a backup failure. +asset_type = +confidence = medium +explanation = This search gives you the hosts where a backup was attempted and then failed. how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. -annotations = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = None identified -providing_technologies = ["Netbackup"] +providing_technologies = none [savedsearch://ESCU - Unusually Long Command Line - Rule] type = detection asset_type = confidence = medium -explanation = This search calculates the average and standard deviation for the length of the command lines on each of your endpoints and alerts when it detects a command line with a length over 10 times the standard deviation larger than the average command line. +explanation = Command lines that are extremely long may be indicative of malicious activity on your hosts. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships, from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Some legitimate applications start with long command lines. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Unusually Long Command Line - MLTK - Rule] type = detection asset_type = confidence = medium -explanation = This search leverages the Machine Learning Toolkit (MLTK) to identify outliers in the length of the command lines observed to be used by a specific user. The companion search, "Baseline of Command Line Length - MLTK," creates a machine-learning (ML) model built over the historical data used by this search. The determination of what is considered an outlier may be adjusted via the threshold parameter in the search. More information on the algorithm used can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +explanation = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. -annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution"], "nist": ["PR.PT", "DE.CM"]} +annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Unusually Long Content-Type Length - Rule] type = detection -asset_type = Web Server -confidence = high -explanation = This detection search uses HTTP traffic data captured with Splunk Stream. The search is constructed to use "stream:http" sourcetype and counts of the number of times an HTTP request is received by a destination which the length of the Content-Type header value the client sends the server is greater than 100 characters long. We calculate this content_type_length field and output the results. +asset_type = +confidence = medium +explanation = This search looks for unusually long strings in the Content-Type http header that the client sends the server. how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. -annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} +annotations = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. -providing_technologies = ["Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - WMI Permanent Event Subscription - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Windows event ID 5861. +explanation = This search looks for the creation of WMI permanent event subscriptions. how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation", "Persistence", "Windows Management Instrumentation Event Subscription"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - WMI Permanent Event Subscription - Sysmon - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI event subscription by watching for Sysmon event ID 21. +explanation = This search looks for the creation of WMI permanent event subscriptions. how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation", "Persistence", "Windows Management Instrumentation Event Subscription"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - WMI Temporary Event Subscription - Rule] type = detection -asset_type = Endpoint +asset_type = confidence = medium -explanation = Attackers are increasingly abusing Windows Management Infrastructure (WMI) for stealth, persistence, lateral movement, or just to leverage its functionality. This search looks for the creation of a WMI temporary event subscription by watching for Windows event ID 5860. +explanation = This search looks for the creation of WMI temporary event subscriptions. how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Execution", "Windows Management Instrumentation", "Persistence", "Windows Management Instrumentation Event Subscription"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} known_false_positives = Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Web Fraud - Account Harvesting - Rule] type = detection -asset_type = Account +asset_type = confidence = medium -explanation = When a fraudster is setting the stage for a campaign, they will often create many user accounts on the website. This is a simple example of how to detect a many-account creation hosted on a Magento2 e-commerce platform, where the fraudster is using email addresses from a single email domain. +explanation = This search is used to identify the creation of multiple user accounts using the same email domain name. how_to_implement = We start with a dataset that provides visibility into the email address used for the account creation. In this example, we are narrowing our search down to the single web page that hosts the Magento2 e-commerce platform (via URI) used for account creation, the single http content-type to grab only the user's clicks, and the http field that provides the username (form_data), for performance reasons. After we have the username and email domain, we look for numerous account creations per email domain. Common data sources used for this detection are customized Apache logs or Splunk Stream. -annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Persistence", "Create Account"], "nist": ["DE.CM", "DE.DP"]} +annotations = {"analytics_story": ["Web Fraud Detection"], "asset_type": "Account", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1136"], "nist": ["DE.CM", "DE.DP"], "security_domain": "threat"} known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamolous behavior. This search will need to be customized to fit your environment—improving its fidelity by counting based on something much more specific, such as a device ID that may be present in your dataset. Consideration for whether the large number of registrations are occuring from a first-time seen domain may also be important. Extending the search window to look further back in time, or even calculating the average per hour/day for each email domain to look for an anomalous spikes, will improve this search. You can also use Shannon entropy or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness or similarity of the email name or email domain, as the names are often machine-generated. -providing_technologies = ["Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Web Fraud - Anomalous User Clickspeed - Rule] type = detection -asset_type = account +asset_type = confidence = medium -explanation = It's suspicious when someone or something is moving throughout your website too quickly or with a perfect click cadence. Fortunately, it's easy to detect by calculating the time between clicks for each session and highlighting the anomalous behavior. +explanation = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. how_to_implement = Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -annotations = {"cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Initial Access", "Valid Accounts"], "nist": ["DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Web Fraud Detection"], "asset_type": "account", "cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1078"], "nist": ["DE.AE", "DE.CM"], "security_domain": "threat"} known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior. -providing_technologies = ["Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Web Fraud - Password Sharing Across Accounts - Rule] type = detection -asset_type = account +asset_type = confidence = medium -explanation = A common password across user accounts generally indicates that the users are choosing poor passwords or that a fraudster has a common password across multiple accounts embedded within a script. The search will extract the username and password information from the form_data field, then calculate the number and values for usernames that have the same passwords. Finally, it outputs the values where the unique usernames sharing passwords are greater than 5 +explanation = This search is used to identify user accounts that share a common password. how_to_implement = We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -annotations = {"cis20": ["CIS 16"], "nist": ["DE.DP"]} +annotations = {"analytics_story": ["Web Fraud Detection"], "asset_type": "account", "cis20": ["CIS 16"], "nist": ["DE.DP"], "security_domain": "threat"} known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior. -providing_technologies = ["Splunk Stream"] +providing_technologies = none [savedsearch://ESCU - Web Servers Executing Suspicious Processes - Rule] type = detection -asset_type = Web Server +asset_type = confidence = medium -explanation = This detection search uses the Enterprise Security Endpoint data model. The search uses tstats to search within an accelerated data model to find suspicious applications or processes such as whoami, ping, iptables, wget, service, or curl, running on hosts which are marked as web servers in the Assets and Identity Framework of ES. +explanation = This search looks for suspicious processes on all systems labeled as web servers. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. -annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Exploitation of Vulnerability", "Execution", "Discovery", "System Information Discovery"], "nist": ["PR.IP"]} +annotations = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1082"], "nist": ["PR.IP"], "security_domain": "endpoint"} known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +providing_technologies = none [savedsearch://ESCU - Windows Event Log Cleared - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = This search looks at the Windows security and system event logs. EventCode 1002 in the security log indicates that the log has been cleared, EventCode 1000 in the security log indicates the event logging service has been shut down, and EventCode 104 in the system log indicates the application log has been cleared. If any of these events are found, a notable will be generated. +asset_type = +confidence = medium +explanation = This search looks for Windows events that indicate one of the Windows event logs has been purged. how_to_implement = To successfully implement this search, you need to be ingesting Windows event logs from your hosts. -annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["Defense Evasion", "Indicator Removal on Host"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"]} +annotations = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} known_false_positives = It is possible that these logs may be legitimately cleared by Administrators. -providing_technologies = ["Microsoft Windows"] +providing_technologies = none [savedsearch://ESCU - Windows hosts file modification - Rule] type = detection -asset_type = Endpoint -confidence = high -explanation = The hosts file is present on both Windows and Linux endpoints. The purpose of the hosts file is to provide a mapping between hostnames and IP addresses, the same way DNS is used to provide such a mapping. However, the information in the hosts file takes precedence over information received via DNS and a DNS query will not be issued if the hostname of interest is found in the hosts file. As such, attackers have been observed adding entries to the host file to override any DNS resolution. For this reason, it is useful to monitor for changes to this file, which typically do not occur very often in legitimate cases. +asset_type = +confidence = medium +explanation = The search looks for modifications to the hosts file on all Windows endpoints across your environment. how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["Command and Control", "Exfiltration"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"]} +annotations = {"analytics_story": ["Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"], "security_domain": "endpoint"} known_false_positives = There may be legitimate reasons for system administrators to add entries to this file. -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon"] +providing_technologies = none ### END DETECTIONS ### -### INVESTIGATIONS ### +### RESPONSE TASKS ### [savedsearch://ESCU - AWS Investigate User Activities By ARN] type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time -earliest_time_offset = 72000 -latest_time_offset = 36000 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - AWS Investigate User Activities By AccessKeyId] type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time -earliest_time_offset = 0 -latest_time_offset = 14400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - AWS Investigate User Activities By Source User] type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -2947,41 +2885,49 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs. -known_false_positives = None at this time -earliest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - AWS Network Interface details via resourceId] type = investigation explanation = none how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS configuration inputs -known_false_positives = None at this time -earliest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - AWS S3 Bucket details via bucketName] type = investigation explanation = none how_to_implement = To implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later) and configure your AWS inputs. -known_false_positives = None at this time -earliest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - All backup logs for host] type = investigation explanation = none how_to_implement = The successfully implement this search you must first send your backup logs to Splunk. -known_false_positives = None at this time -earliest_time_offset = 1209600 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 -[savedsearch://ESCU - Amazon EKS Kubernetes activity by src_ip] +[savedsearch://ESCU - Amazon EKS Kubernetes activity by src ip] type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your Cloud Watch EKS inputs. -known_false_positives = None at this time -earliest_time_offset = -70m@m -latest_time_offset = -10m@m +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 + +[savedsearch://ESCU - Analyze Malicious File] +type = investigation +explanation = none +how_to_implement = none +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - DNS Hijack Enrichment] type = investigation @@ -2989,39 +2935,39 @@ explanation = none how_to_implement = If Splunk>Phantom is also configured in your environment, a Playbook called "DNS Hijack Enrichment" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\ -known_false_positives = None at this time -earliest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Domain Certificate Investigation] type = investigation explanation = none how_to_implement = To successfully implement this phantom playbook, you must integrate Enterprise Security with Phantom. Configure this playbook in the correlation search `Detect DNS requests to Phishing Sites leveraging EvilGinx2` ,as an adaptive response action. -known_false_positives = None at this time -earliest_time_offset = 0 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Excessive Account Lockouts Enrichment And Response] type = investigation explanation = none how_to_implement = Import playbook into phantom -known_false_positives = None at this time -earliest_time_offset = -4h@h -latest_time_offset = -5m@m +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 -[savedsearch://ESCU - GCP Kubernetes activity by src_ip] +[savedsearch://ESCU - GCP Kubernetes activity by src ip] type = investigation explanation = none how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. -known_false_positives = None at this time -earliest_time_offset = -70m@m -latest_time_offset = -10m@m +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get All AWS Activity From City] type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -3029,7 +2975,7 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -3037,7 +2983,7 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -3045,7 +2991,7 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -3053,247 +2999,247 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -known_false_positives = None at this time -earliest_time_offset = 43200 -latest_time_offset = 1 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Backup Logs For Endpoint] type = investigation explanation = none how_to_implement = You must be ingesting your backup logs. -known_false_positives = None at this time -earliest_time_offset = 604800 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get Certificate logs for a domain] type = investigation explanation = none how_to_implement = You must be ingesting your certificates or SSL logs from your network traffic into your Certificates datamodel. Please note the wildcard(*) before domain in the search syntax, we use to match for all domain and subdomain combinations -known_false_positives = None at this time -earliest_time_offset = 36000 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get DNS Server History for a host] type = investigation explanation = none how_to_implement = To successfully implement this search, you must be ingesting your DNS traffic -known_false_positives = None at this time -earliest_time_offset = 0 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get DNS traffic ratio] type = investigation explanation = none how_to_implement = You must be ingesting your network traffic -known_false_positives = None at this time -earliest_time_offset = 0 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get EC2 Instance Details by instanceId] type = investigation explanation = none how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs. -known_false_positives = None at this time -earliest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get EC2 Launch Details] type = investigation explanation = none how_to_implement = In order to implement this search, you must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS(version 4.4.0 or later) and configure your AWS description inputs. -known_false_positives = None at this time -earliest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get Email Info] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting your email logs or capturing unencrypted network traffic which contains email communications. -known_false_positives = None at this time -earliest_time_offset = 0 -latest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Emails From Specific Sender] type = investigation explanation = none how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get First Occurrence and Last Occurrence of a MAC Address] type = investigation explanation = none how_to_implement = To successfully implement this search, you must be ingesting the logs from your DHCP server. -known_false_positives = None at this time -earliest_time_offset = 864000 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get History Of Email Sources] type = investigation explanation = none how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -known_false_positives = None at this time -earliest_time_offset = 172800 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Logon Rights Modifications For Endpoint] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting your Windows event logs -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Logon Rights Modifications For User] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting your Windows event logs -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Notable History] type = investigation explanation = none how_to_implement = If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary. -known_false_positives = None at this time -earliest_time_offset = 864000 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Notable Info] type = investigation explanation = none how_to_implement = If you are using Enterprise Security you are likely already creating notable events with your correlation rules. No additional configuration is necessary. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Outbound Emails to Hidden Cobra Threat Actors] type = investigation explanation = none how_to_implement = To successfully implement this search you must ingest your email logs or capture unencrypted email communications within network traffic, and populate the Email data model. -known_false_positives = None at this time -earliest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get Parent Process Info] type = investigation explanation = none how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -known_false_positives = None at this time -earliest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get Process File Activity] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -known_false_positives = None at this time -earliest_time_offset = 7200 -latest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Process Info] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -known_false_positives = None at this time -earliest_time_offset = 7200 -latest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Process Information For Port Activity] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting endpoint data that associates processes with network events and populate the Endpoint Datamodel -known_false_positives = None at this time -earliest_time_offset = 7200 -latest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Process Registry Activity] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting endpoint data and populating the Endpoint data model. -known_false_positives = None at this time -earliest_time_offset = 7200 -latest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Process Responsible For The DNS Traffic] type = investigation explanation = none how_to_implement = You must be ingesting endpoint data that associates processes with network events into the Endpoint datamodel. This can come from endpoint protection products such as carbon black, or endpoint data sources such as Sysmon. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Registry Activities] type = investigation explanation = none how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. -known_false_positives = None at this time -earliest_time_offset = 0 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Risk Modifiers For Endpoint] type = investigation explanation = none how_to_implement = Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -known_false_positives = None at this time -earliest_time_offset = 604800 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get Risk Modifiers For User] type = investigation explanation = none how_to_implement = Enable the correlation searches included in Splunk Enterprise Security that include Risk Analysis alert actions by leveraging the Risk Analysis Framework -known_false_positives = None at this time -earliest_time_offset = 604800 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get Sysmon WMI Activity for Host] type = investigation explanation = none how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate events for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. -known_false_positives = None at this time -earliest_time_offset = 7200 -latest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Update Logs For Endpoint] type = investigation explanation = none how_to_implement = You need to be ingesting the update logs from your various systems. -known_false_positives = None at this time -earliest_time_offset = 604800 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Get User Information from Identity Table] type = investigation explanation = none how_to_implement = To successfully implement this search you must have populated the identity table with information about your users. -known_false_positives = None at this time -earliest_time_offset = 864000 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Get Vulnerability Logs For Endpoint] type = investigation explanation = none how_to_implement = You need to be ingesting the logs from your vulnerability scanner. -known_false_positives = None at this time -earliest_time_offset = 604800 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 -[savedsearch://ESCU - Get Web Session Information via session_id] +[savedsearch://ESCU - Get Web Session Information via session id] type = investigation explanation = none how_to_implement = This search leverages data extracted from Stream:HTTP. You must configure the HTTP stream using the Splunk Stream App on your Splunk Stream deployment server. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate AWS ECR container listing activity] type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.You must also install Cloud Infrastructure Data Model. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -3301,7 +3247,7 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -3309,7 +3255,7 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = None at this time +known_false_positives = not defined earliest_time_offset = 14400 latest_time_offset = 0 @@ -3317,430 +3263,454 @@ latest_time_offset = 0 type = investigation explanation = none how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = None at this time -earliest_time_offset = 7200 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Investigate Failed Logins for Multiple Destinations] type = investigation explanation = none how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -known_false_positives = None at this time -earliest_time_offset = -7d -latest_time_offset = now +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 -[savedsearch://ESCU - Investigate Network Traffic From src_ip] +[savedsearch://ESCU - Investigate Network Traffic From src ip] type = investigation explanation = none how_to_implement = To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Okta Activity by IP Address] type = investigation explanation = none how_to_implement = You must be ingesting Okta logs -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 14400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Okta Activity by app] type = investigation explanation = none how_to_implement = You must be ingesting Okta logs -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 14400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Pass the Hash Attempts] type = investigation explanation = none how_to_implement = To successfully implement this search you need be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -known_false_positives = None at this time -earliest_time_offset = -24h -latest_time_offset = now +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Pass the Ticket Attempts] type = investigation explanation = none how_to_implement = To successfully implement this search you need to be ingesting windows security logs. This search uses an input macro named `wineventlog_security`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Security logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -known_false_positives = None at this time -earliest_time_offset = -24h -latest_time_offset = now +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Previous Unseen User] type = investigation explanation = none how_to_implement = To successfully implement this search you need to be ingesting authentication logs from your various systems and populating the Authentication data model. -known_false_positives = None at this time -earliest_time_offset = -60d -latest_time_offset = now +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Successful Remote Desktop Authentications] type = investigation explanation = none how_to_implement = You must be populating the Authentication data model with security events from your Windows event logs. -known_false_positives = None at this time -earliest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 latest_time_offset = 0 [savedsearch://ESCU - Investigate Suspicious Strings in HTTP Header] type = investigation explanation = none how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate User Activities In All Cloud Regions] type = investigation explanation = none how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 14400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate User Activities In Okta] type = investigation explanation = none how_to_implement = You must be ingesting Okta logs -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 14400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate User Activities In Single Cloud Region] type = investigation explanation = none how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = None at this time -earliest_time_offset = 86400 -latest_time_offset = 14400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Web Activity From Host] type = investigation explanation = none how_to_implement = To successfully implement this search you must be ingesting your web traffic and populating the Web data model. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 -[savedsearch://ESCU - Investigate Web Activity From src_ip] +[savedsearch://ESCU - Investigate Web Activity From src ip] type = investigation explanation = none how_to_implement = To successfully implement this search, you must be ingesting your web traffic and populating the web data model. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Investigate Web POSTs From src] type = investigation explanation = none how_to_implement = To successfully implement this search, you must be ingesting your web-traffic logs and populating the web data model. -known_false_positives = None at this time -earliest_time_offset = 3600 -latest_time_offset = 3600 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 + +[savedsearch://ESCU - Malware Hunt and Contain] +type = investigation +explanation = none +how_to_implement = none +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 + +[savedsearch://ESCU - Process Chain Analysis] +type = investigation +explanation = none +how_to_implement = none +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 + +[savedsearch://ESCU - Quarantaine Infected Host] +type = investigation +explanation = none +how_to_implement = none +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 [savedsearch://ESCU - Suspicious Email Attachment Investigate and Delete] type = investigation explanation = none how_to_implement = Synchronize the community playbook repository in Phantom, then open the playbook and follow the deployment notes to configure it for your environment. -known_false_positives = None at this time -earliest_time_offset = 0 -latest_time_offset = 86400 +known_false_positives = not defined +earliest_time_offset = 14400 +latest_time_offset = 0 -### END INVESTIGATIONS ### +### END RESPONSE TASKS ### ### BASELINES ### [savedsearch://ESCU - Add Prohibited Processes to Enterprise Security] type = support -explanation = This search outputs the interesting processes lookup table and filters out all processes in the table that haven't already been inserted by ESCU. It then appends to those results all the processes currently identified by ESCU that should be prohibited. Next, it fills in the required fields with processes identified by ESCU, and then writes the results back to the interesting process lookup table. This is done so any new processes identified that should be prohibited will be added to the lookup table without creating any duplicate entries. +explanation = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. how_to_implement = This search should be run on each new install of ESCU. -known_false_positives = -providing_technologies = ["Splunk Enterprise Security"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of API Calls per User ARN] type = support -explanation = This search returns all log events that are API calls, pulls out the ARN that initiated each call, and collects them in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each ARN had. This table is then stored in a lookup file. +explanation = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of Command Line Length - MLTK] type = support -explanation = Create a machine-learning (ML) model to characterize the length of the command lines used in your environment. This can help you identify unusually long ones that may indicate that attackers are executing commands on yout systems. +explanation = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of DNS Query Length - MLTK] type = support -explanation = Create a machine-learning (ML) model to characterize the length of DNS requests seen in your environment to help identify unusually long ones that may be indicative of attacker infrastrucutre or the use of DNS as a command-and-control channel in your environment. +explanation = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = -providing_technologies = ["Splunk Stream", "Bro"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK] type = support -explanation = Create a machine-learning (ML) model to establish a baseline for how many RunInstances users do in the environment. This can help you identify excessive numbers of RunInstances which may warrant further investigation to determine if there is misuse or abuse. +explanation = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK] type = support -explanation = Create a machine-learning (ML) model to establish a baseline for how many TerminateInstances users do in the environment. This can help you identify excessive numbers of TerminateInstances which may warrant further investigation to determine if there is misuse or abuse. +explanation = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of Network ACL Activity by ARN] type = support -explanation = Use this search to create a baseline for API calls related to network ACLs for the users who initiated this activity. It returns all logged API calls for network activity, pulls out the ARN that initiated each call, and collects the `eventNames` in one-hour groupings. Next, it calculates the number of API calls made per ARN per-hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file. +explanation = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of S3 Bucket deletion activity by ARN] type = support -explanation = Use this search to create a baseline for API calls related to deleting an S3 bucket, grouped by the users who initiated this activity. It returns all logged API calls for S3 bucket-deletion activity and then pulls out the ARN that initiated each call. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file. +explanation = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of SMB Traffic - MLTK] type = support -explanation = Create a machine-learning (ML) model to characterize the number of SMB connections observed in your environment. This may help identify spikes in SMB traffic that may be indicative of attackers scanning or attempting to propagate to other systems in your environment. By default, this model is built over 30 days of data and profiles the number of SMB connections in your environment by the hour of day/day of week that the connections occur. +explanation = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -known_false_positives = -providing_technologies = ["Splunk Stream", "Bro"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of Security Group Activity by ARN] type = support -explanation = Use this search to create a baseline for API calls related to security groups by the users who initiated this activity. It returns all logged API calls for all security-group-related activity, pulls out the ARN that initiated each call, and collects the `eventNames` in one-hour groupings. Next, it calculates the number of API calls made per ARN per hour. For each ARN, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points for each ARN. This table is stored in a lookup file. +explanation = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Baseline of blocked outbound traffic from AWS] type = support -explanation = Use this search to create a baseline of blocked outbound network connections by each source IP in your AWS environment. This search returns all log events that correspond to a blocked outbound network connection, extracts the source IP from where the outbound connection was initiated, and collects the events in one-hour groupings. Next, it calculates the number of outbound connections blocked per hour. For each source IP, it calculates the average and standard deviation of this count on a per-hour basis. It also includes the number of data points each source IP had. This table is then stored in a lookup file. +explanation = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Count of Unique IPs Connecting to Ports] type = support -explanation = For each port being accessed on the network, this search gives the total number of connections observed, and the number of unique IP addresses making those connections. +explanation = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. -known_false_positives = -providing_technologies = ["Splunk Stream", "Bro"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Count of assets by category] type = support -explanation = This search gives you the number and the names of the hosts of each host in your environment by category. It will then sort them by the count. +explanation = This search shows you every asset category you have and the assets that belong to those categories. how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. -known_false_positives = -providing_technologies = ["Splunk Enterprise Security"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Create a list of approved AWS service accounts] type = support -explanation = We first look for all successful CloudTrail API activity caused by types of user accounts and then remove all the events caused by users in the Identity table. This generates a list of accounts--typically service accounts--configured in your AWS environment. We output this list of service accounts to `aws_service_accounts.csv`. +explanation = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - DNSTwist Domain Names] type = support -explanation = This search starts with the dnstwist command consuming domains from a file called domains.csv in the DA-ESS-SOC/lookups directory. This search then adds a domain\_abuse=true term to each permutation, removes all the valid domain names and stores all that information into a lookup file that is used in the associated detection search. Alternatively domain dnstwist permutations can be calculated from domains in the `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` lookups located in **Splunk\_SA\_CIM** using argument `populate_from_cim=true`. Also an individual domain can be passed using argument `domain=` +explanation = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. -known_false_positives = -providing_technologies = ["Splunk Enterprise"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Discover DNS records] type = support -explanation = Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named `discovered_dns_records.csv` +explanation = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation -known_false_positives = Please vet the lookup created by this baseline search -providing_technologies = ["Splunk Stream", "Bro"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Identify Systems Creating Remote Desktop Traffic] type = support -explanation = This search counts the numbers of times the system has tried to connect to another system on TCP/3389, the default port used for RDP traffic. +explanation = This search counts the numbers of times the system has generated remote desktop traffic. how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. -known_false_positives = -providing_technologies = ["Splunk Stream", "Bro"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Identify Systems Receiving Remote Desktop Traffic] type = support -explanation = This search counts the numbers of times the system has received a connection to TCP/ 3389, the default port used for RDP traffic. +explanation = This search counts the numbers of times the system has created remote desktop traffic how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. -known_false_positives = -providing_technologies = ["Splunk Stream", "Bro"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Identify Systems Using Remote Desktop] type = support -explanation = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. It does this by looking for the process name in the Endpoint data model. +explanation = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. -known_false_positives = -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Monitor Successful Backups] type = support -explanation = This search gives you the count and the hostname of all the systems that had a successful backup each day. +explanation = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. how_to_implement = To successfully implement this search you must be ingesting your backup logs. -known_false_positives = -providing_technologies = ["Netbackup"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Monitor Unsuccessful Backups] type = support -explanation = This search gives you the count and hostname of all the systems that had a backup failure each day +explanation = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. how_to_implement = To successfully implement this search you must be ingesting your backup logs. -known_false_positives = -providing_technologies = ["Netbackup"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen AWS Cross Account Activity] type = support -explanation = In this support search, we look for **AssumeRole** events where the requesting account is different from the requested account. The first and last times these events are seen are written to a lookup file. +explanation = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen AWS Provisioning Activity Sources] type = support -explanation = This search includes any event name that begins with "run" or "create," and then determines the first and last time these events were seen for each IP address that initiated the action. The search then consults a **GeoIP** database to determine the physical location of this IP address. This table outputs to a file. +explanation = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen AWS Regions] type = support -explanation = In this support search, we create a table of the first time (earliest) and most recent time (latest) that this region has been seen in our dataset, grouped by the value `awsRegion`. We only look for those events where an instance has been started. All of these entries will be added to the `previously_seen_aws_regions.csv` lookup file, which will act like a baseline for detections. Please validate the entries of region names in the lookup file. +explanation = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen Cloud Compute Creations By User] type = support -explanation = In this support search, we create a table of the earliest and latest time for each user that has created a cloud compute instance. +explanation = This search builds a table of previously seen users that have launched a cloud compute instance. how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = -providing_technologies = ["AWS", "Azure", "GCP"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen Cloud Compute Images] type = support -explanation = In this support search, we create a table of the earliest and latest time for each image id that has been seen. This table is then outputted to a csv file. +explanation = This search builds a table of previously seen images used to launch cloud compute instances how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = -providing_technologies = ["AWS", "Azure", "GCP"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen Cloud Compute Instance Types] type = support -explanation = In this support search, we create a table of the first time `firstTime` and most recent time `lastTime` that the compute type has been seen in our dataset. We only look for those events where an instance has been created. All of these entries will be added to the `previously_seen_cloud_compute_instance_types` lookup file, which will act as a baseline for detections. +explanation = This search builds a table of previously seen cloud compute instance types how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = -providing_technologies = ["AWS", "Azure", "GCP"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen Cloud Regions] type = support -explanation = In this support search, we create a table of the first time `firstTime` and most recent time `lastTime` that this region has been seen in our dataset, grouped by the region. We only look for those events where an instance has been started. All of these entries will be added to the `previously_seen_cloud_regions` lookup file, which will act like a baseline for detections. +explanation = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -known_false_positives = -providing_technologies = ["AWS", "Azure", "GCP"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen EC2 AMIs] type = support -explanation = In this support search, we create a table of the earliest and latest time that a specific AMI ID has been seen. This table is then outputted to a csv file. +explanation = This search builds a table of previously seen AMIs used to launch EC2 instances how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen EC2 Instance Types] type = support -explanation = In this support search, we create a table of the earliest and latest time that a specific EC2 instance type has been seen. The instanceType request field is not required and defaults to m1.small, so any time this field is null, the search defaults the field to m1.small. This table is then outputted to a csv file. +explanation = This search builds a table of previously seen EC2 instance types how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen EC2 Launches By User] type = support -explanation = In this support search, we create a table of the earliest and latest times that an ARN has launched a EC2 instance. This table is then outputted to a csv file. +explanation = This search builds a table of previously seen ARNs that have launched a EC2 instance. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen EC2 Modifications By User] type = support -explanation = In this support search, we create a table of the earliest and latest times that an ARN has modified a EC2 instance. The list of APIs that modify an EC2 are defined in the `ec2_modification_api_calls` macro for ease of use. This table is then outputted to a file. +explanation = This search builds a table of previously seen ARNs that have launched a EC2 instance. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously Seen Running Windows Services] type = support -explanation = In this support search, we look for Windows system-event code that indicates a status change of a Windows service. In this specific log event, the `param1` field represents the "service_name" and the `param2` represents the action/status of the service. This search will create a table of the first and last time as particular Windows service was seen to be in the `running` status. +explanation = This collects the services that have been started across your entire enterprise. how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -known_false_positives = -providing_technologies = ["Microsoft Windows"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously seen API call per user roles in CloudTrail] type = support -explanation = In this support search, we are looking for successful API calls made by user roles within your AWS infrastructure. The intent is to create an initial baseline cache of names of the API calls per security role for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of user role and the name of the API call. It is also worth noting that the role of a particular user is parsed as "userName" in the CloudTrail logs. +explanation = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously seen S3 bucket access by remote IP] type = support -explanation = In this support search, we are looking for successful S3 bucket-access attempts made from remote IPs. The intent is to create an initial baseline cache of remote IP addresses per bucket name for the previous 30 days--including the earliest and latest times seen in our dataset--grouped by the value of remote IP and the name of the S3 bucket. +explanation = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. -known_false_positives = -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously seen command line arguments] type = support -explanation = In this support search, we look for command-line arguments using the parameter `/c` to execute processes and create an initial baseline cache for the previous 30 days. This will include the earliest and latest times a particular command-line argument is seen in our dataset, grouped by the command-line value. +explanation = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. -known_false_positives = -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Previously seen users in CloudTrail] type = support -explanation = In this support search, we look for console login events by a particular user and create an initial baseline cache for the previous 30 days, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values. +explanation = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. -known_false_positives = n/a -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Systems Ready for Spectre-Meltdown Windows Patch] type = support -explanation = This search looks to see if a registry key was created at `HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat`. It will tell you when it was created and, if possible, what process created it. +explanation = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -known_false_positives = -providing_technologies = ["Carbon Black Response", "CrowdStrike Falcon", "Sysmon", "Tanium", "Ziften"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Update previously seen users in CloudTrail] type = support -explanation = In this support search, we look for console login events by a particular user to update the baseline cache of users/arns making the accesses, including the earliest and latest times, City, Region, and Country a particular user ARN is seen in our dataset, grouped by the ARN value. In cases where City and Region cannot be determined, the source IP address is substituted for these values. +explanation = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. -known_false_positives = n/a -providing_technologies = ["AWS"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Windows Updates Install Failures] type = support -explanation = This search gives you the count of the number of systems that attempted and failed to install a Windows update each day. +explanation = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. how_to_implement = You must be ingesting your Windows Update Logs -known_false_positives = -providing_technologies = ["Microsoft Windows"] +known_false_positives = not defined +providing_technologies = none [savedsearch://ESCU - Windows Updates Install Successes] type = support -explanation = This search gives you the count and name of all the systems that had a successful update applied each day +explanation = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. how_to_implement = You must be ingesting your Windows Update Logs -known_false_positives = -providing_technologies = ["Microsoft Windows"] +known_false_positives = not defined +providing_technologies = none ### END ESCU BASELINES ### \ No newline at end of file diff --git a/response_tasks/all_backup_logs_for_host.yml b/response_tasks/all_backup_logs_for_host.yml index 0437fd5701..6008ac5583 100644 --- a/response_tasks/all_backup_logs_for_host.yml +++ b/response_tasks/all_backup_logs_for_host.yml @@ -10,3 +10,6 @@ author: Rico Valdez, Splunk inputs: - dest search: '| search sourcetype="netbackup_logs" dest={dest}' +tags: + analytics_story: + - Monitor Backup Solution diff --git a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml index f43e42d0e9..77692a4e2e 100644 --- a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml +++ b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml @@ -15,3 +15,6 @@ search: sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIP as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip +tags: + analytics_story: + - Kubernetes Scanning Activity diff --git a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml index f634fc6df6..a6222a2fcc 100644 --- a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml +++ b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml @@ -13,3 +13,6 @@ inputs: search: '| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' +tags: + analytics_story: + - AWS Cross Account Activity diff --git a/response_tasks/aws_investigate_user_activities_by_arn.yml b/response_tasks/aws_investigate_user_activities_by_arn.yml index caa7a74ae2..a08a1f6743 100644 --- a/response_tasks/aws_investigate_user_activities_by_arn.yml +++ b/response_tasks/aws_investigate_user_activities_by_arn.yml @@ -15,3 +15,14 @@ inputs: search: '| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType' +tags: + analytics_story: + - AWS Cryptomining + - AWS Network ACL Activity + - Cloud Cryptomining + - Command and Control + - Suspicious AWS EC2 Activities + - Suspicious AWS Login Activities + - Suspicious AWS S3 Activities + - Suspicious AWS Traffic + - Unusual AWS EC2 Modifications diff --git a/response_tasks/aws_investigate_user_activities_by_source_user.yml b/response_tasks/aws_investigate_user_activities_by_source_user.yml index b138d68f30..c2dbbe06f8 100644 --- a/response_tasks/aws_investigate_user_activities_by_source_user.yml +++ b/response_tasks/aws_investigate_user_activities_by_source_user.yml @@ -13,3 +13,6 @@ inputs: search: '| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' +tags: + analytics_story: + - AWS Cross Account Activity diff --git a/response_tasks/aws_network_acl_details_from_id.yml b/response_tasks/aws_network_acl_details_from_id.yml index 22a52853d6..821a486c94 100644 --- a/response_tasks/aws_network_acl_details_from_id.yml +++ b/response_tasks/aws_network_acl_details_from_id.yml @@ -12,3 +12,8 @@ inputs: - networkAclId search: '| search sourcetype=aws:description id={networkAclId} | table id account_id vpc_id network_acl_entries{}.*' +tags: + analytics_story: + - AWS Network ACL Activity + - Command and Control + - Suspicious AWS Traffic diff --git a/response_tasks/aws_network_interface_details_via_resourceid.yml b/response_tasks/aws_network_interface_details_via_resourceid.yml index aec37847a5..ac876efd64 100644 --- a/response_tasks/aws_network_interface_details_via_resourceid.yml +++ b/response_tasks/aws_network_interface_details_via_resourceid.yml @@ -15,3 +15,8 @@ inputs: search: '| search sourcetype=aws:config resourceId={resourceId} | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp' +tags: + analytics_story: + - AWS Network ACL Activity + - Command and Control + - Suspicious AWS Traffic diff --git a/response_tasks/aws_s3_bucket_details_via_bucketname.yml b/response_tasks/aws_s3_bucket_details_via_bucketname.yml index be0bf69abf..cef02b7d78 100644 --- a/response_tasks/aws_s3_bucket_details_via_bucketname.yml +++ b/response_tasks/aws_s3_bucket_details_via_bucketname.yml @@ -15,3 +15,6 @@ inputs: - bucketName search: '| search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList' +tags: + analytics_story: + - Suspicious AWS S3 Activities diff --git a/response_tasks/gcp_kubernetes_activity_by_src_ip.yml b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml index c0b890a4f6..555a926e7c 100644 --- a/response_tasks/gcp_kubernetes_activity_by_src_ip.yml +++ b/response_tasks/gcp_kubernetes_activity_by_src_ip.yml @@ -19,3 +19,6 @@ search: sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type +tags: + analytics_story: + - Kubernetes Scanning Activity diff --git a/response_tasks/get_all_aws_activity_from_city.yml b/response_tasks/get_all_aws_activity_from_city.yml index ee8c514915..5e79c1cc66 100644 --- a/response_tasks/get_all_aws_activity_from_city.yml +++ b/response_tasks/get_all_aws_activity_from_city.yml @@ -17,3 +17,6 @@ search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode' +tags: + analytics_story: + - AWS Suspicious Provisioning Activities diff --git a/response_tasks/get_all_aws_activity_from_country.yml b/response_tasks/get_all_aws_activity_from_country.yml index 9bcf654f1e..883f6ccb66 100644 --- a/response_tasks/get_all_aws_activity_from_country.yml +++ b/response_tasks/get_all_aws_activity_from_country.yml @@ -17,3 +17,6 @@ search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode' +tags: + analytics_story: + - AWS Suspicious Provisioning Activities diff --git a/response_tasks/get_all_aws_activity_from_ip_address.yml b/response_tasks/get_all_aws_activity_from_ip_address.yml index 82b3f593c9..8c7f10a917 100644 --- a/response_tasks/get_all_aws_activity_from_ip_address.yml +++ b/response_tasks/get_all_aws_activity_from_ip_address.yml @@ -17,3 +17,10 @@ search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode' +tags: + analytics_story: + - AWS Network ACL Activity + - AWS Suspicious Provisioning Activities + - Command and Control + - Suspicious AWS S3 Activities + - Suspicious AWS Traffic diff --git a/response_tasks/get_all_aws_activity_from_region.yml b/response_tasks/get_all_aws_activity_from_region.yml index 1db6e7e6c2..3a85824785 100644 --- a/response_tasks/get_all_aws_activity_from_region.yml +++ b/response_tasks/get_all_aws_activity_from_region.yml @@ -17,3 +17,6 @@ search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode' +tags: + analytics_story: + - AWS Suspicious Provisioning Activities diff --git a/response_tasks/get_authentication_logs_for_endpoint.yml b/response_tasks/get_authentication_logs_for_endpoint.yml index ad5861aa26..f1c27cb433 100644 --- a/response_tasks/get_authentication_logs_for_endpoint.yml +++ b/response_tasks/get_authentication_logs_for_endpoint.yml @@ -12,3 +12,45 @@ inputs: search: '| tstats count from datamodel=Authentication where Authentication.dest={dest} by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")`' +tags: + analytics_story: + - AWS Network ACL Activity + - Account Monitoring and Controls + - Apache Struts Vulnerability + - Brand Monitoring + - ColdRoot MacOS RAT + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - Data Protection + - Disabling Security Tools + - Dynamic DNS + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Host Redirection + - Lateral Movement + - Malicious PowerShell + - Monitor for Unauthorized Software + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Router and Infrastructure Security + - SQL Injection + - SamSam Ransomware + - Spectre And Meltdown Vulnerabilities + - Suspicious AWS Traffic + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious Emails + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual Processes + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_backup_logs_for_endpoint.yml b/response_tasks/get_backup_logs_for_endpoint.yml index 96638e2beb..eb2042594e 100644 --- a/response_tasks/get_backup_logs_for_endpoint.yml +++ b/response_tasks/get_backup_logs_for_endpoint.yml @@ -10,3 +10,7 @@ inputs: - dest search: '| search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature' +tags: + analytics_story: + - Ransomware + - SamSam Ransomware diff --git a/response_tasks/get_certificate_logs_for_a_domain.yml b/response_tasks/get_certificate_logs_for_a_domain.yml index b4a9420088..0b47390142 100644 --- a/response_tasks/get_certificate_logs_for_a_domain.yml +++ b/response_tasks/get_certificate_logs_for_a_domain.yml @@ -17,3 +17,6 @@ search: '| tstats `summariesonly` count min(_time) as firstTime max(_time) as la All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +tags: + analytics_story: + - Common Phishing Frameworks diff --git a/response_tasks/get_dns_server_history_for_a_host.yml b/response_tasks/get_dns_server_history_for_a_host.yml index 7ac551a567..d948a5a6d1 100644 --- a/response_tasks/get_dns_server_history_for_a_host.yml +++ b/response_tasks/get_dns_server_history_for_a_host.yml @@ -14,3 +14,15 @@ inputs: search: '| search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count' +tags: + analytics_story: + - AWS Network ACL Activity + - Command and Control + - DNS Hijacking + - Data Protection + - Dynamic DNS + - Hidden Cobra Malware + - Host Redirection + - Prohibited Traffic Allowed or Protocol Mismatch + - Suspicious AWS Traffic + - Suspicious DNS Traffic diff --git a/response_tasks/get_dns_traffic_ratio.yml b/response_tasks/get_dns_traffic_ratio.yml index 8c3f05a4bf..bbd2f55cd5 100644 --- a/response_tasks/get_dns_traffic_ratio.yml +++ b/response_tasks/get_dns_traffic_ratio.yml @@ -16,3 +16,12 @@ search: '| tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_ sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval ratio = (bytes_out/bytes_in) | table ratio' +tags: + analytics_story: + - AWS Network ACL Activity + - Command and Control + - Data Protection + - Dynamic DNS + - Hidden Cobra Malware + - Suspicious AWS Traffic + - Suspicious DNS Traffic diff --git a/response_tasks/get_ec2_instance_details_by_instanceid.yml b/response_tasks/get_ec2_instance_details_by_instanceid.yml index ad4f420767..28cbab449e 100644 --- a/response_tasks/get_ec2_instance_details_by_instanceid.yml +++ b/response_tasks/get_ec2_instance_details_by_instanceid.yml @@ -18,3 +18,9 @@ search: '| search sourcetype="aws:description" source="*:ec2_instances"| dedup i instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC' +tags: + analytics_story: + - AWS Cryptomining + - Cloud Cryptomining + - Suspicious AWS EC2 Activities + - Unusual AWS EC2 Modifications diff --git a/response_tasks/get_ec2_launch_details.yml b/response_tasks/get_ec2_launch_details.yml index 7681171576..a43d352f23 100644 --- a/response_tasks/get_ec2_launch_details.yml +++ b/response_tasks/get_ec2_launch_details.yml @@ -15,3 +15,8 @@ search: '| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{ responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName' +tags: + analytics_story: + - AWS Cryptomining + - Cloud Cryptomining + - Suspicious AWS EC2 Activities diff --git a/response_tasks/get_email_info.yml b/response_tasks/get_email_info.yml index de81c4b03c..09ef1ec4b5 100644 --- a/response_tasks/get_email_info.yml +++ b/response_tasks/get_email_info.yml @@ -10,3 +10,7 @@ author: Bhavin Patel, Splunk inputs: - message_id search: '| from datamodel Email.All_Email | search message_id={message_id}' +tags: + analytics_story: + - Brand Monitoring + - Suspicious Emails diff --git a/response_tasks/get_emails_from_specific_sender.yml b/response_tasks/get_emails_from_specific_sender.yml index 318a75d760..57630e5ee2 100644 --- a/response_tasks/get_emails_from_specific_sender.yml +++ b/response_tasks/get_emails_from_specific_sender.yml @@ -11,3 +11,8 @@ author: David Dorsey, Splunk inputs: - src_user search: '| from datamodel Email.All_Email | search src_user={src_user}' +tags: + analytics_story: + - Brand Monitoring + - Suspicious Emails + - Web Fraud Detection diff --git a/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml index ac496cc266..1960efe6fd 100644 --- a/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml +++ b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml @@ -15,3 +15,6 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`' +tags: + analytics_story: + - Asset Tracking diff --git a/response_tasks/get_logon_rights_modifications_for_endpoint.yml b/response_tasks/get_logon_rights_modifications_for_endpoint.yml index 8fac127169..5df2fbf971 100644 --- a/response_tasks/get_logon_rights_modifications_for_endpoint.yml +++ b/response_tasks/get_logon_rights_modifications_for_endpoint.yml @@ -12,3 +12,6 @@ inputs: search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest={dest} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature' +tags: + analytics_story: + - Account Monitoring and Controls diff --git a/response_tasks/get_logon_rights_modifications_for_user.yml b/response_tasks/get_logon_rights_modifications_for_user.yml index 88c2b6612a..d31659ada4 100644 --- a/response_tasks/get_logon_rights_modifications_for_user.yml +++ b/response_tasks/get_logon_rights_modifications_for_user.yml @@ -12,3 +12,6 @@ inputs: search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user={user} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature' +tags: + analytics_story: + - Account Monitoring and Controls diff --git a/response_tasks/get_notable_history.yml b/response_tasks/get_notable_history.yml index 722af7abed..e08af91d68 100644 --- a/response_tasks/get_notable_history.yml +++ b/response_tasks/get_notable_history.yml @@ -12,3 +12,62 @@ inputs: - dest search: '| search `notable` | search dest={dest} | table _time, rule_name, owner, priority, severity, status_description' +tags: + analytics_story: + - AWS Cross Account Activity + - AWS Cryptomining + - AWS Network ACL Activity + - AWS User Monitoring + - Account Monitoring and Controls + - Apache Struts Vulnerability + - Asset Tracking + - Brand Monitoring + - Cloud Cryptomining + - ColdRoot MacOS RAT + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - DNS Amplification Attacks + - Data Protection + - Disabling Security Tools + - Dynamic DNS + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Host Redirection + - JBoss Vulnerability + - Kubernetes Scanning Activity + - Lateral Movement + - Malicious PowerShell + - Monitor Backup Solution + - Monitor for Unauthorized Software + - Monitor for Updates + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Router and Infrastructure Security + - SQL Injection + - SamSam Ransomware + - Spectre And Meltdown Vulnerabilities + - Splunk Enterprise Vulnerability + - Splunk Enterprise Vulnerability CVE-2018-11409 + - Suspicious AWS EC2 Activities + - Suspicious AWS S3 Activities + - Suspicious AWS Traffic + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious Emails + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual AWS EC2 Modifications + - Unusual Processes + - Use of Cleartext Protocols + - Web Fraud Detection + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_notable_info.yml b/response_tasks/get_notable_info.yml index fc44212fe8..9f392da726 100644 --- a/response_tasks/get_notable_info.yml +++ b/response_tasks/get_notable_info.yml @@ -12,3 +12,58 @@ inputs: - event_id search: '| search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description' +tags: + analytics_story: + - AWS Cryptomining + - AWS Network ACL Activity + - AWS User Monitoring + - Account Monitoring and Controls + - Apache Struts Vulnerability + - Asset Tracking + - Brand Monitoring + - Cloud Cryptomining + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - DNS Amplification Attacks + - Data Protection + - Disabling Security Tools + - Dynamic DNS + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Host Redirection + - JBoss Vulnerability + - Kubernetes Scanning Activity + - Lateral Movement + - Malicious PowerShell + - Monitor for Unauthorized Software + - Monitor for Updates + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Router and Infrastructure Security + - SQL Injection + - SamSam Ransomware + - Spectre And Meltdown Vulnerabilities + - Splunk Enterprise Vulnerability + - Splunk Enterprise Vulnerability CVE-2018-11409 + - Suspicious AWS EC2 Activities + - Suspicious AWS S3 Activities + - Suspicious AWS Traffic + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious Emails + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual Processes + - Use of Cleartext Protocols + - Web Fraud Detection + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_parent_process_info.yml b/response_tasks/get_parent_process_info.yml index 4a83624bb6..1eb8425219 100644 --- a/response_tasks/get_parent_process_info.yml +++ b/response_tasks/get_parent_process_info.yml @@ -17,3 +17,33 @@ search: '| tstats `summariesonly` count values(Processes.process) as process min as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' +tags: + analytics_story: + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - Disabling Security Tools + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Lateral Movement + - Malicious PowerShell + - Monitor for Unauthorized Software + - Netsh Abuse + - Orangeworm Attack Group + - Phishing Payloads + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - SamSam Ransomware + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual Processes + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_process_file_activity.yml b/response_tasks/get_process_file_activity.yml index 99c395e87c..306d2293ad 100644 --- a/response_tasks/get_process_file_activity.yml +++ b/response_tasks/get_process_file_activity.yml @@ -15,3 +15,6 @@ search: '| tstats `security_content_summariesonly` values(Filesystem.file_name) from datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path' +tags: + analytics_story: + - DHS Report TA18-074A diff --git a/response_tasks/get_process_info.yml b/response_tasks/get_process_info.yml index 271c5b4642..fcccc68d69 100644 --- a/response_tasks/get_process_info.yml +++ b/response_tasks/get_process_info.yml @@ -15,3 +15,35 @@ search: '| tstats `security_content_summariesonly` count min(_time) max(_time) lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` ' +tags: + analytics_story: + - AWS Network ACL Activity + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - Data Protection + - Disabling Security Tools + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Lateral Movement + - Malicious PowerShell + - Monitor for Unauthorized Software + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - SamSam Ransomware + - Suspicious AWS Traffic + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual Processes + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_process_information_for_port_activity.yml b/response_tasks/get_process_information_for_port_activity.yml index d1d39c7357..01f48a736b 100644 --- a/response_tasks/get_process_information_for_port_activity.yml +++ b/response_tasks/get_process_information_for_port_activity.yml @@ -17,3 +17,16 @@ search: '| tstats `security_content_summariesonly` count min(_time) max(_time) [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]' +tags: + analytics_story: + - AWS Network ACL Activity + - Command and Control + - DHS Report TA18-074A + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Lateral Movement + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - SamSam Ransomware + - Suspicious AWS Traffic + - Use of Cleartext Protocols diff --git a/response_tasks/get_process_registry_activity.yml b/response_tasks/get_process_registry_activity.yml index cba445e477..d67d0a3ffb 100644 --- a/response_tasks/get_process_registry_activity.yml +++ b/response_tasks/get_process_registry_activity.yml @@ -15,3 +15,6 @@ search: '| tstats `security_content_summariesonly` values(Registry.registry_key_ as process_id from datamodel=Endpoint.Registry where Registry.process_id={process_id} AND Registry.dest={dest} by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path' +tags: + analytics_story: + - DHS Report TA18-074A diff --git a/response_tasks/get_process_responsible_for_the_dns_traffic.yml b/response_tasks/get_process_responsible_for_the_dns_traffic.yml index 78a0353925..0607c901c5 100644 --- a/response_tasks/get_process_responsible_for_the_dns_traffic.yml +++ b/response_tasks/get_process_responsible_for_the_dns_traffic.yml @@ -19,3 +19,13 @@ search: '| tstats `security_content_summariesonly` count min(_time) max(_time) [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]' +tags: + analytics_story: + - AWS Network ACL Activity + - Brand Monitoring + - Command and Control + - Data Protection + - Dynamic DNS + - Hidden Cobra Malware + - Suspicious AWS Traffic + - Suspicious DNS Traffic diff --git a/response_tasks/get_registry_activities.yml b/response_tasks/get_registry_activities.yml index ea5c57a116..91c46f85cb 100644 --- a/response_tasks/get_registry_activities.yml +++ b/response_tasks/get_registry_activities.yml @@ -18,3 +18,16 @@ search: '| tstats `security_content_summariesonly` values(Registry.registry_path count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`]' +tags: + analytics_story: + - DHS Report TA18-074A + - 'Emotet Malware DHS Report TA18-201A ' + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Ransomware + - Suspicious Command-Line Executions + - Suspicious MSHTA Activity + - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Persistence Techniques + - Windows Privilege Escalation diff --git a/response_tasks/get_risk_modifiers_for_endpoint.yml b/response_tasks/get_risk_modifiers_for_endpoint.yml index 5c36c8c55a..26b5bea1e5 100644 --- a/response_tasks/get_risk_modifiers_for_endpoint.yml +++ b/response_tasks/get_risk_modifiers_for_endpoint.yml @@ -13,3 +13,53 @@ inputs: search: '| from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' +tags: + analytics_story: + - AWS Network ACL Activity + - Account Monitoring and Controls + - Apache Struts Vulnerability + - Brand Monitoring + - ColdRoot MacOS RAT + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - DNS Amplification Attacks + - Data Protection + - Disabling Security Tools + - Dynamic DNS + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Host Redirection + - JBoss Vulnerability + - Kubernetes Scanning Activity + - Lateral Movement + - Malicious PowerShell + - Monitor Backup Solution + - Monitor for Unauthorized Software + - Monitor for Updates + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Router and Infrastructure Security + - SQL Injection + - SamSam Ransomware + - Spectre And Meltdown Vulnerabilities + - Splunk Enterprise Vulnerability + - Splunk Enterprise Vulnerability CVE-2018-11409 + - Suspicious AWS Traffic + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious Emails + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual Processes + - Use of Cleartext Protocols + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_risk_modifiers_for_user.yml b/response_tasks/get_risk_modifiers_for_user.yml index e7b13eb2ea..ab376cb744 100644 --- a/response_tasks/get_risk_modifiers_for_user.yml +++ b/response_tasks/get_risk_modifiers_for_user.yml @@ -13,3 +13,47 @@ inputs: search: '| from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` ' +tags: + analytics_story: + - AWS Network ACL Activity + - Account Monitoring and Controls + - Apache Struts Vulnerability + - Brand Monitoring + - ColdRoot MacOS RAT + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - DNS Amplification Attacks + - Data Protection + - Disabling Security Tools + - Dynamic DNS + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Host Redirection + - Lateral Movement + - Malicious PowerShell + - Monitor Backup Solution + - Monitor for Unauthorized Software + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Router and Infrastructure Security + - SamSam Ransomware + - Spectre And Meltdown Vulnerabilities + - Suspicious AWS Traffic + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious Emails + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual Processes + - Use of Cleartext Protocols + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_sysmon_wmi_activity_for_host.yml b/response_tasks/get_sysmon_wmi_activity_for_host.yml index d220bb0277..ec20c01540 100644 --- a/response_tasks/get_sysmon_wmi_activity_for_host.yml +++ b/response_tasks/get_sysmon_wmi_activity_for_host.yml @@ -14,3 +14,7 @@ inputs: search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter +tags: + analytics_story: + - Ransomware + - Suspicious WMI Use diff --git a/response_tasks/get_update_logs_for_endpoint.yml b/response_tasks/get_update_logs_for_endpoint.yml index ca5608cf9d..2011cd4e71 100644 --- a/response_tasks/get_update_logs_for_endpoint.yml +++ b/response_tasks/get_update_logs_for_endpoint.yml @@ -10,3 +10,9 @@ inputs: - dest search: '| from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest}' +tags: + analytics_story: + - 'Emotet Malware DHS Report TA18-201A ' + - Monitor for Unauthorized Software + - Ransomware + - SamSam Ransomware diff --git a/response_tasks/get_user_information_from_identity_table.yml b/response_tasks/get_user_information_from_identity_table.yml index f411283077..6f9435f45a 100644 --- a/response_tasks/get_user_information_from_identity_table.yml +++ b/response_tasks/get_user_information_from_identity_table.yml @@ -10,3 +10,49 @@ inputs: - user search: '| `identities` | search identity={user} | table _time, identity, first, last, email, category, watchlist' +tags: + analytics_story: + - AWS Cryptomining + - AWS Network ACL Activity + - Account Monitoring and Controls + - Apache Struts Vulnerability + - Brand Monitoring + - Cloud Cryptomining + - ColdRoot MacOS RAT + - Collection and Staging + - Command and Control + - DHS Report TA18-074A + - Data Protection + - Disabling Security Tools + - Dynamic DNS + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - Host Redirection + - Lateral Movement + - Malicious PowerShell + - Monitor for Unauthorized Software + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Router and Infrastructure Security + - SamSam Ransomware + - Spectre And Meltdown Vulnerabilities + - Suspicious AWS EC2 Activities + - Suspicious AWS S3 Activities + - Suspicious AWS Traffic + - Suspicious Command-Line Executions + - Suspicious DNS Traffic + - Suspicious Emails + - Suspicious MSHTA Activity + - Suspicious WMI Use + - Suspicious Windows Registry Activities + - Unusual Processes + - Use of Cleartext Protocols + - Windows Defense Evasion Tactics + - Windows File Extension and Association Abuse + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation + - Windows Service Abuse diff --git a/response_tasks/get_vulnerability_logs_for_endpoint.yml b/response_tasks/get_vulnerability_logs_for_endpoint.yml index f6ff538252..0d86c377fc 100644 --- a/response_tasks/get_vulnerability_logs_for_endpoint.yml +++ b/response_tasks/get_vulnerability_logs_for_endpoint.yml @@ -9,3 +9,14 @@ author: David Dorsey, Splunk inputs: - dest search: '| from datamodel Vulnerabilities.Vulnerabilities | search dest={dest}' +tags: + analytics_story: + - ColdRoot MacOS RAT + - DHS Report TA18-074A + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - JBoss Vulnerability + - Monitor for Unauthorized Software + - Ransomware + - SamSam Ransomware + - Windows Log Manipulation diff --git a/response_tasks/get_web_session_information_via_session_id.yml b/response_tasks/get_web_session_information_via_session_id.yml index c561f6dc29..a196ae731f 100644 --- a/response_tasks/get_web_session_information_via_session_id.yml +++ b/response_tasks/get_web_session_information_via_session_id.yml @@ -14,3 +14,6 @@ inputs: - session_id search: '| search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) by src_ip status' +tags: + analytics_story: + - Web Fraud Detection diff --git a/response_tasks/investigate_aws_activities_via_region_name.yml b/response_tasks/investigate_aws_activities_via_region_name.yml index 859e5c9de3..2c7b4d9a04 100644 --- a/response_tasks/investigate_aws_activities_via_region_name.yml +++ b/response_tasks/investigate_aws_activities_via_region_name.yml @@ -13,3 +13,9 @@ inputs: - awsRegion search: '| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId' +tags: + analytics_story: + - AWS Cryptomining + - Cloud Cryptomining + - Suspicious AWS EC2 Activities + - Suspicious AWS S3 Activities diff --git a/response_tasks/investigate_aws_ecr_container_listing_activity.yml b/response_tasks/investigate_aws_ecr_container_listing_activity.yml index 85009637fc..435c5c701a 100644 --- a/response_tasks/investigate_aws_ecr_container_listing_activity.yml +++ b/response_tasks/investigate_aws_ecr_container_listing_activity.yml @@ -18,3 +18,6 @@ search: '|tstats count min(_time) as firstTime max(_time) as lastTime FROM datam "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1' +tags: + analytics_story: + - Container Implantation Monitoring and Investigation diff --git a/response_tasks/investigate_aws_user_activities_by_user_field.yml b/response_tasks/investigate_aws_user_activities_by_user_field.yml index 82e1f14b4a..eaf8bfd9bc 100644 --- a/response_tasks/investigate_aws_user_activities_by_user_field.yml +++ b/response_tasks/investigate_aws_user_activities_by_user_field.yml @@ -14,3 +14,6 @@ inputs: - user search: '| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType ' +tags: + analytics_story: + - AWS User Monitoring diff --git a/response_tasks/investigate_cloud_compute_instance_activities.yml b/response_tasks/investigate_cloud_compute_instance_activities.yml index 93743435f3..7f397bad95 100644 --- a/response_tasks/investigate_cloud_compute_instance_activities.yml +++ b/response_tasks/investigate_cloud_compute_instance_activities.yml @@ -10,3 +10,6 @@ inputs: - dest search: '| from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields - _*' +tags: + analytics_story: + - Cloud Cryptomining diff --git a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml index 251dc84b84..fd0ffd8e6c 100644 --- a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml +++ b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml @@ -14,3 +14,6 @@ search: '| tstats count `security_content_summariesonly` earliest(_time) as firs where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")`' +tags: + analytics_story: + - Credential Dumping diff --git a/response_tasks/investigate_network_traffic_from_src_ip.yml b/response_tasks/investigate_network_traffic_from_src_ip.yml index 87bcc2731c..47f5a8a820 100644 --- a/response_tasks/investigate_network_traffic_from_src_ip.yml +++ b/response_tasks/investigate_network_traffic_from_src_ip.yml @@ -10,3 +10,7 @@ author: David Dorsey, Splunk inputs: - src_ip search: '| from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip}' +tags: + analytics_story: + - ColdRoot MacOS RAT + - Splunk Enterprise Vulnerability CVE-2018-11409 diff --git a/response_tasks/investigate_okta_activity_by_app.yml b/response_tasks/investigate_okta_activity_by_app.yml index 2597df23ee..83554e6648 100644 --- a/response_tasks/investigate_okta_activity_by_app.yml +++ b/response_tasks/investigate_okta_activity_by_app.yml @@ -10,3 +10,6 @@ inputs: search: eventtype=okta_log app={app} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason +tags: + analytics_story: + - Suspicious Okta Activity diff --git a/response_tasks/investigate_okta_activity_by_ip_address.yml b/response_tasks/investigate_okta_activity_by_ip_address.yml index 24158fc3af..4216491b2a 100644 --- a/response_tasks/investigate_okta_activity_by_ip_address.yml +++ b/response_tasks/investigate_okta_activity_by_ip_address.yml @@ -10,3 +10,6 @@ inputs: search: eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason +tags: + analytics_story: + - Suspicious Okta Activity diff --git a/response_tasks/investigate_pass_the_hash_attempts.yml b/response_tasks/investigate_pass_the_hash_attempts.yml index b22e2e2ca6..cba30c704f 100644 --- a/response_tasks/investigate_pass_the_hash_attempts.yml +++ b/response_tasks/investigate_pass_the_hash_attempts.yml @@ -15,3 +15,6 @@ inputs: search: '`wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)`' +tags: + analytics_story: + - Credential Dumping diff --git a/response_tasks/investigate_pass_the_ticket_attempts.yml b/response_tasks/investigate_pass_the_ticket_attempts.yml index fc7b48a427..7ca5f470c9 100644 --- a/response_tasks/investigate_pass_the_ticket_attempts.yml +++ b/response_tasks/investigate_pass_the_ticket_attempts.yml @@ -16,3 +16,6 @@ search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=use "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user' +tags: + analytics_story: + - Credential Dumping diff --git a/response_tasks/investigate_previous_unseen_user.yml b/response_tasks/investigate_previous_unseen_user.yml index 3b906920f8..56ac2e87e5 100644 --- a/response_tasks/investigate_previous_unseen_user.yml +++ b/response_tasks/investigate_previous_unseen_user.yml @@ -17,3 +17,6 @@ search: '| tstats count `security_content_summariesonly` earliest(_time) as firs as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")`' +tags: + analytics_story: + - Credential Dumping diff --git a/response_tasks/investigate_successful_remote_desktop_authentications.yml b/response_tasks/investigate_successful_remote_desktop_authentications.yml index 8d761d71d4..41f4407bec 100644 --- a/response_tasks/investigate_successful_remote_desktop_authentications.yml +++ b/response_tasks/investigate_successful_remote_desktop_authentications.yml @@ -16,3 +16,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| table firstTime lastTime src src_nt_domain dest user app count | sort count' +tags: + analytics_story: + - Hidden Cobra Malware + - Lateral Movement + - SamSam Ransomware diff --git a/response_tasks/investigate_suspicious_strings_in_http_header.yml b/response_tasks/investigate_suspicious_strings_in_http_header.yml index af4d1a4a0d..e4d29c4bd2 100644 --- a/response_tasks/investigate_suspicious_strings_in_http_header.yml +++ b/response_tasks/investigate_suspicious_strings_in_http_header.yml @@ -21,3 +21,6 @@ search: '| search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url' +tags: + analytics_story: + - Apache Struts Vulnerability diff --git a/response_tasks/investigate_user_activities_in_all_cloud_regions.yml b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml index 8e016413f7..e9b0624029 100644 --- a/response_tasks/investigate_user_activities_in_all_cloud_regions.yml +++ b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml @@ -12,3 +12,6 @@ inputs: - src_user search: '| from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | fields - _*' +tags: + analytics_story: + - Cloud Cryptomining diff --git a/response_tasks/investigate_user_activities_in_okta.yml b/response_tasks/investigate_user_activities_in_okta.yml index a31571d31e..97132725af 100644 --- a/response_tasks/investigate_user_activities_in_okta.yml +++ b/response_tasks/investigate_user_activities_in_okta.yml @@ -10,3 +10,6 @@ inputs: search: eventtype=okta_log user={user} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason +tags: + analytics_story: + - Suspicious Okta Activity diff --git a/response_tasks/investigate_user_activities_in_single_cloud_region.yml b/response_tasks/investigate_user_activities_in_single_cloud_region.yml index 6153826ae6..e3c3491f19 100644 --- a/response_tasks/investigate_user_activities_in_single_cloud_region.yml +++ b/response_tasks/investigate_user_activities_in_single_cloud_region.yml @@ -12,3 +12,6 @@ inputs: - src_user search: '| from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} | fields - _*' +tags: + analytics_story: + - Cloud Cryptomining diff --git a/response_tasks/investigate_web_activity_from_host.yml b/response_tasks/investigate_web_activity_from_host.yml index 033161bee5..18667da5df 100644 --- a/response_tasks/investigate_web_activity_from_host.yml +++ b/response_tasks/investigate_web_activity_from_host.yml @@ -11,3 +11,25 @@ author: Bhavin Patel, Splunk inputs: - dest search: '| from datamodel Web.Web | search src={dest}' +tags: + analytics_story: + - Brand Monitoring + - DHS Report TA18-074A + - Disabling Security Tools + - 'Emotet Malware DHS Report TA18-201A ' + - Hidden Cobra Malware + - JBoss Vulnerability + - Monitor for Unauthorized Software + - Netsh Abuse + - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Ransomware + - SamSam Ransomware + - Suspicious Command-Line Executions + - Suspicious Emails + - Suspicious MSHTA Activity + - Suspicious Windows Registry Activities + - Unusual Processes + - Windows Log Manipulation + - Windows Persistence Techniques + - Windows Privilege Escalation diff --git a/response_tasks/investigate_web_activity_from_src_ip.yml b/response_tasks/investigate_web_activity_from_src_ip.yml index c151ae28c3..0aac0b5eff 100644 --- a/response_tasks/investigate_web_activity_from_src_ip.yml +++ b/response_tasks/investigate_web_activity_from_src_ip.yml @@ -11,3 +11,8 @@ author: David Dorsey, Splunk inputs: - src_ip search: '| from datamodel Web.Web | search src={src_ip}' +tags: + analytics_story: + - ColdRoot MacOS RAT + - Dynamic DNS + - Splunk Enterprise Vulnerability CVE-2018-11409 diff --git a/response_tasks/investigate_web_posts_from_src.yml b/response_tasks/investigate_web_posts_from_src.yml index 3a10c2872b..d16985c53a 100644 --- a/response_tasks/investigate_web_posts_from_src.yml +++ b/response_tasks/investigate_web_posts_from_src.yml @@ -13,3 +13,6 @@ inputs: search: '| tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "{src}") and like(http_method, "POST")' +tags: + analytics_story: + - Apache Struts Vulnerability diff --git a/stories/container_implantation_monitoring_and_investigation.yml b/stories/container_implantation_monitoring_and_investigation.yml index 4b2d8ce07f..66db77b1f8 100644 --- a/stories/container_implantation_monitoring_and_investigation.yml +++ b/stories/container_implantation_monitoring_and_investigation.yml @@ -20,7 +20,7 @@ type: ESCU references: - https://github.com/splunk/cloud-datamodel-security-research tags: - analytics_story: Container Implantation Monitoring & Investigation + analytics_story: Container Implantation Monitoring and Investigation usecase: Security Monitoring category: - Cloud Security diff --git a/stories/emotet_malware__dhs_report_ta18_201a_.yml b/stories/emotet_malware__dhs_report_ta18_201a_.yml index 0acf0347db..4f26827dfa 100644 --- a/stories/emotet_malware__dhs_report_ta18_201a_.yml +++ b/stories/emotet_malware__dhs_report_ta18_201a_.yml @@ -31,7 +31,7 @@ references: - https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf - https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html tags: - analytics_story: Emotet Malware (DHS Report TA18-201A) + analytics_story: 'Emotet Malware DHS Report TA18-201A ' usecase: Advanced Threat Detection category: - Malware diff --git a/stories/router_and_infrastructure_security.yml b/stories/router_and_infrastructure_security.yml index ed86080e89..b72afd01ba 100644 --- a/stories/router_and_infrastructure_security.yml +++ b/stories/router_and_infrastructure_security.yml @@ -21,7 +21,7 @@ references: - https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html - https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html tags: - analytics_story: Router & Infrastructure Security + analytics_story: Router and Infrastructure Security usecase: Security Monitoring category: - Best Practices From 98aca64eba47b7df0c4888069f10faa6408a87b5 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 7 May 2020 18:43:04 +0200 Subject: [PATCH 17/93] new generate script --- bin/doc-gen.py | 173 +- .../splunk_docs_categories.j2 | 65 + bin/jinja2_templates/stories_categories.j2 | 68 + docs/splunk_docs_categories.wiki | 5052 +++++++------- docs/stories_categories.md | 5833 +++++++---------- 5 files changed, 5142 insertions(+), 6049 deletions(-) create mode 100644 bin/jinja2_templates/splunk_docs_categories.j2 create mode 100644 bin/jinja2_templates/stories_categories.j2 diff --git a/bin/doc-gen.py b/bin/doc-gen.py index 464491504c..8e1cdf0a12 100644 --- a/bin/doc-gen.py +++ b/bin/doc-gen.py @@ -3,6 +3,152 @@ import yaml import argparse from os import path import sys +import re +from jinja2 import Environment, FileSystemLoader + + +def load_objects(file_path): + files = [] + manifest_files = path.join(path.expanduser(REPO_PATH), file_path) + + for file in sorted(glob.glob(manifest_files)): + files.append(load_file(file)) + + return files + + +def load_file(file_path): + with open(file_path, 'r') as stream: + try: + file = list(yaml.safe_load_all(stream))[0] + except yaml.YAMLError as exc: + print(exc) + sys.exit("ERROR: reading {0}".format(file_path)) + return file + + +def prepare_content(stories, detections): + + # enrich stories with information from detections: data_models, mitre_ids, kill_chain_phases, nists + sto_to_data_models = {} + sto_to_mitre_attack_ids = {} + sto_to_kill_chain_phases = {} + sto_to_ciss = {} + sto_to_nists = {} + sto_to_det = {} + for detection in detections: + if 'analytics_story' in detection['tags']: + for story in detection['tags']['analytics_story']: + if story in sto_to_det.keys(): + sto_to_det[story].add(detection['name']) + else: + sto_to_det[story] = {detection['name']} + + data_model = parse_data_models_from_search(detection['search']) + if data_model: + if story in sto_to_data_models.keys(): + sto_to_data_models[story].add(data_model) + else: + sto_to_data_models[story] = {data_model} + + if 'mitre_attack_id' in detection['tags']: + if story in sto_to_mitre_attack_ids.keys(): + for mitre_attack_id in detection['tags']['mitre_attack_id']: + sto_to_mitre_attack_ids[story].add(mitre_attack_id) + else: + for mitre_attack_id in detection['tags']['mitre_attack_id']: + sto_to_mitre_attack_ids[story] = {mitre_attack_id} + + if 'kill_chain_phases' in detection['tags']: + if story in sto_to_kill_chain_phases.keys(): + for kill_chain in detection['tags']['kill_chain_phases']: + sto_to_kill_chain_phases[story].add(kill_chain) + else: + for kill_chain in detection['tags']['kill_chain_phases']: + sto_to_kill_chain_phases[story] = {kill_chain} + + if 'cis20' in detection['tags']: + if story in sto_to_ciss.keys(): + for cis in detection['tags']['cis20']: + sto_to_ciss[story].add(cis) + else: + for cis in detection['tags']['cis20']: + sto_to_ciss[story] = {cis} + + if 'nist' in detection['tags']: + if story in sto_to_nists.keys(): + for nist in detection['tags']['nist']: + sto_to_nists[story].add(nist) + else: + for nist in detection['tags']['nist']: + sto_to_nists[story] = {nist} + + for story in stories: + story['detections'] = sorted(sto_to_det[story['name']]) + if story['name'] in sto_to_data_models: + story['data_models'] = sorted(sto_to_data_models[story['name']]) + if story['name'] in sto_to_mitre_attack_ids: + story['mitre_attack_ids'] = sorted(sto_to_mitre_attack_ids[story['name']]) + if story['name'] in sto_to_kill_chain_phases: + story['kill_chain_phases'] = sorted(sto_to_kill_chain_phases[story['name']]) + if story['name'] in sto_to_ciss: + story['ciss'] = sorted(sto_to_ciss[story['name']]) + if story['name'] in sto_to_nists: + story['nists'] = sorted(sto_to_nists[story['name']]) + + #sort stories into categories + categories = [] + category_names = set() + for story in stories: + if 'category' in story['tags']: + category_names.add(story['tags']['category'][0]) + + for category_name in sorted(category_names): + new_category = {} + new_category['name'] = category_name + new_category['stories'] = [] + categories.append(new_category) + + for story in stories: + for category in categories: + if category['name'] == story['tags']['category'][0]: + category['stories'].append(story) + + return categories + + +def write_splunk_docs(stories, detections, OUTPUT_DIR): + + categories = prepare_content(stories, detections) + + j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), + trim_blocks=True) + template = j2_env.get_template('splunk_docs_categories.j2') + output_path = OUTPUT_DIR + "/splunk_docs_categories.wiki" + output = template.render(categories=categories) + with open(output_path, 'w') as f: + f.write(output) + + return len(stories), output_path + + +def write_markdown_docs(stories, detections, OUTPUT_DIR): + + categories = prepare_content(stories, detections) + + j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), + trim_blocks=True) + template = j2_env.get_template('stories_categories.j2') + output_path = OUTPUT_DIR + "/stories_categories.md" + output = template.render(categories=categories) + with open(output_path, 'w') as f: + f.write(output) + + return len(stories), output_path + + + + # function to get unique values @@ -314,7 +460,7 @@ def generate_stories(REPO_PATH, verbose): return complete_stories -def write_splunk_docs(stories, detections, OUTPUT_DIR): +def write_splunk_docs_bak(stories, detections, OUTPUT_DIR): paths = [] # Create conf files from analytics stories files @@ -402,7 +548,7 @@ def write_splunk_docs(stories, detections, OUTPUT_DIR): return story_count, paths -def write_markdown_docs(stories, detections, OUTPUT_DIR): +def write_markdown_docs_bak(stories, detections, OUTPUT_DIR): paths = [] # Create conf files from analytics stories files splunk_docs_output_path = OUTPUT_DIR + "/stories_categories.md" @@ -510,6 +656,12 @@ def write_markdown_docs(stories, detections, OUTPUT_DIR): return story_count, paths +def parse_data_models_from_search(search): + match = re.search('from\sdatamodel\s?=\s?([^\s.]*)',search) + if match is not None: + return match.group(1) + return False + if __name__ == "__main__": # grab arguments @@ -531,20 +683,21 @@ if __name__ == "__main__": gsd = args.gen_splunk_docs gmd = args.gen_markdown_docs - complete_stories = generate_stories(REPO_PATH, verbose) - complete_detections = generate_detections(REPO_PATH, complete_stories) + stories = load_objects("stories/*.yml") + detections = load_objects("detections/*.yml") + + # complete_stories = generate_stories(REPO_PATH, verbose) + # complete_detections = generate_detections(REPO_PATH, complete_stories) if gsd: - story_count, paths = write_splunk_docs(complete_stories, complete_detections, OUTPUT_DIR) - for p in paths: - print("{0} story documents have been successfully written to {1}".format(story_count, p)) + story_count, path = write_splunk_docs(stories, detections, OUTPUT_DIR) + print("{0} story documents have been successfully written to {1}".format(story_count, path)) else: print("--gen_splunk_docs was set to false, not generating splunk documentation") if gmd: - story_count, paths = write_markdown_docs(complete_stories, complete_detections, OUTPUT_DIR) - for p in paths: - print("{0} story documents have been successfully written to {1}".format(story_count, p)) + story_count, path = write_markdown_docs(stories, detections, OUTPUT_DIR) + print("{0} story documents have been successfully written to {1}".format(story_count, path)) else: print("--gen_splunk_docs was set to false, not generating splunk documentation") diff --git a/bin/jinja2_templates/splunk_docs_categories.j2 b/bin/jinja2_templates/splunk_docs_categories.j2 new file mode 100644 index 0000000000..b0582430a8 --- /dev/null +++ b/bin/jinja2_templates/splunk_docs_categories.j2 @@ -0,0 +1,65 @@ += Use Case Categories= +The collapse... + + +{% for category in categories %} +=={{ category.name }}== + +{% for story in category.stories %} +==={{ story.name }}=== + +{{ story.description }} + +
+
+ +====Narrative==== +{{ story.narrative }} + +====Detections==== +{% for detection in story.detections %} +* {{ detection }} +{% endfor %} + +====Data Models==== +{% for data_model in story.data_models %} +* {{ data_model }} +{% endfor %} + +====Tags==== + +=====ATT&CK===== +{% for mitre_attack_id in story.mitre_attack_ids %} +* {{ mitre_attack_id }} +{% endfor %} + +=====Kill Chain Phases===== +{% for kill_chain_phase in story.kill_chain_phases %} +* {{ kill_chain_phase }} +{% endfor %} + +=====CIS===== +{% for cis in story.ciss %} +* {{ cis }} +{% endfor %} + +=====NIST===== +{% for nist in story.nists %} +* {{ nist }} +{% endfor %} + +====References==== +{% for reference in story.references %} +* {{ reference }} +{% endfor %} + +date = {{ story.date }} + +version = {{ story.version }} + +
+
+ +{% endfor %} + +{% endfor %} diff --git a/bin/jinja2_templates/stories_categories.j2 b/bin/jinja2_templates/stories_categories.j2 new file mode 100644 index 0000000000..7862cd9ed5 --- /dev/null +++ b/bin/jinja2_templates/stories_categories.j2 @@ -0,0 +1,68 @@ + +# Categories +Analytics stories organized by categories +{% for category in categories %} + +* [{{ category.name }}](#{{ category.name | replace(' ','-') }}) +{% endfor %} + + +{% for category in categories %} +## {{ category.name }} +{% for story in category.stories %} + +* [{{ story.name }}](#{{ story.name | replace(' ','-') }}) +{% endfor %} + +{% for story in category.stories %} +### {{ story.name }} +* id = {{ story.id }} +* date = {{ story.date }} +* version = {{ story.version }} + +#### Description +{{ story.description }} + +#### Narrative +{{ story.narrative }} + +#### Detections +{% for detection in story.detections %} +* {{ detection }} +{% endfor %} + +#### Data Models +{% for data_model in story.data_models %} +* {{ data_model }} +{% endfor %} + +#### Mappings + +##### ATT&CK +{% for mitre_attack_id in story.mitre_attack_ids %} +* {{ mitre_attack_id }} +{% endfor %} + +##### Kill Chain Phases +{% for kill_chain_phase in story.kill_chain_phases %} +* {{ kill_chain_phase }} +{% endfor %} + +###### CIS +{% for cis in story.ciss %} +* {{ cis }} +{% endfor %} + +##### NIST +{% for nist in story.nists %} +* {{ nist }} +{% endfor %} + +##### References +{% for reference in story.references %} +* {{ reference }} +{% endfor %} + +{% endfor %} + +{% endfor %} diff --git a/docs/splunk_docs_categories.wiki b/docs/splunk_docs_categories.wiki index c730a3c42f..9aba2decf9 100644 --- a/docs/splunk_docs_categories.wiki +++ b/docs/splunk_docs_categories.wiki @@ -2,1371 +2,6 @@ The collapse... -==Cloud Security== - -===AWS Cross Account Activity=== - -Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. - -
-
- -====Narrative==== -Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ -Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ -This Analytic Story includes searches that will help you monitor your AWS CloudTrail logs for evidence of suspicious cross-account activity. For example, while accessing multiple AWS accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/ - -creation_date = 2018-06-04 - -modification_date = 2018-06-04 - -version = 1.0 - -
-
- -===AWS Cryptomining=== - -Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. - -
-
- -====Narrative==== -Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ -Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ -hen malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So, it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ -This Analytic Story is focused on detecting suspicious new instances in your EC2 environment to help prevent such a disaster. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -creation_date = 2018-03-08 - -modification_date = 2018-03-08 - -version = 1.0 - -
-
- -===AWS Network ACL Activity=== - -Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. - -
-
- -====Narrative==== -AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html -* https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/ - -creation_date = 2018-01-10 - -modification_date = 2018-05-21 - -version = 2.0 - -
-
- -===AWS Suspicious Provisioning Activities=== - -Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. - -
-
- -====Narrative==== -Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ -This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -creation_date = 2018-03-16 - -modification_date = 2018-03-16 - -version = 1.0 - -
-
- -===AWS User Monitoring=== - -Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. - -
-
- -====Narrative==== -It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ -In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ -Fortunately, you can leverage Amazon Web Services (AWS) CloudTrail--a tool that helps you enable governance, compliance, and risk auditing of your AWS account--to give you increased visibility into your user and resource activity by recording AWS Management Console actions and API calls. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred.\ -The detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -* https://redlock.io/blog/cryptojacking-tesla - -creation_date = 2018-03-12 - -modification_date = 2018-03-12 - -version = 1.0 - -
-
- -===Cloud Cryptomining=== - -Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. - -
-
- -====Narrative==== -Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ -Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ -When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ -This Analytic Story is focused on detecting suspicious new instances in your cloud environment to help prevent cryptominers from gaining a foothold. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. - -====Providing Technologies==== -* AWS -* Azure -* GCP - -====Data Models==== -* Cloud_Infrastructure - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -creation_date = 2019-10-02 - -modification_date = 2019-10-02 - -version = 1.0 - -
-
- -===Container Implantation Monitoring & Investigation=== - -Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. - -
-
- -====Narrative==== -Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. - -====Providing Technologies==== -* GCP -* AWS - -====Data Models==== -* Cloud_Infrastructure - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://github.com/splunk/cloud-datamodel-security-research - -creation_date = 2020-02-20 - -modification_date = 2020-02-20 - -version = 1.0 - -
-
- -===Kubernetes Scanning Activity=== - -This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. - -
-
- -====Narrative==== -Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. - -====Providing Technologies==== -* AWS -* GCP - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://github.com/splunk/cloud-datamodel-security-research - -creation_date = 2020-03-24 - -modification_date = 2020-04-15 - -version = 1.0 - -
-
- -===Suspicious AWS EC2 Activities=== - -Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. - -
-
- -====Narrative==== -AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -creation_date = 2018-02-09 - -modification_date = 2018-02-09 - -version = 1.0 - -
-
- -===Suspicious AWS Login Activities=== - -Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. - -
-
- -====Narrative==== -It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html - -creation_date = 2018-02-24 - -modification_date = 2019-05-01 - -version = 1.0 - -
-
- -===Suspicious AWS S3 Activities=== - -Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. - -
-
- -====Narrative==== -As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ -Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ -Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -* https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/ - -creation_date = 2018-06-25 - -modification_date = 2018-07-24 - -version = 2.0 - -
-
- -===Suspicious AWS Traffic=== - -Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). - -
-
- -====Narrative==== -A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ -Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ - Attackers may abuse the AWS infrastructure with insecure VPCs so they can co-opt AWS resources for command-and-control nodes, data exfiltration, and more. Once an EC2 instance is compromised, an attacker may initiate outbound network connections for malicious reasons. Monitoring these network traffic behaviors is crucial for understanding the type of traffic flowing in and out of your network and to alert you to suspicious activities.\ -The searches in this Analytic Story will monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/ - -creation_date = 2018-05-07 - -modification_date = 2018-05-07 - -version = 1.0 - -
-
- -===Unusual AWS EC2 Modifications=== - -Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. - -
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- -====Narrative==== -A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ - Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. - -====Providing Technologies==== -* AWS - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -creation_date = 2018-04-09 - -modification_date = 2018-04-09 - -version = 1.0 - -
-
- - -==Best Practices== - -===Account Monitoring and Controls=== - -A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. - -
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- -====Narrative==== -Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. - -====Providing Technologies==== -* Microsoft Windows -* Active Directory - -====Data Models==== -* Change -* Identity_Management - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf - -creation_date = 2017-08-05 - -modification_date = 2017-09-06 - -version = 1.0 - -
-
- -===Asset Tracking=== - -Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. - -
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- -====Narrative==== -This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. - -====Providing Technologies==== -* Splunk Stream -* Bro - -====Data Models==== -* Network_Sessions - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/ - -creation_date = 2017-06-01 - -modification_date = 2017-09-13 - -version = 1.0 - -
-
- -===Monitor Backup Solution=== - -Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. - -
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- -====Narrative==== -Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. - -====Providing Technologies==== -* Netbackup - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/ - -creation_date = 2017-06-15 - -modification_date = 2017-09-12 - -version = 1.0 - -
-
- -===Monitor for Unauthorized Software=== - -Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. - -
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- -====Narrative==== -It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ -It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ - -creation_date = 2017-06-26 - -modification_date = 2017-09-15 - -version = 1.0 - -
-
- -===Monitor for Updates=== - -Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. - -
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- -====Narrative==== -It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ -Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ -Microsoft releases updates for Windows systems on a monthly cadence. They should be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed. - -====Providing Technologies==== -* Microsoft Windows - -====Data Models==== -* Updates - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://learn.cisecurity.org/20-controls-download - -creation_date = 2017-08-15 - -modification_date = 2017-09-15 - -version = 1.0 - -
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- -===Prohibited Traffic Allowed or Protocol Mismatch=== - -Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. - -
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- -====Narrative==== -A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. - -====Providing Technologies==== -* Splunk Stream -* Bro -* Palo Alto Firewall - -====Data Models==== -* Network_Resolution -* Network_Traffic - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/ - -creation_date = 2017-04-18 - -modification_date = 2017-09-11 - -version = 1.0 - -
-
- -===Router & Infrastructure Security=== - -Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. - -
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- -====Narrative==== -Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ -This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. - -====Providing Technologies==== -* Active Directory -* Palo Alto Firewall - -====Data Models==== -* Authentication - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html -* https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html - -creation_date = 2017-06-01 - -modification_date = 2017-09-12 - -version = 1.0 - -
-
- -===Use of Cleartext Protocols=== - -Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. - -
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- -====Narrative==== -Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. - -====Providing Technologies==== -* Splunk Stream -* Bro - -====Data Models==== -* Network_Traffic - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.monkey.org/~dugsong/dsniff/ - -creation_date = 2016-09-13 - -modification_date = 2017-09-15 - -version = 1.0 - -
-
- - -==Vulnerability== - -===Apache Struts Vulnerability=== - -Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. - -
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- -====Narrative==== -In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ -The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ -This Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the `Content-Type` header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the `Content-Type` header is generally consistent and does not have a large degree of variation.\ -The second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.\ -First, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.\ -hen looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.\ -Various types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.\ -Looking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of "who," in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.\ -Gathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.\ -hen it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -In the event that a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that have the file open, what processes created and/or modified the file, and the number of systems that may have this file can help to determine if the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes quickly help determine whether it is malicious in nature.\ -Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, there may be activity initiated via a compromised website the user visited.\ -It can also be very helpful to examine various behaviors of the process of interest or the parent of the process that is of interest. For example, if it turns out that the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might also be worth further scrutiny. If a process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. - -====Providing Technologies==== -* Splunk Stream -* Bro -* Bluecoat -* Apache -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf - -creation_date = 2017-03-14 - -modification_date = 2018-12-06 - -version = 1.0 - -
-
- -===JBoss Vulnerability=== - -In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. - -
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- -====Narrative==== -This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ -It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ -hen looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.\ -Various types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.\ -The following factors may assist you in determining whether the event is malicious: \ -1. Country of origin\ -1. Responsible party\ -1. Fully qualified domain names associated with the external IP address\ -1. Registration of fully qualified domain names associated with external IP address Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.\ -Gathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.\ -If you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -If a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that opened the file, the processes that may have created and/or modified the file, and how many other systems potentially have this file can you determine whether the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes help you quickly determine if it is malicious in nature.\ -Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. \ -It can also be helpful to examine various behaviors of and the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see whether the parent process spawned other processes that might also warrant further scrutiny. If a process is suspect, a review of the network connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. - -====Providing Technologies==== -* Splunk Stream -* Palo Alto Firewall -* Apache -* Bro - -====Data Models==== -* Web - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html - -creation_date = 2016-10-04 - -modification_date = 2017-09-14 - -version = 1.0 - -
-
- -===Spectre And Meltdown Vulnerabilities=== - -Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. - -
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- -====Narrative==== -Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. - -====Providing Technologies==== -* Nessus -* Qualys - -====Data Models==== -* Vulnerabilities - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://meltdownattack.com/ - -creation_date = 2018-01-08 - -modification_date = 2018-01-08 - -version = 1.0 - -
-
- -===Splunk Enterprise Vulnerability=== - -Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. - -
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- -====Narrative==== -This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ -\ -1. Splunk Enterprise 6.4.x, prior to 6.4.3\ -1. Splunk Enterprise 6.3.x, prior to 6.3.6\ -1. Splunk Enterprise 6.2.x, prior to 6.2.10\ -1. Splunk Enterprise 6.1.x, prior to 6.1.11\ -1. Splunk Enterprise 6.0.x, prior to 6.0.12\ -1. Splunk Enterprise 5.0.x, prior to 5.0.16\ -1. Splunk Light, prior to 6.4.3CVE-2016-4859 allows attackers to redirect users to arbitrary web sites and conduct phishing attacks via unspecified vectors. (Credit: Noriaki Iwasaki, Cyber Defense Institute, Inc.).\ -It is important to ensure that your Splunk deployment is being kept up to date and is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites. - -====Providing Technologies==== -* Splunk Enterprise - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* http://www.splunk.com/view/SP-CAAAPQ6#announce -* https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859 - -creation_date = 2016-09-13 - -modification_date = 2017-09-19 - -version = 1.0 - -
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- -===Splunk Enterprise Vulnerability CVE-2018-11409=== - -Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. - -
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- -====Narrative==== -Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ -Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ -Read more in Splunk's official response: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings.\ -A detection search within this Analytic Story looks for vulnerabilities described in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip. - -====Providing Technologies==== -* Splunk Enterprise - -====Data Models==== - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://nvd.nist.gov/vuln/detail/CVE-2018-11409 -* https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings -* https://www.exploit-db.com/exploits/44865/ - -creation_date = 2018-06-14 - -modification_date = 2018-06-14 - -version = 1.0 - -
-
- - ==Abuse== ===Brand Monitoring=== @@ -1381,49 +16,87 @@ While you can educate your users and customers about the risks and threats posed You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ Notable events will include IP addresses, URLs, and user data. Drilling down can provide you with even more actionable intelligence, including likely geographic information, contextual searches to help you scope the problem, and investigative searches. -====Providing Technologies==== -* Splunk Stream -* Bro -* Microsoft Exchange -* Bluecoat -* Palo Alto Firewall +====Detections==== +* Monitor DNS For Brand Abuse +* Monitor Email For Brand Abuse +* Monitor Web Traffic For Brand Abuse ====Data Models==== -* Network_Resolution * Email +* Network_Resolution * Web -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives +* Delivery =====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 7 =====NIST===== * PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM ====References==== * https://www.zerofox.com/blog/what-is-digital-risk-monitoring/ * https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/ * https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/ -creation_date = 2017-06-01 +date = 2017-12-19 -modification_date = 2017-12-19 +version = 1 -version = 1.0 + + + +===Data Protection=== + +Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. + +
+
+ +====Narrative==== +Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. + +====Detections==== +* Detect USB device insertion +* Detect hosts connecting to dynamic domain providers +* Detection of DNS Tunnels + +====Data Models==== +* Change_Analysis +* Network_Resolution + +====Tags==== + +=====ATT&CK===== +* T1043 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control +* Installation + +=====CIS===== +* CIS 13 + +=====NIST===== +* DE.CM +* PR.DS +* PR.PT + +====References==== +* https://www.cisecurity.org/controls/data-protection/ +* https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022 +* https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ + +date = 2017-09-14 + +version = 1
@@ -1439,97 +112,32 @@ DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it respond The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. -====Providing Technologies==== -* Splunk Stream -* Bro +====Detections==== +* Large Volume of DNS ANY Queries ====Data Models==== * Network_Resolution -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== -* CIS 3 -* CIS 8 * CIS 12 =====NIST===== * PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM ====References==== * https://www.us-cert.gov/ncas/alerts/TA13-088A * https://www.imperva.com/learn/application-security/dns-amplification/ -creation_date = 2016-08-24 +date = 2016-09-13 -modification_date = 2016-09-13 - -version = 1.0 - - - - -===Data Protection=== - -Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. - -
-
- -====Narrative==== -Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. - -====Providing Technologies==== -* Microsoft Windows -* Splunk Stream -* Bro - -====Data Models==== -* Change_Analysis -* Network_Resolution - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.cisecurity.org/controls/data-protection/ -* https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022 -* https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ - -creation_date = 2017-06-01 - -modification_date = 2017-09-14 - -version = 1.0 +version = 1
@@ -1544,46 +152,44 @@ Detect evidence of tactics used to redirect traffic from a host to a destination ====Narrative==== Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. -====Providing Technologies==== -* Splunk Stream -* Bro -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon +====Detections==== +* Clients Connecting to Multiple DNS Servers +* DNS Query Requests Resolved by Unauthorized DNS Servers +* Windows hosts file modification ====Data Models==== * Network_Resolution -* Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1048 =====Kill Chain Phases===== * Command and Control =====CIS===== +* CIS 1 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* ID.AM +* PR.AC +* PR.DS +* PR.IP +* PR.PT ====References==== * https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/ -creation_date = 2017-06-18 +date = 2017-09-14 -modification_date = 2017-09-14 - -version = 1.0 +version = 1 @@ -1599,47 +205,37 @@ Detect activities and various techniques associated with the abuse of `netsh.exe It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Processes created by netsh +* Processes launching netsh ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1059 +* T1089 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== -* CIS 3 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE * DE.CM +* PR.PT ====References==== * https://technet.microsoft.com/library/bb490939.aspx * https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html * http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html -creation_date = 2017-01-04 +date = 2017-01-05 -modification_date = 2017-01-05 - -version = 1.0 +version = 1 @@ -1659,690 +255,38 @@ The account-harvesting search focuses on web pages used for user-account registr The anomalous clickspeed search looks for users who are moving through your website at a faster-than-normal speed or with a perfect click cadence (high periodicity or low standard deviation), which could indicate that the user is a script, not an actual human.\ Another search detects incidents wherein a single password is used across multiple accounts, which may indicate that a fraudster has infiltrated your environment and embedded a common password within a script. -====Providing Technologies==== -* Splunk Stream +====Detections==== +* Web Fraud - Account Harvesting +* Web Fraud - Anomalous User Clickspeed +* Web Fraud - Password Sharing Across Accounts ====Data Models==== -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1078 +* T1136 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 16 +* CIS 6 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* DE.DP ====References==== * https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud * https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718 -creation_date = 2018-07-12 +date = 2018-10-08 -modification_date = 2018-10-08 - -version = 1.0 - - - - - -==Malware== - -===ColdRoot MacOS RAT=== - -Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. - -
-
- -====Narrative==== -Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ -This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ -Searches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger. - -====Providing Technologies==== -* OSquery - -====Data Models==== -* Alerts - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/ -* https://objective-see.com/blog/blog_0x2A.html -* https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/ - -creation_date = 2019-01-29 - -modification_date = 2019-01-09 - -version = 1.0 - -
-
- -===DHS Report TA18-074A=== - -Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. - -
-
- -====Narrative==== -The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ -There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ -One joint Technical Alert (TA) issued by the Department of Homeland and the FBI in mid-March of 2018 attributed some cyber activity targeting utility infrastructure to operatives sponsored by the Russian government. The hackers executed spearfishing attacks, installed malware, employed watering-hole domains, and more. While they caused no physical damage, the attacks provoked fears that a nation-state could turn off water, redirect power, or compromise a nuclear power plant.\ -Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify the network configuration), suspicious registry modifications, and many more--may all be events you may wish to investigate further. While the use of these technique may be an indication that a nation-state actor is attempting to compromise your environment, it is important to note that these techniques are often employed by other groups, as well. - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Microsoft Windows -* Bro -* Splunk Stream - -====Data Models==== -* Endpoint -* Network_Traffic - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.us-cert.gov/ncas/alerts/TA18-074A - -creation_date = 2018-03-19 - -modification_date = 2020-01-22 - -version = 2.0 - -
-
- -===Dynamic DNS=== - -Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. - -
-
- -====Narrative==== -Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. - -====Providing Technologies==== -* Splunk Stream -* Bro -* Bluecoat -* Palo Alto Firewall - -====Data Models==== -* Network_Resolution -* Web - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html -* https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ -* http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ -* https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html - -creation_date = 2017-11-21 - -modification_date = 2018-09-06 - -version = 2.0 - -
-
- -===Emotet Malware (DHS Report TA18-201A)=== - -Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. - -
-
- -====Narrative==== -The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ -According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ -The searches in this Analytic Story will help you find executables that are rarely used in your environment, specific registry paths that malware often uses to ensure survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Microsoft Exchange -* Bro -* Splunk Stream - -====Data Models==== -* Endpoint -* Email -* Network_Traffic - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.us-cert.gov/ncas/alerts/TA18-201A -* https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf -* https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html - -creation_date = 2018-09-11 - -modification_date = 2020-01-27 - -version = 1.0 - -
-
- -===Hidden Cobra Malware=== - -Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. - -
-
- -====Narrative==== -North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ -These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ -In June of 2018, The Department of Homeland Security, together with the FBI and other U.S. government partners, issued Technical Alert (TA-18-149A) to advise the public about two variants of North Korean malware. One variant, dubbed "Joanap," is a multi-stage peer-to-peer botnet that allows North Korean state actors to exfiltrate data, download and execute secondary payloads, and initialize proxy communications. The other variant, "Brambul," is a Windows32 SMB worm that is dropped into a victim network. When executed, the malware attempts to spread laterally within a victim's local subnet, connecting via the SMB protocol and initiating brute-force password attacks. It reports details to the Hidden Cobra actors via email, so they can use the information for secondary remote operations.\ -Among other searches in this Analytic Story is a detection search that looks for the creation or deletion of hidden shares, such as, "adnim$," which the Hidden Cobra malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers. - -====Providing Technologies==== -* Splunk Stream -* Bro -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Network_Resolution -* Network_Traffic -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity -* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf - -creation_date = 2018-06-14 - -modification_date = 2020-01-22 - -version = 2.0 - -
-
- -===Orangeworm Attack Group=== - -Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. - -
-
- -====Narrative==== -In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ -Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ -Although the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage. \ -Healthcare may be a promising target, because it is notoriously behind in technology, often using older operating systems and neglecting to patch computers. Even so, the group was able to evade detection for a full three years. Sources say that the malware spread quickly within the target networks, infecting computers used to control medical devices, such as MRI and X-ray machines.\ -This Analytic Story is designed to help you detect and investigate suspicious activities that may be indicative of an Orangeworm attack. One detection search looks for command-line arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised. - -====Providing Technologies==== -* Microsoft Windows -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia -* https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/ - -creation_date = 2018-06-14 - -modification_date = 2020-01-22 - -version = 2.0 - -
-
- -===Ransomware=== - -Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. - -
-
- -====Narrative==== -Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Palo Alto Firewall -* Bro -* Splunk Stream -* Microsoft Windows - -====Data Models==== -* Endpoint -* Network_Traffic - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/ -* https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html - -creation_date = 2017-07-24 - -modification_date = 2020-02-04 - -version = 1.1 - -
-
- -===SamSam Ransomware=== - -Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. - -
-
- -====Narrative==== -The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ -Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ -SamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.\ -In a typical attack on one large healthcare organization in 2018, the company ended up paying a ransom of four Bitcoins, then worth $56,707. Reports showed that access to the company's files was restored within two hours of paying the sum.\ -According to Sophos, SamSam previously leveraged RDP to gain access to targeted networks via brute force. SamSam is not spread automatically, like other malware. It requires skill because it forces the attacker to adapt their tactics to the individual environment. Next, the actors escalate their privileges to admin level. They scan the networks for worthy targets, using conventional tools, such as PsExec or PaExec, to deploy/execute, quickly encrypting files.\ -This Analytic Story includes searches designed to help detect and investigate signs of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP. - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Splunk Stream -* Palo Alto Firewall -* Apache -* Bro - -====Data Models==== -* Endpoint -* Web -* Network_Traffic - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/ -* https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/ -* https://thehackernews.com/2018/07/samsam-ransomware-attacks.html - -creation_date = 2018-12-13 - -modification_date = 2018-12-13 - -version = 1.0 - -
-
- -===Unusual Processes=== - -Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. - -
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- -====Narrative==== -Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ -This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ -In the event an unusual process is identified, it is imperative to better understand how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity. - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html -* https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf -* https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262 - -creation_date = 2016-08-09 - -modification_date = 2020-02-04 - -version = 2.1 - -
-
- -===Windows File Extension and Association Abuse=== - -Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. - -
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- -====Narrative==== -Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ - Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ - Attackers take advantage of this expectation by obfuscating the true file extension. They can accomplish this in a couple of ways. One technique involves inserting multiple spaces in the file name before the extension to hide the extension from the GUI, obscuring the true nature of the file. Another approach involves prepending the real extension with a different one. This is especially effective when Windows is configured to "hide extensions for known file types." In this case, the real extension is not displayed, but the prepended one is, leading end users to believe the file is a different type than it actually is.\ -Changing the association between a file extension and an application can allow an attacker to execute arbitrary code. The technique typically involves changing the association for an often-launched file type to associate instead with a malicious program the attacker has dropped on the endpoint. When the end user launches a file that has been manipulated in this way, it will execute the attacker's malware. It will also execute the application the end user expected to run, cleverly obscuring the fact that something suspicious has occurred.\ -Run the searches in this story to detect and investigate suspicious behavior that may indicate abuse or manipulation of Windows file extensions and/or associations. - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/ -* https://attack.mitre.org/wiki/Technique/T1042 - -creation_date = 2018-01-26 - -modification_date = 2018-01-26 - -version = 1.0 - -
-
- -===Windows Service Abuse=== - -Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. - -
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- -====Narrative==== -The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. - -====Providing Technologies==== -* Microsoft Windows -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://attack.mitre.org/wiki/Technique/T1050 -* https://attack.mitre.org/wiki/Technique/T1031 - -creation_date = 2017-11-02 - -modification_date = 2017-11-02 - -version = 3.0 +version = 1
@@ -2362,49 +306,43 @@ A common adversary goal is to identify and exfiltrate data of value from a targe Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ Use the searches to detect and monitor suspicious behavior related to these activities. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Bro -* Splunk Stream +====Detections==== +* Email files written outside of the Outlook directory +* Email servers sending high volume traffic to hosts +* Hosts receiving high volume of network traffic from email server +* Suspicious writes to System Volume Information +* Suspicious writes to windows Recycle Bin ====Data Models==== * Endpoint * Network_Traffic -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1043 +* T1074 +* T1114 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== -* CIS 3 +* CIS 7 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* PR.PT ====References==== * https://attack.mitre.org/wiki/Collection * https://attack.mitre.org/wiki/Technique/T1074 -creation_date = 2018-01-08 +date = 2020-02-03 -modification_date = 2020-02-03 - -version = 1.1 +version = 1 @@ -2420,46 +358,62 @@ Detect and investigate tactics, techniques, and procedures leveraged by attacker Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. -====Providing Technologies==== -* Splunk Stream -* Bro -* Palo Alto Firewall -* AWS +====Detections==== +* Clients Connecting to Multiple DNS Servers +* DNS Query Length Outliers - MLTK +* DNS Query Length With High Standard Deviation +* DNS Query Requests Resolved by Unauthorized DNS Servers +* Detect Large Outbound ICMP Packets +* Detect Long DNS TXT Record Response +* Detect Spike in blocked Outbound Traffic from your AWS +* Detect hosts connecting to dynamic domain providers +* Detection of DNS Tunnels +* Excessive DNS Failures +* Prohibited Network Traffic Allowed +* Protocol or Port Mismatch +* TOR Traffic ====Data Models==== * Network_Resolution * Network_Traffic -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1043 +* T1048 +* T1095 =====Kill Chain Phases===== +* Actions on Objectives * Command and Control +* Delivery =====CIS===== +* CIS 1 +* CIS 11 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 +* CIS 9 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* ID.AM +* PR.AC +* PR.DS +* PR.IP +* PR.PT ====References==== * https://attack.mitre.org/wiki/Command_and_Control * https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware -creation_date = 2018-06-01 +date = 2018-06-01 -modification_date = 2018-06-01 - -version = 1.0 +version = 1 @@ -2475,33 +429,24 @@ Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. -====Providing Technologies==== -* Splunk Stream -* Bro +====Detections==== +* Detect DNS requests to Phishing Sites leveraging EvilGinx2 ====Data Models==== * Network_Resolution -* Web -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1192 =====Kill Chain Phases===== * Command and Control =====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 7 =====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE * DE.CM ====References==== @@ -2509,11 +454,9 @@ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilG * https://attack.mitre.org/techniques/T1192/ * https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/ -creation_date = 2019-04-29 +date = 2019-04-29 -modification_date = 2019-04-29 - -version = 1.0 +version = 1 @@ -2530,47 +473,112 @@ Credential dumping—gathering credentials from a target system, often hashed Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ The detection searches in this Analytic Story monitor access to the Local Security Authority Subsystem Service (LSASS) process, the usage of shadowcopies for credential dumping and some other techniques for credential dumping. -====Providing Technologies==== -* Microsoft Windows -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Access LSASS Memory for Dump Creation +* Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass +* Attempted Credential Dump From Registry via Reg exe +* Create Remote Thread into LSASS +* Creation of Shadow Copy +* Creation of Shadow Copy with wmic and powershell +* Credential Dumping via Copy Command from Shadow Copy +* Credential Dumping via Symlink to Shadow Copy +* Detect Credential Dumping through LSASS access +* Detect Mimikatz Using Loaded Images +* Dump LSASS via comsvcs DLL +* Unsigned Image Loaded by LSASS ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1003 +* T1064 +* T1086 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives +* Installation =====CIS===== +* CIS 16 * CIS 3 +* CIS 5 +* CIS 6 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* PR.AC +* PR.IP ====References==== * https://attack.mitre.org/wiki/Technique/T1003 * https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html -creation_date = 2018-08-08 +date = 2020-02-04 -modification_date = 2020-02-04 +version = 3 -version = 3.0 + + + +===Disabling Security Tools=== + +Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. + +
+
+ +====Narrative==== +Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). + +====Detections==== +* Attempt To Add Certificate To Untrusted Store +* Attempt To Stop Security Service +* Processes launching netsh +* Sc exe Manipulating Windows Services +* Suspicious Reg exe Process +* Unload Sysmon Filter Driver + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== +* T1031 +* T1050 +* T1059 +* T1089 +* T1112 + +=====Kill Chain Phases===== +* Actions on Objectives +* Installation + +=====CIS===== +* CIS 3 +* CIS 5 +* CIS 8 + +=====NIST===== +* DE.CM +* PR.AC +* PR.AT +* PR.IP +* PR.PT + +====References==== +* https://attack.mitre.org/wiki/Technique/T1089 +* https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/ +* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf + +date = 2020-02-04 + +version = 2
@@ -2593,33 +601,38 @@ On January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity In DNS hijacking, the attacker assumes control over an account or makes use of a DNS service exploit to make changes to DNS records. Once they gain access, attackers can substitute their own MX records, name-server records, and addresses, redirecting emails and traffic through their infrastructure, where they can read, copy, or modify information seen. They can also generate valid encryption certificates to help them avoid browser-certificate checks. In one notable attack on the Internet service provider, GoDaddy, the hackers altered Sender Policy Framework (SPF) records a relatively minor change that did not inflict excessive damage but allowed for more effective spam campaigns.\ The searches in this Analytic Story help you detect and investigate activities that may indicate that DNS hijacking has taken place within your environment. -====Providing Technologies==== -* Splunk Stream -* Bro +====Detections==== +* Clients Connecting to Multiple DNS Servers +* DNS Query Requests Resolved by Unauthorized DNS Servers +* DNS record changed +* Detect hosts connecting to dynamic domain providers ====Data Models==== * Network_Resolution -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1048 =====Kill Chain Phases===== +* Actions on Objectives * Command and Control =====CIS===== +* CIS 1 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* ID.AM +* PR.DS +* PR.IP +* PR.PT ====References==== * https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html @@ -2627,66 +640,9 @@ The searches in this Analytic Story help you detect and investigate activities t * http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ * https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html -creation_date = 2017-11-21 +date = 2020-02-04 -modification_date = 2020-02-04 - -version = 1.0 - - - - -===Disabling Security Tools=== - -Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. - -
-
- -====Narrative==== -Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). - -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://attack.mitre.org/wiki/Technique/T1089 -* https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/ -* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf - -creation_date = 2018-04-09 - -modification_date = 2020-02-04 - -version = 2.0 +version = 1
@@ -2705,50 +661,43 @@ An adversary can use lateral movement for multiple purposes, including remote ex If there is evidence of lateral movement, it is imperative for analysts to collect evidence of the associated offending hosts. For example, an attacker might leverage host A to gain access to host B. From there, the attacker may try to move laterally to host C. In this example, the analyst should gather as much information as possible from all three hosts. \ It is also important to collect authentication logs for each host, to ensure that the offending accounts are well-documented. Analysts should account for all processes to ensure that the attackers did not install unauthorized software. -====Providing Technologies==== -* Microsoft Windows -* Bro -* Splunk Stream -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Detect Activity Related to Pass the Hash Attacks +* Remote Desktop Network Traffic +* Remote Desktop Process Running On System +* Schtasks scheduling job on remote system ====Data Models==== -* Network_Traffic * Endpoint +* Network_Traffic -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1053 +* T1075 +* T1076 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== +* CIS 16 * CIS 3 -* CIS 8 -* CIS 12 +* CIS 9 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE -* DE.CM +* PR.AC +* PR.IP ====References==== * https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis * https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html -creation_date = 2016-09-13 +date = 2020-02-04 -modification_date = 2020-02-04 - -version = 2.0 +version = 2 @@ -2772,46 +721,43 @@ Often, a simple inspection of the process name and path can tell you if the syst It can also be very helpful to examine various behaviors of the process of interest or the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might be worth further scrutiny. If a process is suspect, a review of the network connections made in and around the time of the event and/or whether the process spawned any child processes could be helpful, as well.\ In the event a system is suspected of having been compromised via a malicious website, we suggest reviewing the browsing activity from that system around the time of the event. If categories are given for the URLs visited, that can help you zero in on possible malicious sites. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass +* Malicious PowerShell Process - Connect To Internet With Hidden Window +* Malicious PowerShell Process - Encoded Command +* Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments +* Malicious PowerShell Process With Obfuscation Techniques ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1064 +* T1086 =====Kill Chain Phases===== +* Actions on Objectives * Command and Control =====CIS===== * CIS 3 +* CIS 7 * CIS 8 -* CIS 12 =====NIST===== +* DE.CM * PR.IP * PR.PT -* PR.AC -* DE.AE -* DE.CM ====References==== * https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/ * https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ -creation_date = 2016-09-18 +date = 2017-08-23 -modification_date = 2017-08-23 - -version = 4.0 +version = 4 @@ -2833,45 +779,35 @@ Following is a typical series of events, according to an [article by Trend Micro 1. Powershell executes a reverse shell, rendering the exploit successful As a side note, adversaries are likely to use a tool like Empire to craft and obfuscate payloads and their post-injection activities, such as [exfiltration, lateral movement, and persistence](https://github.com/EmpireProject/Empire).\ This Analytic Story focuses on detecting signs that a malicious payload has been injected into your environment. For example, one search detects outlook.exe writing a .zip file. Another looks for suspicious .lnk files launching processes. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Detect Oulook exe writing a zip file +* Suspicious LNK file launching a process ====Data Models==== -* Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1193 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives +* Installation =====CIS===== -* CIS 3 +* CIS 7 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM +* ID.AM +* PR.DS ====References==== * https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html -creation_date = 2019-04-29 +date = 2019-04-29 -modification_date = 2019-04-29 - -version = 1.0 +version = 1 @@ -2913,46 +849,47 @@ If behavioral searches included in this story yield positive hits, iDefense reco 1. b8ec65dab97cdef3cd256cc4753f0c54\ 1. 04d83cd3813698de28cfbba326d7647c -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* First time seen command line argument +* Malicious PowerShell Process - Connect To Internet With Hidden Window +* Registry Keys Used For Persistence +* Unusually Long Command Line +* Unusually Long Command Line - MLTK ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1059 +* T1064 +* T1086 +* T1103 +* T1131 =====Kill Chain Phases===== +* Actions on Objectives * Command and Control =====CIS===== * CIS 3 +* CIS 7 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* PR.IP +* PR.PT ====References==== * https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/ * http://blog.amossys.fr/badflick-is-not-so-bad.html -creation_date = 2018-07-24 +date = 2020-01-22 -modification_date = 2020-01-22 - -version = 1.0 +version = 1 @@ -2968,43 +905,33 @@ Use the searches in this Analytic Story to help you detect structured query lang It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. -====Providing Technologies==== -* Splunk Stream -* Bro +====Detections==== +* SQL Injection with Long URLs ====Data Models==== * Web -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1043 =====Kill Chain Phases===== -* Command and Control +* Delivery =====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 18 =====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE * DE.CM ====References==== * https://capec.mitre.org/data/definitions/66.html * https://www.incapsula.com/web-application-security/sql-injection.html -creation_date = 2016-09-13 +date = 2017-09-19 -modification_date = 2017-09-19 - -version = 1.0 +version = 1 @@ -3019,47 +946,46 @@ Leveraging the Windows command-line interface (CLI) is one of the most common at ====Narrative==== The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Detect Prohibited Applications Spawning cmd exe +* Detect Use of cmd exe to Launch Script Interpreters +* First time seen command line argument +* System Processes Run From Unexpected Locations +* Unusually Long Command Line +* Unusually Long Command Line - MLTK ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1036 +* T1059 +* T1064 =====Kill Chain Phases===== +* Actions on Objectives * Command and Control +* Exploitation =====CIS===== * CIS 3 * CIS 8 -* CIS 12 =====NIST===== +* DE.CM * PR.IP * PR.PT -* PR.AC -* DE.AE -* DE.CM ====References==== * https://attack.mitre.org/wiki/Technique/T1059 * https://www.microsoft.com/en-us/wdsi/threats/macro-malware * https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf -creation_date = 2017-10-09 +date = 2020-02-03 -modification_date = 2020-02-03 - -version = 2.1 +version = 2 @@ -3074,44 +1000,53 @@ Attackers often attempt to hide within or otherwise abuse the domain name system ====Narrative==== Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. -====Providing Technologies==== -* Splunk Stream -* Bro +====Detections==== +* Clients Connecting to Multiple DNS Servers +* DNS Query Length Outliers - MLTK +* DNS Query Length With High Standard Deviation +* DNS Query Requests Resolved by Unauthorized DNS Servers +* Detect Long DNS TXT Record Response +* Detect hosts connecting to dynamic domain providers +* Detection of DNS Tunnels +* Excessive DNS Failures ====Data Models==== * Network_Resolution -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1043 +* T1048 =====Kill Chain Phases===== +* Actions on Objectives * Command and Control =====CIS===== +* CIS 1 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 +* CIS 9 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* ID.AM +* PR.DS +* PR.IP +* PR.PT ====References==== * http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/ * http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680 * https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454 -creation_date = 2016-09-13 +date = 2017-09-18 -modification_date = 2017-09-18 - -version = 1.0 +version = 1 @@ -3130,44 +1065,38 @@ Once a phishing message has been detected, the next steps are to answer the foll 1. When did the targeted campaign begin?\ 1. Have any users interacted with the content of the messages (by downloading an attachment or clicking on a malicious URL)?This Analytic Story provides detection searches to identify suspicious emails, as well as contextual and investigative searches to help answer some of these questions. -====Providing Technologies==== -* Microsoft Exchange -* Bro -* Splunk Stream +====Detections==== +* Email Attachments With Lots Of Spaces +* Monitor Email For Brand Abuse +* Suspicious Email - UBA Anomaly +* Suspicious Email Attachment Extensions ====Data Models==== * Email * UEBA -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration =====Kill Chain Phases===== -* Command and Control +* Delivery =====CIS===== -* CIS 3 -* CIS 8 * CIS 12 +* CIS 3 +* CIS 7 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE -* DE.CM +* PR.IP ====References==== * https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/ -creation_date = 2017-03-24 +date = 2020-01-27 -modification_date = 2020-01-27 - -version = 1.0 +version = 1 @@ -3184,47 +1113,41 @@ One common adversary tactic is to bypass application white-listing solutions via One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ The searches in this story help you detect and investigate suspicious activity that may indicate that an attacker is leveraging mshta.exe to execute malicious code. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Detect Prohibited Applications Spawning cmd exe +* Detect mshta exe running scripts in command-line arguments +* Registry Keys Used For Persistence ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1059 +* T1103 +* T1131 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives +* Exploitation =====CIS===== -* CIS 3 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* PR.PT ====References==== * https://redcanary.com/blog/windows-registry-attacks-threat-detection/ * https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5 * https://attack.mitre.org/wiki/Technique/T1170 -creation_date = 2018-08-07 +date = 2020-02-03 -modification_date = 2020-02-03 - -version = 1.1 +version = 1 @@ -3241,30 +1164,25 @@ Okta is the leading single sign on (SSO) provider, allowing users to authenticat While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ With people moving quickly to adopt web-based applications and ways to manage them, many are still struggling to understand how best to monitor these environments. This analytic story provides searches to help monitor this environment, and identify events and activity that warrant further investigation such as credential stuffing or password spraying attacks, and users logging in from multiple locations when travel is disallowed. -====Providing Technologies==== -* Okta +====Detections==== +* Multiple Okta Users With Invalid Credentails From The Same IP +* Okta Account Lockout Events +* Okta Failed SSO Attempts +* Okta User Logins From Multiple Cities ====Data Models==== -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1078 =====Kill Chain Phases===== -* Command and Control =====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 16 =====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE * DE.CM ====References==== @@ -3272,68 +1190,9 @@ With people moving quickly to adopt web-based applications and ways to manage th * https://owasp.org/www-community/attacks/Credential_stuffing * https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work -creation_date = 2020-04-02 +date = 2020-04-02 -modification_date = 2020-04-02 - -version = 1.0 - - - - -===Suspicious WMI Use=== - -Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. - -
-
- -====Narrative==== -WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ -The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ -In the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end. - -====Providing Technologies==== -* Carbon Black Response -* Sysmon -* Tanium -* Ziften -* CrowdStrike Falcon -* Microsoft Windows - -====Data Models==== -* Endpoint - -====Mappings==== - -=====ATT&CK===== -* Command and Control -* Exfiltration - -=====Kill Chain Phases===== -* Command and Control - -=====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 - -=====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -====References==== -* https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf -* https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html - -creation_date = 2017-01-13 - -modification_date = 2018-10-23 - -version = 2.0 +version = 1
@@ -3350,47 +1209,105 @@ Attackers are developing increasingly sophisticated techniques for hijacking tar The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ The searches in this story are designed to help you detect behaviors associated with manipulation of the Windows registry. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Disabling Remote User Account Control +* Monitor Registry Keys for Print Monitors +* Reg exe used to hide files directories via registry keys +* Registry Keys Used For Persistence +* Registry Keys Used For Privilege Escalation +* Registry Keys for Creating SHIM Databases +* Remote Registry Key modifications +* Suspicious Changes to File Associations ====Data Models==== * Endpoint -* Change_Analysis -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1015 +* T1042 +* T1103 +* T1112 +* T1131 +* T1138 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== * CIS 3 +* CIS 5 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* PR.AC +* PR.IP +* PR.PT ====References==== * https://redcanary.com/blog/windows-registry-attacks-threat-detection/ * https://attack.mitre.org/wiki/Technique/T1112 -creation_date = 2018-05-31 +date = 2018-05-31 -modification_date = 2018-05-31 +version = 1 -version = 1.0 + + + +===Suspicious WMI Use=== + +Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. + +
+
+ +====Narrative==== +WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ +The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ +In the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end. + +====Detections==== +* Process Execution via WMI +* Remote Process Instantiation via WMI +* Remote WMI Command Attempt +* Script Execution via WMI +* WMI Permanent Event Subscription +* WMI Permanent Event Subscription - Sysmon +* WMI Temporary Event Subscription + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== +* T1047 +* T1084 + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 3 +* CIS 5 + +=====NIST===== +* PR.AC +* PR.AT +* PR.IP +* PR.PT + +====References==== +* https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf +* https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html + +date = 2018-10-23 + +version = 2
@@ -3405,45 +1322,38 @@ Detect tactics used by malware to evade defenses on Windows endpoints. A few of ====Narrative==== Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Disabling Remote User Account Control +* Hiding Files And Directories With Attrib exe +* Reg exe used to hide files directories via registry keys +* Remote Registry Key modifications +* Suspicious Reg exe Process ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1089 +* T1112 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== -* CIS 3 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC -* DE.AE * DE.CM +* PR.PT ====References==== * https://attack.mitre.org/wiki/Defense_Evasion -creation_date = 2017-10-11 +date = 2018-05-31 -modification_date = 2018-05-31 - -version = 1.0 +version = 1 @@ -3459,48 +1369,47 @@ Adversaries often try to cover their tracks by manipulating Windows logs. Use th Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Microsoft Windows +====Detections==== +* Deleting Shadow Copies +* Suspicious wevtutil Usage +* USN Journal Deletion +* Windows Event Log Cleared ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1070 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives =====CIS===== +* CIS 10 * CIS 3 +* CIS 5 +* CIS 6 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* DE.DP +* PR.AC +* PR.AT +* PR.IP +* PR.PT ====References==== * https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ * https://zeltser.com/security-incident-log-review-checklist/ * http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html -creation_date = 2017-02-17 +date = 2017-09-12 -modification_date = 2017-09-12 - -version = 2.0 +version = 2 @@ -3515,37 +1424,50 @@ Monitor for activities and techniques associated with maintaining persistence on ====Narrative==== Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Tanium -* Ziften -* Sysmon +====Detections==== +* Detect Path Interception By Creation Of program exe +* Hiding Files And Directories With Attrib exe +* Monitor Registry Keys for Print Monitors +* Reg exe Manipulating Windows Services Registry Keys +* Reg exe used to hide files directories via registry keys +* Registry Keys Used For Persistence +* Registry Keys for Creating SHIM Databases +* Remote Registry Key modifications +* Sc exe Manipulating Windows Services +* Schtasks used for forcing a reboot +* Shim Database File Creation +* Shim Database Installation With Suspicious Parameters ====Data Models==== * Endpoint -* Change_Analysis -====Mappings==== +====Tags==== =====ATT&CK===== -* Command and Control -* Exfiltration +* T1031 +* T1050 +* T1053 +* T1089 +* T1103 +* T1131 +* T1138 =====Kill Chain Phases===== -* Command and Control +* Actions on Objectives +* Installation =====CIS===== * CIS 3 +* CIS 5 * CIS 8 -* CIS 12 =====NIST===== -* PR.IP -* PR.PT -* PR.AC * DE.AE * DE.CM +* PR.AC +* PR.AT +* PR.IP +* PR.PT ====References==== * http://www.fuzzysecurity.com/tutorials/19.html @@ -3554,11 +1476,9 @@ Maintaining persistence is one of the first steps taken by attackers after the i * https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html * https://www.youtube.com/watch?v=dq2Hv7J9fvk -creation_date = 2017-04-19 +date = 2018-05-31 -modification_date = 2018-05-31 - -version = 2.0 +version = 2 @@ -3573,47 +1493,1907 @@ Monitor for and investigate activities that may be associated with a Windows pri ====Narrative==== Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. -====Providing Technologies==== -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +====Detections==== +* Child Processes of Spoolsv exe +* Overwriting Accessibility Binaries +* Registry Keys Used For Privilege Escalation +* Uncommon Processes On Endpoint ====Data Models==== * Endpoint -====Mappings==== +====Tags==== =====ATT&CK===== +* T1015 +* T1068 + +=====Kill Chain Phases===== +* Actions on Objectives +* Exploitation + +=====CIS===== +* CIS 2 +* CIS 8 + +=====NIST===== +* DE.CM +* ID.AM +* PR.DS +* PR.PT + +====References==== +* https://attack.mitre.org/tactics/TA0004/ + +date = 2020-02-04 + +version = 2 + + + + + +==Best Practices== + +===Account Monitoring and Controls=== + +A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. + +
+
+ +====Narrative==== +Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. + +====Detections==== +* Detect Excessive Account Lockouts From Endpoint +* Detect Excessive User Account Lockouts +* Identify New User Accounts +* Short Lived Windows Accounts + +====Data Models==== +* Change + +====Tags==== + +=====ATT&CK===== +* T1078 +* T1136 + +=====Kill Chain Phases===== + +=====CIS===== +* CIS 16 + +=====NIST===== +* PR.IP + +====References==== +* https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf + +date = 2017-09-06 + +version = 1 + +
+
+ +===Asset Tracking=== + +Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. + +
+
+ +====Narrative==== +This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. + +====Detections==== +* Detect Unauthorized Assets by MAC address + +====Data Models==== +* Network_Sessions + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 1 + +=====NIST===== +* PR.DS + +====References==== +* https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/ + +date = 2017-09-13 + +version = 1 + +
+
+ +===Monitor Backup Solution=== + +Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. + +
+
+ +====Narrative==== +Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. + +====Detections==== +* Extended Period Without Successful Netbackup Backups +* Unsuccessful Netbackup backups + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== + +=====CIS===== +* CIS 10 + +=====NIST===== +* PR.IP + +====References==== +* https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/ + +date = 2017-09-12 + +version = 1 + +
+
+ +===Monitor for Unauthorized Software=== + +Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. + +
+
+ +====Narrative==== +It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ +It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. + +====Detections==== +* Prohibited Software On Endpoint + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 2 + +=====NIST===== +* PR.DS + +====References==== +* https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ + +date = 2017-09-15 + +version = 1 + +
+
+ +===Monitor for Updates=== + +Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. + +
+
+ +====Narrative==== +It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ +Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ +Microsoft releases updates for Windows systems on a monthly cadence. They should be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed. + +====Detections==== +* No Windows Updates in a time frame + +====Data Models==== +* Updates + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== + +=====CIS===== +* CIS 18 + +=====NIST===== +* PR.MA + +====References==== +* https://learn.cisecurity.org/20-controls-download + +date = 2017-09-15 + +version = 1 + +
+
+ +===Prohibited Traffic Allowed or Protocol Mismatch=== + +Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. + +
+
+ +====Narrative==== +A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. + +====Detections==== +* Detect hosts connecting to dynamic domain providers +* Prohibited Network Traffic Allowed +* Protocol or Port Mismatch +* TOR Traffic + +====Data Models==== +* Network_Resolution +* Network_Traffic + +====Tags==== + +=====ATT&CK===== +* T1043 +* T1048 + +=====Kill Chain Phases===== +* Actions on Objectives * Command and Control -* Exfiltration +* Delivery + +=====CIS===== +* CIS 12 +* CIS 13 +* CIS 9 + +=====NIST===== +* DE.AE +* DE.CM +* PR.AC + +====References==== +* http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/ + +date = 2017-09-11 + +version = 1 + +
+
+ +===Router and Infrastructure Security=== + +Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. + +
+
+ +====Narrative==== +Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ +This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. + +====Detections==== +* Detect New Login Attempts to Routers + +====Data Models==== +* Authentication + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 11 + +=====NIST===== +* PR.IP + +====References==== +* https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html +* https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html + +date = 2017-09-12 + +version = 1 + +
+
+ +===Use of Cleartext Protocols=== + +Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. + +
+
+ +====Narrative==== +Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. + +====Detections==== +* Protocols passing authentication in cleartext + +====Data Models==== +* Network_Traffic + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 14 + +=====NIST===== +* PR.DS + +====References==== +* https://www.monkey.org/~dugsong/dsniff/ + +date = 2017-09-15 + +version = 1 + +
+
+ + +==Cloud Security== + +===AWS Cross Account Activity=== + +Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. + +
+
+ +====Narrative==== +Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ +Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ +This Analytic Story includes searches that will help you monitor your AWS CloudTrail logs for evidence of suspicious cross-account activity. For example, while accessing multiple AWS accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply. + +====Detections==== +* AWS Cross Account Activity From Previously Unseen Account + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 16 + +=====NIST===== +* DE.AE + +====References==== +* https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/ + +date = 2018-06-04 + +version = 1 + +
+
+ +===AWS Cryptomining=== + +Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. + +
+
+ +====Narrative==== +Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ +Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ +hen malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So, it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ +This Analytic Story is focused on detecting suspicious new instances in your EC2 environment to help prevent such a disaster. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. + +====Detections==== +* Abnormally High AWS Instances Launched by User +* EC2 Instance Started In Previously Unseen Region +* EC2 Instance Started With Previously Unseen AMI +* EC2 Instance Started With Previously Unseen Instance Type +* EC2 Instance Started With Previously Unseen User + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 1 +* CIS 12 +* CIS 13 + +=====NIST===== +* DE.AE +* DE.DP +* ID.AM + +====References==== +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +date = 2018-03-08 + +version = 1 + +
+
+ +===AWS Network ACL Activity=== + +Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. + +
+
+ +====Narrative==== +AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. + +====Detections==== +* AWS Network Access Control List Created with All Open Ports +* AWS Network Access Control List Deleted +* Detect Spike in Network ACL Activity +* Detect Spike in blocked Outbound Traffic from your AWS + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control + +=====CIS===== +* CIS 11 +* CIS 12 + +=====NIST===== +* DE.AE +* DE.CM +* DE.DP +* PR.AC + +====References==== +* https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html +* https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/ + +date = 2018-05-21 + +version = 2 + +
+
+ +===AWS Suspicious Provisioning Activities=== + +Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. + +
+
+ +====Narrative==== +Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ +This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. + +====Detections==== +* AWS Cloud Provisioning From Previously Unseen City +* AWS Cloud Provisioning From Previously Unseen Country +* AWS Cloud Provisioning From Previously Unseen IP Address +* AWS Cloud Provisioning From Previously Unseen Region + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== + +=====CIS===== +* CIS 1 + +=====NIST===== +* ID.AM + +====References==== +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +date = 2018-03-16 + +version = 1 + +
+
+ +===AWS User Monitoring=== + +Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. + +
+
+ +====Narrative==== +It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ +In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ +Fortunately, you can leverage Amazon Web Services (AWS) CloudTrail--a tool that helps you enable governance, compliance, and risk auditing of your AWS account--to give you increased visibility into your user and resource activity by recording AWS Management Console actions and API calls. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred.\ +The detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts. + +====Detections==== +* Detect API activity from users without MFA +* Detect AWS API Activities From Unapproved Accounts +* Detect Spike in AWS API Activity +* Detect Spike in Security Group Activity +* Detect new API calls from user roles + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 1 +* CIS 16 + +=====NIST===== +* DE.CM +* DE.DP +* ID.AM +* PR.AC + +====References==== +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +* https://redlock.io/blog/cryptojacking-tesla + +date = 2018-03-12 + +version = 1 + +
+
+ +===Cloud Cryptomining=== + +Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. + +
+
+ +====Narrative==== +Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ +Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ +When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ +This Analytic Story is focused on detecting suspicious new instances in your cloud environment to help prevent cryptominers from gaining a foothold. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. + +====Detections==== +* Abnormally High AWS Instances Launched by User - MLTK +* Cloud Compute Instance Created By Previously Unseen User +* Cloud Compute Instance Created With Previously Unseen Image +* Cloud Compute Instance Created With Previously Unseen Instance Type +* Cloud Compute Instance Started In Previously Unused Region + +====Data Models==== +* Cloud_Infrastructure + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 1 +* CIS 12 +* CIS 13 + +=====NIST===== +* DE.AE +* DE.DP +* ID.AM + +====References==== +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +date = 2019-10-02 + +version = 1 + +
+
+ +===Container Implantation Monitoring and Investigation=== + +Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. + +
+
+ +====Narrative==== +Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. + +====Detections==== +* GCP GCR container uploaded +* New container uploaded to AWS ECR + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== + +=====CIS===== + +=====NIST===== + +====References==== +* https://github.com/splunk/cloud-datamodel-security-research + +date = 2020-02-20 + +version = 1 + +
+
+ +===Kubernetes Scanning Activity=== + +This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. + +
+
+ +====Narrative==== +Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. + +====Detections==== +* Amazon EKS Kubernetes Pod scan detection +* Amazon EKS Kubernetes cluster scan detection +* GCP Kubernetes cluster scan detection + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Reconnaissance + +=====CIS===== + +=====NIST===== + +====References==== +* https://github.com/splunk/cloud-datamodel-security-research + +date = 2020-04-15 + +version = 1 + +
+
+ +===Suspicious AWS EC2 Activities=== + +Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. + +
+
+ +====Narrative==== +AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. + +====Detections==== +* Abnormally High AWS Instances Launched by User +* Abnormally High AWS Instances Launched by User - MLTK +* Abnormally High AWS Instances Terminated by User +* Abnormally High AWS Instances Terminated by User - MLTK +* EC2 Instance Started In Previously Unseen Region +* EC2 Instance Started With Previously Unseen User + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 1 +* CIS 12 +* CIS 13 + +=====NIST===== +* DE.AE +* DE.DP +* ID.AM + +====References==== +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +date = 2018-02-09 + +version = 1 + +
+
+ +===Suspicious AWS Login Activities=== + +Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. + +
+
+ +====Narrative==== +It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. + +====Detections==== +* Detect AWS Console Login by User from New City +* Detect AWS Console Login by User from New Country +* Detect AWS Console Login by User from New Region +* Detect new user AWS Console Login + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 16 + +=====NIST===== +* DE.AE +* DE.DP + +====References==== +* https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html + +date = 2019-05-01 + +version = 1 + +
+
+ +===Suspicious AWS S3 Activities=== + +Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. + +
+
+ +====Narrative==== +As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ +Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ +Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. + +====Detections==== +* Detect New Open S3 buckets +* Detect S3 access from a new IP +* Detect Spike in S3 Bucket deletion + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 13 +* CIS 14 + +=====NIST===== +* DE.CM +* DE.DP +* PR.AC +* PR.DS + +====References==== +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +* https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/ + +date = 2018-07-24 + +version = 2 + +
+
+ +===Suspicious AWS Traffic=== + +Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). + +
+
+ +====Narrative==== +A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ +Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ + Attackers may abuse the AWS infrastructure with insecure VPCs so they can co-opt AWS resources for command-and-control nodes, data exfiltration, and more. Once an EC2 instance is compromised, an attacker may initiate outbound network connections for malicious reasons. Monitoring these network traffic behaviors is crucial for understanding the type of traffic flowing in and out of your network and to alert you to suspicious activities.\ +The searches in this Analytic Story will monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors. + +====Detections==== +* Detect Spike in blocked Outbound Traffic from your AWS + +====Data Models==== + +====Tags==== + +=====ATT&CK===== =====Kill Chain Phases===== * Command and Control =====CIS===== -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 11 =====NIST===== +* PR.AC + +====References==== +* https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/ + +date = 2018-05-07 + +version = 1 + +
+
+ +===Unusual AWS EC2 Modifications=== + +Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. + +
+
+ +====Narrative==== +A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ + Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. + +====Detections==== +* EC2 Instance Modified With Previously Unseen User + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== + +=====CIS===== +* CIS 1 + +=====NIST===== +* ID.AM + +====References==== +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +date = 2018-04-09 + +version = 1 + +
+
+ + +==Malware== + +===ColdRoot MacOS RAT=== + +Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. + +
+
+ +====Narrative==== +Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ +This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ +Searches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger. + +====Detections==== +* Osquery pack - ColdRoot detection +* Processes Tapping Keyboard Events + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Command and Control + +=====CIS===== +* CIS 4 +* CIS 8 + +=====NIST===== +* DE.DP +* PR.PT + +====References==== +* https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/ +* https://objective-see.com/blog/blog_0x2A.html +* https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/ + +date = 2019-01-09 + +version = 1 + +
+
+ +===DHS Report TA18-074A=== + +Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. + +
+
+ +====Narrative==== +The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ +There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ +One joint Technical Alert (TA) issued by the Department of Homeland and the FBI in mid-March of 2018 attributed some cyber activity targeting utility infrastructure to operatives sponsored by the Russian government. The hackers executed spearfishing attacks, installed malware, employed watering-hole domains, and more. While they caused no physical damage, the attacks provoked fears that a nation-state could turn off water, redirect power, or compromise a nuclear power plant.\ +Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify the network configuration), suspicious registry modifications, and many more--may all be events you may wish to investigate further. While the use of these technique may be an indication that a nation-state actor is attempting to compromise your environment, it is important to note that these techniques are often employed by other groups, as well. + +====Detections==== +* Create local admin accounts using net exe +* Detect New Local Admin account +* Detect Outbound SMB Traffic +* Detect PsExec With accepteula Flag +* First time seen command line argument +* Malicious PowerShell Process - Execution Policy Bypass +* Processes launching netsh +* Registry Keys Used For Persistence +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Sc exe Manipulating Windows Services +* Scheduled Task Name Used by Dragonfly Threat Actors +* Single Letter Process On Endpoint +* Suspicious Reg exe Process + +====Data Models==== +* Endpoint +* Network_Traffic + +====Tags==== + +=====ATT&CK===== +* T1031 +* T1043 +* T1050 +* T1053 +* T1059 +* T1064 +* T1078 +* T1086 +* T1089 +* T1103 +* T1112 +* T1131 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control +* Installation + +=====CIS===== +* CIS 12 +* CIS 16 +* CIS 2 +* CIS 3 +* CIS 5 +* CIS 7 +* CIS 8 + +=====NIST===== +* DE.AE +* DE.CM +* ID.AM +* PR.AC +* PR.AT +* PR.DS * PR.IP * PR.PT -* PR.AC + +====References==== +* https://www.us-cert.gov/ncas/alerts/TA18-074A + +date = 2020-01-22 + +version = 2 + +
+
+ +===Dynamic DNS=== + +Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. + +
+
+ +====Narrative==== +Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. + +====Detections==== +* Detect hosts connecting to dynamic domain providers +* Detect web traffic to dynamic domain providers + +====Data Models==== +* Network_Resolution +* Web + +====Tags==== + +=====ATT&CK===== +* T1041 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control + +=====CIS===== +* CIS 13 +* CIS 7 +* CIS 8 + +=====NIST===== +* DE.CM +* DE.DP +* PR.IP + +====References==== +* https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html +* https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ +* http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ +* https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html + +date = 2018-09-06 + +version = 2 + +
+
+ +===Emotet Malware DHS Report TA18-201A === + +Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. + +
+
+ +====Narrative==== +The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ +According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ +The searches in this Analytic Story will help you find executables that are rarely used in your environment, specific registry paths that malware often uses to ensure survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. + +====Detections==== +* Detect Rare Executables +* Detect Use of cmd exe to Launch Script Interpreters +* Detection of tools built by NirSoft +* Email Attachments With Lots Of Spaces +* Prohibited Software On Endpoint +* Registry Keys Used For Persistence +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Suspicious Email Attachment Extensions + +====Data Models==== +* Email +* Endpoint +* Network_Traffic + +====Tags==== + +=====ATT&CK===== +* T1043 +* T1059 +* T1072 +* T1087 +* T1103 +* T1131 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control +* Delivery +* Exploitation +* Installation + +=====CIS===== +* CIS 12 +* CIS 2 +* CIS 3 +* CIS 7 +* CIS 8 + +=====NIST===== * DE.AE * DE.CM +* ID.AM +* PR.DS +* PR.IP +* PR.PT + +====References==== +* https://www.us-cert.gov/ncas/alerts/TA18-201A +* https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf +* https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html + +date = 2020-01-27 + +version = 1 + +
+
+ +===Hidden Cobra Malware=== + +Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. + +
+
+ +====Narrative==== +North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ +These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ +In June of 2018, The Department of Homeland Security, together with the FBI and other U.S. government partners, issued Technical Alert (TA-18-149A) to advise the public about two variants of North Korean malware. One variant, dubbed "Joanap," is a multi-stage peer-to-peer botnet that allows North Korean state actors to exfiltrate data, download and execute secondary payloads, and initialize proxy communications. The other variant, "Brambul," is a Windows32 SMB worm that is dropped into a victim network. When executed, the malware attempts to spread laterally within a victim's local subnet, connecting via the SMB protocol and initiating brute-force password attacks. It reports details to the Hidden Cobra actors via email, so they can use the information for secondary remote operations.\ +Among other searches in this Analytic Story is a detection search that looks for the creation or deletion of hidden shares, such as, "adnim$," which the Hidden Cobra malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers. + +====Detections==== +* Create or delete windows shares using net exe +* DNS Query Length Outliers - MLTK +* DNS Query Length With High Standard Deviation +* Detect Outbound SMB Traffic +* First time seen command line argument +* Remote Desktop Network Traffic +* Remote Desktop Process Running On System +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Suspicious File Write + +====Data Models==== +* Endpoint +* Network_Resolution +* Network_Traffic + +====Tags==== + +=====ATT&CK===== +* T1043 +* T1059 +* T1064 +* T1076 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control + +=====CIS===== +* CIS 12 +* CIS 16 +* CIS 3 +* CIS 8 +* CIS 9 + +=====NIST===== +* DE.AE +* DE.CM +* PR.AC +* PR.IP +* PR.PT + +====References==== +* https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity +* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf + +date = 2020-01-22 + +version = 2 + +
+
+ +===Orangeworm Attack Group=== + +Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. + +
+
+ +====Narrative==== +In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ +Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ +Although the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage. \ +Healthcare may be a promising target, because it is notoriously behind in technology, often using older operating systems and neglecting to patch computers. Even so, the group was able to evade detection for a full three years. Sources say that the malware spread quickly within the target networks, infecting computers used to control medical devices, such as MRI and X-ray machines.\ +This Analytic Story is designed to help you detect and investigate suspicious activities that may be indicative of an Orangeworm attack. One detection search looks for command-line arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised. + +====Detections==== +* First Time Seen Running Windows Service +* First time seen command line argument +* Sc exe Manipulating Windows Services + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== +* T1031 +* T1050 +* T1059 +* T1089 + +=====Kill Chain Phases===== +* Actions on Objectives +* Installation + +=====CIS===== +* CIS 2 +* CIS 3 +* CIS 5 +* CIS 8 +* CIS 9 + +=====NIST===== +* DE.AE +* DE.CM +* ID.AM +* PR.AC +* PR.AT +* PR.DS +* PR.IP +* PR.PT + +====References==== +* https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia +* https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/ + +date = 2020-01-22 + +version = 2 + +
+
+ +===Ransomware=== + +Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. + +
+
+ +====Narrative==== +Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. + +====Detections==== +* Common Ransomware Extensions +* Common Ransomware Notes +* Deleting Shadow Copies +* Prohibited Network Traffic Allowed +* Registry Keys Used For Persistence +* Remote Process Instantiation via WMI +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Scheduled tasks used in BadRabbit ransomware +* Schtasks used for forcing a reboot +* Spike in File Writes +* Suspicious wevtutil Usage +* System Processes Run From Unexpected Locations +* TOR Traffic +* USN Journal Deletion +* Unusually Long Command Line +* Unusually Long Command Line - MLTK +* Windows Event Log Cleared + +====Data Models==== +* Endpoint +* Network_Traffic + +====Tags==== + +=====ATT&CK===== +* T1036 +* T1043 +* T1047 +* T1048 +* T1053 +* T1070 +* T1103 +* T1131 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control +* Delivery + +=====CIS===== +* CIS 10 +* CIS 12 +* CIS 3 +* CIS 5 +* CIS 6 +* CIS 8 +* CIS 9 + +=====NIST===== +* DE.AE +* DE.CM +* DE.DP +* PR.AC +* PR.AT +* PR.IP +* PR.PT + +====References==== +* https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/ +* https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html + +date = 2020-02-04 + +version = 1 + +
+
+ +===SamSam Ransomware=== + +Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. + +
+
+ +====Narrative==== +The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ +Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ +SamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.\ +In a typical attack on one large healthcare organization in 2018, the company ended up paying a ransom of four Bitcoins, then worth $56,707. Reports showed that access to the company's files was restored within two hours of paying the sum.\ +According to Sophos, SamSam previously leveraged RDP to gain access to targeted networks via brute force. SamSam is not spread automatically, like other malware. It requires skill because it forces the attacker to adapt their tactics to the individual environment. Next, the actors escalate their privileges to admin level. They scan the networks for worthy targets, using conventional tools, such as PsExec or PaExec, to deploy/execute, quickly encrypting files.\ +This Analytic Story includes searches designed to help detect and investigate signs of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP. + +====Detections==== +* Batch File Write to System32 +* Common Ransomware Extensions +* Common Ransomware Notes +* Deleting Shadow Copies +* Detect PsExec With accepteula Flag +* Detect attackers scanning for vulnerable JBoss servers +* Detect malicious requests to exploit JBoss servers +* File with Samsam Extension +* Prohibited Software On Endpoint +* Remote Desktop Network Bruteforce +* Remote Desktop Network Traffic +* Samsam Test File Write +* Spike in File Writes + +====Data Models==== +* Endpoint +* Network_Traffic +* Web + +====Tags==== + +=====ATT&CK===== +* T1059 +* T1076 +* T1082 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control +* Delivery +* Installation +* Reconnaissance + +=====CIS===== +* CIS 10 +* CIS 12 +* CIS 16 +* CIS 18 +* CIS 2 +* CIS 3 +* CIS 4 +* CIS 8 +* CIS 9 + +=====NIST===== +* DE.AE +* DE.CM +* ID.AM +* ID.RA +* PR.AC +* PR.DS +* PR.IP +* PR.MA +* PR.PT + +====References==== +* https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/ +* https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/ +* https://thehackernews.com/2018/07/samsam-ransomware-attacks.html + +date = 2018-12-13 + +version = 1 + +
+
+ +===Unusual Processes=== + +Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. + +
+
+ +====Narrative==== +Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ +This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ +In the event an unusual process is identified, it is imperative to better understand how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity. + +====Detections==== +* Detect Rare Executables +* Detect processes used for System Network Configuration Discovery +* RunDLL Loading DLL By Ordinal +* System Processes Run From Unexpected Locations +* Uncommon Processes On Endpoint +* Unusually Long Command Line +* Unusually Long Command Line - MLTK + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== +* T1015 +* T1036 +* T1085 + +=====Kill Chain Phases===== +* Actions on Objectives +* Command and Control +* Installation + +=====CIS===== +* CIS 2 +* CIS 8 + +=====NIST===== +* DE.CM +* ID.AM +* PR.DS +* PR.PT + +====References==== +* https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html +* https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf +* https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262 + +date = 2020-02-04 + +version = 2 + +
+
+ +===Windows File Extension and Association Abuse=== + +Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. + +
+
+ +====Narrative==== +Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ + Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ + Attackers take advantage of this expectation by obfuscating the true file extension. They can accomplish this in a couple of ways. One technique involves inserting multiple spaces in the file name before the extension to hide the extension from the GUI, obscuring the true nature of the file. Another approach involves prepending the real extension with a different one. This is especially effective when Windows is configured to "hide extensions for known file types." In this case, the real extension is not displayed, but the prepended one is, leading end users to believe the file is a different type than it actually is.\ +Changing the association between a file extension and an application can allow an attacker to execute arbitrary code. The technique typically involves changing the association for an often-launched file type to associate instead with a malicious program the attacker has dropped on the endpoint. When the end user launches a file that has been manipulated in this way, it will execute the attacker's malware. It will also execute the application the end user expected to run, cleverly obscuring the fact that something suspicious has occurred.\ +Run the searches in this story to detect and investigate suspicious behavior that may indicate abuse or manipulation of Windows file extensions and/or associations. + +====Detections==== +* Execution of File With Spaces Before Extension +* Execution of File with Multiple Extensions +* Suspicious Changes to File Associations + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== +* T1042 + +=====Kill Chain Phases===== +* Actions on Objectives + +=====CIS===== +* CIS 3 +* CIS 8 + +=====NIST===== +* DE.CM +* PR.IP +* PR.PT + +====References==== +* https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/ +* https://attack.mitre.org/wiki/Technique/T1042 + +date = 2018-01-26 + +version = 1 + +
+
+ +===Windows Service Abuse=== + +Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. + +
+
+ +====Narrative==== +The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. + +====Detections==== +* First Time Seen Running Windows Service +* Reg exe Manipulating Windows Services Registry Keys +* Sc exe Manipulating Windows Services + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== +* T1031 +* T1050 +* T1089 + +=====Kill Chain Phases===== +* Actions on Objectives +* Installation + +=====CIS===== +* CIS 3 +* CIS 5 +* CIS 8 +* CIS 9 + +=====NIST===== +* DE.AE +* DE.CM +* PR.AC +* PR.AT +* PR.IP +* PR.PT + +====References==== +* https://attack.mitre.org/wiki/Technique/T1050 +* https://attack.mitre.org/wiki/Technique/T1031 + +date = 2017-11-02 + +version = 3 + +
+
+ + +==Vulnerability== + +===Apache Struts Vulnerability=== + +Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. + +
+
+ +====Narrative==== +In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ +The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ +This Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the `Content-Type` header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the `Content-Type` header is generally consistent and does not have a large degree of variation.\ +The second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.\ +First, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.\ +hen looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.\ +Various types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.\ +Looking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of "who," in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.\ +Gathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ +hen a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.\ +hen it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ +In the event that a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that have the file open, what processes created and/or modified the file, and the number of systems that may have this file can help to determine if the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes quickly help determine whether it is malicious in nature.\ +Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, there may be activity initiated via a compromised website the user visited.\ +It can also be very helpful to examine various behaviors of the process of interest or the parent of the process that is of interest. For example, if it turns out that the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might also be worth further scrutiny. If a process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. + +====Detections==== +* Suspicious Java Classes +* Unusually Long Content-Type Length +* Web Servers Executing Suspicious Processes + +====Data Models==== +* Endpoint + +====Tags==== + +=====ATT&CK===== +* T1082 + +=====Kill Chain Phases===== +* Actions on Objectives +* Delivery +* Exploitation + +=====CIS===== +* CIS 12 +* CIS 18 +* CIS 3 +* CIS 4 + +=====NIST===== +* DE.AE +* DE.CM +* ID.RA +* PR.IP +* PR.MA +* PR.PT +* RS.MI + +====References==== +* https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf + +date = 2018-12-06 + +version = 1 + +
+
+ +===JBoss Vulnerability=== + +In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. + +
+
+ +====Narrative==== +This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ +It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ +hen looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.\ +Various types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.\ +The following factors may assist you in determining whether the event is malicious: \ +1. Country of origin\ +1. Responsible party\ +1. Fully qualified domain names associated with the external IP address\ +1. Registration of fully qualified domain names associated with external IP address Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.\ +Gathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ +hen a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.\ +If you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ +If a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that opened the file, the processes that may have created and/or modified the file, and how many other systems potentially have this file can you determine whether the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes help you quickly determine if it is malicious in nature.\ +Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. \ +It can also be helpful to examine various behaviors of and the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see whether the parent process spawned other processes that might also warrant further scrutiny. If a process is suspect, a review of the network connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. + +====Detections==== +* Detect attackers scanning for vulnerable JBoss servers +* Detect malicious requests to exploit JBoss servers + +====Data Models==== +* Web + +====Tags==== + +=====ATT&CK===== +* T1082 + +=====Kill Chain Phases===== +* Delivery +* Reconnaissance + +=====CIS===== +* CIS 18 + +=====NIST===== +* DE.CM ====References==== -* https://attack.mitre.org/tactics/TA0004/ +* http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html -creation_date = 2017-12-07 +date = 2017-09-14 -modification_date = 2020-02-04 - -version = 2.0 +version = 1
-[[Category:V:Lab:drafts]] \ No newline at end of file +===Spectre And Meltdown Vulnerabilities=== + +Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. + +
+
+ +====Narrative==== +Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. + +====Detections==== +* Spectre and Meltdown Vulnerable Systems + +====Data Models==== +* Vulnerabilities + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== + +=====CIS===== +* CIS 4 + +=====NIST===== +* DE.CM + +====References==== +* https://meltdownattack.com/ + +date = 2018-01-08 + +version = 1 + +
+
+ +===Splunk Enterprise Vulnerability=== + +Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. + +
+
+ +====Narrative==== +This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ +\ +1. Splunk Enterprise 6.4.x, prior to 6.4.3\ +1. Splunk Enterprise 6.3.x, prior to 6.3.6\ +1. Splunk Enterprise 6.2.x, prior to 6.2.10\ +1. Splunk Enterprise 6.1.x, prior to 6.1.11\ +1. Splunk Enterprise 6.0.x, prior to 6.0.12\ +1. Splunk Enterprise 5.0.x, prior to 5.0.16\ +1. Splunk Light, prior to 6.4.3CVE-2016-4859 allows attackers to redirect users to arbitrary web sites and conduct phishing attacks via unspecified vectors. (Credit: Noriaki Iwasaki, Cyber Defense Institute, Inc.).\ +It is important to ensure that your Splunk deployment is being kept up to date and is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites. + +====Detections==== +* Open Redirect in Splunk Web + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Delivery + +=====CIS===== +* CIS 18 + +=====NIST===== +* DE.CM + +====References==== +* http://www.splunk.com/view/SP-CAAAPQ6#announce +* https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859 + +date = 2017-09-19 + +version = 1 + +
+
+ +===Splunk Enterprise Vulnerability CVE-2018-11409=== + +Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. + +
+
+ +====Narrative==== +Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ +Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ +Read more in Splunk's official response: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings.\ +A detection search within this Analytic Story looks for vulnerabilities described in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip. + +====Detections==== +* Splunk Enterprise Information Disclosure + +====Data Models==== + +====Tags==== + +=====ATT&CK===== + +=====Kill Chain Phases===== +* Delivery + +=====CIS===== +* CIS 18 + +=====NIST===== +* DE.CM + +====References==== +* https://nvd.nist.gov/vuln/detail/CVE-2018-11409 +* https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings +* https://www.exploit-db.com/exploits/44865/ + +date = 2018-06-14 + +version = 1 + +
+
+ + diff --git a/docs/stories_categories.md b/docs/stories_categories.md index c5a02e4949..21a0a8f245 100644 --- a/docs/stories_categories.md +++ b/docs/stories_categories.md @@ -1,1835 +1,234 @@ + # Categories Analytics stories organized by categories -* [Cloud Security](#cloud-security) +* [Abuse](#Abuse) -* [Best Practices](#best-practices) +* [Adversary Tactics](#Adversary-Tactics) -* [Vulnerability](#vulnerability) +* [Best Practices](#Best-Practices) -* [Abuse](#abuse) +* [Cloud Security](#Cloud-Security) -* [Malware](#malware) +* [Malware](#Malware) -* [Adversary Tactics](#adversary-tactics) - - -## Cloud Security - -* [AWS Cross Account Activity](#aws-cross-account-activity) - -* [AWS Cryptomining](#aws-cryptomining) - -* [AWS Network ACL Activity](#aws-network-acl-activity) - -* [AWS Suspicious Provisioning Activities](#aws-suspicious-provisioning-activities) - -* [AWS User Monitoring](#aws-user-monitoring) - -* [Cloud Cryptomining](#cloud-cryptomining) - -* [Container Implantation Monitoring & Investigation](#container-implantation-monitoring-&-investigation) - -* [Kubernetes Scanning Activity](#kubernetes-scanning-activity) - -* [Suspicious AWS EC2 Activities](#suspicious-aws-ec2-activities) - -* [Suspicious AWS Login Activities](#suspicious-aws-login-activities) - -* [Suspicious AWS S3 Activities](#suspicious-aws-s3-activities) - -* [Suspicious AWS Traffic](#suspicious-aws-traffic) - -* [Unusual AWS EC2 Modifications](#unusual-aws-ec2-modifications) - -### AWS Cross Account Activity -* id = `2f2f610a-d64d-48c2-b57c-967a2b49ab5a` -* creation_date = 2018-06-04 -* modification_date = 2018-06-04 -* version = 1.0 -* spec_version = 2 - -##### Description -Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. - -##### Narrative -Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ -Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ -This Analytic Story includes searches that will help you monitor your AWS CloudTrail logs for evidence of suspicious cross-account activity. For example, while accessing multiple AWS accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply. - -##### Detections -* AWS Cross Account Activity From Previously Unseen Account - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/ - -### AWS Cryptomining -* id = `ced74200-8465-4bc3-bd2c-9a782eec6750` -* creation_date = 2018-03-08 -* modification_date = 2018-03-08 -* version = 1.0 -* spec_version = 2 - -##### Description -Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. - -##### Narrative -Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ -Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ -hen malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So, it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ -This Analytic Story is focused on detecting suspicious new instances in your EC2 environment to help prevent such a disaster. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. - -##### Detections -* EC2 Instance Started In Previously Unseen Region -* Abnormally High AWS Instances Launched by User -* EC2 Instance Started With Previously Unseen Instance Type -* EC2 Instance Started With Previously Unseen AMI -* EC2 Instance Started With Previously Unseen User - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -### AWS Network ACL Activity -* id = `2e8948a5-5239-406b-b56b-6c50ff268af4` -* creation_date = 2018-01-10 -* modification_date = 2018-05-21 -* version = 2.0 -* spec_version = 2 - -##### Description -Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. - -##### Narrative -AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. - -##### Detections -* AWS Network Access Control List Created with All Open Ports -* AWS Network Access Control List Deleted -* Detect Spike in blocked Outbound Traffic from your AWS -* Detect Spike in Network ACL Activity - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html -* https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/ - -### AWS Suspicious Provisioning Activities -* id = `3338b567-3804-4261-9889-cf0ca4753c7f` -* creation_date = 2018-03-16 -* modification_date = 2018-03-16 -* version = 1.0 -* spec_version = 2 - -##### Description -Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. - -##### Narrative -Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ -This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. - -##### Detections -* AWS Cloud Provisioning From Previously Unseen Country -* AWS Cloud Provisioning From Previously Unseen Region -* AWS Cloud Provisioning From Previously Unseen City -* AWS Cloud Provisioning From Previously Unseen IP Address - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -### AWS User Monitoring -* id = `2e8948a5-5239-406b-b56b-6c50f1269af3` -* creation_date = 2018-03-12 -* modification_date = 2018-03-12 -* version = 1.0 -* spec_version = 2 - -##### Description -Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. - -##### Narrative -It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ -In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ -Fortunately, you can leverage Amazon Web Services (AWS) CloudTrail--a tool that helps you enable governance, compliance, and risk auditing of your AWS account--to give you increased visibility into your user and resource activity by recording AWS Management Console actions and API calls. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred.\ -The detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts. - -##### Detections -* Detect AWS API Activities From Unapproved Accounts -* Detect Spike in AWS API Activity -* Detect new API calls from user roles -* Detect Spike in Security Group Activity -* Detect API activity from users without MFA - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -* https://redlock.io/blog/cryptojacking-tesla - -### Cloud Cryptomining -* id = `3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a` -* creation_date = 2019-10-02 -* modification_date = 2019-10-02 -* version = 1.0 -* spec_version = 2 - -##### Description -Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. - -##### Narrative -Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ -Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ -When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ -This Analytic Story is focused on detecting suspicious new instances in your cloud environment to help prevent cryptominers from gaining a foothold. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. - -##### Detections -* Cloud Compute Instance Started In Previously Unused Region -* Cloud Compute Instance Created With Previously Unseen Instance Type -* Cloud Compute Instance Created With Previously Unseen Image -* Cloud Compute Instance Created By Previously Unseen User -* Abnormally High AWS Instances Launched by User - MLTK - -##### Providing Technologies -* AWS -* Azure -* GCP - -##### Data Models -Cloud_Infrastructure - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -### Container Implantation Monitoring & Investigation -* id = `aa0e28b1-0521-4b6f-9d2a-7b87e34af246` -* creation_date = 2020-02-20 -* modification_date = 2020-02-20 -* version = 1.0 -* spec_version = 2 - -##### Description -Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. - -##### Narrative -Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. - -##### Detections -* New container uploaded to AWS ECR -* GCP GCR container uploaded - -##### Providing Technologies -* GCP -* AWS - -##### Data Models -Cloud_Infrastructure - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rod Soto, Rico Valdez -* email = rsoto@splunk.com, rvaldez@splunk.com -* company = Splunk - -##### References -* https://github.com/splunk/cloud-datamodel-security-research - -### Kubernetes Scanning Activity -* id = `a9ef59cf-e981-4e66-9eef-bb049f695c09` -* creation_date = 2020-03-24 -* modification_date = 2020-04-15 -* version = 1.0 -* spec_version = 2 - -##### Description -This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. - -##### Narrative -Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. - -##### Detections -* GCP Kubernetes cluster scan detection -* Amazon EKS Kubernetes cluster scan detection -* Amazon EKS Kubernetes Pod scan detection - -##### Providing Technologies -* AWS -* GCP - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rod Soto -* email = rsoto@splunk.com -* company = Splunk - -##### References -* https://github.com/splunk/cloud-datamodel-security-research - -### Suspicious AWS EC2 Activities -* id = `2e8948a5-5239-406b-b56b-6c50f1268af3` -* creation_date = 2018-02-09 -* modification_date = 2018-02-09 -* version = 1.0 -* spec_version = 2 - -##### Description -Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. - -##### Narrative -AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. - -##### Detections -* EC2 Instance Started In Previously Unseen Region -* Abnormally High AWS Instances Terminated by User -* Abnormally High AWS Instances Launched by User -* EC2 Instance Started With Previously Unseen User -* Abnormally High AWS Instances Launched by User - MLTK -* Abnormally High AWS Instances Terminated by User - MLTK - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - -### Suspicious AWS Login Activities -* id = `2e8948a5-5239-406b-b56b-6c59f1268af3` -* creation_date = 2018-02-24 -* modification_date = 2019-05-01 -* version = 1.0 -* spec_version = 2 - -##### Description -Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. - -##### Narrative -It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. - -##### Detections -* Detect new user AWS Console Login -* Detect AWS Console Login by User from New City -* Detect AWS Console Login by User from New Region -* Detect AWS Console Login by User from New Country - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk -* name = Jason Brewer -* email = jbrewer@splunk.com -* company = Splunk - -##### References -* https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html - -### Suspicious AWS S3 Activities -* id = `2e8948a5-5239-406b-b56b-6c50w3168af3` -* creation_date = 2018-06-25 -* modification_date = 2018-07-24 -* version = 2.0 -* spec_version = 2 - -##### Description -Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. - -##### Narrative -As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ -Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ -Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. - -##### Detections -* Detect New Open S3 buckets -* Detect S3 access from a new IP -* Detect Spike in S3 Bucket deletion - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf -* https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/ - -### Suspicious AWS Traffic -* id = `2e8948a5-5239-406b-b56b-6c50f2168af3` -* creation_date = 2018-05-07 -* modification_date = 2018-05-07 -* version = 1.0 -* spec_version = 2 - -##### Description -Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). - -##### Narrative -A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ -Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ - Attackers may abuse the AWS infrastructure with insecure VPCs so they can co-opt AWS resources for command-and-control nodes, data exfiltration, and more. Once an EC2 instance is compromised, an attacker may initiate outbound network connections for malicious reasons. Monitoring these network traffic behaviors is crucial for understanding the type of traffic flowing in and out of your network and to alert you to suspicious activities.\ -The searches in this Analytic Story will monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors. - -##### Detections -* Detect Spike in blocked Outbound Traffic from your AWS - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/ - -### Unusual AWS EC2 Modifications -* id = `73de57ef-0dfc-411f-b1e7-fa24428aeae0` -* creation_date = 2018-04-09 -* modification_date = 2018-04-09 -* version = 1.0 -* spec_version = 2 - -##### Description -Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. - -##### Narrative -A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ - Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. - -##### Detections -* EC2 Instance Modified With Previously Unseen User - -##### Providing Technologies -* AWS - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf - - -## Best Practices - -* [Account Monitoring and Controls](#account-monitoring-and-controls) - -* [Asset Tracking](#asset-tracking) - -* [Monitor Backup Solution](#monitor-backup-solution) - -* [Monitor for Unauthorized Software](#monitor-for-unauthorized-software) - -* [Monitor for Updates](#monitor-for-updates) - -* [Prohibited Traffic Allowed or Protocol Mismatch](#prohibited-traffic-allowed-or-protocol-mismatch) - -* [Router & Infrastructure Security](#router-&-infrastructure-security) - -* [Use of Cleartext Protocols](#use-of-cleartext-protocols) - -### Account Monitoring and Controls -* id = `8892a655-6205-55f7-abba-06460e38c8ae` -* creation_date = 2017-08-05 -* modification_date = 2017-09-06 -* version = 1.0 -* spec_version = 2 - -##### Description -A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. - -##### Narrative -Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. - -##### Detections -* Identify New User Accounts -* Short Lived Windows Accounts -* Detect Excessive Account Lockouts From Endpoint -* Detect Excessive User Account Lockouts - -##### Providing Technologies -* Microsoft Windows -* Active Directory - -##### Data Models -Change -Identity_Management - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf - -### Asset Tracking -* id = `91c676cf-0b23-438d-abee-f6335e1fce77` -* creation_date = 2017-06-01 -* modification_date = 2017-09-13 -* version = 1.0 -* spec_version = 2 - -##### Description -Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. - -##### Narrative -This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. - -##### Detections -* Detect Unauthorized Assets by MAC address - -##### Providing Technologies -* Splunk Stream -* Bro - -##### Data Models -Network_Sessions - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/ - -### Monitor Backup Solution -* id = `abe807c7-1eb6-4304-ac32-6e7aacdb891d` -* creation_date = 2017-06-15 -* modification_date = 2017-09-12 -* version = 1.0 -* spec_version = 2 - -##### Description -Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. - -##### Narrative -Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. - -##### Detections -* Unsuccessful Netbackup backups -* Extended Period Without Successful Netbackup Backups - -##### Providing Technologies -* Netbackup - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/ - -### Monitor for Unauthorized Software -* id = `8892a655-6205-43f7-abba-06460e38c8ae` -* creation_date = 2017-06-26 -* modification_date = 2017-09-15 -* version = 1.0 -* spec_version = 2 - -##### Description -Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. - -##### Narrative -It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ -It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. - -##### Detections -* Prohibited Software On Endpoint - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ - -### Monitor for Updates -* id = `9ef8d677-7b52-4213-a038-99cfc7acc2d8` -* creation_date = 2017-08-15 -* modification_date = 2017-09-15 -* version = 1.0 -* spec_version = 2 - -##### Description -Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. - -##### Narrative -It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ -Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ -Microsoft releases updates for Windows systems on a monthly cadence. They should be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed. - -##### Detections -* No Windows Updates in a time frame - -##### Providing Technologies -* Microsoft Windows - -##### Data Models -Updates - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://learn.cisecurity.org/20-controls-download - -### Prohibited Traffic Allowed or Protocol Mismatch -* id = `6d13121c-90f3-446d-8ac3-27efbbc65218` -* creation_date = 2017-04-18 -* modification_date = 2017-09-11 -* version = 1.0 -* spec_version = 2 - -##### Description -Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. - -##### Narrative -A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. - -##### Detections -* TOR Traffic -* Prohibited Network Traffic Allowed -* Protocol or Port Mismatch -* Detect hosts connecting to dynamic domain providers - -##### Providing Technologies -* Splunk Stream -* Bro -* Palo Alto Firewall - -##### Data Models -Network_Resolution -Network_Traffic - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/ - -### Router & Infrastructure Security -* id = `91c676cf-0b23-438d-abee-f6335e177e77` -* creation_date = 2017-06-01 -* modification_date = 2017-09-12 -* version = 1.0 -* spec_version = 2 - -##### Description -Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. - -##### Narrative -Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ -This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. - -##### Detections -* Detect New Login Attempts to Routers - -##### Providing Technologies -* Active Directory -* Palo Alto Firewall - -##### Data Models -Authentication - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html -* https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html - -### Use of Cleartext Protocols -* id = `826e6431-aeef-41b4-9fc0-6d0985d65a21` -* creation_date = 2016-09-13 -* modification_date = 2017-09-15 -* version = 1.0 -* spec_version = 2 - -##### Description -Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. - -##### Narrative -Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. - -##### Detections -* Protocols passing authentication in cleartext - -##### Providing Technologies -* Splunk Stream -* Bro - -##### Data Models -Network_Traffic - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://www.monkey.org/~dugsong/dsniff/ - - -## Vulnerability - -* [Apache Struts Vulnerability](#apache-struts-vulnerability) - -* [JBoss Vulnerability](#jboss-vulnerability) - -* [Spectre And Meltdown Vulnerabilities](#spectre-and-meltdown-vulnerabilities) - -* [Splunk Enterprise Vulnerability](#splunk-enterprise-vulnerability) - -* [Splunk Enterprise Vulnerability CVE-2018-11409](#splunk-enterprise-vulnerability-cve-2018-11409) - -### Apache Struts Vulnerability -* id = `2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e` -* creation_date = 2017-03-14 -* modification_date = 2018-12-06 -* version = 1.0 -* spec_version = 2 - -##### Description -Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. - -##### Narrative -In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ -The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ -This Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the `Content-Type` header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the `Content-Type` header is generally consistent and does not have a large degree of variation.\ -The second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.\ -First, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.\ -hen looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.\ -Various types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.\ -Looking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of "who," in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.\ -Gathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.\ -hen it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -In the event that a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that have the file open, what processes created and/or modified the file, and the number of systems that may have this file can help to determine if the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes quickly help determine whether it is malicious in nature.\ -Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, there may be activity initiated via a compromised website the user visited.\ -It can also be very helpful to examine various behaviors of the process of interest or the parent of the process that is of interest. For example, if it turns out that the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might also be worth further scrutiny. If a process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. - -##### Detections -* Unusually Long Content-Type Length -* Web Servers Executing Suspicious Processes -* Suspicious Java Classes - -##### Providing Technologies -* Splunk Stream -* Bro -* Bluecoat -* Apache -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Jose Hernandez -* email = jhernandez@splunk.com -* company = Splunk - -##### References -* https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf - -### JBoss Vulnerability -* id = `1f5294cb-b85f-4c2d-9c58-ffcf248f52bd` -* creation_date = 2016-10-04 -* modification_date = 2017-09-14 -* version = 1.0 -* spec_version = 2 - -##### Description -In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. - -##### Narrative -This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ -It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ -hen looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.\ -Various types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.\ -The following factors may assist you in determining whether the event is malicious: \ -1. Country of origin\ -1. Responsible party\ -1. Fully qualified domain names associated with the external IP address\ -1. Registration of fully qualified domain names associated with external IP address Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.\ -Gathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ -hen a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.\ -If you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ -If a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that opened the file, the processes that may have created and/or modified the file, and how many other systems potentially have this file can you determine whether the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes help you quickly determine if it is malicious in nature.\ -Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. \ -It can also be helpful to examine various behaviors of and the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see whether the parent process spawned other processes that might also warrant further scrutiny. If a process is suspect, a review of the network connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. - -##### Detections -* Detect malicious requests to exploit JBoss servers -* Detect attackers scanning for vulnerable JBoss servers - -##### Providing Technologies -* Splunk Stream -* Palo Alto Firewall -* Apache -* Bro - -##### Data Models -Web - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html - -### Spectre And Meltdown Vulnerabilities -* id = `6d3306f6-bb2b-4219-8609-8efad64032f2` -* creation_date = 2018-01-08 -* modification_date = 2018-01-08 -* version = 1.0 -* spec_version = 2 - -##### Description -Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. - -##### Narrative -Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. - -##### Detections -* Spectre and Meltdown Vulnerable Systems - -##### Providing Technologies -* Nessus -* Qualys - -##### Data Models -Vulnerabilities - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://meltdownattack.com/ - -### Splunk Enterprise Vulnerability -* id = `4e692b96-de2d-4bd1-9105-37e2368a8db1` -* creation_date = 2016-09-13 -* modification_date = 2017-09-19 -* version = 1.0 -* spec_version = 2 - -##### Description -Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. - -##### Narrative -This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ -\ -1. Splunk Enterprise 6.4.x, prior to 6.4.3\ -1. Splunk Enterprise 6.3.x, prior to 6.3.6\ -1. Splunk Enterprise 6.2.x, prior to 6.2.10\ -1. Splunk Enterprise 6.1.x, prior to 6.1.11\ -1. Splunk Enterprise 6.0.x, prior to 6.0.12\ -1. Splunk Enterprise 5.0.x, prior to 5.0.16\ -1. Splunk Light, prior to 6.4.3CVE-2016-4859 allows attackers to redirect users to arbitrary web sites and conduct phishing attacks via unspecified vectors. (Credit: Noriaki Iwasaki, Cyber Defense Institute, Inc.).\ -It is important to ensure that your Splunk deployment is being kept up to date and is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites. - -##### Detections -* Open Redirect in Splunk Web - -##### Providing Technologies -* Splunk Enterprise - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* http://www.splunk.com/view/SP-CAAAPQ6#announce -* https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859 - -### Splunk Enterprise Vulnerability CVE-2018-11409 -* id = `1fc34cbc-34e9-43ba-87ab-6811c9e95400` -* creation_date = 2018-06-14 -* modification_date = 2018-06-14 -* version = 1.0 -* spec_version = 2 - -##### Description -Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. - -##### Narrative -Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ -Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ -Read more in Splunk's official response: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings.\ -A detection search within this Analytic Story looks for vulnerabilities described in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip. - -##### Detections -* Splunk Enterprise Information Disclosure - -##### Providing Technologies -* Splunk Enterprise - -##### Data Models - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://nvd.nist.gov/vuln/detail/CVE-2018-11409 -* https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings -* https://www.exploit-db.com/exploits/44865/ +* [Vulnerability](#Vulnerability) ## Abuse -* [Brand Monitoring](#brand-monitoring) +* [Brand Monitoring](#Brand-Monitoring) -* [DNS Amplification Attacks](#dns-amplification-attacks) +* [Data Protection](#Data-Protection) -* [Data Protection](#data-protection) +* [DNS Amplification Attacks](#DNS-Amplification-Attacks) -* [Host Redirection](#host-redirection) +* [Host Redirection](#Host-Redirection) -* [Netsh Abuse](#netsh-abuse) +* [Netsh Abuse](#Netsh-Abuse) -* [Web Fraud Detection](#web-fraud-detection) +* [Web Fraud Detection](#Web-Fraud-Detection) ### Brand Monitoring -* id = `91c676cf-0b23-438d-abee-f6335e1fce78` -* creation_date = 2017-06-01 -* modification_date = 2017-12-19 -* version = 1.0 -* spec_version = 2 +* id = 91c676cf-0b23-438d-abee-f6335e1fce78 +* date = 2017-12-19 +* version = 1 -##### Description +#### Description Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. -##### Narrative +#### Narrative While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ Notable events will include IP addresses, URLs, and user data. Drilling down can provide you with even more actionable intelligence, including likely geographic information, contextual searches to help you scope the problem, and investigative searches. -##### Detections +#### Detections * Monitor DNS For Brand Abuse * Monitor Email For Brand Abuse * Monitor Web Traffic For Brand Abuse -##### Providing Technologies -* Splunk Stream -* Bro -* Microsoft Exchange -* Bluecoat -* Palo Alto Firewall +#### Data Models +* Email +* Network_Resolution +* Web -##### Data Models -Network_Resolution -Email -Web +#### Mappings -##### Mappings +##### ATT&CK -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives +* Delivery ###### CIS -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 7 -###### NIST +##### NIST * PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk ##### References * https://www.zerofox.com/blog/what-is-digital-risk-monitoring/ * https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/ * https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/ -### DNS Amplification Attacks -* id = `e8afd39e-3294-11e6-b39d-a45e60c6700` -* creation_date = 2016-08-24 -* modification_date = 2016-09-13 -* version = 1.0 -* spec_version = 2 - -##### Description -DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. - -##### Narrative -The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ -The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. - -##### Detections -* Large Volume of DNS ANY Queries - -##### Providing Technologies -* Splunk Stream -* Bro - -##### Data Models -Network_Resolution - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://www.us-cert.gov/ncas/alerts/TA13-088A -* https://www.imperva.com/learn/application-security/dns-amplification/ - ### Data Protection -* id = `91c676cf-0b23-438d-abee-f6335e1fce33` -* creation_date = 2017-06-01 -* modification_date = 2017-09-14 -* version = 1.0 -* spec_version = 2 +* id = 91c676cf-0b23-438d-abee-f6335e1fce33 +* date = 2017-09-14 +* version = 1 -##### Description +#### Description Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. -##### Narrative +#### Narrative Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. -##### Detections -* Detection of DNS Tunnels +#### Detections * Detect USB device insertion * Detect hosts connecting to dynamic domain providers +* Detection of DNS Tunnels -##### Providing Technologies -* Microsoft Windows -* Splunk Stream -* Bro +#### Data Models +* Change_Analysis +* Network_Resolution -##### Data Models -Change_Analysis -Network_Resolution +#### Mappings -##### Mappings +##### ATT&CK +* T1043 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases +* Actions on Objectives * Command and Control +* Installation ###### CIS -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 13 -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE +##### NIST * DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk +* PR.DS +* PR.PT ##### References * https://www.cisecurity.org/controls/data-protection/ * https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022 * https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ -### Host Redirection -* id = `2e8948a5-5239-406b-b56b-6c50fe268af4` -* creation_date = 2017-06-18 -* modification_date = 2017-09-14 -* version = 1.0 -* spec_version = 2 +### DNS Amplification Attacks +* id = e8afd39e-3294-11e6-b39d-a45e60c6700 +* date = 2016-09-13 +* version = 1 -##### Description +#### Description +DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. + +#### Narrative +The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ +The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. + +#### Detections +* Large Volume of DNS ANY Queries + +#### Data Models +* Network_Resolution + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 12 + +##### NIST +* PR.IP + +##### References +* https://www.us-cert.gov/ncas/alerts/TA13-088A +* https://www.imperva.com/learn/application-security/dns-amplification/ + +### Host Redirection +* id = 2e8948a5-5239-406b-b56b-6c50fe268af4 +* date = 2017-09-14 +* version = 1 + +#### Description Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. -##### Narrative +#### Narrative Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. -##### Detections +#### Detections * Clients Connecting to Multiple DNS Servers * DNS Query Requests Resolved by Unauthorized DNS Servers * Windows hosts file modification -##### Providing Technologies -* Splunk Stream -* Bro -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon +#### Data Models +* Network_Resolution -##### Data Models -Network_Resolution -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1048 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases * Command and Control ###### CIS +* CIS 1 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk +* ID.AM +* PR.AC +* PR.DS +* PR.IP +* PR.PT ##### References * https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/ ### Netsh Abuse -* id = `2b1800dd-92f9-47ec-a981-fdf1351e5f65` -* creation_date = 2017-01-04 -* modification_date = 2017-01-05 -* version = 1.0 -* spec_version = 2 +* id = 2b1800dd-92f9-47ec-a981-fdf1351e5f65 +* date = 2017-01-05 +* version = 1 -##### Description +#### Description Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. -##### Narrative +#### Narrative It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. -##### Detections +#### Detections * Processes created by netsh * Processes launching netsh -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1059 +* T1089 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives ###### CIS -* CIS 3 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE +##### NIST * DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk +* PR.PT ##### References * https://technet.microsoft.com/library/bb490939.aspx @@ -1837,16 +236,14 @@ Endpoint * http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html ### Web Fraud Detection -* id = `31337aaa-bc22-4752-b599-ef112dq1dq7a` -* creation_date = 2018-07-12 -* modification_date = 2018-10-08 -* version = 1.0 -* spec_version = 2 +* id = 31337aaa-bc22-4752-b599-ef112dq1dq7a +* date = 2018-10-08 +* version = 1 -##### Description +#### Description Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. -##### Narrative +#### Narrative The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ hen developing a strategy for preventing fraud in your environment, its important to look across all of your web services for evidence that attackers are abusing enterprise resources to enumerate systems, harvest data for secondary fraudulent activity, or abuse terms of service.This Analytic Story looks for evidence of common Internet attack techniques that could be indicative of web fraud in your environmentincluding account harvesting, anomalous user clickspeed, and password sharing across accounts, to name just a few.\ @@ -1854,1133 +251,350 @@ The account-harvesting search focuses on web pages used for user-account registr The anomalous clickspeed search looks for users who are moving through your website at a faster-than-normal speed or with a perfect click cadence (high periodicity or low standard deviation), which could indicate that the user is a script, not an actual human.\ Another search detects incidents wherein a single password is used across multiple accounts, which may indicate that a fraudster has infiltrated your environment and embedded a common password within a script. -##### Detections +#### Detections * Web Fraud - Account Harvesting * Web Fraud - Anomalous User Clickspeed * Web Fraud - Password Sharing Across Accounts -##### Providing Technologies -* Splunk Stream +#### Data Models -##### Data Models +#### Mappings -##### Mappings +##### ATT&CK +* T1078 +* T1136 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives ###### CIS -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 16 +* CIS 6 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Jim Apger -* email = Mayhem@splunk.com -* company = Splunk +* DE.DP ##### References * https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud * https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718 -## Malware - -* [ColdRoot MacOS RAT](#coldroot-macos-rat) - -* [DHS Report TA18-074A](#dhs-report-ta18-074a) - -* [Dynamic DNS](#dynamic-dns) - -* [Emotet Malware (DHS Report TA18-201A)](#emotet-malware-(dhs-report-ta18-201a)) - -* [Hidden Cobra Malware](#hidden-cobra-malware) - -* [Orangeworm Attack Group](#orangeworm-attack-group) - -* [Ransomware](#ransomware) - -* [SamSam Ransomware](#samsam-ransomware) - -* [Unusual Processes](#unusual-processes) - -* [Windows File Extension and Association Abuse](#windows-file-extension-and-association-abuse) - -* [Windows Service Abuse](#windows-service-abuse) - -### ColdRoot MacOS RAT -* id = `bd91a2bc-d20b-4f44-a982-1bea98e86390` -* creation_date = 2019-01-29 -* modification_date = 2019-01-09 -* version = 1.0 -* spec_version = 2 - -##### Description -Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. - -##### Narrative -Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ -This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ -Searches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger. - -##### Detections -* Processes Tapping Keyboard Events -* Osquery pack - ColdRoot detection - -##### Providing Technologies -* OSquery - -##### Data Models -Alerts - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Jose Hernandez -* email = jhernandez@splunk.com -* company = Splunk - -##### References -* https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/ -* https://objective-see.com/blog/blog_0x2A.html -* https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/ - -### DHS Report TA18-074A -* id = `0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef` -* creation_date = 2018-03-19 -* modification_date = 2020-01-22 -* version = 2.0 -* spec_version = 2 - -##### Description -Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. - -##### Narrative -The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ -There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ -One joint Technical Alert (TA) issued by the Department of Homeland and the FBI in mid-March of 2018 attributed some cyber activity targeting utility infrastructure to operatives sponsored by the Russian government. The hackers executed spearfishing attacks, installed malware, employed watering-hole domains, and more. While they caused no physical damage, the attacks provoked fears that a nation-state could turn off water, redirect power, or compromise a nuclear power plant.\ -Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify the network configuration), suspicious registry modifications, and many more--may all be events you may wish to investigate further. While the use of these technique may be an indication that a nation-state actor is attempting to compromise your environment, it is important to note that these techniques are often employed by other groups, as well. - -##### Detections -* SMB Traffic Spike -* SMB Traffic Spike - MLTK -* Processes launching netsh -* Suspicious Reg.exe Process -* Sc.exe Manipulating Windows Services -* Registry Keys Used For Persistence -* Create local admin accounts using net.exe -* Single Letter Process On Endpoint -* Scheduled Task Name Used by Dragonfly Threat Actors -* Malicious PowerShell Process - Execution Policy Bypass -* Detect Outbound SMB Traffic -* Detect New Local Admin account -* Detect PsExec With accepteula Flag -* First time seen command line argument - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Microsoft Windows -* Bro -* Splunk Stream - -##### Data Models -Endpoint -Network_Traffic - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://www.us-cert.gov/ncas/alerts/TA18-074A - -### Dynamic DNS -* id = `8169f17b-ef68-4b59-aae8-586907301221` -* creation_date = 2017-11-21 -* modification_date = 2018-09-06 -* version = 2.0 -* spec_version = 2 - -##### Description -Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. - -##### Narrative -Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. - -##### Detections -* Detect hosts connecting to dynamic domain providers -* Detect web traffic to dynamic domain providers - -##### Providing Technologies -* Splunk Stream -* Bro -* Bluecoat -* Palo Alto Firewall - -##### Data Models -Network_Resolution -Web - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html -* https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ -* http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ -* https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html - -### Emotet Malware (DHS Report TA18-201A) -* id = `bb9f5ed2-916e-4364-bb6d-91c310efcf52` -* creation_date = 2018-09-11 -* modification_date = 2020-01-27 -* version = 1.0 -* spec_version = 2 - -##### Description -Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. - -##### Narrative -The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ -According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ -The searches in this Analytic Story will help you find executables that are rarely used in your environment, specific registry paths that malware often uses to ensure survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. - -##### Detections -* Detect Rare Executables -* Registry Keys Used For Persistence -* Detect Use of cmd.exe to Launch Script Interpreters -* Prohibited Software On Endpoint -* SMB Traffic Spike -* SMB Traffic Spike - MLTK -* Suspicious Email Attachment Extensions -* Email Attachments With Lots Of Spaces -* Detection of tools built by NirSoft - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Microsoft Exchange -* Bro -* Splunk Stream - -##### Data Models -Endpoint -Email -Network_Traffic - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://www.us-cert.gov/ncas/alerts/TA18-201A -* https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf -* https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html - -### Hidden Cobra Malware -* id = `baf7580b-d4b4-4774-8173-7d198e9da335` -* creation_date = 2018-06-14 -* modification_date = 2020-01-22 -* version = 2.0 -* spec_version = 2 - -##### Description -Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. - -##### Narrative -North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ -These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ -In June of 2018, The Department of Homeland Security, together with the FBI and other U.S. government partners, issued Technical Alert (TA-18-149A) to advise the public about two variants of North Korean malware. One variant, dubbed "Joanap," is a multi-stage peer-to-peer botnet that allows North Korean state actors to exfiltrate data, download and execute secondary payloads, and initialize proxy communications. The other variant, "Brambul," is a Windows32 SMB worm that is dropped into a victim network. When executed, the malware attempts to spread laterally within a victim's local subnet, connecting via the SMB protocol and initiating brute-force password attacks. It reports details to the Hidden Cobra actors via email, so they can use the information for secondary remote operations.\ -Among other searches in this Analytic Story is a detection search that looks for the creation or deletion of hidden shares, such as, "adnim$," which the Hidden Cobra malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers. - -##### Detections -* SMB Traffic Spike -* SMB Traffic Spike - MLTK -* First time seen command line argument -* Detect Outbound SMB Traffic -* Remote Desktop Network Traffic -* Remote Desktop Process Running On System -* DNS Query Length With High Standard Deviation -* Create or delete hidden shares using net.exe -* Suspicious File Write -* DNS Query Length Outliers - MLTK - -##### Providing Technologies -* Splunk Stream -* Bro -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Network_Resolution -Network_Traffic -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity -* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf - -### Orangeworm Attack Group -* id = `bb9f5ed2-916e-4364-bb6d-97c370efcf52` -* creation_date = 2018-06-14 -* modification_date = 2020-01-22 -* version = 2.0 -* spec_version = 2 - -##### Description -Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. - -##### Narrative -In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ -Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ -Although the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage. \ -Healthcare may be a promising target, because it is notoriously behind in technology, often using older operating systems and neglecting to patch computers. Even so, the group was able to evade detection for a full three years. Sources say that the malware spread quickly within the target networks, infecting computers used to control medical devices, such as MRI and X-ray machines.\ -This Analytic Story is designed to help you detect and investigate suspicious activities that may be indicative of an Orangeworm attack. One detection search looks for command-line arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised. - -##### Detections -* First time seen command line argument -* Sc.exe Manipulating Windows Services -* First Time Seen Running Windows Service - -##### Providing Technologies -* Microsoft Windows -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia -* https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/ - -### Ransomware -* id = `cf309d0d-d4aa-4fbb-963d-1e79febd3756` -* creation_date = 2017-07-24 -* modification_date = 2020-02-04 -* version = 1.1 -* spec_version = 2 - -##### Description -Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. - -##### Narrative -Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. - -##### Detections -* Windows Event Log Cleared -* Suspicious wevtutil Usage -* USN Journal Deletion -* Deleting Shadow Copies -* Spike in File Writes -* Prohibited Network Traffic Allowed -* SMB Traffic Spike -* SMB Traffic Spike - MLTK -* Common Ransomware Extensions -* Common Ransomware Notes -* System Processes Run From Unexpected Locations -* Remote Process Instantiation via WMI -* TOR Traffic -* Registry Keys Used For Persistence -* Unusually Long Command Line -* Unusually Long Command Line - MLTK -* Scheduled tasks used in BadRabbit ransomware -* Schtasks used for forcing a reboot - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Palo Alto Firewall -* Bro -* Splunk Stream -* Microsoft Windows - -##### Data Models -Endpoint -Network_Traffic - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk - -##### References -* https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/ -* https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html - -### SamSam Ransomware -* id = `c4b89506-fbcf-4cb7-bfd6-527e54789604` -* creation_date = 2018-12-13 -* modification_date = 2018-12-13 -* version = 1.0 -* spec_version = 2 - -##### Description -Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. - -##### Narrative -The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ -Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ -SamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.\ -In a typical attack on one large healthcare organization in 2018, the company ended up paying a ransom of four Bitcoins, then worth $56,707. Reports showed that access to the company's files was restored within two hours of paying the sum.\ -According to Sophos, SamSam previously leveraged RDP to gain access to targeted networks via brute force. SamSam is not spread automatically, like other malware. It requires skill because it forces the attacker to adapt their tactics to the individual environment. Next, the actors escalate their privileges to admin level. They scan the networks for worthy targets, using conventional tools, such as PsExec or PaExec, to deploy/execute, quickly encrypting files.\ -This Analytic Story includes searches designed to help detect and investigate signs of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP. - -##### Detections -* Deleting Shadow Copies -* Spike in File Writes -* Common Ransomware Extensions -* Common Ransomware Notes -* Prohibited Software On Endpoint -* Detect PsExec With accepteula Flag -* Remote Desktop Network Traffic -* Detect attackers scanning for vulnerable JBoss servers -* Detect malicious requests to exploit JBoss servers -* Remote Desktop Network Bruteforce -* File with Samsam Extension -* Samsam Test File Write -* Batch File Write to System32 - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Splunk Stream -* Palo Alto Firewall -* Apache -* Bro - -##### Data Models -Endpoint -Web -Network_Traffic - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/ -* https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/ -* https://thehackernews.com/2018/07/samsam-ransomware-attacks.html - -### Unusual Processes -* id = `f4368e3f-d59f-4192-84f6-748ac5a3ddb6` -* creation_date = 2016-08-09 -* modification_date = 2020-02-04 -* version = 2.1 -* spec_version = 2 - -##### Description -Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. - -##### Narrative -Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ -This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ -In the event an unusual process is identified, it is imperative to better understand how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity. - -##### Detections -* Uncommon Processes On Endpoint -* Unusually Long Command Line -* Unusually Long Command Line - MLTK -* Detect Rare Executables -* System Processes Run From Unexpected Locations -* RunDLL Loading DLL By Ordinal -* Detect processes used for System Network Configuration Discovery - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - -##### References -* https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html -* https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf -* https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262 - -### Windows File Extension and Association Abuse -* id = `30552a76-ac78-48e4-b3c0-de4e34e9563d` -* creation_date = 2018-01-26 -* modification_date = 2018-01-26 -* version = 1.0 -* spec_version = 2 - -##### Description -Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. - -##### Narrative -Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ - Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ - Attackers take advantage of this expectation by obfuscating the true file extension. They can accomplish this in a couple of ways. One technique involves inserting multiple spaces in the file name before the extension to hide the extension from the GUI, obscuring the true nature of the file. Another approach involves prepending the real extension with a different one. This is especially effective when Windows is configured to "hide extensions for known file types." In this case, the real extension is not displayed, but the prepended one is, leading end users to believe the file is a different type than it actually is.\ -Changing the association between a file extension and an application can allow an attacker to execute arbitrary code. The technique typically involves changing the association for an often-launched file type to associate instead with a malicious program the attacker has dropped on the endpoint. When the end user launches a file that has been manipulated in this way, it will execute the attacker's malware. It will also execute the application the end user expected to run, cleverly obscuring the fact that something suspicious has occurred.\ -Run the searches in this story to detect and investigate suspicious behavior that may indicate abuse or manipulation of Windows file extensions and/or associations. - -##### Detections -* Execution of File with Multiple Extensions -* Execution of File With Spaces Before Extension -* Suspicious Changes to File Associations - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/ -* https://attack.mitre.org/wiki/Technique/T1042 - -### Windows Service Abuse -* id = `6dbd810e-f66d-414b-8dfc-e46de55cbfe2` -* creation_date = 2017-11-02 -* modification_date = 2017-11-02 -* version = 3.0 -* spec_version = 2 - -##### Description -Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. - -##### Narrative -The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. - -##### Detections -* Sc.exe Manipulating Windows Services -* Reg.exe Manipulating Windows Services Registry Keys -* First Time Seen Running Windows Service - -##### Providing Technologies -* Microsoft Windows -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://attack.mitre.org/wiki/Technique/T1050 -* https://attack.mitre.org/wiki/Technique/T1031 - - ## Adversary Tactics -* [Collection and Staging](#collection-and-staging) +* [Collection and Staging](#Collection-and-Staging) -* [Command and Control](#command-and-control) +* [Command and Control](#Command-and-Control) -* [Common Phishing Frameworks](#common-phishing-frameworks) +* [Common Phishing Frameworks](#Common-Phishing-Frameworks) -* [Credential Dumping](#credential-dumping) +* [Credential Dumping](#Credential-Dumping) -* [DNS Hijacking](#dns-hijacking) +* [Disabling Security Tools](#Disabling-Security-Tools) -* [Disabling Security Tools](#disabling-security-tools) +* [DNS Hijacking](#DNS-Hijacking) -* [Lateral Movement](#lateral-movement) +* [Lateral Movement](#Lateral-Movement) -* [Malicious PowerShell](#malicious-powershell) +* [Malicious PowerShell](#Malicious-PowerShell) -* [Phishing Payloads](#phishing-payloads) +* [Phishing Payloads](#Phishing-Payloads) -* [Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns](#possible-backdoor-activity-associated-with-mudcarp-espionage-campaigns) +* [Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns](#Possible-Backdoor-Activity-Associated-With-MUDCARP-Espionage-Campaigns) -* [SQL Injection](#sql-injection) +* [SQL Injection](#SQL-Injection) -* [Suspicious Command-Line Executions](#suspicious-command-line-executions) +* [Suspicious Command-Line Executions](#Suspicious-Command-Line-Executions) -* [Suspicious DNS Traffic](#suspicious-dns-traffic) +* [Suspicious DNS Traffic](#Suspicious-DNS-Traffic) -* [Suspicious Emails](#suspicious-emails) +* [Suspicious Emails](#Suspicious-Emails) -* [Suspicious MSHTA Activity](#suspicious-mshta-activity) +* [Suspicious MSHTA Activity](#Suspicious-MSHTA-Activity) -* [Suspicious Okta Activity](#suspicious-okta-activity) +* [Suspicious Okta Activity](#Suspicious-Okta-Activity) -* [Suspicious WMI Use](#suspicious-wmi-use) +* [Suspicious Windows Registry Activities](#Suspicious-Windows-Registry-Activities) -* [Suspicious Windows Registry Activities](#suspicious-windows-registry-activities) +* [Suspicious WMI Use](#Suspicious-WMI-Use) -* [Windows Defense Evasion Tactics](#windows-defense-evasion-tactics) +* [Windows Defense Evasion Tactics](#Windows-Defense-Evasion-Tactics) -* [Windows Log Manipulation](#windows-log-manipulation) +* [Windows Log Manipulation](#Windows-Log-Manipulation) -* [Windows Persistence Techniques](#windows-persistence-techniques) +* [Windows Persistence Techniques](#Windows-Persistence-Techniques) -* [Windows Privilege Escalation](#windows-privilege-escalation) +* [Windows Privilege Escalation](#Windows-Privilege-Escalation) ### Collection and Staging -* id = `8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a` -* creation_date = 2018-01-08 -* modification_date = 2020-02-03 -* version = 1.1 -* spec_version = 2 +* id = 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a +* date = 2020-02-03 +* version = 1 -##### Description +#### Description Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. -##### Narrative +#### Narrative A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ Use the searches to detect and monitor suspicious behavior related to these activities. -##### Detections -* Suspicious writes to windows Recycle Bin -* Suspicious writes to System Volume Information +#### Detections * Email files written outside of the Outlook directory -* Hosts receiving high volume of network traffic from email server * Email servers sending high volume traffic to hosts +* Hosts receiving high volume of network traffic from email server +* Suspicious writes to System Volume Information +* Suspicious writes to windows Recycle Bin -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Bro -* Splunk Stream +#### Data Models +* Endpoint +* Network_Traffic -##### Data Models -Endpoint -Network_Traffic +#### Mappings -##### Mappings +##### ATT&CK +* T1043 +* T1074 +* T1114 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives ###### CIS -* CIS 3 +* CIS 7 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk +* PR.PT ##### References * https://attack.mitre.org/wiki/Collection * https://attack.mitre.org/wiki/Technique/T1074 ### Command and Control -* id = `943773c6-c4de-4f38-89a8-0b92f98804d8` -* creation_date = 2018-06-01 -* modification_date = 2018-06-01 -* version = 1.0 -* spec_version = 2 +* id = 943773c6-c4de-4f38-89a8-0b92f98804d8 +* date = 2018-06-01 +* version = 1 -##### Description +#### Description Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. -##### Narrative +#### Narrative Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. -##### Detections -* Detect Large Outbound ICMP Packets -* Protocol or Port Mismatch -* Detection of DNS Tunnels -* TOR Traffic -* Prohibited Network Traffic Allowed +#### Detections * Clients Connecting to Multiple DNS Servers -* DNS Query Length With High Standard Deviation -* Detect hosts connecting to dynamic domain providers -* Excessive DNS Failures -* Detect Long DNS TXT Record Response -* DNS Query Requests Resolved by Unauthorized DNS Servers -* Detect Spike in blocked Outbound Traffic from your AWS * DNS Query Length Outliers - MLTK +* DNS Query Length With High Standard Deviation +* DNS Query Requests Resolved by Unauthorized DNS Servers +* Detect Large Outbound ICMP Packets +* Detect Long DNS TXT Record Response +* Detect Spike in blocked Outbound Traffic from your AWS +* Detect hosts connecting to dynamic domain providers +* Detection of DNS Tunnels +* Excessive DNS Failures +* Prohibited Network Traffic Allowed +* Protocol or Port Mismatch +* TOR Traffic -##### Providing Technologies -* Splunk Stream -* Bro -* Palo Alto Firewall -* AWS +#### Data Models +* Network_Resolution +* Network_Traffic -##### Data Models -Network_Resolution -Network_Traffic +#### Mappings -##### Mappings +##### ATT&CK +* T1043 +* T1048 +* T1095 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases +* Actions on Objectives * Command and Control +* Delivery ###### CIS +* CIS 1 +* CIS 11 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 +* CIS 9 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk +* ID.AM +* PR.AC +* PR.DS +* PR.IP +* PR.PT ##### References * https://attack.mitre.org/wiki/Command_and_Control * https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware ### Common Phishing Frameworks -* id = `9a64ab44-9214-4639-8163-7eaa2621bd61` -* creation_date = 2019-04-29 -* modification_date = 2019-04-29 -* version = 1.0 -* spec_version = 2 +* id = 9a64ab44-9214-4639-8163-7eaa2621bd61 +* date = 2019-04-29 +* version = 1 -##### Description +#### Description Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. -##### Narrative +#### Narrative As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. -##### Detections +#### Detections * Detect DNS requests to Phishing Sites leveraging EvilGinx2 -##### Providing Technologies -* Splunk Stream -* Bro +#### Data Models +* Network_Resolution -##### Data Models -Network_Resolution -Web +#### Mappings -##### Mappings +##### ATT&CK +* T1192 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases * Command and Control ###### CIS -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 7 -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE +##### NIST * DE.CM -##### Maintainers -* name = Splunk Research Team -* email = research@splunk.com -* company = Splunk - ##### References * https://github.com/kgretzky/evilginx2 * https://attack.mitre.org/techniques/T1192/ * https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/ ### Credential Dumping -* id = `854d78bf-d0e2-4f4e-b05c-640905f86d7a` -* creation_date = 2018-08-08 -* modification_date = 2020-02-04 -* version = 3.0 -* spec_version = 2 +* id = 854d78bf-d0e2-4f4e-b05c-640905f86d7a +* date = 2020-02-04 +* version = 3 -##### Description +#### Description Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. -##### Narrative +#### Narrative Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ The detection searches in this Analytic Story monitor access to the Local Security Authority Subsystem Service (LSASS) process, the usage of shadowcopies for credential dumping and some other techniques for credential dumping. -##### Detections +#### Detections * Access LSASS Memory for Dump Creation -* Create Remote Thread into LSASS -* Detect Credential Dumping through LSASS access -* Unsigned Image Loaded by LSASS -* Attempted Credential Dump From Registry via Reg.exe -* Detect Mimikatz Using Loaded Images * Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass +* Attempted Credential Dump From Registry via Reg exe +* Create Remote Thread into LSASS * Creation of Shadow Copy * Creation of Shadow Copy with wmic and powershell -* Credential Dumping via Copy Command from Shadowcopy -* Credential Dumping via Symlink to Shadowcopy +* Credential Dumping via Copy Command from Shadow Copy +* Credential Dumping via Symlink to Shadow Copy +* Detect Credential Dumping through LSASS access +* Detect Mimikatz Using Loaded Images * Dump LSASS via comsvcs DLL +* Unsigned Image Loaded by LSASS -##### Providing Technologies -* Microsoft Windows -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1003 +* T1064 +* T1086 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives +* Installation ###### CIS +* CIS 16 * CIS 3 +* CIS 5 +* CIS 6 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk -* name = Patrick Bareiss -* email = pbareiss@splunk.com -* company = Splunk +* PR.AC +* PR.IP ##### References * https://attack.mitre.org/wiki/Technique/T1003 * https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html -### DNS Hijacking -* id = `8169f17b-ef68-4b59-aa28-586907301221` -* creation_date = 2017-11-21 -* modification_date = 2020-02-04 -* version = 1.0 -* spec_version = 2 +### Disabling Security Tools +* id = fcc27099-46a0-46b0-a271-5c7dab56b6f1 +* date = 2020-02-04 +* version = 2 -##### Description +#### Description +Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. + +#### Narrative +Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). + +#### Detections +* Attempt To Add Certificate To Untrusted Store +* Attempt To Stop Security Service +* Processes launching netsh +* Sc exe Manipulating Windows Services +* Suspicious Reg exe Process +* Unload Sysmon Filter Driver + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK +* T1031 +* T1050 +* T1059 +* T1089 +* T1112 + +##### Kill Chain Phases +* Actions on Objectives +* Installation + +###### CIS +* CIS 3 +* CIS 5 +* CIS 8 + +##### NIST +* DE.CM +* PR.AC +* PR.AT +* PR.IP +* PR.PT + +##### References +* https://attack.mitre.org/wiki/Technique/T1089 +* https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/ +* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf + +### DNS Hijacking +* id = 8169f17b-ef68-4b59-aa28-586907301221 +* date = 2020-02-04 +* version = 1 + +#### Description Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. -##### Narrative +#### Narrative Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ On January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity and Infrastructure Security Agency (CISA) raised awareness of some high-profile DNS hijacking attacks against infrastructure, both in the United States and abroad. It issued Emergency Directive 19-01 (see https://cyber.dhs.gov/ed/19-01/), which summarized the activity and required government agencies to take the following four actions, all within 10 days: \ @@ -2991,44 +605,38 @@ On January 22, 2019, the US Department of Homeland Security 2019's Cybersecurity In DNS hijacking, the attacker assumes control over an account or makes use of a DNS service exploit to make changes to DNS records. Once they gain access, attackers can substitute their own MX records, name-server records, and addresses, redirecting emails and traffic through their infrastructure, where they can read, copy, or modify information seen. They can also generate valid encryption certificates to help them avoid browser-certificate checks. In one notable attack on the Internet service provider, GoDaddy, the hackers altered Sender Policy Framework (SPF) records a relatively minor change that did not inflict excessive damage but allowed for more effective spam campaigns.\ The searches in this Analytic Story help you detect and investigate activities that may indicate that DNS hijacking has taken place within your environment. -##### Detections -* DNS record changed +#### Detections * Clients Connecting to Multiple DNS Servers -* Detect hosts connecting to dynamic domain providers * DNS Query Requests Resolved by Unauthorized DNS Servers +* DNS record changed +* Detect hosts connecting to dynamic domain providers -##### Providing Technologies -* Splunk Stream -* Bro +#### Data Models +* Network_Resolution -##### Data Models -Network_Resolution +#### Mappings -##### Mappings +##### ATT&CK +* T1048 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases +* Actions on Objectives * Command and Control ###### CIS +* CIS 1 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk +* ID.AM +* PR.DS +* PR.IP +* PR.PT ##### References * https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html @@ -3036,146 +644,64 @@ Network_Resolution * http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ * https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html -### Disabling Security Tools -* id = `fcc27099-46a0-46b0-a271-5c7dab56b6f1` -* creation_date = 2018-04-09 -* modification_date = 2020-02-04 -* version = 2.0 -* spec_version = 2 - -##### Description -Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. - -##### Narrative -Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). - -##### Detections -* Sc.exe Manipulating Windows Services -* Suspicious Reg.exe Process -* Processes launching netsh -* Attempt To Stop Security Service -* Attempt To Add Certificate To Untrusted Store -* Unload Sysmon Filter Driver - -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://attack.mitre.org/wiki/Technique/T1089 -* https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/ -* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf - ### Lateral Movement -* id = `399d65dc-1f08-499b-a259-aad9051f38ad` -* creation_date = 2016-09-13 -* modification_date = 2020-02-04 -* version = 2.0 -* spec_version = 2 +* id = 399d65dc-1f08-499b-a259-aad9051f38ad +* date = 2020-02-04 +* version = 2 -##### Description +#### Description Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. -##### Narrative +#### Narrative Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ An adversary can use lateral movement for multiple purposes, including remote execution of tools, pivoting to additional systems, obtaining access to specific information or files, access to additional credentials, exfiltrating data, or delivering a secondary effect. Adversaries may use legitimate credentials alongside inherent network and operating-system functionality to remotely connect to other systems and remain under the radar of network defenders.\ If there is evidence of lateral movement, it is imperative for analysts to collect evidence of the associated offending hosts. For example, an attacker might leverage host A to gain access to host B. From there, the attacker may try to move laterally to host C. In this example, the analyst should gather as much information as possible from all three hosts. \ It is also important to collect authentication logs for each host, to ensure that the offending accounts are well-documented. Analysts should account for all processes to ensure that the attackers did not install unauthorized software. -##### Detections -* Schtasks scheduling job on remote system -* Remote Desktop Process Running On System -* Remote Desktop Network Traffic +#### Detections * Detect Activity Related to Pass the Hash Attacks +* Remote Desktop Network Traffic +* Remote Desktop Process Running On System +* Schtasks scheduling job on remote system -##### Providing Technologies -* Microsoft Windows -* Bro -* Splunk Stream -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint +* Network_Traffic -##### Data Models -Network_Traffic -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1053 +* T1075 +* T1076 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives ###### CIS +* CIS 16 * CIS 3 -* CIS 8 -* CIS 12 +* CIS 9 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk +* PR.AC +* PR.IP ##### References * https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis * https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html ### Malicious PowerShell -* id = `2c8ff66e-0b57-42af-8ad7-912438a403fc` -* creation_date = 2016-09-18 -* modification_date = 2017-08-23 -* version = 4.0 -* spec_version = 2 +* id = 2c8ff66e-0b57-42af-8ad7-912438a403fc +* date = 2017-08-23 +* version = 4 -##### Description +#### Description Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. -##### Narrative +#### Narrative The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ 1. Country of origin\ @@ -3187,64 +713,49 @@ Often, a simple inspection of the process name and path can tell you if the syst It can also be very helpful to examine various behaviors of the process of interest or the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might be worth further scrutiny. If a process is suspect, a review of the network connections made in and around the time of the event and/or whether the process spawned any child processes could be helpful, as well.\ In the event a system is suspected of having been compromised via a malicious website, we suggest reviewing the browsing activity from that system around the time of the event. If categories are given for the URLs visited, that can help you zero in on possible malicious sites. -##### Detections +#### Detections +* Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass * Malicious PowerShell Process - Connect To Internet With Hidden Window * Malicious PowerShell Process - Encoded Command * Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments * Malicious PowerShell Process With Obfuscation Techniques -* Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1064 +* T1086 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases +* Actions on Objectives * Command and Control ###### CIS * CIS 3 +* CIS 7 * CIS 8 -* CIS 12 -###### NIST +##### NIST +* DE.CM * PR.IP * PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk ##### References * https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/ * https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ ### Phishing Payloads -* id = `57226b40-94f3-4ce5-b101-a75f67759c27` -* creation_date = 2019-04-29 -* modification_date = 2019-04-29 -* version = 1.0 -* spec_version = 2 +* id = 57226b40-94f3-4ce5-b101-a75f67759c27 +* date = 2019-04-29 +* version = 1 -##### Description +#### Description Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. -##### Narrative +#### Narrative Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ hile any kind of file may contain a malicious payload, some are more likely to be perceived as benign (and thus more often escape notice) by the average victim—especially when the attacker sends an email that seems to be from one of their contacts. An example is Microsoft Office files. Most corporate users are familiar with documents with the following suffixes: .doc/.docx (MS Word), .xls/.xlsx (MS Excel), and .ppt/.pptx (MS PowerPoint), so they may click without a second thought, slashing a hole in their organizations' security. \ @@ -3254,60 +765,41 @@ Following is a typical series of events, according to an [article by Trend Micro 1. Powershell executes a reverse shell, rendering the exploit successful As a side note, adversaries are likely to use a tool like Empire to craft and obfuscate payloads and their post-injection activities, such as [exfiltration, lateral movement, and persistence](https://github.com/EmpireProject/Empire).\ This Analytic Story focuses on detecting signs that a malicious payload has been injected into your environment. For example, one search detects outlook.exe writing a .zip file. Another looks for suspicious .lnk files launching processes. -##### Detections -* Detect Oulook.exe writing a .zip file +#### Detections +* Detect Oulook exe writing a zip file * Suspicious LNK file launching a process -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1193 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives +* Installation ###### CIS -* CIS 3 +* CIS 7 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Splunk Research Team -* email = research@splunk.com -* company = Splunk +##### NIST +* ID.AM +* PR.DS ##### References * https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html ### Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns -* id = `988C59C5-0A1C-45B6-A555-0C62276E327E` -* creation_date = 2018-07-24 -* modification_date = 2020-01-22 -* version = 1.0 -* spec_version = 2 +* id = 988C59C5-0A1C-45B6-A555-0C62276E327E +* date = 2020-01-22 +* version = 1 -##### Description +#### Description Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. -##### Narrative +#### Narrative This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ The MUDCARP techniques include the use of the compressed-folders module from Microsoft, zipfldr.dll, with RouteTheCall export to run the malicious process or command. After a successful reboot, the malware is made persistent by a manipulating `[HKEY_CURRENT_USER\SOFTWARE\Microsoft\Windows\CurrentVersion\Run]'help'='c:\\windows\\system32\\rundll32.exe c:\\windows\\system32\\zipfldr.dll,RouteTheCall c:\\programdata\\winapp.exe'`. Though this technique is not exclusive to MUDCARP, it has been spotted in the group's arsenal of advanced techniques seen in the wild.\ @@ -3337,163 +829,122 @@ If behavioral searches included in this story yield positive hits, iDefense reco 1. b8ec65dab97cdef3cd256cc4753f0c54\ 1. 04d83cd3813698de28cfbba326d7647c -##### Detections +#### Detections * First time seen command line argument -* Registry Keys Used For Persistence * Malicious PowerShell Process - Connect To Internet With Hidden Window +* Registry Keys Used For Persistence * Unusually Long Command Line * Unusually Long Command Line - MLTK -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1059 +* T1064 +* T1086 +* T1103 +* T1131 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases +* Actions on Objectives * Command and Control ###### CIS * CIS 3 +* CIS 7 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = iDefense Cyber Espionage Team -* email = iDefense.IntelOps@accenture.com -* company = iDefense +* PR.IP +* PR.PT ##### References * https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/ * http://blog.amossys.fr/badflick-is-not-so-bad.html ### SQL Injection -* id = `4f6632f5-449c-4686-80df-57625f59bab3` -* creation_date = 2016-09-13 -* modification_date = 2017-09-19 -* version = 1.0 -* spec_version = 2 +* id = 4f6632f5-449c-4686-80df-57625f59bab3 +* date = 2017-09-19 +* version = 1 -##### Description +#### Description Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. -##### Narrative +#### Narrative It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. -##### Detections +#### Detections * SQL Injection with Long URLs -##### Providing Technologies -* Splunk Stream -* Bro +#### Data Models +* Web -##### Data Models -Web +#### Mappings -##### Mappings +##### ATT&CK +* T1043 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Delivery ###### CIS -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 18 -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE +##### NIST * DE.CM -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk - ##### References * https://capec.mitre.org/data/definitions/66.html * https://www.incapsula.com/web-application-security/sql-injection.html ### Suspicious Command-Line Executions -* id = `f4368ddf-d59f-4192-84f6-778ac5a3ffc7` -* creation_date = 2017-10-09 -* modification_date = 2020-02-03 -* version = 2.1 -* spec_version = 2 +* id = f4368ddf-d59f-4192-84f6-778ac5a3ffc7 +* date = 2020-02-03 +* version = 2 -##### Description +#### Description Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. -##### Narrative +#### Narrative The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. -##### Detections +#### Detections +* Detect Prohibited Applications Spawning cmd exe +* Detect Use of cmd exe to Launch Script Interpreters * First time seen command line argument +* System Processes Run From Unexpected Locations * Unusually Long Command Line * Unusually Long Command Line - MLTK -* Detect Prohibited Applications Spawning cmd.exe -* Detect Use of cmd.exe to Launch Script Interpreters -* System Processes Run From Unexpected Locations -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1036 +* T1059 +* T1064 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases +* Actions on Objectives * Command and Control +* Exploitation ###### CIS * CIS 3 * CIS 8 -* CIS 12 -###### NIST +##### NIST +* DE.CM * PR.IP * PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk ##### References * https://attack.mitre.org/wiki/Technique/T1059 @@ -3501,60 +952,54 @@ Endpoint * https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf ### Suspicious DNS Traffic -* id = `3c3835c0-255d-4f9e-ab84-e29ec9ec9b56` -* creation_date = 2016-09-13 -* modification_date = 2017-09-18 -* version = 1.0 -* spec_version = 2 +* id = 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 +* date = 2017-09-18 +* version = 1 -##### Description +#### Description Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. -##### Narrative +#### Narrative Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. -##### Detections -* Excessive DNS Failures +#### Detections * Clients Connecting to Multiple DNS Servers +* DNS Query Length Outliers - MLTK * DNS Query Length With High Standard Deviation * DNS Query Requests Resolved by Unauthorized DNS Servers * Detect Long DNS TXT Record Response -* Detection of DNS Tunnels * Detect hosts connecting to dynamic domain providers -* DNS Query Length Outliers - MLTK +* Detection of DNS Tunnels +* Excessive DNS Failures -##### Providing Technologies -* Splunk Stream -* Bro +#### Data Models +* Network_Resolution -##### Data Models -Network_Resolution +#### Mappings -##### Mappings +##### ATT&CK +* T1043 +* T1048 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases +##### Kill Chain Phases +* Actions on Objectives * Command and Control ###### CIS +* CIS 1 +* CIS 12 +* CIS 13 * CIS 3 * CIS 8 -* CIS 12 +* CIS 9 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk +* ID.AM +* PR.DS +* PR.IP +* PR.PT ##### References * http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/ @@ -3562,121 +1007,88 @@ Network_Resolution * https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454 ### Suspicious Emails -* id = `2b1800dd-92f9-47ec-a981-fdf1351e5d55` -* creation_date = 2017-03-24 -* modification_date = 2020-01-27 -* version = 1.0 -* spec_version = 2 +* id = 2b1800dd-92f9-47ec-a981-fdf1351e5d55 +* date = 2020-01-27 +* version = 1 -##### Description +#### Description Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. -##### Narrative +#### Narrative It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ 1. Which users have received this or a similar message in the past?\ 1. When did the targeted campaign begin?\ 1. Have any users interacted with the content of the messages (by downloading an attachment or clicking on a malicious URL)?This Analytic Story provides detection searches to identify suspicious emails, as well as contextual and investigative searches to help answer some of these questions. -##### Detections -* Monitor Email For Brand Abuse -* Suspicious Email Attachment Extensions +#### Detections * Email Attachments With Lots Of Spaces +* Monitor Email For Brand Abuse * Suspicious Email - UBA Anomaly +* Suspicious Email Attachment Extensions -##### Providing Technologies -* Microsoft Exchange -* Bro -* Splunk Stream +#### Data Models +* Email +* UEBA -##### Data Models -Email -UEBA +#### Mappings -##### Mappings +##### ATT&CK -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Delivery ###### CIS -* CIS 3 -* CIS 8 * CIS 12 +* CIS 3 +* CIS 7 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE -* DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk +* PR.IP ##### References * https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/ ### Suspicious MSHTA Activity -* id = `2b1800dd-92f9-47dd-a981-fdf13w1q5d55` -* creation_date = 2018-08-07 -* modification_date = 2020-02-03 -* version = 1.1 -* spec_version = 2 +* id = 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 +* date = 2020-02-03 +* version = 1 -##### Description +#### Description Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. -##### Narrative +#### Narrative One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ The searches in this story help you detect and investigate suspicious activity that may indicate that an attacker is leveraging mshta.exe to execute malicious code. -##### Detections -* Detect mshta.exe running scripts in command-line arguments +#### Detections +* Detect Prohibited Applications Spawning cmd exe +* Detect mshta exe running scripts in command-line arguments * Registry Keys Used For Persistence -* Detect Prohibited Applications Spawning cmd.exe -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1059 +* T1103 +* T1131 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives +* Exploitation ###### CIS -* CIS 3 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk +* PR.PT ##### References * https://redcanary.com/blog/windows-registry-attacks-threat-detection/ @@ -3684,308 +1096,231 @@ Endpoint * https://attack.mitre.org/wiki/Technique/T1170 ### Suspicious Okta Activity -* id = `9cbd34af-8f39-4476-a423-bacd126c750b` -* creation_date = 2020-04-02 -* modification_date = 2020-04-02 -* version = 1.0 -* spec_version = 2 +* id = 9cbd34af-8f39-4476-a423-bacd126c750b +* date = 2020-04-02 +* version = 1 -##### Description +#### Description Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. -##### Narrative +#### Narrative Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ With people moving quickly to adopt web-based applications and ways to manage them, many are still struggling to understand how best to monitor these environments. This analytic story provides searches to help monitor this environment, and identify events and activity that warrant further investigation such as credential stuffing or password spraying attacks, and users logging in from multiple locations when travel is disallowed. -##### Detections -* Okta Failed SSO Attempts +#### Detections * Multiple Okta Users With Invalid Credentails From The Same IP * Okta Account Lockout Events +* Okta Failed SSO Attempts * Okta User Logins From Multiple Cities -##### Providing Technologies -* Okta +#### Data Models -##### Data Models +#### Mappings -##### Mappings +##### ATT&CK +* T1078 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases ###### CIS -* CIS 3 -* CIS 8 -* CIS 12 +* CIS 16 -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE +##### NIST * DE.CM -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - ##### References * https://attack.mitre.org/wiki/Technique/T1078 * https://owasp.org/www-community/attacks/Credential_stuffing * https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work -### Suspicious WMI Use -* id = `c8ddc5be-69bc-4202-b3ab-4010b27d7ad5` -* creation_date = 2017-01-13 -* modification_date = 2018-10-23 -* version = 2.0 -* spec_version = 2 - -##### Description -Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. - -##### Narrative -WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ -The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ -In the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end. - -##### Detections -* Remote WMI Command Attempt -* Remote Process Instantiation via WMI -* WMI Permanent Event Subscription -* WMI Permanent Event Subscription - Sysmon -* WMI Temporary Event Subscription -* Process Execution via WMI -* Script Execution via WMI - -##### Providing Technologies -* Carbon Black Response -* Sysmon -* Tanium -* Ziften -* CrowdStrike Falcon -* Microsoft Windows - -##### Data Models -Endpoint - -##### Mappings - -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control - -###### CIS -* CIS 3 -* CIS 8 -* CIS 12 - -###### NIST -* PR.IP -* PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk - -##### References -* https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf -* https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html - ### Suspicious Windows Registry Activities -* id = `2b1800dd-92f9-47dd-a981-fdf1351e5d55` -* creation_date = 2018-05-31 -* modification_date = 2018-05-31 -* version = 1.0 -* spec_version = 2 +* id = 2b1800dd-92f9-47dd-a981-fdf1351e5d55 +* date = 2018-05-31 +* version = 1 -##### Description +#### Description Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. -##### Narrative +#### Narrative Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ The searches in this story are designed to help you detect behaviors associated with manipulation of the Windows registry. -##### Detections -* Remote Registry Key modifications -* Suspicious Changes to File Associations +#### Detections * Disabling Remote User Account Control -* Registry Keys for Creating SHIM Databases * Monitor Registry Keys for Print Monitors -* Reg.exe used to hide files/directories via registry keys +* Reg exe used to hide files directories via registry keys * Registry Keys Used For Persistence * Registry Keys Used For Privilege Escalation +* Registry Keys for Creating SHIM Databases +* Remote Registry Key modifications +* Suspicious Changes to File Associations -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint -Change_Analysis +#### Mappings -##### Mappings +##### ATT&CK +* T1015 +* T1042 +* T1103 +* T1112 +* T1131 +* T1138 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives ###### CIS * CIS 3 +* CIS 5 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk +* PR.AC +* PR.IP +* PR.PT ##### References * https://redcanary.com/blog/windows-registry-attacks-threat-detection/ * https://attack.mitre.org/wiki/Technique/T1112 -### Windows Defense Evasion Tactics -* id = `56e24a28-5003-4047-b2db-e8f3c4618064` -* creation_date = 2017-10-11 -* modification_date = 2018-05-31 -* version = 1.0 -* spec_version = 2 +### Suspicious WMI Use +* id = c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 +* date = 2018-10-23 +* version = 2 -##### Description -Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others +#### Description +Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. -##### Narrative -Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. +#### Narrative +WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ +The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ +In the event that unauthorized WMI execution occurs, it will be important for analysts and investigators to determine the context of the event. These details may provide insights related to how WMI was used and to what end. -##### Detections -* Suspicious Reg.exe Process -* Disabling Remote User Account Control -* Hiding Files And Directories With Attrib.exe -* Reg.exe used to hide files/directories via registry keys -* Remote Registry Key modifications +#### Detections +* Process Execution via WMI +* Remote Process Instantiation via WMI +* Remote WMI Command Attempt +* Script Execution via WMI +* WMI Permanent Event Subscription +* WMI Permanent Event Subscription - Sysmon +* WMI Temporary Event Subscription -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1047 +* T1084 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives ###### CIS * CIS 3 -* CIS 8 -* CIS 12 +* CIS 5 -###### NIST +##### NIST +* PR.AC +* PR.AT * PR.IP * PR.PT -* PR.AC -* DE.AE -* DE.CM -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk +##### References +* https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf +* https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html + +### Windows Defense Evasion Tactics +* id = 56e24a28-5003-4047-b2db-e8f3c4618064 +* date = 2018-05-31 +* version = 1 + +#### Description +Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others + +#### Narrative +Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. + +#### Detections +* Disabling Remote User Account Control +* Hiding Files And Directories With Attrib exe +* Reg exe used to hide files directories via registry keys +* Remote Registry Key modifications +* Suspicious Reg exe Process + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK +* T1089 +* T1112 + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 8 + +##### NIST +* DE.CM +* PR.PT ##### References * https://attack.mitre.org/wiki/Defense_Evasion ### Windows Log Manipulation -* id = `b6db2c60-a281-48b4-95f1-2cd99ed56835` -* creation_date = 2017-02-17 -* modification_date = 2017-09-12 -* version = 2.0 -* spec_version = 2 +* id = b6db2c60-a281-48b4-95f1-2cd99ed56835 +* date = 2017-09-12 +* version = 2 -##### Description +#### Description Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. -##### Narrative +#### Narrative Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). -##### Detections +#### Detections * Deleting Shadow Copies -* Windows Event Log Cleared * Suspicious wevtutil Usage * USN Journal Deletion +* Windows Event Log Cleared -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften -* Microsoft Windows +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1070 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives ###### CIS +* CIS 10 * CIS 3 +* CIS 5 +* CIS 6 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = Rico Valdez -* email = rvaldez@splunk.com -* company = Splunk +* DE.DP +* PR.AC +* PR.AT +* PR.IP +* PR.PT ##### References * https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ @@ -3993,71 +1328,60 @@ Endpoint * http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html ### Windows Persistence Techniques -* id = `30874d4f-20a1-488f-85ec-5d52ef74e3f9` -* creation_date = 2017-04-19 -* modification_date = 2018-05-31 -* version = 2.0 -* spec_version = 2 +* id = 30874d4f-20a1-488f-85ec-5d52ef74e3f9 +* date = 2018-05-31 +* version = 2 -##### Description +#### Description Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. -##### Narrative +#### Narrative Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. -##### Detections -* Registry Keys for Creating SHIM Databases -* Shim Database Installation With Suspicious Parameters -* Shim Database File Creation -* Registry Keys Used For Persistence -* Schtasks used for forcing a reboot -* Sc.exe Manipulating Windows Services -* Reg.exe Manipulating Windows Services Registry Keys -* Hiding Files And Directories With Attrib.exe -* Reg.exe used to hide files/directories via registry keys -* Detect Path Interception By Creation Of program.exe +#### Detections +* Detect Path Interception By Creation Of program exe +* Hiding Files And Directories With Attrib exe * Monitor Registry Keys for Print Monitors +* Reg exe Manipulating Windows Services Registry Keys +* Reg exe used to hide files directories via registry keys +* Registry Keys Used For Persistence +* Registry Keys for Creating SHIM Databases * Remote Registry Key modifications +* Sc exe Manipulating Windows Services +* Schtasks used for forcing a reboot +* Shim Database File Creation +* Shim Database Installation With Suspicious Parameters -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Tanium -* Ziften -* Sysmon +#### Data Models +* Endpoint -##### Data Models -Endpoint -Change_Analysis +#### Mappings -##### Mappings +##### ATT&CK +* T1031 +* T1050 +* T1053 +* T1089 +* T1103 +* T1131 +* T1138 -###### ATT&CK -* Command and Control -* Exfiltration - -###### Kill Chain Phases -* Command and Control +##### Kill Chain Phases +* Actions on Objectives +* Installation ###### CIS * CIS 3 +* CIS 5 * CIS 8 -* CIS 12 -###### NIST -* PR.IP -* PR.PT -* PR.AC +##### NIST * DE.AE * DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk -* name = Bhavin Patel -* email = bpatel@splunk.com -* company = Splunk +* PR.AC +* PR.AT +* PR.IP +* PR.PT ##### References * http://www.fuzzysecurity.com/tutorials/19.html @@ -4067,59 +1391,1762 @@ Change_Analysis * https://www.youtube.com/watch?v=dq2Hv7J9fvk ### Windows Privilege Escalation -* id = `644e22d3-598a-429c-a007-16fdb802cae5` -* creation_date = 2017-12-07 -* modification_date = 2020-02-04 -* version = 2.0 -* spec_version = 2 +* id = 644e22d3-598a-429c-a007-16fdb802cae5 +* date = 2020-02-04 +* version = 2 -##### Description +#### Description Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. -##### Narrative +#### Narrative Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. -##### Detections +#### Detections +* Child Processes of Spoolsv exe * Overwriting Accessibility Binaries * Registry Keys Used For Privilege Escalation * Uncommon Processes On Endpoint -* Child Processes of Spoolsv.exe -##### Providing Technologies -* Carbon Black Response -* CrowdStrike Falcon -* Sysmon -* Tanium -* Ziften +#### Data Models +* Endpoint -##### Data Models -Endpoint +#### Mappings -##### Mappings +##### ATT&CK +* T1015 +* T1068 -###### ATT&CK +##### Kill Chain Phases +* Actions on Objectives +* Exploitation + +###### CIS +* CIS 2 +* CIS 8 + +##### NIST +* DE.CM +* ID.AM +* PR.DS +* PR.PT + +##### References +* https://attack.mitre.org/tactics/TA0004/ + + +## Best Practices + +* [Account Monitoring and Controls](#Account-Monitoring-and-Controls) + +* [Asset Tracking](#Asset-Tracking) + +* [Monitor Backup Solution](#Monitor-Backup-Solution) + +* [Monitor for Unauthorized Software](#Monitor-for-Unauthorized-Software) + +* [Monitor for Updates](#Monitor-for-Updates) + +* [Prohibited Traffic Allowed or Protocol Mismatch](#Prohibited-Traffic-Allowed-or-Protocol-Mismatch) + +* [Router and Infrastructure Security](#Router-and-Infrastructure-Security) + +* [Use of Cleartext Protocols](#Use-of-Cleartext-Protocols) + +### Account Monitoring and Controls +* id = 8892a655-6205-55f7-abba-06460e38c8ae +* date = 2017-09-06 +* version = 1 + +#### Description +A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. + +#### Narrative +Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. + +#### Detections +* Detect Excessive Account Lockouts From Endpoint +* Detect Excessive User Account Lockouts +* Identify New User Accounts +* Short Lived Windows Accounts + +#### Data Models +* Change + +#### Mappings + +##### ATT&CK +* T1078 +* T1136 + +##### Kill Chain Phases + +###### CIS +* CIS 16 + +##### NIST +* PR.IP + +##### References +* https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf + +### Asset Tracking +* id = 91c676cf-0b23-438d-abee-f6335e1fce77 +* date = 2017-09-13 +* version = 1 + +#### Description +Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. + +#### Narrative +This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. + +#### Detections +* Detect Unauthorized Assets by MAC address + +#### Data Models +* Network_Sessions + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 1 + +##### NIST +* PR.DS + +##### References +* https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/ + +### Monitor Backup Solution +* id = abe807c7-1eb6-4304-ac32-6e7aacdb891d +* date = 2017-09-12 +* version = 1 + +#### Description +Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. + +#### Narrative +Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. + +#### Detections +* Extended Period Without Successful Netbackup Backups +* Unsuccessful Netbackup backups + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases + +###### CIS +* CIS 10 + +##### NIST +* PR.IP + +##### References +* https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/ + +### Monitor for Unauthorized Software +* id = 8892a655-6205-43f7-abba-06460e38c8ae +* date = 2017-09-15 +* version = 1 + +#### Description +Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. + +#### Narrative +It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ +It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. + +#### Detections +* Prohibited Software On Endpoint + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 2 + +##### NIST +* PR.DS + +##### References +* https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/ + +### Monitor for Updates +* id = 9ef8d677-7b52-4213-a038-99cfc7acc2d8 +* date = 2017-09-15 +* version = 1 + +#### Description +Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. + +#### Narrative +It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ +Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ +Microsoft releases updates for Windows systems on a monthly cadence. They should be installed as soon as possible after following internal testing and validation procedures. Patches and updates for other systems or applications are typically released as needed. + +#### Detections +* No Windows Updates in a time frame + +#### Data Models +* Updates + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases + +###### CIS +* CIS 18 + +##### NIST +* PR.MA + +##### References +* https://learn.cisecurity.org/20-controls-download + +### Prohibited Traffic Allowed or Protocol Mismatch +* id = 6d13121c-90f3-446d-8ac3-27efbbc65218 +* date = 2017-09-11 +* version = 1 + +#### Description +Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. + +#### Narrative +A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. + +#### Detections +* Detect hosts connecting to dynamic domain providers +* Prohibited Network Traffic Allowed +* Protocol or Port Mismatch +* TOR Traffic + +#### Data Models +* Network_Resolution +* Network_Traffic + +#### Mappings + +##### ATT&CK +* T1043 +* T1048 + +##### Kill Chain Phases +* Actions on Objectives * Command and Control -* Exfiltration +* Delivery -###### Kill Chain Phases +###### CIS +* CIS 12 +* CIS 13 +* CIS 9 + +##### NIST +* DE.AE +* DE.CM +* PR.AC + +##### References +* http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/ + +### Router and Infrastructure Security +* id = 91c676cf-0b23-438d-abee-f6335e177e77 +* date = 2017-09-12 +* version = 1 + +#### Description +Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. + +#### Narrative +Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ +This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. + +#### Detections +* Detect New Login Attempts to Routers + +#### Data Models +* Authentication + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 11 + +##### NIST +* PR.IP + +##### References +* https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html +* https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html + +### Use of Cleartext Protocols +* id = 826e6431-aeef-41b4-9fc0-6d0985d65a21 +* date = 2017-09-15 +* version = 1 + +#### Description +Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. + +#### Narrative +Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. + +#### Detections +* Protocols passing authentication in cleartext + +#### Data Models +* Network_Traffic + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 14 + +##### NIST +* PR.DS + +##### References +* https://www.monkey.org/~dugsong/dsniff/ + + +## Cloud Security + +* [AWS Cross Account Activity](#AWS-Cross-Account-Activity) + +* [AWS Cryptomining](#AWS-Cryptomining) + +* [AWS Network ACL Activity](#AWS-Network-ACL-Activity) + +* [AWS Suspicious Provisioning Activities](#AWS-Suspicious-Provisioning-Activities) + +* [AWS User Monitoring](#AWS-User-Monitoring) + +* [Cloud Cryptomining](#Cloud-Cryptomining) + +* [Container Implantation Monitoring and Investigation](#Container-Implantation-Monitoring-and-Investigation) + +* [Kubernetes Scanning Activity](#Kubernetes-Scanning-Activity) + +* [Suspicious AWS EC2 Activities](#Suspicious-AWS-EC2-Activities) + +* [Suspicious AWS Login Activities](#Suspicious-AWS-Login-Activities) + +* [Suspicious AWS S3 Activities](#Suspicious-AWS-S3-Activities) + +* [Suspicious AWS Traffic](#Suspicious-AWS-Traffic) + +* [Unusual AWS EC2 Modifications](#Unusual-AWS-EC2-Modifications) + +### AWS Cross Account Activity +* id = 2f2f610a-d64d-48c2-b57c-967a2b49ab5a +* date = 2018-06-04 +* version = 1 + +#### Description +Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. + +#### Narrative +Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ +Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ +This Analytic Story includes searches that will help you monitor your AWS CloudTrail logs for evidence of suspicious cross-account activity. For example, while accessing multiple AWS accounts and roles may be perfectly valid behavior, it may be suspicious when an account requests privileges of an account it has not accessed in the past. After identifying suspicious activities, you can use the provided investigative searches to help you probe more deeply. + +#### Detections +* AWS Cross Account Activity From Previously Unseen Account + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 16 + +##### NIST +* DE.AE + +##### References +* https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/ + +### AWS Cryptomining +* id = ced74200-8465-4bc3-bd2c-9a782eec6750 +* date = 2018-03-08 +* version = 1 + +#### Description +Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. + +#### Narrative +Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ +Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ +hen malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So, it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ +This Analytic Story is focused on detecting suspicious new instances in your EC2 environment to help prevent such a disaster. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. + +#### Detections +* Abnormally High AWS Instances Launched by User +* EC2 Instance Started In Previously Unseen Region +* EC2 Instance Started With Previously Unseen AMI +* EC2 Instance Started With Previously Unseen Instance Type +* EC2 Instance Started With Previously Unseen User + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 1 +* CIS 12 +* CIS 13 + +##### NIST +* DE.AE +* DE.DP +* ID.AM + +##### References +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +### AWS Network ACL Activity +* id = 2e8948a5-5239-406b-b56b-6c50ff268af4 +* date = 2018-05-21 +* version = 2 + +#### Description +Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. + +#### Narrative +AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. + +#### Detections +* AWS Network Access Control List Created with All Open Ports +* AWS Network Access Control List Deleted +* Detect Spike in Network ACL Activity +* Detect Spike in blocked Outbound Traffic from your AWS + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives * Command and Control +###### CIS +* CIS 11 +* CIS 12 + +##### NIST +* DE.AE +* DE.CM +* DE.DP +* PR.AC + +##### References +* https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html +* https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/ + +### AWS Suspicious Provisioning Activities +* id = 3338b567-3804-4261-9889-cf0ca4753c7f +* date = 2018-03-16 +* version = 1 + +#### Description +Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. + +#### Narrative +Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ +This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. + +#### Detections +* AWS Cloud Provisioning From Previously Unseen City +* AWS Cloud Provisioning From Previously Unseen Country +* AWS Cloud Provisioning From Previously Unseen IP Address +* AWS Cloud Provisioning From Previously Unseen Region + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases + +###### CIS +* CIS 1 + +##### NIST +* ID.AM + +##### References +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +### AWS User Monitoring +* id = 2e8948a5-5239-406b-b56b-6c50f1269af3 +* date = 2018-03-12 +* version = 1 + +#### Description +Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. + +#### Narrative +It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ +In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ +Fortunately, you can leverage Amazon Web Services (AWS) CloudTrail--a tool that helps you enable governance, compliance, and risk auditing of your AWS account--to give you increased visibility into your user and resource activity by recording AWS Management Console actions and API calls. You can identify which users and accounts called AWS, the source IP address from which the calls were made, and when the calls occurred.\ +The detection searches in this Analytic Story are designed to help you uncover AWS API activities from users not listed in the identity table, as well as similar activities from disabled accounts. + +#### Detections +* Detect API activity from users without MFA +* Detect AWS API Activities From Unapproved Accounts +* Detect Spike in AWS API Activity +* Detect Spike in Security Group Activity +* Detect new API calls from user roles + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 1 +* CIS 16 + +##### NIST +* DE.CM +* DE.DP +* ID.AM +* PR.AC + +##### References +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +* https://redlock.io/blog/cryptojacking-tesla + +### Cloud Cryptomining +* id = 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a +* date = 2019-10-02 +* version = 1 + +#### Description +Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. + +#### Narrative +Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ +Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ +When malicious miners appropriate a cloud instance, often spinning up hundreds of new instances, the costs can become astronomical for the account holder. So it is critically important to monitor your systems for suspicious activities that could indicate that your network has been infiltrated. \ +This Analytic Story is focused on detecting suspicious new instances in your cloud environment to help prevent cryptominers from gaining a foothold. It contains detection searches that will detect when a previously unused instance type or AMI is used. It also contains support searches to build lookup files to ensure proper execution of the detection searches. + +#### Detections +* Abnormally High AWS Instances Launched by User - MLTK +* Cloud Compute Instance Created By Previously Unseen User +* Cloud Compute Instance Created With Previously Unseen Image +* Cloud Compute Instance Created With Previously Unseen Instance Type +* Cloud Compute Instance Started In Previously Unused Region + +#### Data Models +* Cloud_Infrastructure + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 1 +* CIS 12 +* CIS 13 + +##### NIST +* DE.AE +* DE.DP +* ID.AM + +##### References +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +### Container Implantation Monitoring and Investigation +* id = aa0e28b1-0521-4b6f-9d2a-7b87e34af246 +* date = 2020-02-20 +* version = 1 + +#### Description +Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. + +#### Narrative +Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. + +#### Detections +* GCP GCR container uploaded +* New container uploaded to AWS ECR + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases + +###### CIS + +##### NIST + +##### References +* https://github.com/splunk/cloud-datamodel-security-research + +### Kubernetes Scanning Activity +* id = a9ef59cf-e981-4e66-9eef-bb049f695c09 +* date = 2020-04-15 +* version = 1 + +#### Description +This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. + +#### Narrative +Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. + +#### Detections +* Amazon EKS Kubernetes Pod scan detection +* Amazon EKS Kubernetes cluster scan detection +* GCP Kubernetes cluster scan detection + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Reconnaissance + +###### CIS + +##### NIST + +##### References +* https://github.com/splunk/cloud-datamodel-security-research + +### Suspicious AWS EC2 Activities +* id = 2e8948a5-5239-406b-b56b-6c50f1268af3 +* date = 2018-02-09 +* version = 1 + +#### Description +Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. + +#### Narrative +AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. + +#### Detections +* Abnormally High AWS Instances Launched by User +* Abnormally High AWS Instances Launched by User - MLTK +* Abnormally High AWS Instances Terminated by User +* Abnormally High AWS Instances Terminated by User - MLTK +* EC2 Instance Started In Previously Unseen Region +* EC2 Instance Started With Previously Unseen User + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 1 +* CIS 12 +* CIS 13 + +##### NIST +* DE.AE +* DE.DP +* ID.AM + +##### References +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + +### Suspicious AWS Login Activities +* id = 2e8948a5-5239-406b-b56b-6c59f1268af3 +* date = 2019-05-01 +* version = 1 + +#### Description +Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. + +#### Narrative +It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. + +#### Detections +* Detect AWS Console Login by User from New City +* Detect AWS Console Login by User from New Country +* Detect AWS Console Login by User from New Region +* Detect new user AWS Console Login + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 16 + +##### NIST +* DE.AE +* DE.DP + +##### References +* https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html + +### Suspicious AWS S3 Activities +* id = 2e8948a5-5239-406b-b56b-6c50w3168af3 +* date = 2018-07-24 +* version = 2 + +#### Description +Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. + +#### Narrative +As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ +Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ +Among things to look out for are S3 access from unfamiliar locations and by unfamiliar users. Some of the searches in this Analytic Story help you detect suspicious behavior and others help you investigate more deeply, when the situation warrants. + +#### Detections +* Detect New Open S3 buckets +* Detect S3 access from a new IP +* Detect Spike in S3 Bucket deletion + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Actions on Objectives + +###### CIS +* CIS 13 +* CIS 14 + +##### NIST +* DE.CM +* DE.DP +* PR.AC +* PR.DS + +##### References +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf +* https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/ + +### Suspicious AWS Traffic +* id = 2e8948a5-5239-406b-b56b-6c50f2168af3 +* date = 2018-05-07 +* version = 1 + +#### Description +Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). + +#### Narrative +A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ +Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ + Attackers may abuse the AWS infrastructure with insecure VPCs so they can co-opt AWS resources for command-and-control nodes, data exfiltration, and more. Once an EC2 instance is compromised, an attacker may initiate outbound network connections for malicious reasons. Monitoring these network traffic behaviors is crucial for understanding the type of traffic flowing in and out of your network and to alert you to suspicious activities.\ +The searches in this Analytic Story will monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors. + +#### Detections +* Detect Spike in blocked Outbound Traffic from your AWS + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Command and Control + +###### CIS +* CIS 11 + +##### NIST +* PR.AC + +##### References +* https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/ + +### Unusual AWS EC2 Modifications +* id = 73de57ef-0dfc-411f-b1e7-fa24428aeae0 +* date = 2018-04-09 +* version = 1 + +#### Description +Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. + +#### Narrative +A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ + Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. + +#### Detections +* EC2 Instance Modified With Previously Unseen User + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases + +###### CIS +* CIS 1 + +##### NIST +* ID.AM + +##### References +* https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf + + +## Malware + +* [ColdRoot MacOS RAT](#ColdRoot-MacOS-RAT) + +* [DHS Report TA18-074A](#DHS-Report-TA18-074A) + +* [Dynamic DNS](#Dynamic-DNS) + +* [Emotet Malware DHS Report TA18-201A ](#Emotet-Malware--DHS-Report-TA18-201A-) + +* [Hidden Cobra Malware](#Hidden-Cobra-Malware) + +* [Orangeworm Attack Group](#Orangeworm-Attack-Group) + +* [Ransomware](#Ransomware) + +* [SamSam Ransomware](#SamSam-Ransomware) + +* [Unusual Processes](#Unusual-Processes) + +* [Windows File Extension and Association Abuse](#Windows-File-Extension-and-Association-Abuse) + +* [Windows Service Abuse](#Windows-Service-Abuse) + +### ColdRoot MacOS RAT +* id = bd91a2bc-d20b-4f44-a982-1bea98e86390 +* date = 2019-01-09 +* version = 1 + +#### Description +Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. + +#### Narrative +Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ +This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ +Searches in this Analytic Story leverage the capabilities of OSquery to address ColdRoot detection from several different angles, such as looking for the existence of associated files and processes, and monitoring for signs of an installed keylogger. + +#### Detections +* Osquery pack - ColdRoot detection +* Processes Tapping Keyboard Events + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Command and Control + +###### CIS +* CIS 4 +* CIS 8 + +##### NIST +* DE.DP +* PR.PT + +##### References +* https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/ +* https://objective-see.com/blog/blog_0x2A.html +* https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/ + +### DHS Report TA18-074A +* id = 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef +* date = 2020-01-22 +* version = 2 + +#### Description +Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. + +#### Narrative +The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ +There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ +One joint Technical Alert (TA) issued by the Department of Homeland and the FBI in mid-March of 2018 attributed some cyber activity targeting utility infrastructure to operatives sponsored by the Russian government. The hackers executed spearfishing attacks, installed malware, employed watering-hole domains, and more. While they caused no physical damage, the attacks provoked fears that a nation-state could turn off water, redirect power, or compromise a nuclear power plant.\ +Suspicious activities--spikes in SMB traffic, processes that launch netsh (to modify the network configuration), suspicious registry modifications, and many more--may all be events you may wish to investigate further. While the use of these technique may be an indication that a nation-state actor is attempting to compromise your environment, it is important to note that these techniques are often employed by other groups, as well. + +#### Detections +* Create local admin accounts using net exe +* Detect New Local Admin account +* Detect Outbound SMB Traffic +* Detect PsExec With accepteula Flag +* First time seen command line argument +* Malicious PowerShell Process - Execution Policy Bypass +* Processes launching netsh +* Registry Keys Used For Persistence +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Sc exe Manipulating Windows Services +* Scheduled Task Name Used by Dragonfly Threat Actors +* Single Letter Process On Endpoint +* Suspicious Reg exe Process + +#### Data Models +* Endpoint +* Network_Traffic + +#### Mappings + +##### ATT&CK +* T1031 +* T1043 +* T1050 +* T1053 +* T1059 +* T1064 +* T1078 +* T1086 +* T1089 +* T1103 +* T1112 +* T1131 + +##### Kill Chain Phases +* Actions on Objectives +* Command and Control +* Installation + +###### CIS +* CIS 12 +* CIS 16 +* CIS 2 +* CIS 3 +* CIS 5 +* CIS 7 +* CIS 8 + +##### NIST +* DE.AE +* DE.CM +* ID.AM +* PR.AC +* PR.AT +* PR.DS +* PR.IP +* PR.PT + +##### References +* https://www.us-cert.gov/ncas/alerts/TA18-074A + +### Dynamic DNS +* id = 8169f17b-ef68-4b59-aae8-586907301221 +* date = 2018-09-06 +* version = 2 + +#### Description +Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. + +#### Narrative +Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. + +#### Detections +* Detect hosts connecting to dynamic domain providers +* Detect web traffic to dynamic domain providers + +#### Data Models +* Network_Resolution +* Web + +#### Mappings + +##### ATT&CK +* T1041 + +##### Kill Chain Phases +* Actions on Objectives +* Command and Control + +###### CIS +* CIS 13 +* CIS 7 +* CIS 8 + +##### NIST +* DE.CM +* DE.DP +* PR.IP + +##### References +* https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html +* https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/ +* http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/ +* https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html + +### Emotet Malware DHS Report TA18-201A +* id = bb9f5ed2-916e-4364-bb6d-91c310efcf52 +* date = 2020-01-27 +* version = 1 + +#### Description +Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. + +#### Narrative +The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ +According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ +The searches in this Analytic Story will help you find executables that are rarely used in your environment, specific registry paths that malware often uses to ensure survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that Emotet or other malware has compromised your environment. + +#### Detections +* Detect Rare Executables +* Detect Use of cmd exe to Launch Script Interpreters +* Detection of tools built by NirSoft +* Email Attachments With Lots Of Spaces +* Prohibited Software On Endpoint +* Registry Keys Used For Persistence +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Suspicious Email Attachment Extensions + +#### Data Models +* Email +* Endpoint +* Network_Traffic + +#### Mappings + +##### ATT&CK +* T1043 +* T1059 +* T1072 +* T1087 +* T1103 +* T1131 + +##### Kill Chain Phases +* Actions on Objectives +* Command and Control +* Delivery +* Exploitation +* Installation + +###### CIS +* CIS 12 +* CIS 2 +* CIS 3 +* CIS 7 +* CIS 8 + +##### NIST +* DE.AE +* DE.CM +* ID.AM +* PR.DS +* PR.IP +* PR.PT + +##### References +* https://www.us-cert.gov/ncas/alerts/TA18-201A +* https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf +* https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html + +### Hidden Cobra Malware +* id = baf7580b-d4b4-4774-8173-7d198e9da335 +* date = 2020-01-22 +* version = 2 + +#### Description +Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. + +#### Narrative +North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ +These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ +In June of 2018, The Department of Homeland Security, together with the FBI and other U.S. government partners, issued Technical Alert (TA-18-149A) to advise the public about two variants of North Korean malware. One variant, dubbed "Joanap," is a multi-stage peer-to-peer botnet that allows North Korean state actors to exfiltrate data, download and execute secondary payloads, and initialize proxy communications. The other variant, "Brambul," is a Windows32 SMB worm that is dropped into a victim network. When executed, the malware attempts to spread laterally within a victim's local subnet, connecting via the SMB protocol and initiating brute-force password attacks. It reports details to the Hidden Cobra actors via email, so they can use the information for secondary remote operations.\ +Among other searches in this Analytic Story is a detection search that looks for the creation or deletion of hidden shares, such as, "adnim$," which the Hidden Cobra malware creates on the target system. Another looks for the creation of three malicious files associated with the malware. You can also use a search in this story to investigate activity that indicates that malware is sending email back to the attackers. + +#### Detections +* Create or delete windows shares using net exe +* DNS Query Length Outliers - MLTK +* DNS Query Length With High Standard Deviation +* Detect Outbound SMB Traffic +* First time seen command line argument +* Remote Desktop Network Traffic +* Remote Desktop Process Running On System +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Suspicious File Write + +#### Data Models +* Endpoint +* Network_Resolution +* Network_Traffic + +#### Mappings + +##### ATT&CK +* T1043 +* T1059 +* T1064 +* T1076 + +##### Kill Chain Phases +* Actions on Objectives +* Command and Control + +###### CIS +* CIS 12 +* CIS 16 +* CIS 3 +* CIS 8 +* CIS 9 + +##### NIST +* DE.AE +* DE.CM +* PR.AC +* PR.IP +* PR.PT + +##### References +* https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity +* https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf + +### Orangeworm Attack Group +* id = bb9f5ed2-916e-4364-bb6d-97c370efcf52 +* date = 2020-01-22 +* version = 2 + +#### Description +Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. + +#### Narrative +In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ +Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ +Although the group's motivation is unknown, its goal may be stealing patient information to sell on the black market. Another possible explanation is corporate espionage. \ +Healthcare may be a promising target, because it is notoriously behind in technology, often using older operating systems and neglecting to patch computers. Even so, the group was able to evade detection for a full three years. Sources say that the malware spread quickly within the target networks, infecting computers used to control medical devices, such as MRI and X-ray machines.\ +This Analytic Story is designed to help you detect and investigate suspicious activities that may be indicative of an Orangeworm attack. One detection search looks for command-line arguments. Another monitors for uses of sc.exe, a non-essential Windows file that can manipulate Windows services. One of the investigative searches helps you get more information on web hosts that you suspect have been compromised. + +#### Detections +* First Time Seen Running Windows Service +* First time seen command line argument +* Sc exe Manipulating Windows Services + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK +* T1031 +* T1050 +* T1059 +* T1089 + +##### Kill Chain Phases +* Actions on Objectives +* Installation + +###### CIS +* CIS 2 +* CIS 3 +* CIS 5 +* CIS 8 +* CIS 9 + +##### NIST +* DE.AE +* DE.CM +* ID.AM +* PR.AC +* PR.AT +* PR.DS +* PR.IP +* PR.PT + +##### References +* https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia +* https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/ + +### Ransomware +* id = cf309d0d-d4aa-4fbb-963d-1e79febd3756 +* date = 2020-02-04 +* version = 1 + +#### Description +Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. + +#### Narrative +Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. + +#### Detections +* Common Ransomware Extensions +* Common Ransomware Notes +* Deleting Shadow Copies +* Prohibited Network Traffic Allowed +* Registry Keys Used For Persistence +* Remote Process Instantiation via WMI +* SMB Traffic Spike +* SMB Traffic Spike - MLTK +* Scheduled tasks used in BadRabbit ransomware +* Schtasks used for forcing a reboot +* Spike in File Writes +* Suspicious wevtutil Usage +* System Processes Run From Unexpected Locations +* TOR Traffic +* USN Journal Deletion +* Unusually Long Command Line +* Unusually Long Command Line - MLTK +* Windows Event Log Cleared + +#### Data Models +* Endpoint +* Network_Traffic + +#### Mappings + +##### ATT&CK +* T1036 +* T1043 +* T1047 +* T1048 +* T1053 +* T1070 +* T1103 +* T1131 + +##### Kill Chain Phases +* Actions on Objectives +* Command and Control +* Delivery + +###### CIS +* CIS 10 +* CIS 12 +* CIS 3 +* CIS 5 +* CIS 6 +* CIS 8 +* CIS 9 + +##### NIST +* DE.AE +* DE.CM +* DE.DP +* PR.AC +* PR.AT +* PR.IP +* PR.PT + +##### References +* https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/ +* https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html + +### SamSam Ransomware +* id = c4b89506-fbcf-4cb7-bfd6-527e54789604 +* date = 2018-12-13 +* version = 1 + +#### Description +Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. + +#### Narrative +The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ +Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ +SamSam attacks are different beasts. They have become progressively more targeted and skillful than typical ransomware attacks. First, malicious actors break into a victim's network, surveil it, then run the malware manually. The attacks are tailored to cause maximum damage and the threat actors usually demand amounts in the tens of thousands of dollars.\ +In a typical attack on one large healthcare organization in 2018, the company ended up paying a ransom of four Bitcoins, then worth $56,707. Reports showed that access to the company's files was restored within two hours of paying the sum.\ +According to Sophos, SamSam previously leveraged RDP to gain access to targeted networks via brute force. SamSam is not spread automatically, like other malware. It requires skill because it forces the attacker to adapt their tactics to the individual environment. Next, the actors escalate their privileges to admin level. They scan the networks for worthy targets, using conventional tools, such as PsExec or PaExec, to deploy/execute, quickly encrypting files.\ +This Analytic Story includes searches designed to help detect and investigate signs of the SamSam ransomware, such as the creation of fileswrites to system32, writes with tell-tale extensions, batch files written to system32, and evidence of brute-force attacks via RDP. + +#### Detections +* Batch File Write to System32 +* Common Ransomware Extensions +* Common Ransomware Notes +* Deleting Shadow Copies +* Detect PsExec With accepteula Flag +* Detect attackers scanning for vulnerable JBoss servers +* Detect malicious requests to exploit JBoss servers +* File with Samsam Extension +* Prohibited Software On Endpoint +* Remote Desktop Network Bruteforce +* Remote Desktop Network Traffic +* Samsam Test File Write +* Spike in File Writes + +#### Data Models +* Endpoint +* Network_Traffic +* Web + +#### Mappings + +##### ATT&CK +* T1059 +* T1076 +* T1082 + +##### Kill Chain Phases +* Actions on Objectives +* Command and Control +* Delivery +* Installation +* Reconnaissance + +###### CIS +* CIS 10 +* CIS 12 +* CIS 16 +* CIS 18 +* CIS 2 +* CIS 3 +* CIS 4 +* CIS 8 +* CIS 9 + +##### NIST +* DE.AE +* DE.CM +* ID.AM +* ID.RA +* PR.AC +* PR.DS +* PR.IP +* PR.MA +* PR.PT + +##### References +* https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/ +* https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/ +* https://thehackernews.com/2018/07/samsam-ransomware-attacks.html + +### Unusual Processes +* id = f4368e3f-d59f-4192-84f6-748ac5a3ddb6 +* date = 2020-02-04 +* version = 2 + +#### Description +Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. + +#### Narrative +Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ +This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ +In the event an unusual process is identified, it is imperative to better understand how that process was able to execute on the host, when it first executed, and whether other hosts are affected. This extra information may provide clues that can help the analyst further investigate any suspicious activity. + +#### Detections +* Detect Rare Executables +* Detect processes used for System Network Configuration Discovery +* RunDLL Loading DLL By Ordinal +* System Processes Run From Unexpected Locations +* Uncommon Processes On Endpoint +* Unusually Long Command Line +* Unusually Long Command Line - MLTK + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK +* T1015 +* T1036 +* T1085 + +##### Kill Chain Phases +* Actions on Objectives +* Command and Control +* Installation + +###### CIS +* CIS 2 +* CIS 8 + +##### NIST +* DE.CM +* ID.AM +* PR.DS +* PR.PT + +##### References +* https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html +* https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf +* https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262 + +### Windows File Extension and Association Abuse +* id = 30552a76-ac78-48e4-b3c0-de4e34e9563d +* date = 2018-01-26 +* version = 1 + +#### Description +Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. + +#### Narrative +Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ + Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ + Attackers take advantage of this expectation by obfuscating the true file extension. They can accomplish this in a couple of ways. One technique involves inserting multiple spaces in the file name before the extension to hide the extension from the GUI, obscuring the true nature of the file. Another approach involves prepending the real extension with a different one. This is especially effective when Windows is configured to "hide extensions for known file types." In this case, the real extension is not displayed, but the prepended one is, leading end users to believe the file is a different type than it actually is.\ +Changing the association between a file extension and an application can allow an attacker to execute arbitrary code. The technique typically involves changing the association for an often-launched file type to associate instead with a malicious program the attacker has dropped on the endpoint. When the end user launches a file that has been manipulated in this way, it will execute the attacker's malware. It will also execute the application the end user expected to run, cleverly obscuring the fact that something suspicious has occurred.\ +Run the searches in this story to detect and investigate suspicious behavior that may indicate abuse or manipulation of Windows file extensions and/or associations. + +#### Detections +* Execution of File With Spaces Before Extension +* Execution of File with Multiple Extensions +* Suspicious Changes to File Associations + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK +* T1042 + +##### Kill Chain Phases +* Actions on Objectives + ###### CIS * CIS 3 * CIS 8 -* CIS 12 -###### NIST +##### NIST +* DE.CM * PR.IP * PR.PT -* PR.AC -* DE.AE -* DE.CM - -##### Maintainers -* name = David Dorsey -* email = davidd@splunk.com -* company = Splunk ##### References -* https://attack.mitre.org/tactics/TA0004/ +* https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/ +* https://attack.mitre.org/wiki/Technique/T1042 + +### Windows Service Abuse +* id = 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 +* date = 2017-11-02 +* version = 3 + +#### Description +Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. + +#### Narrative +The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. + +#### Detections +* First Time Seen Running Windows Service +* Reg exe Manipulating Windows Services Registry Keys +* Sc exe Manipulating Windows Services + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK +* T1031 +* T1050 +* T1089 + +##### Kill Chain Phases +* Actions on Objectives +* Installation + +###### CIS +* CIS 3 +* CIS 5 +* CIS 8 +* CIS 9 + +##### NIST +* DE.AE +* DE.CM +* PR.AC +* PR.AT +* PR.IP +* PR.PT + +##### References +* https://attack.mitre.org/wiki/Technique/T1050 +* https://attack.mitre.org/wiki/Technique/T1031 + + +## Vulnerability + +* [Apache Struts Vulnerability](#Apache-Struts-Vulnerability) + +* [JBoss Vulnerability](#JBoss-Vulnerability) + +* [Spectre And Meltdown Vulnerabilities](#Spectre-And-Meltdown-Vulnerabilities) + +* [Splunk Enterprise Vulnerability](#Splunk-Enterprise-Vulnerability) + +* [Splunk Enterprise Vulnerability CVE-2018-11409](#Splunk-Enterprise-Vulnerability-CVE-2018-11409) + +### Apache Struts Vulnerability +* id = 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e +* date = 2018-12-06 +* version = 1 + +#### Description +Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. + +#### Narrative +In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ +The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ +This Analytic Story contains two different searches that help to identify activity that may be related to this issue. The first search looks for characteristics of the `Content-Type` header consistent with attempts to exploit the vulnerability. This should be a relatively pertinent indicator, as the `Content-Type` header is generally consistent and does not have a large degree of variation.\ +The second search looks for the execution of various commands typically entered on the command shell when an attacker first lands on a system. These commands are not generally executed on web servers during the course of day-to-day operation, but they may be used when the system is undergoing maintenance or troubleshooting.\ +First, it is helpful is to understand how often the notable event is generated, as well as the commonalities in some of these events. This may help determine whether this is a common occurrence that is of a lesser concern or a rare event that may require more extensive investigation. It can also help to understand whether the issue is restricted to a single user or system or is broader in scope.\ +hen looking at the target of the behavior illustrated by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to see what other events involving the target have occurred in the recent past. This can help tie different events together and give further situational awareness regarding the target.\ +Various types of information for external systems should be reviewed and (potentially) collected if the incident is, indeed, judged to be malicious. Information like this can be useful in generating your own threat intelligence to create alerts in the future.\ +Looking at the country, responsible party, and fully qualified domain names associated with the external IP address--as well as the registration information associated with those domain names, if they are frequently visited by others--can help you answer the question of "who," in regard to the external system. Answering that can help qualify the event and may serve useful for tracking. In addition, there are various sources that can provide some reputation information on the IP address or domain name, which can assist in determining if the event is malicious in nature. Finally, determining whether or not there are other events associated with the IP address may help connect some dots or show other events that should be brought into scope.\ +Gathering various data elements on the system of interest can sometimes help quickly determine that something suspicious may be happening. Some of these items include determining who else may have recently logged into the system, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ +hen a specific service or application is targeted, it is often helpful to know the associated version to help determine whether or not it is vulnerable to a specific exploit.\ +hen it is suspected there is an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ +In the event that a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that have the file open, what processes created and/or modified the file, and the number of systems that may have this file can help to determine if the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes quickly help determine whether it is malicious in nature.\ +Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if `svchost.exe` is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. Similarly, if the process itself seems legitimate, but the parent process is running from the temporary browser cache, there may be activity initiated via a compromised website the user visited.\ +It can also be very helpful to examine various behaviors of the process of interest or the parent of the process that is of interest. For example, if it turns out that the process of interest is malicious, it would be good to see if the parent to that process spawned other processes that might also be worth further scrutiny. If a process is suspect, reviewing the network connections made around the time of the event and/or if the process spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. + +#### Detections +* Suspicious Java Classes +* Unusually Long Content-Type Length +* Web Servers Executing Suspicious Processes + +#### Data Models +* Endpoint + +#### Mappings + +##### ATT&CK +* T1082 + +##### Kill Chain Phases +* Actions on Objectives +* Delivery +* Exploitation + +###### CIS +* CIS 12 +* CIS 18 +* CIS 3 +* CIS 4 + +##### NIST +* DE.AE +* DE.CM +* ID.RA +* PR.IP +* PR.MA +* PR.PT +* RS.MI + +##### References +* https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf + +### JBoss Vulnerability +* id = 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd +* date = 2017-09-14 +* version = 1 + +#### Description +In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. + +#### Narrative +This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ +It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ +hen looking at the target of the behavior uncovered by the event, you should note the sensitivity of the user and or/system to help determine the potential impact. It is also helpful to identify other recent events involving the target. This can help tie different events together and give further situational awareness regarding the target host.\ +Various types of information for external systems should be reviewed and, potentially, collected if the incident is, indeed, judged to be malicious. This data may be useful for generating your own threat intelligence, so you can create future alerts.\ +The following factors may assist you in determining whether the event is malicious: \ +1. Country of origin\ +1. Responsible party\ +1. Fully qualified domain names associated with the external IP address\ +1. Registration of fully qualified domain names associated with external IP address Determining whether it is a dynamic domain frequently visited by others and/or how third parties categorize it can also help you qualify and understand the event and possible motivation for the attack. In addition, there are various sources that may provide reputation information on the IP address or domain name, which can assist you in determining whether the event is malicious in nature. Finally, determining whether there are other events associated with the IP address may help connect data points or expose other historic events that might be brought back into scope.\ +Gathering various data on the system of interest can sometimes help quickly determine whether something suspicious is happening. Some of these items include determining who else may have logged into the system recently, whether any unusual scheduled tasks exist, whether the system is communicating on suspicious ports, whether there are modifications to sensitive registry keys, and/or whether there are any known vulnerabilities on the system. This information can often highlight other activity commonly seen in attack scenarios or give more information about how the system may have been targeted.\ +hen a specific service or application is targeted, it is often helpful to know the associated version, to help determine whether it is vulnerable to a specific exploit.\ +If you suspect an attack targeting a web server, it is helpful to look at some of the behavior of the web service to see if there is evidence that the service has been compromised. Some indications of this might be network connections to external resources, the web service spawning child processes that are not associated with typical behavior, and whether the service wrote any files that might be malicious in nature.\ +If a suspicious file is found, we can review more information about it to help determine if it is, in fact, malicious. Identifying the file type, any processes that opened the file, the processes that may have created and/or modified the file, and how many other systems potentially have this file can you determine whether the file is malicious. Also, determining the file hash and checking it against reputation sources, such as VirusTotal, can sometimes help you quickly determine if it is malicious in nature.\ +Often, a simple inspection of a suspect process name and path can tell you if the system has been compromised. For example, if svchost.exe is found running from a location other than `C:\Windows\System32`, it is likely something malicious designed to hide in plain sight when simply reviewing process names. \ +It can also be helpful to examine various behaviors of and the parent of the process of interest. For example, if it turns out the process of interest is malicious, it would be good to see whether the parent process spawned other processes that might also warrant further scrutiny. If a process is suspect, a review of the network connections made around the time of the event and noting whether the process has spawned any child processes could be helpful in determining whether it is malicious or executing a malicious script. + +#### Detections +* Detect attackers scanning for vulnerable JBoss servers +* Detect malicious requests to exploit JBoss servers + +#### Data Models +* Web + +#### Mappings + +##### ATT&CK +* T1082 + +##### Kill Chain Phases +* Delivery +* Reconnaissance + +###### CIS +* CIS 18 + +##### NIST +* DE.CM + +##### References +* http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html + +### Spectre And Meltdown Vulnerabilities +* id = 6d3306f6-bb2b-4219-8609-8efad64032f2 +* date = 2018-01-08 +* version = 1 + +#### Description +Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. + +#### Narrative +Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. + +#### Detections +* Spectre and Meltdown Vulnerable Systems + +#### Data Models +* Vulnerabilities + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases + +###### CIS +* CIS 4 + +##### NIST +* DE.CM + +##### References +* https://meltdownattack.com/ + +### Splunk Enterprise Vulnerability +* id = 4e692b96-de2d-4bd1-9105-37e2368a8db1 +* date = 2017-09-19 +* version = 1 + +#### Description +Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. + +#### Narrative +This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ +\ +1. Splunk Enterprise 6.4.x, prior to 6.4.3\ +1. Splunk Enterprise 6.3.x, prior to 6.3.6\ +1. Splunk Enterprise 6.2.x, prior to 6.2.10\ +1. Splunk Enterprise 6.1.x, prior to 6.1.11\ +1. Splunk Enterprise 6.0.x, prior to 6.0.12\ +1. Splunk Enterprise 5.0.x, prior to 5.0.16\ +1. Splunk Light, prior to 6.4.3CVE-2016-4859 allows attackers to redirect users to arbitrary web sites and conduct phishing attacks via unspecified vectors. (Credit: Noriaki Iwasaki, Cyber Defense Institute, Inc.).\ +It is important to ensure that your Splunk deployment is being kept up to date and is properly configured. This detection search allows analysts to monitor internal logs to ensure users are properly authenticated and cannot be redirected to any malicious third-party websites. + +#### Detections +* Open Redirect in Splunk Web + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Delivery + +###### CIS +* CIS 18 + +##### NIST +* DE.CM + +##### References +* http://www.splunk.com/view/SP-CAAAPQ6#announce +* https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859 + +### Splunk Enterprise Vulnerability CVE-2018-11409 +* id = 1fc34cbc-34e9-43ba-87ab-6811c9e95400 +* date = 2018-06-14 +* version = 1 + +#### Description +Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. + +#### Narrative +Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ +Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ +Read more in Splunk's official response: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings.\ +A detection search within this Analytic Story looks for vulnerabilities described in CVE-2018-11409: Information Exposure (https://nvd.nist.gov/vuln/detail/CVE-2018-11409). If it turns up activities that may be specific, you can use the included investigative searches to return information regarding web activity and network traffic by src_ip. + +#### Detections +* Splunk Enterprise Information Disclosure + +#### Data Models + +#### Mappings + +##### ATT&CK + +##### Kill Chain Phases +* Delivery + +###### CIS +* CIS 18 + +##### NIST +* DE.CM + +##### References +* https://nvd.nist.gov/vuln/detail/CVE-2018-11409 +* https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings +* https://www.exploit-db.com/exploits/44865/ + + From d0c8956368a80090702ba68b2a49803679f7730d Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 7 May 2020 20:08:36 +0200 Subject: [PATCH 18/93] new generate script --- README.md | 137 +----------------------------------------------------- 1 file changed, 1 insertion(+), 136 deletions(-) diff --git a/README.md b/README.md index 535019e29f..d5ae5b7ada 100644 --- a/README.md +++ b/README.md @@ -1,136 +1 @@ -# Splunk Security Content -![security-content](docs/static/logo.png) -===== - -| branch | build status | -| --- | --- | -| develop| [![develop status](https://circleci.com/gh/splunk/security-content/tree/develop.svg?style=svg&circle-token=67ad1fa7779c57d7e5bcfc42bd617baf607ec269)](https://circleci.com/gh/splunk/security-content/tree/develop)| -| master | [![master status](https://circleci.com/gh/splunk/security-content/tree/master.svg?style=svg&circle-token=67ad1fa7779c57d7e5bcfc42bd617baf607ec269)](https://circleci.com/gh/splunk/security-content/tree/master)| - -Welcome to the Splunk Security Research Team's Security Content Exchange! - -This project gives you access to our repository of Analytic Stories--themed security guides that contain that provide background on TTPs, mapped to the MITRE framework, the Lockheed Martin Kill Chain, and CIS controls. They include Splunk searches, machine-learning algorithms, and Splunk Phantom playbooks (where available)—all designed to work together to detect, investigate, and respond to threats. - -While this content is available via Splunk Enterprise Security and Enterprise Security Content Updates (https://splunkbase.splunk.com/app/3449/), we have now made it available as an open-source project (which you just found--hi!). The Security Research Content Exchange was designed to bring the community together to improve our collective defenses. By sharing research and analytics, we can help the entire industry craft more effective strategies. This project provides a mechanism to facilitate this exchange. - - -# Usage -The Splunk Security Content Exchange can be used via: - -#### [Splunk App](https://github.com/splunk/security-content/releases) -Grab the latest release of DA-ESS-ContentUpdate and install it on a Splunk Enterprise server (search head). - -#### [API](https://docs.splunkresearch.com/?version=latest) -``` -curl -s https://content.splunkresearch.com | jq -{ - "hello": "welcome to Splunks Research security content api", - "available_endpoints": [ - "/stories", - "/detections", - "/investigations", - "/baselines", - "/responses", - "/package" - ] -} -``` -# How to Get Started - -While you you can configure each detection individually, the real power lies in running the Analytic Stories end-to-end. Using the Analytic Story Execution (ASX) app (https://github.com/splunk/analytic_story_execution), you can funnel the results to investigations, reducing the need for manual intervention. When available, you can automatically trigger reponses, as well. The alerts you'll get include context (history, correlations, etc.), so they help you better understand their importance. The net effect is a more efficient workflow, as well as more comprehensive, effective defenses. - -Follow the instructions below to get started. - -# What's in an Analytic Story? -[Analytic Stories](https://github.com/splunk/security-content/blob/develop/docs/stories_categories.md) and their corresponding searches are composed of **.yml** files (manifests) and associated .conf files. The stories reside in [/stories](https://github.com/splunk/security-content/tree/develop/stories) and the searches live in [/detections](https://github.com/splunk/security-content/tree/develop/detections). - -Manifests contain a number of mandatory and optional fields. You can see the full field list for each piece of content [here](https://github.com/splunk/security-content/tree/develop/docs#spec-documentation). - -# Customize to your Environment - -After release [1.0.46](https://github.com/splunk/security-content/releases) we introduced a concept of input(pre-filter) and output(post-filter) macros for each of our detection search. The intention behind introducing these macros is primarily to help our users to update the macro definition “once” and those changes will be applicable across all detections that leverage that macro and local to your Splunk Environment. - -**input(pre-filter):** This macro is to specify your environment-specific configurations (index, source, sourcetype, etc.) to get the specific data sources that you would like to bring in. Replace the macro definition with configurations for your Splunk environment. - -**output(post-filter):** This macro is to specify your environment-specific values (eg: dest, user), to filter out known false positives.. Replace the macro definition with values that you’d like to exclude from detection results. Think of this as a whitelisting/blacklisting using macros. - -Note: we are currently working on coming up with a better naming convention and making this consistent across all our detections, investigations and baselines. Suggestions are welcomed :stuck_out_tongue: - -# Writing Content -Before you begin, follow the steps to install **dependencies and pre-commit hooks** under ["Developing"](https://github.com/splunk/security-content#developing). - -1. Select the content [piece](https://github.com/splunk/security-content#content-parts) you want to write. -2. Copy an example and edit it to suit your needs. At a minimum, you must write a [story](stories/), [a detection search](detections/), and an [investigative search](investigations/). -3. Make a pull request. The pull request will trigger CircleCI, a continuous-integration app thatintegrates with a VCS and automatically runs a series of steps every time that it detects a change to your repository. A CircleCI build consists of a series of steps, usually Dependencies, Testing, and Deployment. If your tests pass, you're good to go! If the CircleCI check fails, refer to [troubleshooting](https://github.com/splunk/security-content#troubleshooting). - -For a more detailed explanation on how to contribute to the project, please see ["Contributing"](#Contributing) - -# Security Content Layout -![](docs/static/structure.png) - -#### Content Parts -* [stories/](stories/): All Analytic Stories -* [detections/](detections/): Splunk Enterprise, Splunk UBA, and Splunk Phantom detections that power Analytic Stories -* [investigations/](investigations/): Splunk Enterprise and Splunk Phantom investigative searches and playbooks employed by Analytic Stories -* [responses/](responses/): Automated Splunk Enterprise and Splunk Phantom responses triggered by Analytic Stories -* [baselines/](baselines/): Splunk Phantom and Splunk Enterprise baseline searches needed to support detection searches in Analytic Stories - -#### Supporting Parts -* [package/](package/): Splunk content app-source files, including lookups, binaries, and default config files -* [bin/](bin/): All binaries required to produce and test content - -# Docs -* [docs/](docs/): Documentation for all spec files -* [spec/](spec/): All spec files that describe the security content - -# Developing -##### Dependecies and Pre-Commit Hooks -Install project dependecies and tests that run before content is committed: - -1. Create virtualenv and install requirements: `virtualenv venv && source venv/bin/activate && pip install -r requirements.txt`. -2. Install `pre-commit install`. - -##### CI Tools -Tools that help with testing CI jobs: - -1. Install CircleCI [CLI Tool](https://circleci.com/docs/2.0/local-cli/). -2. To test a local change to CircleCI or build, make sure you are running Docker, then enter -`circleci local execute -e GITHUB_TOKEN=$GITHUB_TOKEN --branch `. - -##### Generate Docs from Schema -To automatically generate docs from schema: - -1. Install https://github.com/adobe/jsonschema2md. -2. Enter `jsonschema2md -d spec/v2/detections.spec.json -o docs`. - -# Troubleshooting - -### Our Automated Tests -1. [CI](https://github.com/splunk/security-content/blob/44946063173f7bc9921f0da0aa62139c084d1c51/.circleci/config.yml#L27) validates that the content was written to spec using [`validate.py`](https://github.com/splunk/security-content/blob/runstory/bin/generate.py). To run validation manually, run: `python bin/validate.py --path . --verbose`. -2. [CI](https://github.com/splunk/security-content/blob/44946063173f7bc9921f0da0aa62139c084d1c51/.circleci/config.yml#L60) generates Splunk configuration files using [`generate.py`](https://github.com/splunk/security-content/blob/develop/bin/generate.py). If you want to export Splunk .conf files manually from the content, run `python bin/generate.py --path . --output package --verbose`. -3. [CI](https://github.com/splunk/security-content/blob/44946063173f7bc9921f0da0aa62139c084d1c51/.circleci/config.yml#L107) builds a DA-ESS-ContentUpdate Splunk package using the [Splunk Packaging Toolkit](http://dev.splunk.com/view/packaging-toolkit/SP-CAAAE9V). -4. [CI](https://github.com/splunk/security-content/blob/44946063173f7bc9921f0da0aa62139c084d1c51/.circleci/config.yml#L145) tests the newly produced package using [Splunk Appinspect](http://dev.splunk.com/view/appinspect/SP-CAAAE9U). - -* note that [requirements.txt](https://github.com/splunk/security-content/blob/develop/requirements.txt) hard codes the versions for packages we use [dependabot](https://dependabot.com/) to make sure we safely always upgrade to the latest versions. - -## Customize to Your Environment -Release 1.0.46 introduced input(pre-filter) and output(post-filter) macros for each of our detection searches. These macros let you update a macro definition once and then apply the new definition across all detections that leverage that macro. These changes will be local to your Splunk environment. - -input(pre-filter): This macro specifies your environment-specific configurations (index, source, sourcetype, etc.) to get the specific data sources that you require. Replace the macro definition with configurations for your Splunk environment. -output(post-filter): This macro specifies your environment-specific values (dest, user, etc,), to filter out known false positives. Replace the macro definition with values that you'd like to exclude from detection results. Think of this as whitelisting/blacklisting using macros. -Note: Coming soon is an improved naming convention that will be consistent across all of our detections, investigations, and baselines. - -## Support -Please use the [GitHub Issue Tracker](https://github.com/splunk/security-content/issues) to submit bugs or request features. - -If you have questions or need support, you can: - -* Post a question to [Splunk Answers](http://answers.splunk.com) -* Join the [#security-research](https://splunk-usergroups.slack.com/messages/C1RH09ERM/) room in the [Splunk Slack channel](http://splunk-usergroups.slack.com) -* If you are a Splunk Enterprise customer with a valid support entitlement contract and have a Splunk-related question, you can also open a support case on the https://www.splunk.com/ support portal - -## Contributing -We welcome feedback and contributions from the community! Please see our [contribution guidelines](docs/CONTRIBUTING.md) for more information on how to get involved. - -# To Dos -* Build CLI for interacting and developing +new version of the README needs to be done From 76f94e5bb38ed2a1adac511feb74e2bbe6363b38 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 7 May 2020 20:18:14 +0200 Subject: [PATCH 19/93] new generate script --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index d5ae5b7ada..30a7160243 100644 --- a/README.md +++ b/README.md @@ -1 +1 @@ -new version of the README needs to be done +new version of the README needs to be done. From 2e15e6a9ba84f8c9d0e4b4df98d3ca92cf667988 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 7 May 2020 20:27:17 +0200 Subject: [PATCH 20/93] new generate script --- package/default/analytic_stories.conf | 90 +++++++++++++-------------- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 90 +++++++++++++-------------- 5 files changed, 93 insertions(+), 93 deletions(-) diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 685be01a88..5c6b2f132b 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-06T14:58:49 UTC +# On Date: 2020-05-07T18:22:26 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -31,7 +31,7 @@ modification_date = 2018-03-08 id = ced74200-8465-4bc3-bd2c-9a782eec6750 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started In Previously Unseen Region"] +detection_searches = ["EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "EC2 Instance Started With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User"] mappings = {"analytics_story": "AWS Cryptomining", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -49,7 +49,7 @@ modification_date = 2018-05-21 id = 2e8948a5-5239-406b-b56b-6c50ff268af4 version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] -detection_searches = ["AWS Network Access Control List Deleted", "Detect Spike in blocked Outbound Traffic from your AWS", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in Network ACL Activity"] +detection_searches = ["AWS Network Access Control List Deleted", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity"] mappings = {"analytics_story": "AWS Network ACL Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -80,7 +80,7 @@ modification_date = 2018-03-12 id = 2e8948a5-5239-406b-b56b-6c50f1269af3 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] -detection_searches = ["Detect new API calls from user roles", "Detect Spike in Security Group Activity", "Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts"] +detection_searches = ["Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] mappings = {"analytics_story": "AWS User Monitoring", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -98,7 +98,7 @@ modification_date = 2017-09-06 id = 8892a655-6205-55f7-abba-06460e38c8ae version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] -detection_searches = ["Short Lived Windows Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint", "Identify New User Accounts"] +detection_searches = ["Short Lived Windows Accounts", "Identify New User Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint"] mappings = {"analytics_story": "Account Monitoring and Controls", "category": ["Best Practices"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -156,7 +156,7 @@ modification_date = 2017-12-19 id = 91c676cf-0b23-438d-abee-f6335e1fce78 version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] -detection_searches = ["Monitor Web Traffic For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse"] +detection_searches = ["Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse"] mappings = {"analytics_story": "Brand Monitoring", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -173,7 +173,7 @@ modification_date = 2019-10-02 id = 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] +detection_searches = ["Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] mappings = {"analytics_story": "Cloud Cryptomining", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -208,7 +208,7 @@ modification_date = 2020-02-03 id = 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] -detection_searches = ["Email files written outside of the Outlook directory", "Suspicious writes to windows Recycle Bin", "Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server"] +detection_searches = ["Hosts receiving high volume of network traffic from email server", "Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] mappings = {"analytics_story": "Collection and Staging", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -225,7 +225,7 @@ modification_date = 2018-06-01 id = 943773c6-c4de-4f38-89a8-0b92f98804d8 version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Long DNS TXT Record Response", "DNS Query Length Outliers - MLTK", "TOR Traffic", "Protocol or Port Mismatch", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Large Outbound ICMP Packets", "Prohibited Network Traffic Allowed", "Excessive DNS Failures"] +detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Clients Connecting to Multiple DNS Servers", "TOR Traffic", "Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Protocol or Port Mismatch", "Detect Large Outbound ICMP Packets"] mappings = {"analytics_story": "Command and Control", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -257,7 +257,7 @@ modification_date = 2020-02-20 id = aa0e28b1-0521-4b6f-9d2a-7b87e34af246 version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] +detection_searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded"] mappings = {"analytics_story": "Container Implantation Monitoring and Investigation", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -272,7 +272,7 @@ modification_date = 2020-02-04 id = 854d78bf-d0e2-4f4e-b05c-640905f86d7a version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] -detection_searches = ["Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Detect Credential Dumping through LSASS access", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Access LSASS Memory for Dump Creation", "Create Remote Thread into LSASS", "Detect Mimikatz Using Loaded Images"] +detection_searches = ["Credential Dumping via Copy Command from Shadow Copy", "Access LSASS Memory for Dump Creation", "Detect Mimikatz Using Loaded Images", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Detect Credential Dumping through LSASS access", "Creation of Shadow Copy with wmic and powershell", "Unsigned Image Loaded by LSASS", "Create Remote Thread into LSASS", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Creation of Shadow Copy", "Credential Dumping via Symlink to Shadow Copy"] mappings = {"analytics_story": "Credential Dumping", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -289,7 +289,7 @@ modification_date = 2020-01-22 id = 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] -detection_searches = ["SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Processes launching netsh", "Registry Keys Used For Persistence", "Detect Outbound SMB Traffic", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Detect New Local Admin account", "Single Letter Process On Endpoint", "Detect PsExec With accepteula Flag", "Create local admin accounts using net exe", "First time seen command line argument", "Scheduled Task Name Used by Dragonfly Threat Actors", "Malicious PowerShell Process - Execution Policy Bypass"] +detection_searches = ["Processes launching netsh", "Suspicious Reg exe Process", "First time seen command line argument", "Detect PsExec With accepteula Flag", "Sc exe Manipulating Windows Services", "Detect New Local Admin account", "Single Letter Process On Endpoint", "SMB Traffic Spike - MLTK", "Create local admin accounts using net exe", "Registry Keys Used For Persistence", "Scheduled Task Name Used by Dragonfly Threat Actors", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Malicious PowerShell Process - Execution Policy Bypass"] mappings = {"analytics_story": "DHS Report TA18-074A", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -323,7 +323,7 @@ modification_date = 2020-02-04 id = 8169f17b-ef68-4b59-aa28-586907301221 version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "DNS record changed"] +detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS record changed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect hosts connecting to dynamic domain providers"] mappings = {"analytics_story": "DNS Hijacking", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -346,7 +346,7 @@ modification_date = 2017-09-14 id = 91c676cf-0b23-438d-abee-f6335e1fce33 version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Detection of DNS Tunnels"] +detection_searches = ["Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Detect USB device insertion"] mappings = {"analytics_story": "Data Protection", "category": ["Abuse"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -361,7 +361,7 @@ modification_date = 2020-02-04 id = fcc27099-46a0-46b0-a271-5c7dab56b6f1 version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] -detection_searches = ["Unload Sysmon Filter Driver", "Processes launching netsh", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service"] +detection_searches = ["Processes launching netsh", "Attempt To Add Certificate To Untrusted Store", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Unload Sysmon Filter Driver", "Attempt To Stop Security Service"] mappings = {"analytics_story": "Disabling Security Tools", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -376,7 +376,7 @@ modification_date = 2018-09-06 id = 8169f17b-ef68-4b59-aae8-586907301221 version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] +detection_searches = ["Detect web traffic to dynamic domain providers", "Detect hosts connecting to dynamic domain providers"] mappings = {"analytics_story": "Dynamic DNS", "category": ["Malware"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -391,7 +391,7 @@ modification_date = 2020-01-27 id = bb9f5ed2-916e-4364-bb6d-91c310efcf52 version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] -detection_searches = ["Prohibited Software On Endpoint", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Registry Keys Used For Persistence", "Detection of tools built by NirSoft", "Suspicious Email Attachment Extensions", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Rare Executables", "Email Attachments With Lots Of Spaces"] +detection_searches = ["Detection of tools built by NirSoft", "Detect Rare Executables", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions", "Registry Keys Used For Persistence", "Prohibited Software On Endpoint", "Detect Use of cmd exe to Launch Script Interpreters", "SMB Traffic Spike"] mappings = {"analytics_story": "Emotet Malware DHS Report TA18-201A ", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -408,7 +408,7 @@ modification_date = 2020-01-22 id = baf7580b-d4b4-4774-8173-7d198e9da335 version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] -detection_searches = ["Create or delete windows shares using net exe", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Remote Desktop Network Traffic", "Detect Outbound SMB Traffic", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "First time seen command line argument", "Remote Desktop Process Running On System", "Suspicious File Write"] +detection_searches = ["First time seen command line argument", "Remote Desktop Network Traffic", "Create or delete windows shares using net exe", "DNS Query Length With High Standard Deviation", "Suspicious File Write", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "DNS Query Length Outliers - MLTK", "Remote Desktop Process Running On System", "Detect Outbound SMB Traffic"] mappings = {"analytics_story": "Hidden Cobra Malware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -426,7 +426,7 @@ modification_date = 2017-09-14 id = 2e8948a5-5239-406b-b56b-6c50fe268af4 version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] -detection_searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Windows hosts file modification"] +detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] mappings = {"analytics_story": "Host Redirection", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -470,7 +470,7 @@ modification_date = 2020-04-15 id = a9ef59cf-e981-4e66-9eef-bb049f695c09 version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] +detection_searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection"] mappings = {"analytics_story": "Kubernetes Scanning Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -485,7 +485,7 @@ modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] -detection_searches = ["Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks", "Schtasks scheduling job on remote system", "Remote Desktop Process Running On System"] +detection_searches = ["Schtasks scheduling job on remote system", "Remote Desktop Process Running On System", "Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks"] mappings = {"analytics_story": "Lateral Movement", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -576,7 +576,7 @@ modification_date = 2017-01-05 id = 2b1800dd-92f9-47ec-a981-fdf1351e5f65 version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] -detection_searches = ["Processes created by netsh", "Processes launching netsh"] +detection_searches = ["Processes launching netsh", "Processes created by netsh"] mappings = {"analytics_story": "Netsh Abuse", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -592,7 +592,7 @@ modification_date = 2020-01-22 id = bb9f5ed2-916e-4364-bb6d-97c370efcf52 version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] -detection_searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "First time seen command line argument"] +detection_searches = ["First time seen command line argument", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] mappings = {"analytics_story": "Orangeworm Attack Group", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -633,7 +633,7 @@ modification_date = 2020-01-22 id = 988C59C5-0A1C-45B6-A555-0C62276E327E version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] -detection_searches = ["Registry Keys Used For Persistence", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] +detection_searches = ["First time seen command line argument", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] mappings = {"analytics_story": "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -675,7 +675,7 @@ modification_date = 2017-09-11 id = 6d13121c-90f3-446d-8ac3-27efbbc65218 version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch"] +detection_searches = ["Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch", "Detect hosts connecting to dynamic domain providers"] mappings = {"analytics_story": "Prohibited Traffic Allowed or Protocol Mismatch", "category": ["Best Practices"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -690,7 +690,7 @@ modification_date = 2020-02-04 id = cf309d0d-d4aa-4fbb-963d-1e79febd3756 version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] -detection_searches = ["Scheduled tasks used in BadRabbit ransomware", "Suspicious wevtutil Usage", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Registry Keys Used For Persistence", "Common Ransomware Notes", "Remote Process Instantiation via WMI", "USN Journal Deletion", "Common Ransomware Extensions", "System Processes Run From Unexpected Locations", "TOR Traffic", "Schtasks used for forcing a reboot", "Spike in File Writes", "Unusually Long Command Line", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Unusually Long Command Line - MLTK"] +detection_searches = ["Scheduled tasks used in BadRabbit ransomware", "TOR Traffic", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "Common Ransomware Notes", "Suspicious wevtutil Usage", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Common Ransomware Extensions", "Spike in File Writes", "SMB Traffic Spike", "Schtasks used for forcing a reboot", "USN Journal Deletion", "Remote Process Instantiation via WMI", "System Processes Run From Unexpected Locations"] mappings = {"analytics_story": "Ransomware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -737,7 +737,7 @@ modification_date = 2018-12-13 id = c4b89506-fbcf-4cb7-bfd6-527e54789604 version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] -detection_searches = ["Detect malicious requests to exploit JBoss servers", "Prohibited Software On Endpoint", "Common Ransomware Notes", "Remote Desktop Network Traffic", "Common Ransomware Extensions", "Batch File Write to System32", "Spike in File Writes", "Samsam Test File Write", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Bruteforce", "File with Samsam Extension"] +detection_searches = ["File with Samsam Extension", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Batch File Write to System32", "Samsam Test File Write", "Common Ransomware Notes", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Extensions", "Detect attackers scanning for vulnerable JBoss servers", "Prohibited Software On Endpoint", "Spike in File Writes"] mappings = {"analytics_story": "SamSam Ransomware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -814,7 +814,7 @@ modification_date = 2018-02-09 id = 2e8948a5-5239-406b-b56b-6c50f1268af3 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region"] +detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User"] mappings = {"analytics_story": "Suspicious AWS EC2 Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -829,7 +829,7 @@ modification_date = 2019-05-01 id = 2e8948a5-5239-406b-b56b-6c59f1268af3 version = 1 reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] -detection_searches = ["Detect new user AWS Console Login", "Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New Country"] +detection_searches = ["Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New City"] mappings = {"analytics_story": "Suspicious AWS Login Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -844,7 +844,7 @@ modification_date = 2018-07-24 id = 2e8948a5-5239-406b-b56b-6c50w3168af3 version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] -detection_searches = ["Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets", "Detect S3 access from a new IP"] +detection_searches = ["Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets"] mappings = {"analytics_story": "Suspicious AWS S3 Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -879,7 +879,7 @@ modification_date = 2020-02-03 id = f4368ddf-d59f-4192-84f6-778ac5a3ffc7 version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] -detection_searches = ["System Processes Run From Unexpected Locations", "Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK"] +detection_searches = ["First time seen command line argument", "Detect Prohibited Applications Spawning cmd exe", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "System Processes Run From Unexpected Locations"] mappings = {"analytics_story": "Suspicious Command-Line Executions", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -894,7 +894,7 @@ modification_date = 2017-09-18 id = 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Excessive DNS Failures"] +detection_searches = ["Clients Connecting to Multiple DNS Servers", "Detect hosts connecting to dynamic domain providers", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response"] mappings = {"analytics_story": "Suspicious DNS Traffic", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -909,7 +909,7 @@ modification_date = 2020-01-27 id = 2b1800dd-92f9-47ec-a981-fdf1351e5d55 version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] -detection_searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions"] +detection_searches = ["Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions", "Email Attachments With Lots Of Spaces"] mappings = {"analytics_story": "Suspicious Emails", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -928,7 +928,7 @@ modification_date = 2020-02-03 id = 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] -detection_searches = ["Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments"] +detection_searches = ["Registry Keys Used For Persistence", "Detect mshta exe running scripts in command-line arguments", "Detect Prohibited Applications Spawning cmd exe"] mappings = {"analytics_story": "Suspicious MSHTA Activity", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -945,7 +945,7 @@ modification_date = 2020-04-02 id = 9cbd34af-8f39-4476-a423-bacd126c750b version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] -detection_searches = ["Okta Account Lockout Events", "Okta Failed SSO Attempts", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta User Logins From Multiple Cities"] +detection_searches = ["Okta User Logins From Multiple Cities", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts"] mappings = {"analytics_story": "Suspicious Okta Activity", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -962,7 +962,7 @@ modification_date = 2018-10-23 id = c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] -detection_searches = ["WMI Permanent Event Subscription", "Remote Process Instantiation via WMI", "WMI Temporary Event Subscription", "Process Execution via WMI", "WMI Permanent Event Subscription - Sysmon", "Script Execution via WMI", "Remote WMI Command Attempt"] +detection_searches = ["Script Execution via WMI", "WMI Permanent Event Subscription", "Remote WMI Command Attempt", "WMI Temporary Event Subscription", "Remote Process Instantiation via WMI", "WMI Permanent Event Subscription - Sysmon", "Process Execution via WMI"] mappings = {"analytics_story": "Suspicious WMI Use", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -979,7 +979,7 @@ modification_date = 2018-05-31 id = 2b1800dd-92f9-47dd-a981-fdf1351e5d55 version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] -detection_searches = ["Monitor Registry Keys for Print Monitors", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Suspicious Changes to File Associations"] +detection_searches = ["Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Suspicious Changes to File Associations", "Disabling Remote User Account Control", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Privilege Escalation", "Remote Registry Key modifications"] mappings = {"analytics_story": "Suspicious Windows Registry Activities", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -1012,7 +1012,7 @@ modification_date = 2020-02-04 id = f4368e3f-d59f-4192-84f6-748ac5a3ddb6 version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] -detection_searches = ["Uncommon Processes On Endpoint", "System Processes Run From Unexpected Locations", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Detect Rare Executables", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal"] +detection_searches = ["Uncommon Processes On Endpoint", "Detect Rare Executables", "RunDLL Loading DLL By Ordinal", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect processes used for System Network Configuration Discovery", "System Processes Run From Unexpected Locations"] mappings = {"analytics_story": "Unusual Processes", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -1044,7 +1044,7 @@ modification_date = 2018-10-08 id = 31337aaa-bc22-4752-b599-ef112dq1dq7a version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] -detection_searches = ["Web Fraud - Account Harvesting", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed"] +detection_searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Account Harvesting"] mappings = {"analytics_story": "Web Fraud Detection", "category": ["Abuse"], "usecase": "Fraud Detection"} support_searches = none data_models = none @@ -1064,7 +1064,7 @@ modification_date = 2018-05-31 id = 56e24a28-5003-4047-b2db-e8f3c4618064 version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] -detection_searches = ["Remote Registry Key modifications", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Suspicious Reg exe Process", "Hiding Files And Directories With Attrib exe"] +detection_searches = ["Suspicious Reg exe Process", "Reg exe used to hide files directories via registry keys", "Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications"] mappings = {"analytics_story": "Windows Defense Evasion Tactics", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -1079,7 +1079,7 @@ modification_date = 2018-01-26 id = 30552a76-ac78-48e4-b3c0-de4e34e9563d version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] -detection_searches = ["Execution of File with Multiple Extensions", "Suspicious Changes to File Associations", "Execution of File With Spaces Before Extension"] +detection_searches = ["Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Suspicious Changes to File Associations"] mappings = {"analytics_story": "Windows File Extension and Association Abuse", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -1098,7 +1098,7 @@ modification_date = 2017-09-12 id = b6db2c60-a281-48b4-95f1-2cd99ed56835 version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] -detection_searches = ["Suspicious wevtutil Usage", "Windows Event Log Cleared", "USN Journal Deletion", "Deleting Shadow Copies"] +detection_searches = ["Windows Event Log Cleared", "USN Journal Deletion", "Suspicious wevtutil Usage", "Deleting Shadow Copies"] mappings = {"analytics_story": "Windows Log Manipulation", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} support_searches = none data_models = none @@ -1114,7 +1114,7 @@ modification_date = 2018-05-31 id = 30874d4f-20a1-488f-85ec-5d52ef74e3f9 version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] -detection_searches = ["Monitor Registry Keys for Print Monitors", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters", "Reg exe used to hide files directories via registry keys", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Detect Path Interception By Creation Of program exe", "Reg exe Manipulating Windows Services Registry Keys"] +detection_searches = ["Detect Path Interception By Creation Of program exe", "Shim Database File Creation", "Monitor Registry Keys for Print Monitors", "Sc exe Manipulating Windows Services", "Reg exe used to hide files directories via registry keys", "Reg exe Manipulating Windows Services Registry Keys", "Registry Keys Used For Persistence", "Shim Database Installation With Suspicious Parameters", "Hiding Files And Directories With Attrib exe", "Registry Keys for Creating SHIM Databases", "Schtasks used for forcing a reboot", "Remote Registry Key modifications"] mappings = {"analytics_story": "Windows Persistence Techniques", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -1129,7 +1129,7 @@ modification_date = 2020-02-04 id = 644e22d3-598a-429c-a007-16fdb802cae5 version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] -detection_searches = ["Child Processes of Spoolsv exe", "Registry Keys Used For Privilege Escalation", "Overwriting Accessibility Binaries", "Uncommon Processes On Endpoint"] +detection_searches = ["Uncommon Processes On Endpoint", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation"] mappings = {"analytics_story": "Windows Privilege Escalation", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none @@ -1144,7 +1144,7 @@ modification_date = 2017-11-02 id = 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] -detection_searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys"] +detection_searches = ["Reg exe Manipulating Windows Services Registry Keys", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] mappings = {"analytics_story": "Windows Service Abuse", "category": ["Malware"], "usecase": "Advanced Threat Detection"} support_searches = none data_models = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 1dae9053d7..60003c64bc 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-06T14:58:49 UTC +# On Date: 2020-05-07T18:22:26 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 12833ea6d5..8b8e3807a4 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-06T14:58:49 UTC +# On Date: 2020-05-07T18:22:26 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 2e2a9467ec..76ef8c951e 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-06T14:58:49 UTC +# On Date: 2020-05-07T18:22:26 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 4d20e72ad4..5ece8602e0 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-06T14:58:49 UTC +# On Date: 2020-05-07T18:22:26 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started In Previously Unseen Region"] +searches = ["EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "EC2 Instance Started With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["AWS Network Access Control List Deleted", "Detect Spike in blocked Outbound Traffic from your AWS", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in Network ACL Activity"] +searches = ["AWS Network Access Control List Deleted", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect new API calls from user roles", "Detect Spike in Security Group Activity", "Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts"] +searches = ["Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Short Lived Windows Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint", "Identify New User Accounts"] +searches = ["Short Lived Windows Accounts", "Identify New User Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Monitor Web Traffic For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse"] +searches = ["Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] +searches = ["Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Email files written outside of the Outlook directory", "Suspicious writes to windows Recycle Bin", "Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server"] +searches = ["Hosts receiving high volume of network traffic from email server", "Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Long DNS TXT Record Response", "DNS Query Length Outliers - MLTK", "TOR Traffic", "Protocol or Port Mismatch", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Large Outbound ICMP Packets", "Prohibited Network Traffic Allowed", "Excessive DNS Failures"] +searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Clients Connecting to Multiple DNS Servers", "TOR Traffic", "Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Protocol or Port Mismatch", "Detect Large Outbound ICMP Packets"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] +searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Detect Credential Dumping through LSASS access", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Access LSASS Memory for Dump Creation", "Create Remote Thread into LSASS", "Detect Mimikatz Using Loaded Images"] +searches = ["Credential Dumping via Copy Command from Shadow Copy", "Access LSASS Memory for Dump Creation", "Detect Mimikatz Using Loaded Images", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Detect Credential Dumping through LSASS access", "Creation of Shadow Copy with wmic and powershell", "Unsigned Image Loaded by LSASS", "Create Remote Thread into LSASS", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Creation of Shadow Copy", "Credential Dumping via Symlink to Shadow Copy"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Processes launching netsh", "Registry Keys Used For Persistence", "Detect Outbound SMB Traffic", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Detect New Local Admin account", "Single Letter Process On Endpoint", "Detect PsExec With accepteula Flag", "Create local admin accounts using net exe", "First time seen command line argument", "Scheduled Task Name Used by Dragonfly Threat Actors", "Malicious PowerShell Process - Execution Policy Bypass"] +searches = ["Processes launching netsh", "Suspicious Reg exe Process", "First time seen command line argument", "Detect PsExec With accepteula Flag", "Sc exe Manipulating Windows Services", "Detect New Local Admin account", "Single Letter Process On Endpoint", "SMB Traffic Spike - MLTK", "Create local admin accounts using net exe", "Registry Keys Used For Persistence", "Scheduled Task Name Used by Dragonfly Threat Actors", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Malicious PowerShell Process - Execution Policy Bypass"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "DNS record changed"] +searches = ["Clients Connecting to Multiple DNS Servers", "DNS record changed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect hosts connecting to dynamic domain providers"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Detection of DNS Tunnels"] +searches = ["Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Detect USB device insertion"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Unload Sysmon Filter Driver", "Processes launching netsh", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service"] +searches = ["Processes launching netsh", "Attempt To Add Certificate To Untrusted Store", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Unload Sysmon Filter Driver", "Attempt To Stop Security Service"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] +searches = ["Detect web traffic to dynamic domain providers", "Detect hosts connecting to dynamic domain providers"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Prohibited Software On Endpoint", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Registry Keys Used For Persistence", "Detection of tools built by NirSoft", "Suspicious Email Attachment Extensions", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Rare Executables", "Email Attachments With Lots Of Spaces"] +searches = ["Detection of tools built by NirSoft", "Detect Rare Executables", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions", "Registry Keys Used For Persistence", "Prohibited Software On Endpoint", "Detect Use of cmd exe to Launch Script Interpreters", "SMB Traffic Spike"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Create or delete windows shares using net exe", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Remote Desktop Network Traffic", "Detect Outbound SMB Traffic", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "First time seen command line argument", "Remote Desktop Process Running On System", "Suspicious File Write"] +searches = ["First time seen command line argument", "Remote Desktop Network Traffic", "Create or delete windows shares using net exe", "DNS Query Length With High Standard Deviation", "Suspicious File Write", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "DNS Query Length Outliers - MLTK", "Remote Desktop Process Running On System", "Detect Outbound SMB Traffic"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Windows hosts file modification"] +searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] +searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks", "Schtasks scheduling job on remote system", "Remote Desktop Process Running On System"] +searches = ["Schtasks scheduling job on remote system", "Remote Desktop Process Running On System", "Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Processes created by netsh", "Processes launching netsh"] +searches = ["Processes launching netsh", "Processes created by netsh"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "First time seen command line argument"] +searches = ["First time seen command line argument", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["Registry Keys Used For Persistence", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] +searches = ["First time seen command line argument", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch"] +searches = ["Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch", "Detect hosts connecting to dynamic domain providers"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Scheduled tasks used in BadRabbit ransomware", "Suspicious wevtutil Usage", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "Registry Keys Used For Persistence", "Common Ransomware Notes", "Remote Process Instantiation via WMI", "USN Journal Deletion", "Common Ransomware Extensions", "System Processes Run From Unexpected Locations", "TOR Traffic", "Schtasks used for forcing a reboot", "Spike in File Writes", "Unusually Long Command Line", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Unusually Long Command Line - MLTK"] +searches = ["Scheduled tasks used in BadRabbit ransomware", "TOR Traffic", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "Common Ransomware Notes", "Suspicious wevtutil Usage", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Common Ransomware Extensions", "Spike in File Writes", "SMB Traffic Spike", "Schtasks used for forcing a reboot", "USN Journal Deletion", "Remote Process Instantiation via WMI", "System Processes Run From Unexpected Locations"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect malicious requests to exploit JBoss servers", "Prohibited Software On Endpoint", "Common Ransomware Notes", "Remote Desktop Network Traffic", "Common Ransomware Extensions", "Batch File Write to System32", "Spike in File Writes", "Samsam Test File Write", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Bruteforce", "File with Samsam Extension"] +searches = ["File with Samsam Extension", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Batch File Write to System32", "Samsam Test File Write", "Common Ransomware Notes", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Extensions", "Detect attackers scanning for vulnerable JBoss servers", "Prohibited Software On Endpoint", "Spike in File Writes"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region"] +searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect new user AWS Console Login", "Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New Country"] +searches = ["Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New City"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets", "Detect S3 access from a new IP"] +searches = ["Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["System Processes Run From Unexpected Locations", "Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "Unusually Long Command Line", "First time seen command line argument", "Unusually Long Command Line - MLTK"] +searches = ["First time seen command line argument", "Detect Prohibited Applications Spawning cmd exe", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "System Processes Run From Unexpected Locations"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Clients Connecting to Multiple DNS Servers", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Excessive DNS Failures"] +searches = ["Clients Connecting to Multiple DNS Servers", "Detect hosts connecting to dynamic domain providers", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions"] +searches = ["Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions", "Email Attachments With Lots Of Spaces"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments"] +searches = ["Registry Keys Used For Persistence", "Detect mshta exe running scripts in command-line arguments", "Detect Prohibited Applications Spawning cmd exe"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Okta Account Lockout Events", "Okta Failed SSO Attempts", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta User Logins From Multiple Cities"] +searches = ["Okta User Logins From Multiple Cities", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["WMI Permanent Event Subscription", "Remote Process Instantiation via WMI", "WMI Temporary Event Subscription", "Process Execution via WMI", "WMI Permanent Event Subscription - Sysmon", "Script Execution via WMI", "Remote WMI Command Attempt"] +searches = ["Script Execution via WMI", "WMI Permanent Event Subscription", "Remote WMI Command Attempt", "WMI Temporary Event Subscription", "Remote Process Instantiation via WMI", "WMI Permanent Event Subscription - Sysmon", "Process Execution via WMI"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Monitor Registry Keys for Print Monitors", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Suspicious Changes to File Associations"] +searches = ["Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Suspicious Changes to File Associations", "Disabling Remote User Account Control", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Privilege Escalation", "Remote Registry Key modifications"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Uncommon Processes On Endpoint", "System Processes Run From Unexpected Locations", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Detect Rare Executables", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal"] +searches = ["Uncommon Processes On Endpoint", "Detect Rare Executables", "RunDLL Loading DLL By Ordinal", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect processes used for System Network Configuration Discovery", "System Processes Run From Unexpected Locations"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["Web Fraud - Account Harvesting", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed"] +searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Account Harvesting"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Remote Registry Key modifications", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Suspicious Reg exe Process", "Hiding Files And Directories With Attrib exe"] +searches = ["Suspicious Reg exe Process", "Reg exe used to hide files directories via registry keys", "Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Execution of File with Multiple Extensions", "Suspicious Changes to File Associations", "Execution of File With Spaces Before Extension"] +searches = ["Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Suspicious Changes to File Associations"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious wevtutil Usage", "Windows Event Log Cleared", "USN Journal Deletion", "Deleting Shadow Copies"] +searches = ["Windows Event Log Cleared", "USN Journal Deletion", "Suspicious wevtutil Usage", "Deleting Shadow Copies"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Monitor Registry Keys for Print Monitors", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters", "Reg exe used to hide files directories via registry keys", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Detect Path Interception By Creation Of program exe", "Reg exe Manipulating Windows Services Registry Keys"] +searches = ["Detect Path Interception By Creation Of program exe", "Shim Database File Creation", "Monitor Registry Keys for Print Monitors", "Sc exe Manipulating Windows Services", "Reg exe used to hide files directories via registry keys", "Reg exe Manipulating Windows Services Registry Keys", "Registry Keys Used For Persistence", "Shim Database Installation With Suspicious Parameters", "Hiding Files And Directories With Attrib exe", "Registry Keys for Creating SHIM Databases", "Schtasks used for forcing a reboot", "Remote Registry Key modifications"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Child Processes of Spoolsv exe", "Registry Keys Used For Privilege Escalation", "Overwriting Accessibility Binaries", "Uncommon Processes On Endpoint"] +searches = ["Uncommon Processes On Endpoint", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys"] +searches = ["Reg exe Manipulating Windows Services Registry Keys", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 93143c804998ea012d4b1cc18f414b730416ac9b Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 09:46:20 +0200 Subject: [PATCH 21/93] new generate script --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 30a7160243..d5ae5b7ada 100644 --- a/README.md +++ b/README.md @@ -1 +1 @@ -new version of the README needs to be done. +new version of the README needs to be done From 0feba4ea6df53894acfc1bcbdd4277e0aabf78f1 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 11:21:52 +0200 Subject: [PATCH 22/93] bug in generate --- bin/generate.py | 83 +++++++++ bin/jinja2_templates/analytic_stories.j2 | 4 +- package/default/analytic_stories.conf | 228 +++++++++++------------ package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 96 +++++----- 7 files changed, 251 insertions(+), 166 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 0e21341c0c..5027429980 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -113,6 +113,8 @@ def generate_analytics_story_conf(stories, detections, response_tasks): if story['name'] in sto_res: story['response_tasks'] = list(sto_res[story['name']]) + stories = prepare_stories(stories, detections) + utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), @@ -266,6 +268,87 @@ def custom_jinja2_enrichment_filter(string, object): return customized_string + +def prepare_stories(stories, detections): + + # enrich stories with information from detections: data_models, mitre_ids, kill_chain_phases, nists + sto_to_data_models = {} + sto_to_mitre_attack_ids = {} + sto_to_kill_chain_phases = {} + sto_to_ciss = {} + sto_to_nists = {} + sto_to_det = {} + for detection in detections: + if 'analytics_story' in detection['tags']: + for story in detection['tags']['analytics_story']: + if story in sto_to_det.keys(): + sto_to_det[story].add(detection['name']) + else: + sto_to_det[story] = {detection['name']} + + data_model = parse_data_models_from_search(detection['search']) + if data_model: + if story in sto_to_data_models.keys(): + sto_to_data_models[story].add(data_model) + else: + sto_to_data_models[story] = {data_model} + + if 'mitre_attack_id' in detection['tags']: + if story in sto_to_mitre_attack_ids.keys(): + for mitre_attack_id in detection['tags']['mitre_attack_id']: + sto_to_mitre_attack_ids[story].add(mitre_attack_id) + else: + for mitre_attack_id in detection['tags']['mitre_attack_id']: + sto_to_mitre_attack_ids[story] = {mitre_attack_id} + + if 'kill_chain_phases' in detection['tags']: + if story in sto_to_kill_chain_phases.keys(): + for kill_chain in detection['tags']['kill_chain_phases']: + sto_to_kill_chain_phases[story].add(kill_chain) + else: + for kill_chain in detection['tags']['kill_chain_phases']: + sto_to_kill_chain_phases[story] = {kill_chain} + + if 'cis20' in detection['tags']: + if story in sto_to_ciss.keys(): + for cis in detection['tags']['cis20']: + sto_to_ciss[story].add(cis) + else: + for cis in detection['tags']['cis20']: + sto_to_ciss[story] = {cis} + + if 'nist' in detection['tags']: + if story in sto_to_nists.keys(): + for nist in detection['tags']['nist']: + sto_to_nists[story].add(nist) + else: + for nist in detection['tags']['nist']: + sto_to_nists[story] = {nist} + + for story in stories: + story['detections'] = sorted(sto_to_det[story['name']]) + if story['name'] in sto_to_data_models: + story['data_models'] = sorted(sto_to_data_models[story['name']]) + if story['name'] in sto_to_mitre_attack_ids: + story['mitre_attack'] = sorted(sto_to_mitre_attack_ids[story['name']]) + if story['name'] in sto_to_kill_chain_phases: + story['kill_chain_phases'] = sorted(sto_to_kill_chain_phases[story['name']]) + if story['name'] in sto_to_ciss: + story['cis20'] = sorted(sto_to_ciss[story['name']]) + if story['name'] in sto_to_nists: + story['nist'] = sorted(sto_to_nists[story['name']]) + + keys = ['mitre_attack', 'kill_chain_phases', 'cis20', 'nist'] + mappings = {} + for key in keys: + if key in story: + mappings[key] = story[key] + + story['mappings'] = mappings + + return stories + + if __name__ == "__main__": parser = argparse.ArgumentParser(description="generates splunk conf files out of security-content manifests", epilog=""" diff --git a/bin/jinja2_templates/analytic_stories.j2 b/bin/jinja2_templates/analytic_stories.j2 index 362525e03b..1317ee5315 100644 --- a/bin/jinja2_templates/analytic_stories.j2 +++ b/bin/jinja2_templates/analytic_stories.j2 @@ -16,7 +16,9 @@ id = {{ story.id }} version = {{ story.version }} reference = {{ story.references | tojson }} detection_searches = {{ story.detections | tojson }} -mappings = {{ story.tags | tojson }} +{% if story.mappings is defined %} +mappings = {{ story.mappings | tojson }} +{% endif %} {% if story.response_tasks is defined %} investigative_searches = {{ story.response_tasks | tojson }} {% endif %} diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 5c6b2f132b..169b75d163 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-07T18:22:26 UTC +# On Date: 2020-05-08T09:21:06 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -15,7 +15,7 @@ id = 2f2f610a-d64d-48c2-b57c-967a2b49ab5a version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["AWS Cross Account Activity From Previously Unseen Account"] -mappings = {"analytics_story": "AWS Cross Account Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} support_searches = none data_models = none providing_technologies = none @@ -31,8 +31,8 @@ modification_date = 2018-03-08 id = ced74200-8465-4bc3-bd2c-9a782eec6750 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "EC2 Instance Started With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User"] -mappings = {"analytics_story": "AWS Cryptomining", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started With Previously Unseen User"] +mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} support_searches = none data_models = none providing_technologies = none @@ -49,8 +49,8 @@ modification_date = 2018-05-21 id = 2e8948a5-5239-406b-b56b-6c50ff268af4 version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] -detection_searches = ["AWS Network Access Control List Deleted", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity"] -mappings = {"analytics_story": "AWS Network ACL Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["AWS Network Access Control List Created with All Open Ports", "AWS Network Access Control List Deleted", "Detect Spike in Network ACL Activity", "Detect Spike in blocked Outbound Traffic from your AWS"] +mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} support_searches = none data_models = none providing_technologies = none @@ -64,8 +64,8 @@ modification_date = 2018-03-16 id = 3338b567-3804-4261-9889-cf0ca4753c7f version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region", "AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country"] -mappings = {"analytics_story": "AWS Suspicious Provisioning Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region"] +mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} support_searches = none data_models = none providing_technologies = none @@ -80,8 +80,8 @@ modification_date = 2018-03-12 id = 2e8948a5-5239-406b-b56b-6c50f1269af3 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] -detection_searches = ["Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] -mappings = {"analytics_story": "AWS User Monitoring", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["Detect API activity from users without MFA", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in AWS API Activity", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] +mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} support_searches = none data_models = none providing_technologies = none @@ -98,8 +98,8 @@ modification_date = 2017-09-06 id = 8892a655-6205-55f7-abba-06460e38c8ae version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] -detection_searches = ["Short Lived Windows Accounts", "Identify New User Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint"] -mappings = {"analytics_story": "Account Monitoring and Controls", "category": ["Best Practices"], "usecase": "Security Monitoring"} +detection_searches = ["Detect Excessive Account Lockouts From Endpoint", "Detect Excessive User Account Lockouts", "Identify New User Accounts", "Short Lived Windows Accounts"] +mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -114,7 +114,7 @@ id = 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] -mappings = {"analytics_story": "Apache Struts Vulnerability", "category": ["Vulnerability"], "usecase": "Advanced Threat Detection"} +mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} support_searches = none data_models = none providing_technologies = none @@ -142,7 +142,7 @@ id = 91c676cf-0b23-438d-abee-f6335e1fce77 version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["Detect Unauthorized Assets by MAC address"] -mappings = {"analytics_story": "Asset Tracking", "category": ["Best Practices"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} support_searches = none data_models = none providing_technologies = none @@ -156,8 +156,8 @@ modification_date = 2017-12-19 id = 91c676cf-0b23-438d-abee-f6335e1fce78 version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] -detection_searches = ["Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse"] -mappings = {"analytics_story": "Brand Monitoring", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] +mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -173,8 +173,8 @@ modification_date = 2019-10-02 id = 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] -mappings = {"analytics_story": "Cloud Cryptomining", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Started In Previously Unused Region"] +mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} support_searches = none data_models = none providing_technologies = none @@ -191,8 +191,8 @@ modification_date = 2019-01-09 id = bd91a2bc-d20b-4f44-a982-1bea98e86390 version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] -detection_searches = ["Processes Tapping Keyboard Events", "Osquery pack - ColdRoot detection"] -mappings = {"analytics_story": "ColdRoot MacOS RAT", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events"] +mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -208,8 +208,8 @@ modification_date = 2020-02-03 id = 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] -detection_searches = ["Hosts receiving high volume of network traffic from email server", "Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] -mappings = {"analytics_story": "Collection and Staging", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +detection_searches = ["Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] +mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -225,8 +225,8 @@ modification_date = 2018-06-01 id = 943773c6-c4de-4f38-89a8-0b92f98804d8 version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] -detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Clients Connecting to Multiple DNS Servers", "TOR Traffic", "Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Protocol or Port Mismatch", "Detect Large Outbound ICMP Packets"] -mappings = {"analytics_story": "Command and Control", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] +mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -242,7 +242,7 @@ id = 9a64ab44-9214-4639-8163-7eaa2621bd61 version = 1 reference = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] detection_searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] -mappings = {"analytics_story": "Common Phishing Frameworks", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1192"], "nist": ["DE.CM"]} support_searches = none data_models = none providing_technologies = none @@ -257,8 +257,8 @@ modification_date = 2020-02-20 id = aa0e28b1-0521-4b6f-9d2a-7b87e34af246 version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded"] -mappings = {"analytics_story": "Container Implantation Monitoring and Investigation", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] +mappings = {} support_searches = none data_models = none providing_technologies = none @@ -272,8 +272,8 @@ modification_date = 2020-02-04 id = 854d78bf-d0e2-4f4e-b05c-640905f86d7a version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] -detection_searches = ["Credential Dumping via Copy Command from Shadow Copy", "Access LSASS Memory for Dump Creation", "Detect Mimikatz Using Loaded Images", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Detect Credential Dumping through LSASS access", "Creation of Shadow Copy with wmic and powershell", "Unsigned Image Loaded by LSASS", "Create Remote Thread into LSASS", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Creation of Shadow Copy", "Credential Dumping via Symlink to Shadow Copy"] -mappings = {"analytics_story": "Credential Dumping", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Attempted Credential Dump From Registry via Reg exe", "Create Remote Thread into LSASS", "Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS"] +mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -289,8 +289,8 @@ modification_date = 2020-01-22 id = 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] -detection_searches = ["Processes launching netsh", "Suspicious Reg exe Process", "First time seen command line argument", "Detect PsExec With accepteula Flag", "Sc exe Manipulating Windows Services", "Detect New Local Admin account", "Single Letter Process On Endpoint", "SMB Traffic Spike - MLTK", "Create local admin accounts using net exe", "Registry Keys Used For Persistence", "Scheduled Task Name Used by Dragonfly Threat Actors", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Malicious PowerShell Process - Execution Policy Bypass"] -mappings = {"analytics_story": "DHS Report TA18-074A", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Create local admin accounts using net exe", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Malicious PowerShell Process - Execution Policy Bypass", "Processes launching netsh", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Sc exe Manipulating Windows Services", "Scheduled Task Name Used by Dragonfly Threat Actors", "Single Letter Process On Endpoint", "Suspicious Reg exe Process"] +mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -308,7 +308,7 @@ id = e8afd39e-3294-11e6-b39d-a45e60c6700 version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["Large Volume of DNS ANY Queries"] -mappings = {"analytics_story": "DNS Amplification Attacks", "category": ["Abuse"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -323,8 +323,8 @@ modification_date = 2020-02-04 id = 8169f17b-ef68-4b59-aa28-586907301221 version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS record changed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect hosts connecting to dynamic domain providers"] -mappings = {"analytics_story": "DNS Hijacking", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers"] +mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -346,8 +346,8 @@ modification_date = 2017-09-14 id = 91c676cf-0b23-438d-abee-f6335e1fce33 version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] -detection_searches = ["Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Detect USB device insertion"] -mappings = {"analytics_story": "Data Protection", "category": ["Abuse"], "usecase": "Security Monitoring"} +detection_searches = ["Detect USB device insertion", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels"] +mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -361,8 +361,8 @@ modification_date = 2020-02-04 id = fcc27099-46a0-46b0-a271-5c7dab56b6f1 version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] -detection_searches = ["Processes launching netsh", "Attempt To Add Certificate To Untrusted Store", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Unload Sysmon Filter Driver", "Attempt To Stop Security Service"] -mappings = {"analytics_story": "Disabling Security Tools", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +detection_searches = ["Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Unload Sysmon Filter Driver"] +mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -376,8 +376,8 @@ modification_date = 2018-09-06 id = 8169f17b-ef68-4b59-aae8-586907301221 version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["Detect web traffic to dynamic domain providers", "Detect hosts connecting to dynamic domain providers"] -mappings = {"analytics_story": "Dynamic DNS", "category": ["Malware"], "usecase": "Security Monitoring"} +detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] +mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -391,8 +391,8 @@ modification_date = 2020-01-27 id = bb9f5ed2-916e-4364-bb6d-91c310efcf52 version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] -detection_searches = ["Detection of tools built by NirSoft", "Detect Rare Executables", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions", "Registry Keys Used For Persistence", "Prohibited Software On Endpoint", "Detect Use of cmd exe to Launch Script Interpreters", "SMB Traffic Spike"] -mappings = {"analytics_story": "Emotet Malware DHS Report TA18-201A ", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect Rare Executables", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Email Attachments With Lots Of Spaces", "Prohibited Software On Endpoint", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions"] +mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -408,8 +408,8 @@ modification_date = 2020-01-22 id = baf7580b-d4b4-4774-8173-7d198e9da335 version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] -detection_searches = ["First time seen command line argument", "Remote Desktop Network Traffic", "Create or delete windows shares using net exe", "DNS Query Length With High Standard Deviation", "Suspicious File Write", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "DNS Query Length Outliers - MLTK", "Remote Desktop Process Running On System", "Detect Outbound SMB Traffic"] -mappings = {"analytics_story": "Hidden Cobra Malware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Create or delete windows shares using net exe", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "Detect Outbound SMB Traffic", "First time seen command line argument", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious File Write"] +mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -427,7 +427,7 @@ id = 2e8948a5-5239-406b-b56b-6c50fe268af4 version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] -mappings = {"analytics_story": "Host Redirection", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} +mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -441,8 +441,8 @@ modification_date = 2017-09-14 id = 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] -detection_searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers"] -mappings = {"analytics_story": "JBoss Vulnerability", "category": ["Vulnerability"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] +mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} support_searches = none data_models = none providing_technologies = none @@ -470,8 +470,8 @@ modification_date = 2020-04-15 id = a9ef59cf-e981-4e66-9eef-bb049f695c09 version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection"] -mappings = {"analytics_story": "Kubernetes Scanning Activity", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] +mappings = {"kill_chain_phases": ["Reconnaissance"]} support_searches = none data_models = none providing_technologies = none @@ -485,8 +485,8 @@ modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] -detection_searches = ["Schtasks scheduling job on remote system", "Remote Desktop Process Running On System", "Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks"] -mappings = {"analytics_story": "Lateral Movement", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system"] +mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -504,8 +504,8 @@ modification_date = 2017-08-23 id = 2c8ff66e-0b57-42af-8ad7-912438a403fc version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -detection_searches = ["Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process With Obfuscation Techniques", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] -mappings = {"analytics_story": "Malicious PowerShell", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques"] +mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -529,7 +529,7 @@ id = abe807c7-1eb6-4304-ac32-6e7aacdb891d version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] -mappings = {"analytics_story": "Monitor Backup Solution", "category": ["Best Practices"], "usecase": "Compliance"} +mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -544,7 +544,7 @@ id = 8892a655-6205-43f7-abba-06460e38c8ae version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["Prohibited Software On Endpoint"] -mappings = {"analytics_story": "Monitor for Unauthorized Software", "category": ["Best Practices"], "usecase": "Compliance"} +mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} support_searches = none data_models = none providing_technologies = none @@ -560,7 +560,7 @@ id = 9ef8d677-7b52-4213-a038-99cfc7acc2d8 version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["No Windows Updates in a time frame"] -mappings = {"analytics_story": "Monitor for Updates", "category": ["Best Practices"], "usecase": "Compliance"} +mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} support_searches = none data_models = none providing_technologies = none @@ -576,8 +576,8 @@ modification_date = 2017-01-05 id = 2b1800dd-92f9-47ec-a981-fdf1351e5f65 version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] -detection_searches = ["Processes launching netsh", "Processes created by netsh"] -mappings = {"analytics_story": "Netsh Abuse", "category": ["Abuse"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Processes created by netsh", "Processes launching netsh"] +mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -592,8 +592,8 @@ modification_date = 2020-01-22 id = bb9f5ed2-916e-4364-bb6d-97c370efcf52 version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] -detection_searches = ["First time seen command line argument", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] -mappings = {"analytics_story": "Orangeworm Attack Group", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["First Time Seen Running Windows Service", "First time seen command line argument", "Sc exe Manipulating Windows Services"] +mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -611,8 +611,8 @@ modification_date = 2019-04-29 id = 57226b40-94f3-4ce5-b101-a75f67759c27 version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] -detection_searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file"] -mappings = {"analytics_story": "Phishing Payloads", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process"] +mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} support_searches = none data_models = none providing_technologies = none @@ -633,8 +633,8 @@ modification_date = 2020-01-22 id = 988C59C5-0A1C-45B6-A555-0C62276E327E version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] -detection_searches = ["First time seen command line argument", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] -mappings = {"analytics_story": "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] +mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -675,8 +675,8 @@ modification_date = 2017-09-11 id = 6d13121c-90f3-446d-8ac3-27efbbc65218 version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] -detection_searches = ["Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch", "Detect hosts connecting to dynamic domain providers"] -mappings = {"analytics_story": "Prohibited Traffic Allowed or Protocol Mismatch", "category": ["Best Practices"], "usecase": "Security Monitoring"} +detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] +mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} support_searches = none data_models = none providing_technologies = none @@ -690,8 +690,8 @@ modification_date = 2020-02-04 id = cf309d0d-d4aa-4fbb-963d-1e79febd3756 version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] -detection_searches = ["Scheduled tasks used in BadRabbit ransomware", "TOR Traffic", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "Common Ransomware Notes", "Suspicious wevtutil Usage", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Common Ransomware Extensions", "Spike in File Writes", "SMB Traffic Spike", "Schtasks used for forcing a reboot", "USN Journal Deletion", "Remote Process Instantiation via WMI", "System Processes Run From Unexpected Locations"] -mappings = {"analytics_story": "Ransomware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Registry Keys Used For Persistence", "Remote Process Instantiation via WMI", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Scheduled tasks used in BadRabbit ransomware", "Schtasks used for forcing a reboot", "Spike in File Writes", "Suspicious wevtutil Usage", "System Processes Run From Unexpected Locations", "TOR Traffic", "USN Journal Deletion", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared"] +mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -706,7 +706,7 @@ id = 91c676cf-0b23-438d-abee-f6335e177e77 version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["Detect New Login Attempts to Routers"] -mappings = {"analytics_story": "Router and Infrastructure Security", "category": ["Best Practices"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -722,7 +722,7 @@ id = 4f6632f5-449c-4686-80df-57625f59bab3 version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["SQL Injection with Long URLs"] -mappings = {"analytics_story": "SQL Injection", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} support_searches = none data_models = none providing_technologies = none @@ -737,8 +737,8 @@ modification_date = 2018-12-13 id = c4b89506-fbcf-4cb7-bfd6-527e54789604 version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] -detection_searches = ["File with Samsam Extension", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Batch File Write to System32", "Samsam Test File Write", "Common Ransomware Notes", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Extensions", "Detect attackers scanning for vulnerable JBoss servers", "Prohibited Software On Endpoint", "Spike in File Writes"] -mappings = {"analytics_story": "SamSam Ransomware", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Batch File Write to System32", "Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Detect PsExec With accepteula Flag", "Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers", "File with Samsam Extension", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Samsam Test File Write", "Spike in File Writes"] +mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -758,7 +758,7 @@ id = 6d3306f6-bb2b-4219-8609-8efad64032f2 version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["Spectre and Meltdown Vulnerable Systems"] -mappings = {"analytics_story": "Spectre And Meltdown Vulnerabilities", "category": ["Vulnerability"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} support_searches = none data_models = none providing_technologies = none @@ -773,7 +773,7 @@ id = 4e692b96-de2d-4bd1-9105-37e2368a8db1 version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["Open Redirect in Splunk Web"] -mappings = {"analytics_story": "Splunk Enterprise Vulnerability", "category": ["Vulnerability"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} support_searches = none data_models = none providing_technologies = none @@ -797,7 +797,7 @@ id = 1fc34cbc-34e9-43ba-87ab-6811c9e95400 version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["Splunk Enterprise Information Disclosure"] -mappings = {"analytics_story": "Splunk Enterprise Vulnerability CVE-2018-11409", "category": ["Vulnerability"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} support_searches = none data_models = none providing_technologies = none @@ -814,8 +814,8 @@ modification_date = 2018-02-09 id = 2e8948a5-5239-406b-b56b-6c50f1268af3 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User"] -mappings = {"analytics_story": "Suspicious AWS EC2 Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User"] +mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} support_searches = none data_models = none providing_technologies = none @@ -829,8 +829,8 @@ modification_date = 2019-05-01 id = 2e8948a5-5239-406b-b56b-6c59f1268af3 version = 1 reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] -detection_searches = ["Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New City"] -mappings = {"analytics_story": "Suspicious AWS Login Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login"] +mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP"]} support_searches = none data_models = none providing_technologies = none @@ -844,8 +844,8 @@ modification_date = 2018-07-24 id = 2e8948a5-5239-406b-b56b-6c50w3168af3 version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] -detection_searches = ["Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets"] -mappings = {"analytics_story": "Suspicious AWS S3 Activities", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +detection_searches = ["Detect New Open S3 buckets", "Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion"] +mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} support_searches = none data_models = none providing_technologies = none @@ -862,7 +862,7 @@ id = 2e8948a5-5239-406b-b56b-6c50f2168af3 version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] -mappings = {"analytics_story": "Suspicious AWS Traffic", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} support_searches = none data_models = none providing_technologies = none @@ -879,8 +879,8 @@ modification_date = 2020-02-03 id = f4368ddf-d59f-4192-84f6-778ac5a3ffc7 version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] -detection_searches = ["First time seen command line argument", "Detect Prohibited Applications Spawning cmd exe", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "System Processes Run From Unexpected Locations"] -mappings = {"analytics_story": "Suspicious Command-Line Executions", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] +mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -894,8 +894,8 @@ modification_date = 2017-09-18 id = 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] -detection_searches = ["Clients Connecting to Multiple DNS Servers", "Detect hosts connecting to dynamic domain providers", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response"] -mappings = {"analytics_story": "Suspicious DNS Traffic", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures"] +mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -909,8 +909,8 @@ modification_date = 2020-01-27 id = 2b1800dd-92f9-47ec-a981-fdf1351e5d55 version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] -detection_searches = ["Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions", "Email Attachments With Lots Of Spaces"] -mappings = {"analytics_story": "Suspicious Emails", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions"] +mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} support_searches = none data_models = none providing_technologies = none @@ -928,8 +928,8 @@ modification_date = 2020-02-03 id = 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] -detection_searches = ["Registry Keys Used For Persistence", "Detect mshta exe running scripts in command-line arguments", "Detect Prohibited Applications Spawning cmd exe"] -mappings = {"analytics_story": "Suspicious MSHTA Activity", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] +mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -945,8 +945,8 @@ modification_date = 2020-04-02 id = 9cbd34af-8f39-4476-a423-bacd126c750b version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] -detection_searches = ["Okta User Logins From Multiple Cities", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts"] -mappings = {"analytics_story": "Suspicious Okta Activity", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +detection_searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts", "Okta User Logins From Multiple Cities"] +mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} support_searches = none data_models = none providing_technologies = none @@ -962,8 +962,8 @@ modification_date = 2018-10-23 id = c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] -detection_searches = ["Script Execution via WMI", "WMI Permanent Event Subscription", "Remote WMI Command Attempt", "WMI Temporary Event Subscription", "Remote Process Instantiation via WMI", "WMI Permanent Event Subscription - Sysmon", "Process Execution via WMI"] -mappings = {"analytics_story": "Suspicious WMI Use", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Process Execution via WMI", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription"] +mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -979,8 +979,8 @@ modification_date = 2018-05-31 id = 2b1800dd-92f9-47dd-a981-fdf1351e5d55 version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] -detection_searches = ["Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Suspicious Changes to File Associations", "Disabling Remote User Account Control", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Privilege Escalation", "Remote Registry Key modifications"] -mappings = {"analytics_story": "Suspicious Windows Registry Activities", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Disabling Remote User Account Control", "Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Suspicious Changes to File Associations"] +mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -997,7 +997,7 @@ id = 73de57ef-0dfc-411f-b1e7-fa24428aeae0 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["EC2 Instance Modified With Previously Unseen User"] -mappings = {"analytics_story": "Unusual AWS EC2 Modifications", "category": ["Cloud Security"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} support_searches = none data_models = none providing_technologies = none @@ -1012,8 +1012,8 @@ modification_date = 2020-02-04 id = f4368e3f-d59f-4192-84f6-748ac5a3ddb6 version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] -detection_searches = ["Uncommon Processes On Endpoint", "Detect Rare Executables", "RunDLL Loading DLL By Ordinal", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect processes used for System Network Configuration Discovery", "System Processes Run From Unexpected Locations"] -mappings = {"analytics_story": "Unusual Processes", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect Rare Executables", "Detect processes used for System Network Configuration Discovery", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Uncommon Processes On Endpoint", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] +mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -1030,7 +1030,7 @@ id = 826e6431-aeef-41b4-9fc0-6d0985d65a21 version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["Protocols passing authentication in cleartext"] -mappings = {"analytics_story": "Use of Cleartext Protocols", "category": ["Best Practices"], "usecase": "Security Monitoring"} +mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} support_searches = none data_models = none providing_technologies = none @@ -1044,8 +1044,8 @@ modification_date = 2018-10-08 id = 31337aaa-bc22-4752-b599-ef112dq1dq7a version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] -detection_searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Account Harvesting"] -mappings = {"analytics_story": "Web Fraud Detection", "category": ["Abuse"], "usecase": "Fraud Detection"} +detection_searches = ["Web Fraud - Account Harvesting", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts"] +mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} support_searches = none data_models = none providing_technologies = none @@ -1064,8 +1064,8 @@ modification_date = 2018-05-31 id = 56e24a28-5003-4047-b2db-e8f3c4618064 version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] -detection_searches = ["Suspicious Reg exe Process", "Reg exe used to hide files directories via registry keys", "Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications"] -mappings = {"analytics_story": "Windows Defense Evasion Tactics", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Suspicious Reg exe Process"] +mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -1079,8 +1079,8 @@ modification_date = 2018-01-26 id = 30552a76-ac78-48e4-b3c0-de4e34e9563d version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] -detection_searches = ["Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Suspicious Changes to File Associations"] -mappings = {"analytics_story": "Windows File Extension and Association Abuse", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions", "Suspicious Changes to File Associations"] +mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -1098,8 +1098,8 @@ modification_date = 2017-09-12 id = b6db2c60-a281-48b4-95f1-2cd99ed56835 version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] -detection_searches = ["Windows Event Log Cleared", "USN Journal Deletion", "Suspicious wevtutil Usage", "Deleting Shadow Copies"] -mappings = {"analytics_story": "Windows Log Manipulation", "category": ["Adversary Tactics"], "usecase": "Security Monitoring"} +detection_searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] +mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -1114,8 +1114,8 @@ modification_date = 2018-05-31 id = 30874d4f-20a1-488f-85ec-5d52ef74e3f9 version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] -detection_searches = ["Detect Path Interception By Creation Of program exe", "Shim Database File Creation", "Monitor Registry Keys for Print Monitors", "Sc exe Manipulating Windows Services", "Reg exe used to hide files directories via registry keys", "Reg exe Manipulating Windows Services Registry Keys", "Registry Keys Used For Persistence", "Shim Database Installation With Suspicious Parameters", "Hiding Files And Directories With Attrib exe", "Registry Keys for Creating SHIM Databases", "Schtasks used for forcing a reboot", "Remote Registry Key modifications"] -mappings = {"analytics_story": "Windows Persistence Techniques", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Detect Path Interception By Creation Of program exe", "Hiding Files And Directories With Attrib exe", "Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters"] +mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -1129,8 +1129,8 @@ modification_date = 2020-02-04 id = 644e22d3-598a-429c-a007-16fdb802cae5 version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] -detection_searches = ["Uncommon Processes On Endpoint", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation"] -mappings = {"analytics_story": "Windows Privilege Escalation", "category": ["Adversary Tactics"], "usecase": "Advanced Threat Detection"} +detection_searches = ["Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint"] +mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} support_searches = none data_models = none providing_technologies = none @@ -1144,8 +1144,8 @@ modification_date = 2017-11-02 id = 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] -detection_searches = ["Reg exe Manipulating Windows Services Registry Keys", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] -mappings = {"analytics_story": "Windows Service Abuse", "category": ["Malware"], "usecase": "Advanced Threat Detection"} +detection_searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] +mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none data_models = none providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 60003c64bc..5d8ccb119b 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-07T18:22:26 UTC +# On Date: 2020-05-08T09:21:06 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 8b8e3807a4..a107bc33d2 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-07T18:22:26 UTC +# On Date: 2020-05-08T09:21:06 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 76ef8c951e..f1b97b61f1 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-07T18:22:26 UTC +# On Date: 2020-05-08T09:21:06 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 5ece8602e0..ffc8a80891 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-07T18:22:26 UTC +# On Date: 2020-05-08T09:21:06 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "EC2 Instance Started With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User"] +searches = ["EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started With Previously Unseen User"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["AWS Network Access Control List Deleted", "AWS Network Access Control List Created with All Open Ports", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity"] +searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity", "AWS Network Access Control List Created with All Open Ports", "AWS Network Access Control List Deleted"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region", "AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country"] +searches = ["AWS Cloud Provisioning From Previously Unseen Region", "AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen IP Address"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect API activity from users without MFA", "Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] +searches = ["Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts", "Detect new API calls from user roles", "Detect Spike in Security Group Activity", "Detect API activity from users without MFA"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] +searches = ["Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes", "Suspicious Java Classes"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse"] +searches = ["Monitor Web Traffic For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Started In Previously Unused Region"] +searches = ["Cloud Compute Instance Started In Previously Unused Region", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Hosts receiving high volume of network traffic from email server", "Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] +searches = ["Email files written outside of the Outlook directory", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to windows Recycle Bin", "Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Clients Connecting to Multiple DNS Servers", "TOR Traffic", "Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Protocol or Port Mismatch", "Detect Large Outbound ICMP Packets"] +searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "TOR Traffic", "Prohibited Network Traffic Allowed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length With High Standard Deviation", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Excessive DNS Failures", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "Protocol or Port Mismatch"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded"] +searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Credential Dumping via Copy Command from Shadow Copy", "Access LSASS Memory for Dump Creation", "Detect Mimikatz Using Loaded Images", "Attempted Credential Dump From Registry via Reg exe", "Dump LSASS via comsvcs DLL", "Detect Credential Dumping through LSASS access", "Creation of Shadow Copy with wmic and powershell", "Unsigned Image Loaded by LSASS", "Create Remote Thread into LSASS", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Creation of Shadow Copy", "Credential Dumping via Symlink to Shadow Copy"] +searches = ["Access LSASS Memory for Dump Creation", "Creation of Shadow Copy with wmic and powershell", "Detect Credential Dumping through LSASS access", "Creation of Shadow Copy", "Credential Dumping via Copy Command from Shadow Copy", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Detect Mimikatz Using Loaded Images", "Unsigned Image Loaded by LSASS", "Create Remote Thread into LSASS", "Dump LSASS via comsvcs DLL", "Credential Dumping via Symlink to Shadow Copy", "Attempted Credential Dump From Registry via Reg exe"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Processes launching netsh", "Suspicious Reg exe Process", "First time seen command line argument", "Detect PsExec With accepteula Flag", "Sc exe Manipulating Windows Services", "Detect New Local Admin account", "Single Letter Process On Endpoint", "SMB Traffic Spike - MLTK", "Create local admin accounts using net exe", "Registry Keys Used For Persistence", "Scheduled Task Name Used by Dragonfly Threat Actors", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Malicious PowerShell Process - Execution Policy Bypass"] +searches = ["SMB Traffic Spike - MLTK", "First time seen command line argument", "Registry Keys Used For Persistence", "Suspicious Reg exe Process", "Create local admin accounts using net exe", "Sc exe Manipulating Windows Services", "Detect Outbound SMB Traffic", "Scheduled Task Name Used by Dragonfly Threat Actors", "Processes launching netsh", "SMB Traffic Spike", "Detect New Local Admin account", "Detect PsExec With accepteula Flag", "Malicious PowerShell Process - Execution Policy Bypass", "Single Letter Process On Endpoint"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Clients Connecting to Multiple DNS Servers", "DNS record changed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect hosts connecting to dynamic domain providers"] +searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Detect USB device insertion"] +searches = ["Detection of DNS Tunnels", "Detect USB device insertion", "Detect hosts connecting to dynamic domain providers"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Processes launching netsh", "Attempt To Add Certificate To Untrusted Store", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Unload Sysmon Filter Driver", "Attempt To Stop Security Service"] +searches = ["Unload Sysmon Filter Driver", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Processes launching netsh", "Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect web traffic to dynamic domain providers", "Detect hosts connecting to dynamic domain providers"] +searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detection of tools built by NirSoft", "Detect Rare Executables", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions", "Registry Keys Used For Persistence", "Prohibited Software On Endpoint", "Detect Use of cmd exe to Launch Script Interpreters", "SMB Traffic Spike"] +searches = ["Detect Rare Executables", "Email Attachments With Lots Of Spaces", "Registry Keys Used For Persistence", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions", "Detection of tools built by NirSoft", "SMB Traffic Spike", "Detect Use of cmd exe to Launch Script Interpreters", "Prohibited Software On Endpoint"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["First time seen command line argument", "Remote Desktop Network Traffic", "Create or delete windows shares using net exe", "DNS Query Length With High Standard Deviation", "Suspicious File Write", "SMB Traffic Spike - MLTK", "SMB Traffic Spike", "DNS Query Length Outliers - MLTK", "Remote Desktop Process Running On System", "Detect Outbound SMB Traffic"] +searches = ["Remote Desktop Process Running On System", "SMB Traffic Spike - MLTK", "First time seen command line argument", "Detect Outbound SMB Traffic", "DNS Query Length With High Standard Deviation", "SMB Traffic Spike", "Suspicious File Write", "Create or delete windows shares using net exe", "Remote Desktop Network Traffic", "DNS Query Length Outliers - MLTK"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] +searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification", "Clients Connecting to Multiple DNS Servers"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers"] +searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection"] +searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Schtasks scheduling job on remote system", "Remote Desktop Process Running On System", "Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks"] +searches = ["Remote Desktop Process Running On System", "Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Schtasks scheduling job on remote system"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process With Obfuscation Techniques", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] +searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] +searches = ["Unsuccessful Netbackup backups", "Extended Period Without Successful Netbackup Backups"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Processes launching netsh", "Processes created by netsh"] +searches = ["Processes created by netsh", "Processes launching netsh"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file"] +searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["First time seen command line argument", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] +searches = ["First time seen command line argument", "Registry Keys Used For Persistence", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Prohibited Network Traffic Allowed", "TOR Traffic", "Protocol or Port Mismatch", "Detect hosts connecting to dynamic domain providers"] +searches = ["TOR Traffic", "Prohibited Network Traffic Allowed", "Detect hosts connecting to dynamic domain providers", "Protocol or Port Mismatch"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Scheduled tasks used in BadRabbit ransomware", "TOR Traffic", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "Common Ransomware Notes", "Suspicious wevtutil Usage", "Registry Keys Used For Persistence", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Common Ransomware Extensions", "Spike in File Writes", "SMB Traffic Spike", "Schtasks used for forcing a reboot", "USN Journal Deletion", "Remote Process Instantiation via WMI", "System Processes Run From Unexpected Locations"] +searches = ["SMB Traffic Spike - MLTK", "Schtasks used for forcing a reboot", "Registry Keys Used For Persistence", "Prohibited Network Traffic Allowed", "Windows Event Log Cleared", "System Processes Run From Unexpected Locations", "Remote Process Instantiation via WMI", "Common Ransomware Notes", "SMB Traffic Spike", "Spike in File Writes", "USN Journal Deletion", "Common Ransomware Extensions", "Unusually Long Command Line", "Suspicious wevtutil Usage", "Unusually Long Command Line - MLTK", "Deleting Shadow Copies", "Scheduled tasks used in BadRabbit ransomware", "TOR Traffic"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["File with Samsam Extension", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Detect PsExec With accepteula Flag", "Deleting Shadow Copies", "Batch File Write to System32", "Samsam Test File Write", "Common Ransomware Notes", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Extensions", "Detect attackers scanning for vulnerable JBoss servers", "Prohibited Software On Endpoint", "Spike in File Writes"] +searches = ["Common Ransomware Notes", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Spike in File Writes", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Traffic", "Samsam Test File Write", "Common Ransomware Extensions", "Detect PsExec With accepteula Flag", "File with Samsam Extension", "Batch File Write to System32", "Detect malicious requests to exploit JBoss servers", "Deleting Shadow Copies"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User"] +searches = ["EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New City"] +searches = ["Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Country", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New Region"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets"] +searches = ["Detect Spike in S3 Bucket deletion", "Detect S3 access from a new IP", "Detect New Open S3 buckets"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["First time seen command line argument", "Detect Prohibited Applications Spawning cmd exe", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "System Processes Run From Unexpected Locations"] +searches = ["First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Prohibited Applications Spawning cmd exe"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Clients Connecting to Multiple DNS Servers", "Detect hosts connecting to dynamic domain providers", "Excessive DNS Failures", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response"] +searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length With High Standard Deviation", "Detect Long DNS TXT Record Response", "Excessive DNS Failures", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions", "Email Attachments With Lots Of Spaces"] +searches = ["Email Attachments With Lots Of Spaces", "Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Suspicious Email Attachment Extensions"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Okta User Logins From Multiple Cities", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts"] +searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts", "Okta User Logins From Multiple Cities"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Script Execution via WMI", "WMI Permanent Event Subscription", "Remote WMI Command Attempt", "WMI Temporary Event Subscription", "Remote Process Instantiation via WMI", "WMI Permanent Event Subscription - Sysmon", "Process Execution via WMI"] +searches = ["WMI Permanent Event Subscription - Sysmon", "Remote WMI Command Attempt", "Script Execution via WMI", "Remote Process Instantiation via WMI", "Process Execution via WMI", "WMI Temporary Event Subscription", "WMI Permanent Event Subscription"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Suspicious Changes to File Associations", "Disabling Remote User Account Control", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Privilege Escalation", "Remote Registry Key modifications"] +searches = ["Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Registry Keys Used For Persistence", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Suspicious Changes to File Associations", "Monitor Registry Keys for Print Monitors", "Disabling Remote User Account Control"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Uncommon Processes On Endpoint", "Detect Rare Executables", "RunDLL Loading DLL By Ordinal", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect processes used for System Network Configuration Discovery", "System Processes Run From Unexpected Locations"] +searches = ["Detect Rare Executables", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Uncommon Processes On Endpoint"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Account Harvesting"] +searches = ["Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Account Harvesting"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Suspicious Reg exe Process", "Reg exe used to hide files directories via registry keys", "Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Remote Registry Key modifications"] +searches = ["Reg exe used to hide files directories via registry keys", "Hiding Files And Directories With Attrib exe", "Suspicious Reg exe Process", "Remote Registry Key modifications", "Disabling Remote User Account Control"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Suspicious Changes to File Associations"] +searches = ["Suspicious Changes to File Associations", "Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Windows Event Log Cleared", "USN Journal Deletion", "Suspicious wevtutil Usage", "Deleting Shadow Copies"] +searches = ["Suspicious wevtutil Usage", "Windows Event Log Cleared", "Deleting Shadow Copies", "USN Journal Deletion"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Path Interception By Creation Of program exe", "Shim Database File Creation", "Monitor Registry Keys for Print Monitors", "Sc exe Manipulating Windows Services", "Reg exe used to hide files directories via registry keys", "Reg exe Manipulating Windows Services Registry Keys", "Registry Keys Used For Persistence", "Shim Database Installation With Suspicious Parameters", "Hiding Files And Directories With Attrib exe", "Registry Keys for Creating SHIM Databases", "Schtasks used for forcing a reboot", "Remote Registry Key modifications"] +searches = ["Reg exe used to hide files directories via registry keys", "Schtasks used for forcing a reboot", "Registry Keys Used For Persistence", "Reg exe Manipulating Windows Services Registry Keys", "Hiding Files And Directories With Attrib exe", "Sc exe Manipulating Windows Services", "Shim Database File Creation", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Shim Database Installation With Suspicious Parameters", "Detect Path Interception By Creation Of program exe", "Monitor Registry Keys for Print Monitors"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Uncommon Processes On Endpoint", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation"] +searches = ["Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Reg exe Manipulating Windows Services Registry Keys", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] +searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 865538a209cd4f249551fa14d03e7ee435f03c66 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 14:16:14 +0200 Subject: [PATCH 23/93] bug in generate --- bin/generate.py | 8 + bin/jinja2_templates/analytic_stories.j2 | 4 + bin/jinja2_templates/savedsearches.j2 | 2 +- package/default/analytic_stories.conf | 94 +++++------ package/default/macros.conf | 2 +- package/default/savedsearches.conf | 206 +++++++++++------------ package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 96 +++++------ 8 files changed, 213 insertions(+), 201 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 5027429980..24ddb8f08b 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -70,6 +70,14 @@ def generate_savedsearches_conf(detections, response_tasks, baselines, deploymen if len(nes_fields) > 0: detection['nes_fields'] = nes_fields + keys = ['mitre_attack', 'kill_chain_phases', 'cis20', 'nist'] + mappings = {} + for key in keys: + if key in detection: + mappings[key] = detection[key] + + detection['mappings'] = mappings + for baseline in baselines: data_model = parse_data_models_from_search(baseline['search']) diff --git a/bin/jinja2_templates/analytic_stories.j2 b/bin/jinja2_templates/analytic_stories.j2 index 1317ee5315..9af67de1a5 100644 --- a/bin/jinja2_templates/analytic_stories.j2 +++ b/bin/jinja2_templates/analytic_stories.j2 @@ -23,7 +23,11 @@ mappings = {{ story.mappings | tojson }} investigative_searches = {{ story.response_tasks | tojson }} {% endif %} support_searches = none +{% if story.data_models is defined %} +data_models = {{ story.data_models | tojson }} +{% else %} data_models = none +{% endif %} providing_technologies = none description = {{ story.description }} {% if story.narrative is defined %} diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index cc0b0dea71..44100cb886 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -14,7 +14,7 @@ action.escu.enabled = 1 description = {{ detection.description }} action.escu.mappings = {{ detection.tags | tojson }} {% if detection.data_model is defined %} -action.escu.data_models = {{ detection.data_model }} +action.escu.data_models = [{{ detection.data_model }}] {% endif %} action.escu.eli5 = {{ detection.description }} {% if detection.how_to_implement is defined %} diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 169b75d163..6b476f9e6c 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T09:21:06 UTC +# On Date: 2020-05-08T12:14:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -101,7 +101,7 @@ reference = ["https://www.sans.org/media/critical-security-controls/critical-con detection_searches = ["Detect Excessive Account Lockouts From Endpoint", "Detect Excessive User Account Lockouts", "Identify New User Accounts", "Short Lived Windows Accounts"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} support_searches = none -data_models = none +data_models = ["Change"] providing_technologies = none description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -116,7 +116,7 @@ reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/ detection_searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ @@ -144,7 +144,7 @@ reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-un detection_searches = ["Detect Unauthorized Assets by MAC address"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} support_searches = none -data_models = none +data_models = ["Network_Sessions"] providing_technologies = none description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -159,7 +159,7 @@ reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "h detection_searches = ["Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} support_searches = none -data_models = none +data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ @@ -176,7 +176,7 @@ reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.p detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Started In Previously Unused Region"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} support_searches = none -data_models = none +data_models = ["Cloud_Infrastructure"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ @@ -211,7 +211,7 @@ reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.o detection_searches = ["Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ @@ -228,7 +228,7 @@ reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searc detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ @@ -244,7 +244,7 @@ reference = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/ detection_searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1192"], "nist": ["DE.CM"]} support_searches = none -data_models = none +data_models = ["Network_Resolution"] providing_technologies = none description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. narrative = As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ @@ -275,7 +275,7 @@ reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberward detection_searches = ["Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Attempted Credential Dump From Registry via Reg exe", "Create Remote Thread into LSASS", "Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ @@ -292,7 +292,7 @@ reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["Create local admin accounts using net exe", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Malicious PowerShell Process - Execution Policy Bypass", "Processes launching netsh", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Sc exe Manipulating Windows Services", "Scheduled Task Name Used by Dragonfly Threat Actors", "Single Letter Process On Endpoint", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ @@ -310,7 +310,7 @@ reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imper detection_searches = ["Large Volume of DNS ANY Queries"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} support_searches = none -data_models = none +data_models = ["Network_Resolution"] providing_technologies = none description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ @@ -326,7 +326,7 @@ reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insight detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Network_Resolution"] providing_technologies = none description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ @@ -349,7 +349,7 @@ reference = ["https://www.cisecurity.org/controls/data-protection/", "https://ww detection_searches = ["Detect USB device insertion", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -364,7 +364,7 @@ reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malw detection_searches = ["Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Unload Sysmon Filter Driver"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -379,7 +379,7 @@ reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insight detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} support_searches = none -data_models = none +data_models = ["Network_Resolution", "Web"] providing_technologies = none description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -394,7 +394,7 @@ reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first detection_searches = ["Detect Rare Executables", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Email Attachments With Lots Of Spaces", "Prohibited Software On Endpoint", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ @@ -411,7 +411,7 @@ reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber- detection_searches = ["Create or delete windows shares using net exe", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "Detect Outbound SMB Traffic", "First time seen command line argument", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious File Write"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ @@ -429,7 +429,7 @@ reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijack detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Network_Resolution"] providing_technologies = none description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -444,7 +444,7 @@ reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-vi detection_searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} support_searches = none -data_models = none +data_models = ["Web"] providing_technologies = none description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ @@ -488,7 +488,7 @@ reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-th detection_searches = ["Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} support_searches = none -data_models = none +data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ @@ -507,7 +507,7 @@ reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to detection_searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ @@ -546,7 +546,7 @@ reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic- detection_searches = ["Prohibited Software On Endpoint"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ @@ -562,7 +562,7 @@ reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["No Windows Updates in a time frame"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} support_searches = none -data_models = none +data_models = ["Updates"] providing_technologies = none description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ @@ -579,7 +579,7 @@ reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htm detection_searches = ["Processes created by netsh", "Processes launching netsh"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ @@ -595,7 +595,7 @@ reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targ detection_searches = ["First Time Seen Running Windows Service", "First time seen command line argument", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ @@ -636,7 +636,7 @@ reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attack detection_searches = ["First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ @@ -678,7 +678,7 @@ reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} support_searches = none -data_models = none +data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -693,7 +693,7 @@ reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-researc detection_searches = ["Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Registry Keys Used For Persistence", "Remote Process Instantiation via WMI", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Scheduled tasks used in BadRabbit ransomware", "Schtasks used for forcing a reboot", "Spike in File Writes", "Suspicious wevtutil Usage", "System Processes Run From Unexpected Locations", "TOR Traffic", "USN Journal Deletion", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -708,7 +708,7 @@ reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new detection_searches = ["Detect New Login Attempts to Routers"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} support_searches = none -data_models = none +data_models = ["Authentication"] providing_technologies = none description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ @@ -724,7 +724,7 @@ reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.in detection_searches = ["SQL Injection with Long URLs"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} support_searches = none -data_models = none +data_models = ["Web"] providing_technologies = none description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ @@ -740,7 +740,7 @@ reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ra detection_searches = ["Batch File Write to System32", "Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Detect PsExec With accepteula Flag", "Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers", "File with Samsam Extension", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Samsam Test File Write", "Spike in File Writes"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ @@ -760,7 +760,7 @@ reference = ["https://meltdownattack.com/"] detection_searches = ["Spectre and Meltdown Vulnerable Systems"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} support_searches = none -data_models = none +data_models = ["Vulnerabilities"] providing_technologies = none description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -882,7 +882,7 @@ reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.micro detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -897,7 +897,7 @@ reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Network_Resolution"] providing_technologies = none description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -912,7 +912,7 @@ reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-o detection_searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} support_searches = none -data_models = none +data_models = ["Email", "UEBA"] providing_technologies = none description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ @@ -931,7 +931,7 @@ reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detecti detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ @@ -965,7 +965,7 @@ reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusin detection_searches = ["Process Execution via WMI", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ @@ -982,7 +982,7 @@ reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detecti detection_searches = ["Disabling Remote User Account Control", "Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ @@ -1015,7 +1015,7 @@ reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-wi detection_searches = ["Detect Rare Executables", "Detect processes used for System Network Configuration Discovery", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Uncommon Processes On Endpoint", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ @@ -1032,7 +1032,7 @@ reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["Protocols passing authentication in cleartext"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} support_searches = none -data_models = none +data_models = ["Network_Traffic"] providing_technologies = none description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -1067,7 +1067,7 @@ reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -1082,7 +1082,7 @@ reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2 detection_searches = ["Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ @@ -1101,7 +1101,7 @@ reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic- detection_searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ @@ -1117,7 +1117,7 @@ reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fire detection_searches = ["Detect Path Interception By Creation Of program exe", "Hiding Files And Directories With Attrib exe", "Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -1132,7 +1132,7 @@ reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -1147,7 +1147,7 @@ reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mi detection_searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} support_searches = none -data_models = none +data_models = ["Endpoint"] providing_technologies = none description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. diff --git a/package/default/macros.conf b/package/default/macros.conf index 5d8ccb119b..80f70e99e7 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T09:21:06 UTC +# On Date: 2020-05-08T12:14:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index a107bc33d2..450af1e543 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T09:21:06 UTC +# On Date: 2020-05-08T12:14:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -500,7 +500,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attempt to add a certificate to the untrusted certificate store action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. @@ -536,7 +536,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.mappings = {"analytics_story": ["Credential Dumping", "Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. action.escu.known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. @@ -572,7 +572,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for attempts to stop security-related services on the endpoint. action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., action.escu.known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. @@ -608,7 +608,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -642,7 +642,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. @@ -678,7 +678,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. action.escu.known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. @@ -714,7 +714,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.mappings = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ @@ -752,7 +752,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances created by users who have not created them before. action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. action.escu.known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. @@ -788,7 +788,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. action.escu.known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. @@ -824,7 +824,7 @@ action.escu = 0 action.escu.enabled = 1 description = Find EC2 instances being created with previously unseen instance types. action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. @@ -860,7 +860,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. @@ -896,7 +896,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file modifications with extensions commonly used by Ransomware action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ @@ -936,7 +936,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. @@ -1005,7 +1005,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of local administrator accounts using net.exe. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create admin accounts. @@ -1041,7 +1041,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. @@ -1077,7 +1077,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. @@ -1144,7 +1144,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects credential dumping using copy command from a shadow copy. action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1178,7 +1178,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the creation of a symlink to a shadow copy. action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1212,7 +1212,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -1254,7 +1254,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It's possible there can be long domain names that are legitimate. @@ -1289,7 +1289,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.mappings = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. action.escu.known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. @@ -1325,7 +1325,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.mappings = {"analytics_story": ["DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ **Splunk>Phantom Playbook Integration**\ @@ -1365,7 +1365,7 @@ action.escu = 0 action.escu.enabled = 1 description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. @@ -1656,7 +1656,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.mappings = {"analytics_story": ["Common Phishing Frameworks"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ **Splunk>Phantom Playbook Integration**\ @@ -1696,7 +1696,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} -action.escu.data_models = Change +action.escu.data_models = [Change] action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ **Splunk>Phantom Playbook Integration**\ @@ -1736,7 +1736,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} -action.escu.data_models = Change +action.escu.data_models = [Change] action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. action.escu.known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. @@ -1772,7 +1772,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.mappings = {"analytics_story": ["Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1095"], "nist": ["DE.AE"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. @@ -1807,7 +1807,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.mappings = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. action.escu.known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. @@ -1949,7 +1949,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.mappings = {"analytics_story": ["Router and Infrastructure Security"], "asset_type": "Endpoint", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"], "security_domain": "network"} -action.escu.data_models = Authentication +action.escu.data_models = [Authentication] action.escu.eli5 = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. action.escu.known_false_positives = Legitimate router connections may appear as new connections @@ -2055,7 +2055,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. @@ -2090,7 +2090,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. action.escu.known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. @@ -2126,7 +2126,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. action.escu.known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. @@ -2162,7 +2162,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine @@ -2198,7 +2198,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.mappings = {"analytics_story": ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. action.escu.known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. @@ -2448,7 +2448,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.mappings = {"analytics_story": ["Data Protection"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"], "security_domain": "endpoint"} -action.escu.data_models = Change_Analysis +action.escu.data_models = [Change_Analysis] action.escu.eli5 = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. action.escu.known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. @@ -2484,7 +2484,7 @@ action.escu = 0 action.escu.enabled = 1 description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.mappings = {"analytics_story": ["Asset Tracking"], "asset_type": "Infrastructure", "cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} -action.escu.data_models = Network_Sessions +action.escu.data_models = [Network_Sessions] action.escu.eli5 = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. action.escu.known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. @@ -2519,7 +2519,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Some legitimate applications may exhibit this behavior. @@ -2555,7 +2555,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.mappings = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "kill_chain_phases": ["Reconnaissance"], "mitre_attack_id": ["T1082"], "security_domain": "network"} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. action.escu.known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. @@ -2591,7 +2591,7 @@ action.escu = 0 action.escu.enabled = 1 description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -2632,7 +2632,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.mappings = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model action.escu.known_false_positives = No known false positives for this detection. @@ -2668,7 +2668,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.mappings = {"analytics_story": ["Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. @@ -2774,7 +2774,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.mappings = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. action.escu.known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. @@ -2810,7 +2810,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for web connections to dynamic DNS providers. action.escu.mappings = {"analytics_story": ["Dynamic DNS"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"], "security_domain": "network"} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for web connections to dynamic DNS providers. action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ @@ -2848,7 +2848,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.mappings = {"analytics_story": ["Data Protection", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "PR.DS"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. action.escu.known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. @@ -2884,7 +2884,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.mappings = {"analytics_story": ["Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1072", "T1087"], "nist": ["PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. @@ -2955,7 +2955,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -3162,7 +3162,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} -action.escu.data_models = Email +action.escu.data_models = [Email] action.escu.eli5 = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ **Splunk Phantom Playbook Integration**\ @@ -3199,7 +3199,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. @@ -3235,7 +3235,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -3270,7 +3270,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.mappings = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. @@ -3305,7 +3305,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = None identified. @@ -3341,7 +3341,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. action.escu.known_false_positives = None identified. @@ -3412,7 +3412,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. @@ -3483,7 +3483,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. action.escu.known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name @@ -3587,7 +3587,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.mappings = {"analytics_story": ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. @@ -3623,7 +3623,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -3692,7 +3692,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.mappings = {"analytics_story": ["DNS Amplification Attacks"], "asset_type": "DNS Servers", "cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. @@ -3727,7 +3727,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.mappings = {"asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"], "security_domain": "threat"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. action.escu.known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. @@ -3762,7 +3762,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.mappings = {"analytics_story": ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -3798,7 +3798,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = System administrators may use this option, but it's not common. @@ -3834,7 +3834,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. @@ -3870,7 +3870,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -3906,7 +3906,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = These characters might be legitimately on the command-line, but it is not common. @@ -3942,7 +3942,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.mappings = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "kill_chain_phases": ["Delivery", "Actions on Objectives"], "security_domain": "network"} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -3977,7 +3977,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} -action.escu.data_models = Email +action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4047,7 +4047,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.mappings = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4152,7 +4152,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.mappings = {"analytics_story": ["Monitor for Updates"], "asset_type": "Endpoint", "cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"], "security_domain": "endpoint"} -action.escu.data_models = Updates +action.escu.data_models = [Updates] action.escu.eli5 = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. action.escu.known_false_positives = None identified @@ -4359,7 +4359,7 @@ action.escu = 0 action.escu.enabled = 1 description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. @@ -4464,7 +4464,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.mappings = {"analytics_story": ["Netsh Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. @@ -4500,7 +4500,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model action.escu.known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. @@ -4536,7 +4536,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None identified @@ -4571,7 +4571,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. action.escu.known_false_positives = None identified @@ -4607,7 +4607,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. action.escu.known_false_positives = None identified @@ -4642,7 +4642,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.mappings = {"analytics_story": ["Use of Cleartext Protocols"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. action.escu.known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. @@ -4713,7 +4713,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None at the moment @@ -4853,7 +4853,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. action.escu.known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. @@ -4889,7 +4889,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -4925,7 +4925,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -4961,7 +4961,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.mappings = {"analytics_story": ["Suspicious WMI Use", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. @@ -5032,7 +5032,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may use this legitimately to gather info from remote systems. @@ -5068,7 +5068,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.mappings = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1085"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process @@ -5104,7 +5104,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. action.escu.known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. @@ -5140,7 +5140,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ @@ -5179,7 +5179,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for long URLs that have several SQL commands visible within them. action.escu.mappings = {"analytics_story": ["SQL Injection"], "asset_type": "Database Server", "cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"], "security_domain": "network"} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. action.escu.known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. @@ -5215,7 +5215,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = No false positives have been identified. @@ -5251,7 +5251,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.mappings = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. @@ -5287,7 +5287,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -5323,7 +5323,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.mappings = {"analytics_story": ["Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -5359,7 +5359,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.mappings = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. @@ -5395,7 +5395,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. @@ -5501,7 +5501,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -5537,7 +5537,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects accounts that were created and deleted in a short time period. action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} -action.escu.data_models = Change +action.escu.data_models = [Change] action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ action.escu.known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. @@ -5573,7 +5573,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for process names that consist only of a single letter. action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for process names that consist only of a single letter. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. @@ -5608,7 +5608,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.mappings = {"analytics_story": ["Spectre And Meltdown Vulnerabilities"], "asset_type": "Endpoint", "cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Vulnerabilities +action.escu.data_models = [Vulnerabilities] action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. action.escu.known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. @@ -5748,7 +5748,7 @@ action.escu = 0 action.escu.enabled = 1 description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.mappings = {"analytics_story": ["Suspicious Emails"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "threat"} -action.escu.data_models = UEBA +action.escu.data_models = [UEBA] action.escu.eli5 = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. action.escu.known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. @@ -5784,7 +5784,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails that have attachments with suspicious file extensions. action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"], "security_domain": "network"} -action.escu.data_models = Email +action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ **Splunk Phantom Playbook Integration**\ @@ -5961,7 +5961,7 @@ action.escu = 0 action.escu.enabled = 1 description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.mappings = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. @@ -6101,7 +6101,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE"], "security_domain": "network"} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None at this time @@ -6136,7 +6136,7 @@ action.escu = 0 action.escu.enabled = 1 description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.mappings = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -6172,7 +6172,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. action.escu.known_false_positives = None identified @@ -6208,7 +6208,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. action.escu.known_false_positives = @@ -6623,7 +6623,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious processes on all systems labeled as web servers. action.escu.mappings = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1082"], "nist": ["PR.IP"], "security_domain": "endpoint"} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for suspicious processes on all systems labeled as web servers. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. action.escu.known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. diff --git a/package/default/transforms.conf b/package/default/transforms.conf index f1b97b61f1..38d8f3ebc6 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T09:21:06 UTC +# On Date: 2020-05-08T12:14:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index ffc8a80891..895e5bd30d 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T09:21:06 UTC +# On Date: 2020-05-08T12:14:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started With Previously Unseen User"] +searches = ["EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen Instance Type"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity", "AWS Network Access Control List Created with All Open Ports", "AWS Network Access Control List Deleted"] +searches = ["AWS Network Access Control List Deleted", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity", "AWS Network Access Control List Created with All Open Ports"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["AWS Cloud Provisioning From Previously Unseen Region", "AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen IP Address"] +searches = ["AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Region", "AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Country"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Spike in AWS API Activity", "Detect AWS API Activities From Unapproved Accounts", "Detect new API calls from user roles", "Detect Spike in Security Group Activity", "Detect API activity from users without MFA"] +searches = ["Detect API activity from users without MFA", "Detect Spike in Security Group Activity", "Detect Spike in AWS API Activity", "Detect new API calls from user roles", "Detect AWS API Activities From Unapproved Accounts"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Short Lived Windows Accounts", "Identify New User Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint"] +searches = ["Detect Excessive User Account Lockouts", "Identify New User Accounts", "Detect Excessive Account Lockouts From Endpoint", "Short Lived Windows Accounts"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Monitor Web Traffic For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse"] +searches = ["Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Cloud Compute Instance Started In Previously Unused Region", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type"] +searches = ["Cloud Compute Instance Created With Previously Unseen Image", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Started In Previously Unused Region", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["Processes Tapping Keyboard Events", "Osquery pack - ColdRoot detection"] +searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Email files written outside of the Outlook directory", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to windows Recycle Bin", "Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts"] +searches = ["Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin", "Email files written outside of the Outlook directory", "Hosts receiving high volume of network traffic from email server", "Email servers sending high volume traffic to hosts"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "TOR Traffic", "Prohibited Network Traffic Allowed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length With High Standard Deviation", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Excessive DNS Failures", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "Protocol or Port Mismatch"] +searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Spike in blocked Outbound Traffic from your AWS", "Clients Connecting to Multiple DNS Servers", "Excessive DNS Failures", "Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Detect Long DNS TXT Record Response", "Protocol or Port Mismatch", "Detect Large Outbound ICMP Packets", "DNS Query Length With High Standard Deviation", "TOR Traffic", "Detection of DNS Tunnels", "DNS Query Length Outliers - MLTK"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] +searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Access LSASS Memory for Dump Creation", "Creation of Shadow Copy with wmic and powershell", "Detect Credential Dumping through LSASS access", "Creation of Shadow Copy", "Credential Dumping via Copy Command from Shadow Copy", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Detect Mimikatz Using Loaded Images", "Unsigned Image Loaded by LSASS", "Create Remote Thread into LSASS", "Dump LSASS via comsvcs DLL", "Credential Dumping via Symlink to Shadow Copy", "Attempted Credential Dump From Registry via Reg exe"] +searches = ["Dump LSASS via comsvcs DLL", "Credential Dumping via Symlink to Shadow Copy", "Credential Dumping via Copy Command from Shadow Copy", "Create Remote Thread into LSASS", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Unsigned Image Loaded by LSASS", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Creation of Shadow Copy with wmic and powershell", "Access LSASS Memory for Dump Creation", "Attempted Credential Dump From Registry via Reg exe", "Creation of Shadow Copy"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["SMB Traffic Spike - MLTK", "First time seen command line argument", "Registry Keys Used For Persistence", "Suspicious Reg exe Process", "Create local admin accounts using net exe", "Sc exe Manipulating Windows Services", "Detect Outbound SMB Traffic", "Scheduled Task Name Used by Dragonfly Threat Actors", "Processes launching netsh", "SMB Traffic Spike", "Detect New Local Admin account", "Detect PsExec With accepteula Flag", "Malicious PowerShell Process - Execution Policy Bypass", "Single Letter Process On Endpoint"] +searches = ["First time seen command line argument", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "SMB Traffic Spike - MLTK", "Single Letter Process On Endpoint", "Scheduled Task Name Used by Dragonfly Threat Actors", "SMB Traffic Spike", "Processes launching netsh", "Detect PsExec With accepteula Flag", "Malicious PowerShell Process - Execution Policy Bypass", "Create local admin accounts using net exe", "Registry Keys Used For Persistence"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers"] +searches = ["DNS record changed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Detect hosts connecting to dynamic domain providers"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detection of DNS Tunnels", "Detect USB device insertion", "Detect hosts connecting to dynamic domain providers"] +searches = ["Detect USB device insertion", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Unload Sysmon Filter Driver", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "Processes launching netsh", "Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service"] +searches = ["Attempt To Add Certificate To Untrusted Store", "Unload Sysmon Filter Driver", "Suspicious Reg exe Process", "Attempt To Stop Security Service", "Sc exe Manipulating Windows Services", "Processes launching netsh"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] +searches = ["Detect web traffic to dynamic domain providers", "Detect hosts connecting to dynamic domain providers"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Rare Executables", "Email Attachments With Lots Of Spaces", "Registry Keys Used For Persistence", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions", "Detection of tools built by NirSoft", "SMB Traffic Spike", "Detect Use of cmd exe to Launch Script Interpreters", "Prohibited Software On Endpoint"] +searches = ["Prohibited Software On Endpoint", "Detection of tools built by NirSoft", "Detect Rare Executables", "Suspicious Email Attachment Extensions", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike - MLTK", "Detect Use of cmd exe to Launch Script Interpreters", "SMB Traffic Spike", "Registry Keys Used For Persistence"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Remote Desktop Process Running On System", "SMB Traffic Spike - MLTK", "First time seen command line argument", "Detect Outbound SMB Traffic", "DNS Query Length With High Standard Deviation", "SMB Traffic Spike", "Suspicious File Write", "Create or delete windows shares using net exe", "Remote Desktop Network Traffic", "DNS Query Length Outliers - MLTK"] +searches = ["First time seen command line argument", "Create or delete windows shares using net exe", "Detect Outbound SMB Traffic", "Suspicious File Write", "Remote Desktop Process Running On System", "DNS Query Length With High Standard Deviation", "SMB Traffic Spike - MLTK", "Remote Desktop Network Traffic", "SMB Traffic Spike", "DNS Query Length Outliers - MLTK"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification", "Clients Connecting to Multiple DNS Servers"] +searches = ["Windows hosts file modification", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] +searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] +searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Remote Desktop Process Running On System", "Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Schtasks scheduling job on remote system"] +searches = ["Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system", "Detect Activity Related to Pass the Hash Attacks"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Connect To Internet With Hidden Window"] +searches = ["Malicious PowerShell Process With Obfuscation Techniques", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Processes created by netsh", "Processes launching netsh"] +searches = ["Processes launching netsh", "Processes created by netsh"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process"] +searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["First time seen command line argument", "Registry Keys Used For Persistence", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] +searches = ["First time seen command line argument", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["TOR Traffic", "Prohibited Network Traffic Allowed", "Detect hosts connecting to dynamic domain providers", "Protocol or Port Mismatch"] +searches = ["TOR Traffic", "Protocol or Port Mismatch", "Prohibited Network Traffic Allowed", "Detect hosts connecting to dynamic domain providers"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["SMB Traffic Spike - MLTK", "Schtasks used for forcing a reboot", "Registry Keys Used For Persistence", "Prohibited Network Traffic Allowed", "Windows Event Log Cleared", "System Processes Run From Unexpected Locations", "Remote Process Instantiation via WMI", "Common Ransomware Notes", "SMB Traffic Spike", "Spike in File Writes", "USN Journal Deletion", "Common Ransomware Extensions", "Unusually Long Command Line", "Suspicious wevtutil Usage", "Unusually Long Command Line - MLTK", "Deleting Shadow Copies", "Scheduled tasks used in BadRabbit ransomware", "TOR Traffic"] +searches = ["Common Ransomware Notes", "System Processes Run From Unexpected Locations", "Suspicious wevtutil Usage", "Prohibited Network Traffic Allowed", "Deleting Shadow Copies", "Common Ransomware Extensions", "Scheduled tasks used in BadRabbit ransomware", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared", "Spike in File Writes", "SMB Traffic Spike - MLTK", "Schtasks used for forcing a reboot", "SMB Traffic Spike", "TOR Traffic", "USN Journal Deletion", "Remote Process Instantiation via WMI", "Registry Keys Used For Persistence"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Common Ransomware Notes", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Spike in File Writes", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Traffic", "Samsam Test File Write", "Common Ransomware Extensions", "Detect PsExec With accepteula Flag", "File with Samsam Extension", "Batch File Write to System32", "Detect malicious requests to exploit JBoss servers", "Deleting Shadow Copies"] +searches = ["Common Ransomware Notes", "Prohibited Software On Endpoint", "Batch File Write to System32", "Deleting Shadow Copies", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Extensions", "File with Samsam Extension", "Detect attackers scanning for vulnerable JBoss servers", "Spike in File Writes", "Remote Desktop Network Traffic", "Remote Desktop Network Bruteforce", "Detect PsExec With accepteula Flag", "Samsam Test File Write"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User"] +searches = ["Abnormally High AWS Instances Launched by User - MLTK", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Terminated by User - MLTK"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Country", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New Region"] +searches = ["Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New City", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New Country"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Spike in S3 Bucket deletion", "Detect S3 access from a new IP", "Detect New Open S3 buckets"] +searches = ["Detect New Open S3 buckets", "Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Prohibited Applications Spawning cmd exe"] +searches = ["Detect Prohibited Applications Spawning cmd exe", "System Processes Run From Unexpected Locations", "First time seen command line argument", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Detect Use of cmd exe to Launch Script Interpreters"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length With High Standard Deviation", "Detect Long DNS TXT Record Response", "Excessive DNS Failures", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK"] +searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Excessive DNS Failures", "Detect hosts connecting to dynamic domain providers", "Detect Long DNS TXT Record Response", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "DNS Query Length Outliers - MLTK"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Email Attachments With Lots Of Spaces", "Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Suspicious Email Attachment Extensions"] +searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Registry Keys Used For Persistence", "Detect mshta exe running scripts in command-line arguments", "Detect Prohibited Applications Spawning cmd exe"] +searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts", "Okta User Logins From Multiple Cities"] +searches = ["Okta Failed SSO Attempts", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta User Logins From Multiple Cities"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["WMI Permanent Event Subscription - Sysmon", "Remote WMI Command Attempt", "Script Execution via WMI", "Remote Process Instantiation via WMI", "Process Execution via WMI", "WMI Temporary Event Subscription", "WMI Permanent Event Subscription"] +searches = ["WMI Permanent Event Subscription - Sysmon", "Process Execution via WMI", "Remote Process Instantiation via WMI", "WMI Temporary Event Subscription", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Registry Keys Used For Persistence", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Suspicious Changes to File Associations", "Monitor Registry Keys for Print Monitors", "Disabling Remote User Account Control"] +searches = ["Suspicious Changes to File Associations", "Registry Keys Used For Privilege Escalation", "Remote Registry Key modifications", "Monitor Registry Keys for Print Monitors", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Rare Executables", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Uncommon Processes On Endpoint"] +searches = ["System Processes Run From Unexpected Locations", "Detect Rare Executables", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal", "Uncommon Processes On Endpoint", "Detect processes used for System Network Configuration Discovery"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Account Harvesting"] +searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Account Harvesting", "Web Fraud - Password Sharing Across Accounts"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Reg exe used to hide files directories via registry keys", "Hiding Files And Directories With Attrib exe", "Suspicious Reg exe Process", "Remote Registry Key modifications", "Disabling Remote User Account Control"] +searches = ["Suspicious Reg exe Process", "Remote Registry Key modifications", "Hiding Files And Directories With Attrib exe", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious wevtutil Usage", "Windows Event Log Cleared", "Deleting Shadow Copies", "USN Journal Deletion"] +searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Reg exe used to hide files directories via registry keys", "Schtasks used for forcing a reboot", "Registry Keys Used For Persistence", "Reg exe Manipulating Windows Services Registry Keys", "Hiding Files And Directories With Attrib exe", "Sc exe Manipulating Windows Services", "Shim Database File Creation", "Remote Registry Key modifications", "Registry Keys for Creating SHIM Databases", "Shim Database Installation With Suspicious Parameters", "Detect Path Interception By Creation Of program exe", "Monitor Registry Keys for Print Monitors"] +searches = ["Shim Database File Creation", "Detect Path Interception By Creation Of program exe", "Remote Registry Key modifications", "Monitor Registry Keys for Print Monitors", "Hiding Files And Directories With Attrib exe", "Sc exe Manipulating Windows Services", "Reg exe used to hide files directories via registry keys", "Schtasks used for forcing a reboot", "Reg exe Manipulating Windows Services Registry Keys", "Shim Database Installation With Suspicious Parameters", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries"] +searches = ["Uncommon Processes On Endpoint", "Overwriting Accessibility Binaries", "Child Processes of Spoolsv exe", "Registry Keys Used For Privilege Escalation"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] +searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 260c9118272b79d0555528f0a3bb2904f0fca082 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 14:53:55 +0200 Subject: [PATCH 24/93] bug in generate --- bin/generate.py | 15 +- bin/jinja2_templates/analytic_stories.j2 | 4 +- bin/jinja2_templates/savedsearches.j2 | 2 +- package/default/analytic_stories.conf | 197 ++++++++---- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 380 +++++++++++------------ package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 132 ++++---- 8 files changed, 403 insertions(+), 331 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 24ddb8f08b..52c217114f 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -73,8 +73,13 @@ def generate_savedsearches_conf(detections, response_tasks, baselines, deploymen keys = ['mitre_attack', 'kill_chain_phases', 'cis20', 'nist'] mappings = {} for key in keys: - if key in detection: - mappings[key] = detection[key] + if key == 'mitre_attack': + if 'mitre_attack_id' in detection: + mappings[key] = detection['mitre_attack_id'] + else: + if key in detection: + mappings[key] = detection[key] + detection['mappings'] = mappings @@ -256,9 +261,9 @@ def map_detection_to_stories(detections): def map_response_tasks_to_stories(response_tasks): sto_res = {} for response_task in response_tasks: - if 'tags' in response_tasks: - if 'analytics_story' in response_tasks['tags']: - for story in response_tasks['tags']['analytics_story']: + if 'tags' in response_task: + if 'analytics_story' in response_task['tags']: + for story in response_task['tags']['analytics_story']: if not (story in sto_res): sto_res[story] = {response_task['name']} else: diff --git a/bin/jinja2_templates/analytic_stories.j2 b/bin/jinja2_templates/analytic_stories.j2 index 9af67de1a5..47e3efbbf8 100644 --- a/bin/jinja2_templates/analytic_stories.j2 +++ b/bin/jinja2_templates/analytic_stories.j2 @@ -21,8 +21,10 @@ mappings = {{ story.mappings | tojson }} {% endif %} {% if story.response_tasks is defined %} investigative_searches = {{ story.response_tasks | tojson }} +{% else %} +investigative_searches = [] {% endif %} -support_searches = none +support_searches = [] {% if story.data_models is defined %} data_models = {{ story.data_models | tojson }} {% else %} diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 44100cb886..6c89f2fccb 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -12,7 +12,7 @@ action.escu = 0 action.escu.enabled = 1 description = {{ detection.description }} -action.escu.mappings = {{ detection.tags | tojson }} +action.escu.mappings = {{ detection.mappings | tojson }} {% if detection.data_model is defined %} action.escu.data_models = [{{ detection.data_model }}] {% endif %} diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 6b476f9e6c..523050bdca 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T12:14:41 UTC +# On Date: 2020-05-08T12:53:42 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,8 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["AWS Cross Account Activity From Previously Unseen Account"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -support_searches = none +investigative_searches = ["AWS Investigate User Activities By AccessKeyId", "Get Notable History", "AWS Investigate User Activities By Source User"] +support_searches = [] data_models = none providing_technologies = none description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. @@ -33,7 +34,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started With Previously Unseen User"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +support_searches = [] data_models = none providing_technologies = none description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -51,7 +53,8 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["AWS Network Access Control List Created with All Open Ports", "AWS Network Access Control List Deleted", "Detect Spike in Network ACL Activity", "Detect Spike in blocked Outbound Traffic from your AWS"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +support_searches = [] data_models = none providing_technologies = none description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. @@ -66,7 +69,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -support_searches = none +investigative_searches = ["Get All AWS Activity From City", "Get All AWS Activity From Region", "Get All AWS Activity From IP Address", "Get All AWS Activity From Country"] +support_searches = [] data_models = none providing_technologies = none description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. @@ -82,7 +86,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["Detect API activity from users without MFA", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in AWS API Activity", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -support_searches = none +investigative_searches = ["Investigate AWS User Activities by user field", "Get Notable Info", "Get Notable History"] +support_searches = [] data_models = none providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. @@ -100,7 +105,8 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["Detect Excessive Account Lockouts From Endpoint", "Detect Excessive User Account Lockouts", "Identify New User Accounts", "Short Lived Windows Accounts"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Logon Rights Modifications For User", "Get Logon Rights Modifications For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Change"] providing_technologies = none description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. @@ -115,7 +121,8 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Suspicious Strings in HTTP Header", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Investigate Web POSTs From src", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. @@ -143,7 +150,8 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["Detect Unauthorized Assets by MAC address"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get First Occurrence and Last Occurrence of a MAC Address"] +support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. @@ -158,7 +166,8 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] +support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. @@ -175,7 +184,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Started In Previously Unused Region"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Investigate Cloud Compute Instance Activities", "Investigate User Activities In Single Cloud Region", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -193,7 +203,8 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable History", "Get Risk Modifiers For User", "Investigate Network Traffic From src ip", "Get Authentication Logs For Endpoint", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = none providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. @@ -210,7 +221,8 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. @@ -227,7 +239,8 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "Get Parent Process Info", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. @@ -243,7 +256,8 @@ version = 1 reference = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] detection_searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1192"], "nist": ["DE.CM"]} -support_searches = none +investigative_searches = ["Get Certificate logs for a domain"] +support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. @@ -259,7 +273,8 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] mappings = {} -support_searches = none +investigative_searches = ["Investigate AWS ECR container listing activity"] +support_searches = [] data_models = none providing_technologies = none description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. @@ -274,7 +289,8 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Attempted Credential Dump From Registry via Reg exe", "Create Remote Thread into LSASS", "Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -support_searches = none +investigative_searches = ["Investigate Pass the Ticket Attempts", "Investigate Failed Logins for Multiple Destinations", "Investigate Previous Unseen User", "Investigate Pass the Hash Attempts"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. @@ -291,7 +307,8 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["Create local admin accounts using net exe", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Malicious PowerShell Process - Execution Policy Bypass", "Processes launching netsh", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Sc exe Manipulating Windows Services", "Scheduled Task Name Used by Dragonfly Threat Actors", "Single Letter Process On Endpoint", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Registry Activity", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Process File Activity", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. @@ -309,7 +326,8 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["Large Volume of DNS ANY Queries"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -support_searches = none +investigative_searches = ["Get Risk Modifiers For User", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. @@ -325,7 +343,8 @@ version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get DNS Server History for a host"] +support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. @@ -348,7 +367,8 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["Detect USB device insertion", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. @@ -363,7 +383,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Unload Sysmon Filter Driver"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. @@ -378,7 +399,8 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Investigate Web Activity From src ip"] +support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. @@ -393,7 +415,8 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["Detect Rare Executables", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Email Attachments With Lots Of Spaces", "Prohibited Software On Endpoint", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. @@ -410,7 +433,8 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["Create or delete windows shares using net exe", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "Detect Outbound SMB Traffic", "First time seen command line argument", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious File Write"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. @@ -428,7 +452,8 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. @@ -443,7 +468,8 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Investigate Web Activity From Host", "Get Risk Modifiers For Endpoint", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Web"] providing_technologies = none description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. @@ -472,7 +498,8 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "GCP Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint", "Amazon EKS Kubernetes activity by src ip"] +support_searches = [] data_models = none providing_technologies = none description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. @@ -487,7 +514,8 @@ version = 2 reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. @@ -506,7 +534,8 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. @@ -530,7 +559,8 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -support_searches = none +investigative_searches = ["All backup logs for host", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] +support_searches = [] data_models = none providing_technologies = none description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. @@ -545,7 +575,8 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["Prohibited Software On Endpoint"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. @@ -561,7 +592,8 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["No Windows Updates in a time frame"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +support_searches = [] data_models = ["Updates"] providing_technologies = none description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. @@ -578,7 +610,8 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["Processes created by netsh", "Processes launching netsh"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. @@ -594,7 +627,8 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["First Time Seen Running Windows Service", "First time seen command line argument", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. @@ -613,7 +647,8 @@ version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] detection_searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} -support_searches = none +investigative_searches = ["Get Parent Process Info"] +support_searches = [] data_models = none providing_technologies = none description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. @@ -635,7 +670,8 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. @@ -677,7 +713,8 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. @@ -692,7 +729,8 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Registry Keys Used For Persistence", "Remote Process Instantiation via WMI", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Scheduled tasks used in BadRabbit ransomware", "Schtasks used for forcing a reboot", "Spike in File Writes", "Suspicious wevtutil Usage", "System Processes Run From Unexpected Locations", "TOR Traffic", "USN Journal Deletion", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. @@ -707,7 +745,8 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["Detect New Login Attempts to Routers"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Authentication"] providing_technologies = none description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. @@ -723,7 +762,8 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["SQL Injection with Long URLs"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +support_searches = [] data_models = ["Web"] providing_technologies = none description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. @@ -739,7 +779,8 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["Batch File Write to System32", "Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Detect PsExec With accepteula Flag", "Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers", "File with Samsam Extension", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Samsam Test File Write", "Spike in File Writes"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. @@ -759,7 +800,8 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["Spectre and Meltdown Vulnerable Systems"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. @@ -774,7 +816,8 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["Open Redirect in Splunk Web"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +support_searches = [] data_models = none providing_technologies = none description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. @@ -798,7 +841,8 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["Splunk Enterprise Information Disclosure"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Investigate Network Traffic From src ip", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] +support_searches = [] data_models = none providing_technologies = none description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. @@ -816,7 +860,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +support_searches = [] data_models = none providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. @@ -831,7 +876,8 @@ version = 1 reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] detection_searches = ["Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP"]} -support_searches = none +investigative_searches = ["AWS Investigate User Activities By ARN"] +support_searches = [] data_models = none providing_technologies = none description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. @@ -846,7 +892,8 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["Detect New Open S3 buckets", "Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Investigate AWS activities via region name", "AWS S3 Bucket details via bucketName", "Get All AWS Activity From IP Address", "AWS Investigate User Activities By ARN", "Get User Information from Identity Table"] +support_searches = [] data_models = none providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. @@ -863,7 +910,8 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +support_searches = [] data_models = none providing_technologies = none description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). @@ -881,7 +929,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. @@ -896,7 +945,8 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. @@ -911,7 +961,8 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] +support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. @@ -930,7 +981,8 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. @@ -947,7 +999,8 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts", "Okta User Logins From Multiple Cities"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -support_searches = none +investigative_searches = ["Investigate User Activities In Okta", "Investigate Okta Activity by IP Address", "Investigate Okta Activity by app"] +support_searches = [] data_models = none providing_technologies = none description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. @@ -964,7 +1017,8 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["Process Execution via WMI", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. @@ -981,7 +1035,8 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["Disabling Remote User Account Control", "Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. @@ -998,7 +1053,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["EC2 Instance Modified With Previously Unseen User"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -support_searches = none +investigative_searches = ["AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get Notable History"] +support_searches = [] data_models = none providing_technologies = none description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. @@ -1014,7 +1070,8 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["Detect Rare Executables", "Detect processes used for System Network Configuration Discovery", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Uncommon Processes On Endpoint", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. @@ -1031,7 +1088,8 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["Protocols passing authentication in cleartext"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -support_searches = none +investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. @@ -1046,7 +1104,8 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["Web Fraud - Account Harvesting", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -support_searches = none +investigative_searches = ["Get Web Session Information via session id", "Get Emails From Specific Sender", "Get Notable History", "Get Notable Info"] +support_searches = [] data_models = none providing_technologies = none description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. @@ -1066,7 +1125,8 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others @@ -1081,7 +1141,8 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. @@ -1100,7 +1161,8 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. @@ -1116,7 +1178,8 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["Detect Path Interception By Creation Of program exe", "Hiding Files And Directories With Attrib exe", "Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. @@ -1131,7 +1194,8 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. @@ -1146,7 +1210,8 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -support_searches = none +investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +support_searches = [] data_models = ["Endpoint"] providing_technologies = none description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. diff --git a/package/default/macros.conf b/package/default/macros.conf index 80f70e99e7..dd1f54bff7 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T12:14:41 UTC +# On Date: 2020-05-08T12:53:42 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 450af1e543..b07ae74e5b 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T12:14:41 UTC +# On Date: 2020-05-08T12:53:42 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -11,7 +11,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -47,7 +47,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceI action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -83,7 +83,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceI action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -119,7 +119,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) [search `cloudtrail` action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -155,7 +155,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceI action.escu = 0 action.escu.enabled = 1 description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. -action.escu.mappings = {"analytics_story": ["AWS Cross Account Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. action.escu.known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. @@ -190,7 +190,7 @@ search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId pa action.escu = 0 action.escu.enabled = 1 description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. -action.escu.mappings = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. @@ -225,7 +225,7 @@ search = `cloudtrail` eventName=CreateNetworkAclEntry | mvexpand requestParamete action.escu = 0 action.escu.enabled = 1 description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. -action.escu.mappings = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that a user has legitimately deleted a network ACL. @@ -260,7 +260,7 @@ search = `cloudtrail` eventName=DeleteNetworkAcl|rename userIdentity.arn as arn action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -294,7 +294,7 @@ search = `cloudtrail` eventName=RunInstances errorCode=success | bucket span=10m action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -329,7 +329,7 @@ search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_ru action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window -action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. @@ -363,7 +363,7 @@ search = `cloudtrail` eventName=TerminateInstances errorCode=success | bucket sp action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. -action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -398,7 +398,7 @@ search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excess action.escu = 0 action.escu.enabled = 1 description = Detect memory dumping of the LSASS process. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = Detect memory dumping of the LSASS process. action.escu.how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. @@ -431,7 +431,7 @@ search = `sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR action.escu = 0 action.escu.enabled = 1 description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API -action.escu.mappings = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster Pod", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. @@ -465,7 +465,7 @@ search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list o action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS -action.escu.mappings = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. @@ -499,7 +499,7 @@ search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!= action.escu = 0 action.escu.enabled = 1 description = Attempt to add a certificate to the untrusted certificate store -action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -535,7 +535,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -action.escu.mappings = {"analytics_story": ["Credential Dumping", "Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. @@ -571,7 +571,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for attempts to stop security-related services on the endpoint. -action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., @@ -607,7 +607,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -641,7 +641,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for a batch file (.bat) written to the Windows system directory tree. -action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -677,7 +677,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. -action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. @@ -713,7 +713,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. -action.escu.mappings = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ @@ -751,7 +751,7 @@ search = | tstats `security_content_summariesonly` count, values(DNS.dest) AS de action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances created by users who have not created them before. -action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. @@ -787,7 +787,7 @@ search = | tstats `security_content_summariesonly` earliest(_time) as firstTime, action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances being created with previously unseen image IDs. -action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. @@ -823,7 +823,7 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = Find EC2 instances being created with previously unseen instance types. -action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. @@ -859,7 +859,7 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. -action.escu.mappings = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. @@ -895,7 +895,7 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = The search looks for file modifications with extensions commonly used by Ransomware -action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ @@ -935,7 +935,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. -action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. @@ -971,7 +971,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Detect remote thread creation into LSASS consistent with credential dumping. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = Detect remote thread creation into LSASS consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. @@ -1004,7 +1004,7 @@ search = `sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as f action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of local administrator accounts using net.exe. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1040,7 +1040,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.user) action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation or deletion of hidden shares using net.exe. -action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1076,7 +1076,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.user) action.escu = 0 action.escu.enabled = 1 description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1110,7 +1110,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects the use of wmic and Powershell to create a shadow copy. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search detects the use of wmic and Powershell to create a shadow copy. action.escu.how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. @@ -1143,7 +1143,7 @@ search = `sysmon` Message=*win32_shadowcopy* Message=*Create* | stats count min( action.escu = 0 action.escu.enabled = 1 description = This search detects credential dumping using copy command from a shadow copy. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1177,7 +1177,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects the creation of a symlink to a shadow copy. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1211,7 +1211,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. -action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ @@ -1253,7 +1253,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as start_tim action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. -action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. @@ -1288,7 +1288,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. -action.escu.mappings = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. @@ -1324,7 +1324,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. -action.escu.mappings = {"analytics_story": ["DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ @@ -1364,7 +1364,7 @@ search = | inputlookup discovered_dns_records.csv | rename answer as discovered_ action.escu = 0 action.escu.enabled = 1 description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. -action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1400,7 +1400,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. -action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -1441,7 +1441,7 @@ search = `cloudtrail` userIdentity.sessionContext.attributes.mfaAuthenticated=fa action.escu = 0 action.escu.enabled = 1 description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. -action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -1482,7 +1482,7 @@ search = `cloudtrail` errorCode=success | rename userName as identity | search N action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1517,7 +1517,7 @@ search = | inputlookup previously_seen_users_console_logins.csv | stats min(firs action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1552,7 +1552,7 @@ search = | inputlookup previously_seen_users_console_logins.csv | stats min(firs action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1587,7 +1587,7 @@ search = | inputlookup previously_seen_users_console_logins.csv | stats min(firs action.escu = 0 action.escu.enabled = 1 description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. -action.escu.mappings = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. action.escu.how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. action.escu.known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. @@ -1622,7 +1622,7 @@ search = `wineventlog_security` EventCode=4624 (Logon_Type=3 LogonProcessName=Nt action.escu = 0 action.escu.enabled = 1 description = This search looks for reading lsass memory consistent with credential dumping. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for reading lsass memory consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. @@ -1655,7 +1655,7 @@ search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR G action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. -action.escu.mappings = {"analytics_story": ["Common Phishing Frameworks"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ @@ -1695,7 +1695,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. -action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.mappings = {} action.escu.data_models = [Change] action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ @@ -1735,7 +1735,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects user accounts that have been locked out a relatively high number of times in a short period. -action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.mappings = {} action.escu.data_models = [Change] action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. @@ -1771,7 +1771,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. -action.escu.mappings = {"analytics_story": ["Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1095"], "nist": ["DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model @@ -1806,7 +1806,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) as firs action.escu = 0 action.escu.enabled = 1 description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. -action.escu.mappings = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. @@ -1842,7 +1842,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.AE", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for reading loaded Images unique to credential dumping with Mimikatz. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. @@ -1875,7 +1875,7 @@ search = `sysmon` EventCode=7 | stats values(ImageLoaded) as ImageLoaded values( action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell requesting privileges consistent with credential dumping. -action.escu.mappings = {"asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = This search looks for PowerShell requesting privileges consistent with credential dumping. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. action.escu.known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. @@ -1907,7 +1907,7 @@ search = `wineventlog_security` signature_id=4703 Process_Name=*powershell.exe | action.escu = 0 action.escu.enabled = 1 description = This search looks for newly created accounts that have been elevated to local administrators. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Windows", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1078"], "nist": ["PR.AC", "DE.CM"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = This search looks for newly created accounts that have been elevated to local administrators. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ @@ -1948,7 +1948,7 @@ search = `wineventlog_security` signature_id=4720 OR (signature_id=4732 Group_Na action.escu = 0 action.escu.enabled = 1 description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. -action.escu.mappings = {"analytics_story": ["Router and Infrastructure Security"], "asset_type": "Endpoint", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Authentication] action.escu.eli5 = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. @@ -1984,7 +1984,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) as earl action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. -action.escu.mappings = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events where a user has created an open/public S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. @@ -2019,7 +2019,7 @@ search = `cloudtrail` AllUsers eventName=PutBucketAcl | spath output=userIdentit action.escu = 0 action.escu.enabled = 1 description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. -action.escu.mappings = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. @@ -2054,7 +2054,7 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max( action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model @@ -2089,7 +2089,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) as earl action.escu = 0 action.escu.enabled = 1 description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. -action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. @@ -2125,7 +2125,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. -action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. @@ -2161,7 +2161,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2197,7 +2197,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. -action.escu.mappings = {"analytics_story": ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. @@ -2233,7 +2233,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.dest) action.escu = 0 action.escu.enabled = 1 description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. -action.escu.mappings = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access logs' inputs. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. action.escu.known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour @@ -2267,7 +2267,7 @@ search = `aws_s3_accesslogs` http_status=200 [search `aws_s3_accesslogs` http_s action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -2308,7 +2308,7 @@ search = `cloudtrail` eventType=AwsApiCall [search `cloudtrail` eventType=AwsApi action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. -action.escu.mappings = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. @@ -2343,7 +2343,7 @@ search = `cloudtrail` `network_acl_events` [search `cloudtrail` `network_acl_eve action.escu = 0 action.escu.enabled = 1 description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. @@ -2378,7 +2378,7 @@ search = `cloudtrail` eventName=DeleteBucket [search `cloudtrail` eventName=Dele action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. @@ -2413,7 +2413,7 @@ search = `cloudtrail` `security_group_api_calls` [search `cloudtrail` `security_ action.escu = 0 action.escu.enabled = 1 description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {"analytics_story": ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. @@ -2447,7 +2447,7 @@ search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=17 action.escu = 0 action.escu.enabled = 1 description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. -action.escu.mappings = {"analytics_story": ["Data Protection"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Change_Analysis] action.escu.eli5 = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. @@ -2483,7 +2483,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) AS earl action.escu = 0 action.escu.enabled = 1 description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. -action.escu.mappings = {"analytics_story": ["Asset Tracking"], "asset_type": "Infrastructure", "cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Sessions] action.escu.eli5 = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. @@ -2518,7 +2518,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine -action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -2554,7 +2554,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. -action.escu.mappings = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "kill_chain_phases": ["Reconnaissance"], "mitre_attack_id": ["T1082"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Web] action.escu.eli5 = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. @@ -2590,7 +2590,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. -action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ @@ -2631,7 +2631,7 @@ search = | tstats `security_content_summariesonly` count values(DNS.answer) as a action.escu = 0 action.escu.enabled = 1 description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. -action.escu.mappings = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Web] action.escu.eli5 = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model @@ -2667,7 +2667,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. -action.escu.mappings = {"analytics_story": ["Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -2703,7 +2703,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. -action.escu.mappings = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. action.escu.known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. @@ -2738,7 +2738,7 @@ search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=A action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -2773,7 +2773,7 @@ search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | action.escu = 0 action.escu.enabled = 1 description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. -action.escu.mappings = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. @@ -2809,7 +2809,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for web connections to dynamic DNS providers. -action.escu.mappings = {"analytics_story": ["Dynamic DNS"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Web] action.escu.eli5 = This search looks for web connections to dynamic DNS providers. action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ @@ -2847,7 +2847,7 @@ search = | tstats `security_content_summariesonly` count values(Web.url) as url action.escu = 0 action.escu.enabled = 1 description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. -action.escu.mappings = {"analytics_story": ["Data Protection", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "PR.DS"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. @@ -2883,7 +2883,7 @@ search = | tstats `security_content_summariesonly` dc("DNS.query") as count fro action.escu = 0 action.escu.enabled = 1 description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. -action.escu.mappings = {"analytics_story": ["Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1072", "T1087"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2919,7 +2919,7 @@ search = | tstats `security_content_summariesonly` count min(_time) values(Proce action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). -action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. @@ -2954,7 +2954,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Detect the usage of comsvcs.dll for dumping the lsass process. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2988,7 +2988,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being modified by users who have not previously modified them. -action.escu.mappings = {"analytics_story": ["Unusual AWS EC2 Modifications"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for EC2 instances being modified by users who have not previously modified them. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. action.escu.known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. @@ -3023,7 +3023,7 @@ search = `cloudtrail` `ec2_modification_api_calls` [search `cloudtrail` `ec2_mod action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started -action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. @@ -3057,7 +3057,7 @@ search = `cloudtrail` earliest=-1h StartInstances | stats earliest(_time) as ear action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen AMIs. -action.escu.mappings = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for EC2 instances being created with previously unseen AMIs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. action.escu.known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. @@ -3091,7 +3091,7 @@ search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunI action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen instance types. -action.escu.mappings = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. @@ -3126,7 +3126,7 @@ search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunI action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created by users who have not created them before. -action.escu.mappings = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for EC2 instances being created by users who have not created them before. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. action.escu.known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. @@ -3161,7 +3161,7 @@ search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunI action.escu = 0 action.escu.enabled = 1 description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. -action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Email] action.escu.eli5 = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ @@ -3198,7 +3198,7 @@ search = | tstats `security_content_summariesonly` count values(All_Email.recipi action.escu = 0 action.escu.enabled = 1 description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. -action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. @@ -3234,7 +3234,7 @@ search = | tstats `security_content_summariesonly` count values(Filesystem.file_ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. -action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. @@ -3269,7 +3269,7 @@ search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as action.escu = 0 action.escu.enabled = 1 description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. -action.escu.mappings = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. @@ -3304,7 +3304,7 @@ search = | tstats `security_content_summariesonly` count values("DNS.query") as action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. -action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -3340,7 +3340,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. -action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. @@ -3376,7 +3376,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search returns a list of hosts that have not successfully completed a backup in over a week. -action.escu.mappings = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search returns a list of hosts that have not successfully completed a backup in over a week. action.escu.how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. action.escu.known_false_positives = None identified @@ -3411,7 +3411,7 @@ search = `netbackup` MESSAGE="Disk/Partition backup completed successfully." | s action.escu = 0 action.escu.enabled = 1 description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. -action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -3447,7 +3447,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for the first time a Windows service is seen running in your environment. -action.escu.mappings = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for the first time a Windows service is seen running in your environment. action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. action.escu.known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. @@ -3482,7 +3482,7 @@ search = `wineventlog_system` signature_id=7036 | rename param1 as service_name action.escu = 0 action.escu.enabled = 1 description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. -action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. @@ -3517,7 +3517,7 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_ action.escu = 0 action.escu.enabled = 1 description = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. -action.escu.mappings = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "GCP GCR Container", "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. @@ -3552,7 +3552,7 @@ search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM data action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster -action.escu.mappings = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "GCP Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. @@ -3586,7 +3586,7 @@ search = `google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp! action.escu = 0 action.escu.enabled = 1 description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. -action.escu.mappings = {"analytics_story": ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3622,7 +3622,7 @@ search = | tstats `security_content_summariesonly` count min(_time) values(Proce action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. -action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. @@ -3657,7 +3657,7 @@ search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as action.escu = 0 action.escu.enabled = 1 description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. -action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Domain Server", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. action.escu.how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. action.escu.known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. @@ -3691,7 +3691,7 @@ search = | from datamodel Identity_Management.All_Identities | eval empStatus=c action.escu = 0 action.escu.enabled = 1 description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. -action.escu.mappings = {"analytics_story": ["DNS Amplification Attacks"], "asset_type": "DNS Servers", "cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. @@ -3726,7 +3726,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. -action.escu.mappings = {"asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. @@ -3761,7 +3761,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. -action.escu.mappings = {"analytics_story": ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3797,7 +3797,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. -action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3833,7 +3833,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3869,7 +3869,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process_id) action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. -action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3905,7 +3905,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. -action.escu.mappings = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3941,7 +3941,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. -action.escu.mappings = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "kill_chain_phases": ["Delivery", "Actions on Objectives"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -3976,7 +3976,7 @@ search = | tstats `security_content_summariesonly` values(DNS.answer) as IPs min action.escu = 0 action.escu.enabled = 1 description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. -action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -4011,7 +4011,7 @@ search = | tstats `security_content_summariesonly` values(All_Email.recipient) a action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. -action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = You will encounter noise from legitimate print-monitor registry entries. @@ -4046,7 +4046,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. -action.escu.mappings = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Web] action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -4082,7 +4082,7 @@ search = | tstats `security_content_summariesonly` values(Web.url) as urls min(_ action.escu = 0 action.escu.enabled = 1 description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. -action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. @@ -4116,7 +4116,7 @@ search = `okta` outcome.reason=INVALID_CREDENTIALS | rename client.geographicalC action.escu = 0 action.escu.enabled = 1 description = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. -action.escu.mappings = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "AWS ECR container", "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. @@ -4151,7 +4151,7 @@ search = | tstats count min(_time) as firstTime max(_time) as lastTime FROM data action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. -action.escu.mappings = {"analytics_story": ["Monitor for Updates"], "asset_type": "Endpoint", "cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Updates] action.escu.eli5 = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. @@ -4187,7 +4187,7 @@ search = | tstats `security_content_summariesonly` max(_time) as lastTime from d action.escu = 0 action.escu.enabled = 1 description = Detect Okta user lockout events -action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = Detect Okta user lockout events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. @@ -4221,7 +4221,7 @@ search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.g action.escu = 0 action.escu.enabled = 1 description = Detect failed Okta SSO events -action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = Detect failed Okta SSO events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. @@ -4255,7 +4255,7 @@ search = `okta` displayMessage="User attempted unauthorized access to app" | sta action.escu = 0 action.escu.enabled = 1 description = This search detects logins from the same user from different states in a 24 hour period. -action.escu.mappings = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +action.escu.mappings = {} action.escu.eli5 = This search detects logins from the same user from different states in a 24 hour period. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. @@ -4290,7 +4290,7 @@ search = `okta` displayMessage="User login to Okta" client.geographicalContext.c action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. -action.escu.mappings = {"analytics_story": ["Splunk Enterprise Vulnerability"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.escu.how_to_implement = No extra steps needed to implement this search. action.escu.known_false_positives = None identified @@ -4324,7 +4324,7 @@ search = index=_internal sourcetype=splunk_web_access return_to="/%09/*" | `open action.escu = 0 action.escu.enabled = 1 description = This search looks for ColdRoot events from the osx-attacks osquery pack. -action.escu.mappings = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This search looks for ColdRoot events from the osx-attacks osquery pack. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model action.escu.known_false_positives = There are no known false positives. @@ -4358,7 +4358,7 @@ search = | from datamodel Alerts.Alerts | search app=osquery:results (name=pack_ action.escu = 0 action.escu.enabled = 1 description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. -action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -4394,7 +4394,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched via WMI. -action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for processes launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. @@ -4429,7 +4429,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input -action.escu.mappings = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. action.escu.known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. @@ -4463,7 +4463,7 @@ search = | from datamodel Alerts.Alerts | search app=osquery:results name=pack_o action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. -action.escu.mappings = {"analytics_story": ["Netsh Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -4499,7 +4499,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model @@ -4535,7 +4535,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. -action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. @@ -4570,7 +4570,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as prohibited. -action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. @@ -4606,7 +4606,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. -action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. @@ -4641,7 +4641,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. -action.escu.mappings = {"analytics_story": ["Use of Cleartext Protocols"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. @@ -4677,7 +4677,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. -action.escu.mappings = {"analytics_story": ["Windows Service Abuse", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. @@ -4712,7 +4712,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for command-line arguments used to hide a file or directory using the reg add command. -action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -4748,7 +4748,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. -action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. @@ -4783,7 +4783,7 @@ search = | tstats `security_content_summariesonly` count values(Registry.registr action.escu = 0 action.escu.enabled = 1 description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. -action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. @@ -4818,7 +4818,7 @@ search = | tstats `security_content_summariesonly` count values(Registry.registr action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. -action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. action.escu.how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications @@ -4852,7 +4852,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. -action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. @@ -4888,7 +4888,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. -action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. @@ -4924,7 +4924,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. -action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. @@ -4960,7 +4960,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. -action.escu.mappings = {"analytics_story": ["Suspicious WMI Use", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -4996,7 +4996,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search monitors for remote modifications to registry keys. -action.escu.mappings = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search monitors for remote modifications to registry keys. action.escu.how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. @@ -5031,7 +5031,7 @@ search = | tstats `security_content_summariesonly` count values(Registry.registr action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to operate on remote systems. -action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5067,7 +5067,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -action.escu.mappings = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1085"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5103,7 +5103,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. @@ -5139,7 +5139,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ @@ -5178,7 +5178,7 @@ search = | tstats `security_content_summariesonly` count values(All_Traffic.dest action.escu = 0 action.escu.enabled = 1 description = This search looks for long URLs that have several SQL commands visible within them. -action.escu.mappings = {"analytics_story": ["SQL Injection"], "asset_type": "Database Server", "cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Web] action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. @@ -5214,7 +5214,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Web wher action.escu = 0 action.escu.enabled = 1 description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. -action.escu.mappings = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -5250,7 +5250,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. -action.escu.mappings = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5286,7 +5286,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5322,7 +5322,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. -action.escu.mappings = {"analytics_story": ["Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5358,7 +5358,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. -action.escu.mappings = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5394,7 +5394,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. -action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -5430,7 +5430,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search looks for scripts launched via WMI. -action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for scripts launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. @@ -5465,7 +5465,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. -action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. @@ -5500,7 +5500,7 @@ search = | tstats `security_content_summariesonly` count values(Filesystem.actio action.escu = 0 action.escu.enabled = 1 description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. -action.escu.mappings = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5536,7 +5536,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search detects accounts that were created and deleted in a short time period. -action.escu.mappings = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} +action.escu.mappings = {} action.escu.data_models = [Change] action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ @@ -5572,7 +5572,7 @@ search = | tstats `security_content_summariesonly` values(All_Changes.result_id) action.escu = 0 action.escu.enabled = 1 description = This search looks for process names that consist only of a single letter. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for process names that consist only of a single letter. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5607,7 +5607,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. -action.escu.mappings = {"analytics_story": ["Spectre And Meltdown Vulnerabilities"], "asset_type": "Endpoint", "cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Vulnerabilities] action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. @@ -5642,7 +5642,7 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_ action.escu = 0 action.escu.enabled = 1 description = The search looks for a sharp increase in the number of files written to a particular host -action.escu.mappings = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = The search looks for a sharp increase in the number of files written to a particular host action.escu.how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, such as Carbon Black or endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the file system. action.escu.known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. @@ -5677,7 +5677,7 @@ search = | tstats `security_content_summariesonly` count FROM datamodel=Endpoint action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. -action.escu.mappings = {"analytics_story": ["Splunk Enterprise Vulnerability CVE-2018-11409"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. action.escu.how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. action.escu.known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. @@ -5712,7 +5712,7 @@ search = index=_internal sourcetype=splunkd_ui_access server-info | search clien action.escu = 0 action.escu.enabled = 1 description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. -action.escu.mappings = {"analytics_story": ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. @@ -5747,7 +5747,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). -action.escu.mappings = {"analytics_story": ["Suspicious Emails"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.data_models = [UEBA] action.escu.eli5 = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. @@ -5783,7 +5783,7 @@ search = |tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for emails that have attachments with suspicious file extensions. -action.escu.mappings = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ @@ -5820,7 +5820,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names that have been linked to malicious activity. -action.escu.mappings = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = The search looks for files created with names that have been linked to malicious activity. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. action.escu.known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. @@ -5855,7 +5855,7 @@ search = | tstats `security_content_summariesonly` count values(Filesystem.actio action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. -action.escu.mappings = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"], "security_domain": "threat"} +action.escu.mappings = {} action.escu.eli5 = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. action.escu.known_false_positives = There are no known false positives. @@ -5890,7 +5890,7 @@ search = `stream_http` http_method=POST http_content_length>1 | regex form_data= action.escu = 0 action.escu.enabled = 1 description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. -action.escu.mappings = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. @@ -5925,7 +5925,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. -action.escu.mappings = {"analytics_story": ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112", "T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. @@ -5960,7 +5960,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. -action.escu.mappings = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5996,7 +5996,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the 'System Volume Information' folder by something other than the System process. -action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search detects writes to the 'System Volume Information' folder by something other than the System process. action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. @@ -6030,7 +6030,7 @@ search = (`sysmon` OR tag=process) EventCode=11 process_id!=4 file_path=*System\ action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the recycle bin by a process other than explorer.exe. -action.escu.mappings = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search detects writes to the recycle bin by a process other than explorer.exe. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. action.escu.known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. @@ -6065,7 +6065,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. -action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1036"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. action.escu.how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. action.escu.known_false_positives = None identified @@ -6100,7 +6100,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. -action.escu.mappings = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE"], "security_domain": "network"} +action.escu.mappings = {} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. @@ -6135,7 +6135,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. -action.escu.mappings = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -6171,7 +6171,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as uncommon. -action.escu.mappings = {"analytics_story": ["Windows Privilege Escalation", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. @@ -6207,7 +6207,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. -action.escu.mappings = {"analytics_story": ["Disabling Security Tools"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. @@ -6243,7 +6243,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects loading of unsigned images by LSASS. -action.escu.mappings = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search detects loading of unsigned images by LSASS. action.escu.how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. @@ -6276,7 +6276,7 @@ search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_tim action.escu = 0 action.escu.enabled = 1 description = This search gives you the hosts where a backup was attempted and then failed. -action.escu.mappings = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search gives you the hosts where a backup was attempted and then failed. action.escu.how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. action.escu.known_false_positives = None identified @@ -6310,7 +6310,7 @@ search = `netbackup` | stats latest(_time) as latestTime by COMPUTERNAME, MESSAG action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. -action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships, from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some legitimate applications start with long command lines. @@ -6345,7 +6345,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. -action.escu.mappings = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. action.escu.how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. action.escu.known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. @@ -6380,7 +6380,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. -action.escu.mappings = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} +action.escu.mappings = {} action.escu.eli5 = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.escu.how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. action.escu.known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. @@ -6414,7 +6414,7 @@ search = `stream_http` | eval cs_content_type_length = len(cs_content_type) | wh action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI permanent event subscriptions. -action.escu.mappings = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +action.escu.mappings = {} action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. @@ -6449,7 +6449,7 @@ search = `wmi` EventCode=5861 Binding | rex field=Message "Consumer =\s+(? 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Unauthorized Assets by MAC address"] +searches = ["Detect Unauthorized Assets by MAC address", "Get Notable Info", "Get Notable History", "Get First Occurrence and Last Occurrence of a MAC Address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Monitor Email For Brand Abuse", "Monitor DNS For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] +searches = ["Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse", "Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Cloud Compute Instance Created With Previously Unseen Image", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Started In Previously Unused Region", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Instance Type"] +searches = ["Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Started In Previously Unused Region", "Abnormally High AWS Instances Launched by User - MLTK", "Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Investigate Cloud Compute Instance Activities", "Investigate User Activities In Single Cloud Region", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events"] +searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events", "Get Notable History", "Get Risk Modifiers For User", "Investigate Network Traffic From src ip", "Get Authentication Logs For Endpoint", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin", "Email files written outside of the Outlook directory", "Hosts receiving high volume of network traffic from email server", "Email servers sending high volume traffic to hosts"] +searches = ["Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts", "Suspicious writes to windows Recycle Bin", "Hosts receiving high volume of network traffic from email server", "Email files written outside of the Outlook directory", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Spike in blocked Outbound Traffic from your AWS", "Clients Connecting to Multiple DNS Servers", "Excessive DNS Failures", "Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Detect Long DNS TXT Record Response", "Protocol or Port Mismatch", "Detect Large Outbound ICMP Packets", "DNS Query Length With High Standard Deviation", "TOR Traffic", "Detection of DNS Tunnels", "DNS Query Length Outliers - MLTK"] +searches = ["Detect Large Outbound ICMP Packets", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detection of DNS Tunnels", "Detect Spike in blocked Outbound Traffic from your AWS", "Prohibited Network Traffic Allowed", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "Protocol or Port Mismatch", "Excessive DNS Failures", "DNS Query Length Outliers - MLTK", "TOR Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "Get Parent Process Info", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -189,7 +189,7 @@ version = 1 references = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] +searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2", "Get Certificate logs for a domain"] description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. narrative = As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded"] +searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded", "Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Dump LSASS via comsvcs DLL", "Credential Dumping via Symlink to Shadow Copy", "Credential Dumping via Copy Command from Shadow Copy", "Create Remote Thread into LSASS", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Unsigned Image Loaded by LSASS", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Creation of Shadow Copy with wmic and powershell", "Access LSASS Memory for Dump Creation", "Attempted Credential Dump From Registry via Reg exe", "Creation of Shadow Copy"] +searches = ["Detect Credential Dumping through LSASS access", "Creation of Shadow Copy with wmic and powershell", "Unsigned Image Loaded by LSASS", "Creation of Shadow Copy", "Attempted Credential Dump From Registry via Reg exe", "Credential Dumping via Symlink to Shadow Copy", "Create Remote Thread into LSASS", "Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Credential Dumping via Copy Command from Shadow Copy", "Dump LSASS via comsvcs DLL", "Detect Mimikatz Using Loaded Images", "Investigate Pass the Ticket Attempts", "Investigate Failed Logins for Multiple Destinations", "Investigate Previous Unseen User", "Investigate Pass the Hash Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["First time seen command line argument", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Suspicious Reg exe Process", "Sc exe Manipulating Windows Services", "SMB Traffic Spike - MLTK", "Single Letter Process On Endpoint", "Scheduled Task Name Used by Dragonfly Threat Actors", "SMB Traffic Spike", "Processes launching netsh", "Detect PsExec With accepteula Flag", "Malicious PowerShell Process - Execution Policy Bypass", "Create local admin accounts using net exe", "Registry Keys Used For Persistence"] +searches = ["SMB Traffic Spike - MLTK", "Malicious PowerShell Process - Execution Policy Bypass", "Single Letter Process On Endpoint", "Registry Keys Used For Persistence", "Scheduled Task Name Used by Dragonfly Threat Actors", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Detect New Local Admin account", "Processes launching netsh", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Sc exe Manipulating Windows Services", "Create local admin accounts using net exe", "Suspicious Reg exe Process", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Registry Activity", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Process File Activity", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Large Volume of DNS ANY Queries"] +searches = ["Large Volume of DNS ANY Queries", "Get Risk Modifiers For User", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["DNS record changed", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Detect hosts connecting to dynamic domain providers"] +searches = ["Clients Connecting to Multiple DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect USB device insertion", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers"] +searches = ["Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Detection of DNS Tunnels", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Attempt To Add Certificate To Untrusted Store", "Unload Sysmon Filter Driver", "Suspicious Reg exe Process", "Attempt To Stop Security Service", "Sc exe Manipulating Windows Services", "Processes launching netsh"] +searches = ["Attempt To Add Certificate To Untrusted Store", "Unload Sysmon Filter Driver", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect web traffic to dynamic domain providers", "Detect hosts connecting to dynamic domain providers"] +searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Investigate Web Activity From src ip"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Prohibited Software On Endpoint", "Detection of tools built by NirSoft", "Detect Rare Executables", "Suspicious Email Attachment Extensions", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike - MLTK", "Detect Use of cmd exe to Launch Script Interpreters", "SMB Traffic Spike", "Registry Keys Used For Persistence"] +searches = ["SMB Traffic Spike - MLTK", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Registry Keys Used For Persistence", "Prohibited Software On Endpoint", "SMB Traffic Spike", "Detect Rare Executables", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["First time seen command line argument", "Create or delete windows shares using net exe", "Detect Outbound SMB Traffic", "Suspicious File Write", "Remote Desktop Process Running On System", "DNS Query Length With High Standard Deviation", "SMB Traffic Spike - MLTK", "Remote Desktop Network Traffic", "SMB Traffic Spike", "DNS Query Length Outliers - MLTK"] +searches = ["DNS Query Length With High Standard Deviation", "SMB Traffic Spike - MLTK", "Suspicious File Write", "Create or delete windows shares using net exe", "First time seen command line argument", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Remote Desktop Process Running On System", "DNS Query Length Outliers - MLTK", "Remote Desktop Network Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Windows hosts file modification", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers"] +searches = ["Clients Connecting to Multiple DNS Servers", "Windows hosts file modification", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers"] +searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers", "Get Notable Info", "Get Notable History", "Investigate Web Activity From Host", "Get Risk Modifiers For Endpoint", "Get Vulnerability Logs For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection"] +searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Get Notable Info", "Get Notable History", "GCP Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint", "Amazon EKS Kubernetes activity by src ip"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system", "Detect Activity Related to Pass the Hash Attacks"] +searches = ["Schtasks scheduling job on remote system", "Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Process Running On System", "Remote Desktop Network Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Malicious PowerShell Process With Obfuscation Techniques", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments"] +searches = ["Malicious PowerShell Process With Obfuscation Techniques", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Unsuccessful Netbackup backups", "Extended Period Without Successful Netbackup Backups"] +searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups", "All backup logs for host", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Prohibited Software On Endpoint"] +searches = ["Prohibited Software On Endpoint", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["No Windows Updates in a time frame"] +searches = ["No Windows Updates in a time frame", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Processes launching netsh", "Processes created by netsh"] +searches = ["Processes launching netsh", "Processes created by netsh", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["First time seen command line argument", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services"] +searches = ["First time seen command line argument", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file"] +searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process", "Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["First time seen command line argument", "Unusually Long Command Line - MLTK", "Unusually Long Command Line", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence"] +searches = ["Unusually Long Command Line", "Registry Keys Used For Persistence", "First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Unusually Long Command Line - MLTK", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["TOR Traffic", "Protocol or Port Mismatch", "Prohibited Network Traffic Allowed", "Detect hosts connecting to dynamic domain providers"] +searches = ["Detect hosts connecting to dynamic domain providers", "Protocol or Port Mismatch", "Prohibited Network Traffic Allowed", "TOR Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Common Ransomware Notes", "System Processes Run From Unexpected Locations", "Suspicious wevtutil Usage", "Prohibited Network Traffic Allowed", "Deleting Shadow Copies", "Common Ransomware Extensions", "Scheduled tasks used in BadRabbit ransomware", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared", "Spike in File Writes", "SMB Traffic Spike - MLTK", "Schtasks used for forcing a reboot", "SMB Traffic Spike", "TOR Traffic", "USN Journal Deletion", "Remote Process Instantiation via WMI", "Registry Keys Used For Persistence"] +searches = ["Unusually Long Command Line", "Common Ransomware Notes", "Remote Process Instantiation via WMI", "SMB Traffic Spike - MLTK", "USN Journal Deletion", "Spike in File Writes", "Scheduled tasks used in BadRabbit ransomware", "Registry Keys Used For Persistence", "Common Ransomware Extensions", "Suspicious wevtutil Usage", "Prohibited Network Traffic Allowed", "SMB Traffic Spike", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Deleting Shadow Copies", "Schtasks used for forcing a reboot", "Windows Event Log Cleared", "TOR Traffic", "Get Process Information For Port Activity", "Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect New Login Attempts to Routers"] +searches = ["Detect New Login Attempts to Routers", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["SQL Injection with Long URLs"] +searches = ["SQL Injection with Long URLs", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Common Ransomware Notes", "Prohibited Software On Endpoint", "Batch File Write to System32", "Deleting Shadow Copies", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Extensions", "File with Samsam Extension", "Detect attackers scanning for vulnerable JBoss servers", "Spike in File Writes", "Remote Desktop Network Traffic", "Remote Desktop Network Bruteforce", "Detect PsExec With accepteula Flag", "Samsam Test File Write"] +searches = ["Common Ransomware Notes", "Spike in File Writes", "Remote Desktop Network Bruteforce", "Detect PsExec With accepteula Flag", "Common Ransomware Extensions", "File with Samsam Extension", "Detect malicious requests to exploit JBoss servers", "Prohibited Software On Endpoint", "Samsam Test File Write", "Deleting Shadow Copies", "Batch File Write to System32", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Spectre and Meltdown Vulnerable Systems"] +searches = ["Spectre and Meltdown Vulnerable Systems", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Open Redirect in Splunk Web"] +searches = ["Open Redirect in Splunk Web", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Splunk Enterprise Information Disclosure"] +searches = ["Splunk Enterprise Information Disclosure", "Get Notable Info", "Get Notable History", "Investigate Network Traffic From src ip", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Abnormally High AWS Instances Launched by User - MLTK", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Terminated by User - MLTK"] +searches = ["EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Terminated by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New City", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New Country"] +searches = ["Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login", "AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect New Open S3 buckets", "Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion"] +searches = ["Detect New Open S3 buckets", "Detect Spike in S3 Bucket deletion", "Detect S3 access from a new IP", "Get Notable Info", "Get Notable History", "Investigate AWS activities via region name", "AWS S3 Bucket details via bucketName", "Get All AWS Activity From IP Address", "AWS Investigate User Activities By ARN", "Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] +searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Prohibited Applications Spawning cmd exe", "System Processes Run From Unexpected Locations", "First time seen command line argument", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Detect Use of cmd exe to Launch Script Interpreters"] +searches = ["Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Detect Prohibited Applications Spawning cmd exe", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Requests Resolved by Unauthorized DNS Servers", "Clients Connecting to Multiple DNS Servers", "Excessive DNS Failures", "Detect hosts connecting to dynamic domain providers", "Detect Long DNS TXT Record Response", "DNS Query Length With High Standard Deviation", "Detection of DNS Tunnels", "DNS Query Length Outliers - MLTK"] +searches = ["DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "Excessive DNS Failures", "DNS Query Length Outliers - MLTK", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions"] +searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions", "Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] +searches = ["Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Okta Failed SSO Attempts", "Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta User Logins From Multiple Cities"] +searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Failed SSO Attempts", "Okta Account Lockout Events", "Okta User Logins From Multiple Cities", "Investigate User Activities In Okta", "Investigate Okta Activity by IP Address", "Investigate Okta Activity by app"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["WMI Permanent Event Subscription - Sysmon", "Process Execution via WMI", "Remote Process Instantiation via WMI", "WMI Temporary Event Subscription", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription"] +searches = ["Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription", "Process Execution via WMI", "Script Execution via WMI", "Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Suspicious Changes to File Associations", "Registry Keys Used For Privilege Escalation", "Remote Registry Key modifications", "Monitor Registry Keys for Print Monitors", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence"] +searches = ["Monitor Registry Keys for Print Monitors", "Registry Keys Used For Privilege Escalation", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Registry Keys Used For Persistence", "Suspicious Changes to File Associations", "Registry Keys for Creating SHIM Databases", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["EC2 Instance Modified With Previously Unseen User"] +searches = ["EC2 Instance Modified With Previously Unseen User", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get Notable History"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["System Processes Run From Unexpected Locations", "Detect Rare Executables", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal", "Uncommon Processes On Endpoint", "Detect processes used for System Network Configuration Discovery"] +searches = ["Unusually Long Command Line", "Uncommon Processes On Endpoint", "RunDLL Loading DLL By Ordinal", "Detect processes used for System Network Configuration Discovery", "Detect Rare Executables", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Protocols passing authentication in cleartext"] +searches = ["Protocols passing authentication in cleartext", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Account Harvesting", "Web Fraud - Password Sharing Across Accounts"] +searches = ["Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Account Harvesting", "Get Web Session Information via session id", "Get Emails From Specific Sender", "Get Notable History", "Get Notable Info"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Suspicious Reg exe Process", "Remote Registry Key modifications", "Hiding Files And Directories With Attrib exe", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys"] +searches = ["Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Hiding Files And Directories With Attrib exe", "Suspicious Reg exe Process", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious Changes to File Associations", "Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions"] +searches = ["Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Suspicious Changes to File Associations", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] +searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "Windows Event Log Cleared", "USN Journal Deletion", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Shim Database File Creation", "Detect Path Interception By Creation Of program exe", "Remote Registry Key modifications", "Monitor Registry Keys for Print Monitors", "Hiding Files And Directories With Attrib exe", "Sc exe Manipulating Windows Services", "Reg exe used to hide files directories via registry keys", "Schtasks used for forcing a reboot", "Reg exe Manipulating Windows Services Registry Keys", "Shim Database Installation With Suspicious Parameters", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence"] +searches = ["Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Registry Keys Used For Persistence", "Shim Database File Creation", "Detect Path Interception By Creation Of program exe", "Shim Database Installation With Suspicious Parameters", "Registry Keys for Creating SHIM Databases", "Sc exe Manipulating Windows Services", "Hiding Files And Directories With Attrib exe", "Schtasks used for forcing a reboot", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Uncommon Processes On Endpoint", "Overwriting Accessibility Binaries", "Child Processes of Spoolsv exe", "Registry Keys Used For Privilege Escalation"] +searches = ["Registry Keys Used For Privilege Escalation", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Uncommon Processes On Endpoint", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys"] +searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 9e1cf7b65dd85fbaee0a853afc1c9c87020e62c8 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 15:09:51 +0200 Subject: [PATCH 25/93] bug in generate --- bin/generate.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 52c217114f..303fab440a 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -75,10 +75,10 @@ def generate_savedsearches_conf(detections, response_tasks, baselines, deploymen for key in keys: if key == 'mitre_attack': if 'mitre_attack_id' in detection: - mappings[key] = detection['mitre_attack_id'] + mappings[key] = detection['tags']['mitre_attack_id'] else: if key in detection: - mappings[key] = detection[key] + mappings[key] = detection['tags'][key] detection['mappings'] = mappings From 8cf0c8a78819d647de5a65101e215e63e8b9cd44 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 15:12:40 +0200 Subject: [PATCH 26/93] bug in generate --- bin/generate.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 303fab440a..656b171edd 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -74,10 +74,10 @@ def generate_savedsearches_conf(detections, response_tasks, baselines, deploymen mappings = {} for key in keys: if key == 'mitre_attack': - if 'mitre_attack_id' in detection: + if 'mitre_attack_id' in detection['tags']: mappings[key] = detection['tags']['mitre_attack_id'] else: - if key in detection: + if key in detection['tags']: mappings[key] = detection['tags'][key] From d9c5d38d40ba8cc708f7f1541eeb27df5f4cf9dd Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 18:24:14 +0200 Subject: [PATCH 27/93] bug in generate --- bin/generate.py | 10 +- bin/jinja2_templates/savedsearches.j2 | 4 +- package/default/analytic_stories.conf | 120 +- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 376 ++--- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 128 +- tmp.js | 2232 +++++++++++++++++++++++++ 8 files changed, 2555 insertions(+), 319 deletions(-) create mode 100644 tmp.js diff --git a/bin/generate.py b/bin/generate.py index 656b171edd..08b0b2b50e 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -149,6 +149,8 @@ def generate_use_case_library_conf(stories, detections, response_tasks, baseline for story in stories: if story['name'] in sto_det: + detetions_new = [] + for detection in story['detections'] = list(sto_det[story['name']]) if story['name'] in sto_res: story['response_tasks'] = list(sto_res[story['name']]) @@ -253,9 +255,9 @@ def map_detection_to_stories(detections): if 'analytics_story' in detection['tags']: for story in detection['tags']['analytics_story']: if not (story in sto_det): - sto_det[story] = {detection['name']} + sto_det[story] = {str('ESCU - ' + detection['name'] + '- Rule')} else: - sto_det[story].add(detection['name']) + sto_det[story].add(str('ESCU - ' + detection['name'] + '- Rule')) return sto_det def map_response_tasks_to_stories(response_tasks): @@ -265,9 +267,9 @@ def map_response_tasks_to_stories(response_tasks): if 'analytics_story' in response_task['tags']: for story in response_task['tags']['analytics_story']: if not (story in sto_res): - sto_res[story] = {response_task['name']} + sto_res[story] = {str('ESCU - ' + response_task['name'])} else: - sto_res[story].add(response_task['name']) + sto_res[story].add(str('ESCU - ' + response_task['name'])) return sto_res diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 6c89f2fccb..3d1c186551 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -14,7 +14,7 @@ action.escu.enabled = 1 description = {{ detection.description }} action.escu.mappings = {{ detection.mappings | tojson }} {% if detection.data_model is defined %} -action.escu.data_models = [{{ detection.data_model }}] +action.escu.data_models = {{ detection.data_model }} {% endif %} action.escu.eli5 = {{ detection.description }} {% if detection.how_to_implement is defined %} @@ -34,6 +34,8 @@ action.escu.full_search_name = ESCU - {{ detection.name }} - Rule action.escu.search_type = detection {% if detection.providing_technologies is defined %} action.escu.providing_technologies = {{ detection.providing_technologies | tojson }} +{% else %} +action.escu.providing_technologies = none {% endif %} {% if detection.tags.analytics_story is defined %} action.escu.analytic_story = {{ detection.tags.analytics_story | tojson }} diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 523050bdca..5e7e7e30b8 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T12:53:42 UTC +# On Date: 2020-05-08T13:13:04 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started With Previously Unseen User"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Get EC2 Launch Details"] support_searches = [] data_models = none providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["AWS Network Access Control List Created with All Open Ports", "AWS Network Access Control List Deleted", "Detect Spike in Network ACL Activity", "Detect Spike in blocked Outbound Traffic from your AWS"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +investigative_searches = ["AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = none providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["Get All AWS Activity From City", "Get All AWS Activity From Region", "Get All AWS Activity From IP Address", "Get All AWS Activity From Country"] +investigative_searches = ["Get All AWS Activity From IP Address", "Get All AWS Activity From City", "Get All AWS Activity From Region", "Get All AWS Activity From Country"] support_searches = [] data_models = none providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["Detect API activity from users without MFA", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in AWS API Activity", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["Investigate AWS User Activities by user field", "Get Notable Info", "Get Notable History"] +investigative_searches = ["Get Notable History", "Get Notable Info", "Investigate AWS User Activities by user field"] support_searches = [] data_models = none providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["Detect Excessive Account Lockouts From Endpoint", "Detect Excessive User Account Lockouts", "Identify New User Accounts", "Short Lived Windows Accounts"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Logon Rights Modifications For User", "Get Logon Rights Modifications For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Logon Rights Modifications For User", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Logon Rights Modifications For Endpoint", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Suspicious Strings in HTTP Header", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Investigate Web POSTs From src", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Investigate Suspicious Strings in HTTP Header", "Investigate Web POSTs From src", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["Detect Unauthorized Assets by MAC address"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get First Occurrence and Last Occurrence of a MAC Address"] +investigative_searches = ["Get First Occurrence and Last Occurrence of a MAC Address", "Get Notable History", "Get Notable Info"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Started In Previously Unused Region"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Investigate Cloud Compute Instance Activities", "Investigate User Activities In Single Cloud Region", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate User Activities In Single Cloud Region", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Investigate Cloud Compute Instance Activities", "Get EC2 Launch Details"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["Get Notable History", "Get Risk Modifiers For User", "Investigate Network Traffic From src ip", "Get Authentication Logs For Endpoint", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Get Vulnerability Logs For Endpoint", "Investigate Network Traffic From src ip", "Get User Information from Identity Table", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = none providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "Get Parent Process Info", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +investigative_searches = ["AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Attempted Credential Dump From Registry via Reg exe", "Create Remote Thread into LSASS", "Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["Investigate Pass the Ticket Attempts", "Investigate Failed Logins for Multiple Destinations", "Investigate Previous Unseen User", "Investigate Pass the Hash Attempts"] +investigative_searches = ["Investigate Previous Unseen User", "Investigate Failed Logins for Multiple Destinations", "Investigate Pass the Hash Attempts", "Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["Create local admin accounts using net exe", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Malicious PowerShell Process - Execution Policy Bypass", "Processes launching netsh", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Sc exe Manipulating Windows Services", "Scheduled Task Name Used by Dragonfly Threat Actors", "Single Letter Process On Endpoint", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Registry Activity", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Process File Activity", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Process File Activity", "Get Parent Process Info", "Get Process Info", "Get Process Registry Activity", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["Large Volume of DNS ANY Queries"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["Get Risk Modifiers For User", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["Detect USB device insertion", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] +investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Unload Sysmon Filter Driver"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Investigate Web Activity From src ip"] +investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get DNS traffic ratio", "Investigate Web Activity From src ip", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["Detect Rare Executables", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Email Attachments With Lots Of Spaces", "Prohibited Software On Endpoint", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["Create or delete windows shares using net exe", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "Detect Outbound SMB Traffic", "First time seen command line argument", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious File Write"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get DNS Server History for a host", "Get Notable Info", "Get Vulnerability Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Investigate Web Activity From Host", "Get Risk Modifiers For Endpoint", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "GCP Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint", "Amazon EKS Kubernetes activity by src ip"] +investigative_searches = ["Get Notable Info", "GCP Kubernetes activity by src ip", "Get Notable History", "Amazon EKS Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint"] support_searches = [] data_models = none providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["All backup logs for host", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] +investigative_searches = ["Get Notable History", "All backup logs for host", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] support_searches = [] data_models = none providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["Prohibited Software On Endpoint"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["No Windows Updates in a time frame"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["Processes created by netsh", "Processes launching netsh"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["First Time Seen Running Windows Service", "First time seen command line argument", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Registry Keys Used For Persistence", "Remote Process Instantiation via WMI", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Scheduled tasks used in BadRabbit ransomware", "Schtasks used for forcing a reboot", "Spike in File Writes", "Suspicious wevtutil Usage", "System Processes Run From Unexpected Locations", "TOR Traffic", "USN Journal Deletion", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get Registry Activities", "Get Risk Modifiers For User", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["Detect New Login Attempts to Routers"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["SQL Injection with Long URLs"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["Batch File Write to System32", "Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Detect PsExec With accepteula Flag", "Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers", "File with Samsam Extension", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Samsam Test File Write", "Spike in File Writes"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["Spectre and Meltdown Vulnerable Systems"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["Open Redirect in Splunk Web"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] support_searches = [] data_models = none providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["Splunk Enterprise Information Disclosure"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Investigate Network Traffic From src ip", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["Get Notable Info", "Investigate Network Traffic From src ip", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] support_searches = [] data_models = none providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Get EC2 Launch Details"] support_searches = [] data_models = none providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["Detect New Open S3 buckets", "Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Investigate AWS activities via region name", "AWS S3 Bucket details via bucketName", "Get All AWS Activity From IP Address", "AWS Investigate User Activities By ARN", "Get User Information from Identity Table"] +investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get All AWS Activity From IP Address", "Get Notable History", "Get User Information from Identity Table", "AWS S3 Bucket details via bucketName"] support_searches = [] data_models = none providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +investigative_searches = ["AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = none providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] +investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts", "Okta User Logins From Multiple Cities"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["Investigate User Activities In Okta", "Investigate Okta Activity by IP Address", "Investigate Okta Activity by app"] +investigative_searches = ["Investigate Okta Activity by app", "Investigate User Activities In Okta", "Investigate Okta Activity by IP Address"] support_searches = [] data_models = none providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["Process Execution via WMI", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["Disabling Remote User Account Control", "Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["EC2 Instance Modified With Previously Unseen User"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get Notable History"] +investigative_searches = ["Get Notable History", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId"] support_searches = [] data_models = none providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["Detect Rare Executables", "Detect processes used for System Network Configuration Discovery", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Uncommon Processes On Endpoint", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["Protocols passing authentication in cleartext"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Process Information For Port Activity"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["Web Fraud - Account Harvesting", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["Get Web Session Information via session id", "Get Emails From Specific Sender", "Get Notable History", "Get Notable Info"] +investigative_searches = ["Get Notable History", "Get Notable Info", "Get Emails From Specific Sender", "Get Web Session Information via session id"] support_searches = [] data_models = none providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["Detect Path Interception By Creation Of program exe", "Hiding Files And Directories With Attrib exe", "Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index dd1f54bff7..1ad01626ec 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T12:53:42 UTC +# On Date: 2020-05-08T13:13:04 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index b07ae74e5b..4976edf7fc 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T12:53:42 UTC +# On Date: 2020-05-08T13:13:04 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -11,7 +11,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -47,7 +47,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceI action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -83,7 +83,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceI action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -119,7 +119,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) [search `cloudtrail` action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -155,7 +155,7 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceI action.escu = 0 action.escu.enabled = 1 description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} action.escu.eli5 = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. action.escu.known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. @@ -190,7 +190,7 @@ search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId pa action.escu = 0 action.escu.enabled = 1 description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. @@ -225,7 +225,7 @@ search = `cloudtrail` eventName=CreateNetworkAclEntry | mvexpand requestParamete action.escu = 0 action.escu.enabled = 1 description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that a user has legitimately deleted a network ACL. @@ -260,7 +260,7 @@ search = `cloudtrail` eventName=DeleteNetworkAcl|rename userIdentity.arn as arn action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -294,7 +294,7 @@ search = `cloudtrail` eventName=RunInstances errorCode=success | bucket span=10m action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -329,7 +329,7 @@ search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_ru action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. @@ -363,7 +363,7 @@ search = `cloudtrail` eventName=TerminateInstances errorCode=success | bucket sp action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -398,7 +398,7 @@ search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excess action.escu = 0 action.escu.enabled = 1 description = Detect memory dumping of the LSASS process. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.eli5 = Detect memory dumping of the LSASS process. action.escu.how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. @@ -431,7 +431,7 @@ search = `sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR action.escu = 0 action.escu.enabled = 1 description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API -action.escu.mappings = {} +action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} action.escu.eli5 = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. @@ -465,7 +465,7 @@ search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list o action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS -action.escu.mappings = {} +action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. @@ -499,7 +499,7 @@ search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!= action.escu = 0 action.escu.enabled = 1 description = Attempt to add a certificate to the untrusted certificate store -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -535,7 +535,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. @@ -571,7 +571,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for attempts to stop security-related services on the endpoint. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., @@ -607,7 +607,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -641,7 +641,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for a batch file (.bat) written to the Windows system directory tree. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -677,7 +677,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. @@ -713,7 +713,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ @@ -751,7 +751,7 @@ search = | tstats `security_content_summariesonly` count, values(DNS.dest) AS de action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances created by users who have not created them before. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. @@ -787,7 +787,7 @@ search = | tstats `security_content_summariesonly` earliest(_time) as firstTime, action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances being created with previously unseen image IDs. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. @@ -823,7 +823,7 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = Find EC2 instances being created with previously unseen instance types. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. @@ -859,7 +859,7 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. @@ -895,7 +895,7 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values action.escu = 0 action.escu.enabled = 1 description = The search looks for file modifications with extensions commonly used by Ransomware -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ @@ -935,7 +935,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. @@ -971,7 +971,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Detect remote thread creation into LSASS consistent with credential dumping. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.eli5 = Detect remote thread creation into LSASS consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. @@ -1004,7 +1004,7 @@ search = `sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as f action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of local administrator accounts using net.exe. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1040,7 +1040,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.user) action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation or deletion of hidden shares using net.exe. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1076,7 +1076,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.user) action.escu = 0 action.escu.enabled = 1 description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1110,7 +1110,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects the use of wmic and Powershell to create a shadow copy. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.eli5 = This search detects the use of wmic and Powershell to create a shadow copy. action.escu.how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. @@ -1143,7 +1143,7 @@ search = `sysmon` Message=*win32_shadowcopy* Message=*Create* | stats count min( action.escu = 0 action.escu.enabled = 1 description = This search detects credential dumping using copy command from a shadow copy. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1177,7 +1177,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects the creation of a symlink to a shadow copy. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1211,7 +1211,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ @@ -1253,7 +1253,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as start_tim action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. @@ -1288,7 +1288,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. @@ -1324,7 +1324,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ @@ -1364,7 +1364,7 @@ search = | inputlookup discovered_dns_records.csv | rename answer as discovered_ action.escu = 0 action.escu.enabled = 1 description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1400,7 +1400,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"]} action.escu.eli5 = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -1441,7 +1441,7 @@ search = `cloudtrail` userIdentity.sessionContext.attributes.mfaAuthenticated=fa action.escu = 0 action.escu.enabled = 1 description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} action.escu.eli5 = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -1482,7 +1482,7 @@ search = `cloudtrail` errorCode=success | rename userName as identity | search N action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1517,7 +1517,7 @@ search = | inputlookup previously_seen_users_console_logins.csv | stats min(firs action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1552,7 +1552,7 @@ search = | inputlookup previously_seen_users_console_logins.csv | stats min(firs action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1587,7 +1587,7 @@ search = | inputlookup previously_seen_users_console_logins.csv | stats min(firs action.escu = 0 action.escu.enabled = 1 description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} action.escu.eli5 = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. action.escu.how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. action.escu.known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. @@ -1622,7 +1622,7 @@ search = `wineventlog_security` EventCode=4624 (Logon_Type=3 LogonProcessName=Nt action.escu = 0 action.escu.enabled = 1 description = This search looks for reading lsass memory consistent with credential dumping. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} action.escu.eli5 = This search looks for reading lsass memory consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. @@ -1655,7 +1655,7 @@ search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR G action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ @@ -1695,7 +1695,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} action.escu.data_models = [Change] action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ @@ -1735,7 +1735,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects user accounts that have been locked out a relatively high number of times in a short period. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} action.escu.data_models = [Change] action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. @@ -1771,7 +1771,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model @@ -1806,7 +1806,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) as firs action.escu = 0 action.escu.enabled = 1 description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. @@ -1842,7 +1842,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.AE", "DE.CM"]} action.escu.eli5 = This search looks for reading loaded Images unique to credential dumping with Mimikatz. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. @@ -1875,7 +1875,7 @@ search = `sysmon` EventCode=7 | stats values(ImageLoaded) as ImageLoaded values( action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell requesting privileges consistent with credential dumping. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} action.escu.eli5 = This search looks for PowerShell requesting privileges consistent with credential dumping. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. action.escu.known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. @@ -1907,7 +1907,7 @@ search = `wineventlog_security` signature_id=4703 Process_Name=*powershell.exe | action.escu = 0 action.escu.enabled = 1 description = This search looks for newly created accounts that have been elevated to local administrators. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1078"], "nist": ["PR.AC", "DE.CM"]} action.escu.eli5 = This search looks for newly created accounts that have been elevated to local administrators. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ @@ -1948,7 +1948,7 @@ search = `wineventlog_security` signature_id=4720 OR (signature_id=4732 Group_Na action.escu = 0 action.escu.enabled = 1 description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} action.escu.data_models = [Authentication] action.escu.eli5 = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. @@ -1984,7 +1984,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) as earl action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} action.escu.eli5 = This search looks for CloudTrail events where a user has created an open/public S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. @@ -2019,7 +2019,7 @@ search = `cloudtrail` AllUsers eventName=PutBucketAcl | spath output=userIdentit action.escu = 0 action.escu.enabled = 1 description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} action.escu.eli5 = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. @@ -2054,7 +2054,7 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max( action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model @@ -2089,7 +2089,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) as earl action.escu = 0 action.escu.enabled = 1 description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. @@ -2125,7 +2125,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. @@ -2161,7 +2161,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2197,7 +2197,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. @@ -2233,7 +2233,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.dest) action.escu = 0 action.escu.enabled = 1 description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} action.escu.eli5 = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access logs' inputs. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. action.escu.known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour @@ -2267,7 +2267,7 @@ search = `aws_s3_accesslogs` http_status=200 [search `aws_s3_accesslogs` http_s action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} action.escu.eli5 = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -2308,7 +2308,7 @@ search = `cloudtrail` eventType=AwsApiCall [search `cloudtrail` eventType=AwsApi action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} action.escu.eli5 = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. @@ -2343,7 +2343,7 @@ search = `cloudtrail` `network_acl_events` [search `cloudtrail` `network_acl_eve action.escu = 0 action.escu.enabled = 1 description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} action.escu.eli5 = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. @@ -2378,7 +2378,7 @@ search = `cloudtrail` eventName=DeleteBucket [search `cloudtrail` eventName=Dele action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} action.escu.eli5 = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. @@ -2413,7 +2413,7 @@ search = `cloudtrail` `security_group_api_calls` [search `cloudtrail` `security_ action.escu = 0 action.escu.enabled = 1 description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} action.escu.eli5 = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. @@ -2447,7 +2447,7 @@ search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=17 action.escu = 0 action.escu.enabled = 1 description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} action.escu.data_models = [Change_Analysis] action.escu.eli5 = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. @@ -2483,7 +2483,7 @@ search = | tstats `security_content_summariesonly` count earliest(_time) AS earl action.escu = 0 action.escu.enabled = 1 description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} action.escu.data_models = [Network_Sessions] action.escu.eli5 = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. @@ -2518,7 +2518,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -2554,7 +2554,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. -action.escu.mappings = {} +action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} action.escu.data_models = [Web] action.escu.eli5 = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. @@ -2590,7 +2590,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ @@ -2631,7 +2631,7 @@ search = | tstats `security_content_summariesonly` count values(DNS.answer) as a action.escu = 0 action.escu.enabled = 1 description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} action.escu.data_models = [Web] action.escu.eli5 = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model @@ -2667,7 +2667,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -2703,7 +2703,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. action.escu.known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. @@ -2738,7 +2738,7 @@ search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=A action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -2773,7 +2773,7 @@ search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | action.escu = 0 action.escu.enabled = 1 description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. @@ -2809,7 +2809,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for web connections to dynamic DNS providers. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"]} action.escu.data_models = [Web] action.escu.eli5 = This search looks for web connections to dynamic DNS providers. action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ @@ -2847,7 +2847,7 @@ search = | tstats `security_content_summariesonly` count values(Web.url) as url action.escu = 0 action.escu.enabled = 1 description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "PR.DS"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. @@ -2883,7 +2883,7 @@ search = | tstats `security_content_summariesonly` dc("DNS.query") as count fro action.escu = 0 action.escu.enabled = 1 description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072", "T1087"], "nist": ["PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2919,7 +2919,7 @@ search = | tstats `security_content_summariesonly` count min(_time) values(Proce action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. @@ -2954,7 +2954,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Detect the usage of comsvcs.dll for dumping the lsass process. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2988,7 +2988,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being modified by users who have not previously modified them. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for EC2 instances being modified by users who have not previously modified them. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. action.escu.known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. @@ -3023,7 +3023,7 @@ search = `cloudtrail` `ec2_modification_api_calls` [search `cloudtrail` `ec2_mod action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} action.escu.eli5 = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. @@ -3057,7 +3057,7 @@ search = `cloudtrail` earliest=-1h StartInstances | stats earliest(_time) as ear action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen AMIs. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for EC2 instances being created with previously unseen AMIs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. action.escu.known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. @@ -3091,7 +3091,7 @@ search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunI action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen instance types. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. @@ -3126,7 +3126,7 @@ search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunI action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created by users who have not created them before. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} action.escu.eli5 = This search looks for EC2 instances being created by users who have not created them before. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. action.escu.known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. @@ -3161,7 +3161,7 @@ search = `cloudtrail` eventName=RunInstances [search `cloudtrail` eventName=RunI action.escu = 0 action.escu.enabled = 1 description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} action.escu.data_models = [Email] action.escu.eli5 = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ @@ -3198,7 +3198,7 @@ search = | tstats `security_content_summariesonly` count values(All_Email.recipi action.escu = 0 action.escu.enabled = 1 description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. @@ -3234,7 +3234,7 @@ search = | tstats `security_content_summariesonly` count values(Filesystem.file_ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. @@ -3269,7 +3269,7 @@ search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_out) as action.escu = 0 action.escu.enabled = 1 description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. @@ -3304,7 +3304,7 @@ search = | tstats `security_content_summariesonly` count values("DNS.query") as action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -3340,7 +3340,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. @@ -3376,7 +3376,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search returns a list of hosts that have not successfully completed a backup in over a week. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} action.escu.eli5 = This search returns a list of hosts that have not successfully completed a backup in over a week. action.escu.how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. action.escu.known_false_positives = None identified @@ -3411,7 +3411,7 @@ search = `netbackup` MESSAGE="Disk/Partition backup completed successfully." | s action.escu = 0 action.escu.enabled = 1 description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -3447,7 +3447,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for the first time a Windows service is seen running in your environment. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} action.escu.eli5 = This search looks for the first time a Windows service is seen running in your environment. action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. action.escu.known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. @@ -3482,7 +3482,7 @@ search = `wineventlog_system` signature_id=7036 | rename param1 as service_name action.escu = 0 action.escu.enabled = 1 description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. @@ -3552,7 +3552,7 @@ search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM data action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster -action.escu.mappings = {} +action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. @@ -3586,7 +3586,7 @@ search = `google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp! action.escu = 0 action.escu.enabled = 1 description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3622,7 +3622,7 @@ search = | tstats `security_content_summariesonly` count min(_time) values(Proce action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. @@ -3657,7 +3657,7 @@ search = | tstats `security_content_summariesonly` sum(All_Traffic.bytes_in) as action.escu = 0 action.escu.enabled = 1 description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} action.escu.eli5 = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. action.escu.how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. action.escu.known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. @@ -3691,7 +3691,7 @@ search = | from datamodel Identity_Management.All_Identities | eval empStatus=c action.escu = 0 action.escu.enabled = 1 description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. @@ -3726,7 +3726,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. @@ -3761,7 +3761,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3797,7 +3797,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3833,7 +3833,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3869,7 +3869,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process_id) action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3905,7 +3905,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -3941,7 +3941,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. -action.escu.mappings = {} +action.escu.mappings = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -3976,7 +3976,7 @@ search = | tstats `security_content_summariesonly` values(DNS.answer) as IPs min action.escu = 0 action.escu.enabled = 1 description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -4011,7 +4011,7 @@ search = | tstats `security_content_summariesonly` values(All_Email.recipient) a action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} action.escu.eli5 = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = You will encounter noise from legitimate print-monitor registry entries. @@ -4046,7 +4046,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} action.escu.data_models = [Web] action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -4082,7 +4082,7 @@ search = | tstats `security_content_summariesonly` values(Web.url) as urls min(_ action.escu = 0 action.escu.enabled = 1 description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} action.escu.eli5 = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. @@ -4151,7 +4151,7 @@ search = | tstats count min(_time) as firstTime max(_time) as lastTime FROM data action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} action.escu.data_models = [Updates] action.escu.eli5 = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. @@ -4187,7 +4187,7 @@ search = | tstats `security_content_summariesonly` max(_time) as lastTime from d action.escu = 0 action.escu.enabled = 1 description = Detect Okta user lockout events -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} action.escu.eli5 = Detect Okta user lockout events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. @@ -4221,7 +4221,7 @@ search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.g action.escu = 0 action.escu.enabled = 1 description = Detect failed Okta SSO events -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} action.escu.eli5 = Detect failed Okta SSO events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. @@ -4255,7 +4255,7 @@ search = `okta` displayMessage="User attempted unauthorized access to app" | sta action.escu = 0 action.escu.enabled = 1 description = This search detects logins from the same user from different states in a 24 hour period. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} action.escu.eli5 = This search detects logins from the same user from different states in a 24 hour period. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. @@ -4290,7 +4290,7 @@ search = `okta` displayMessage="User login to Okta" client.geographicalContext.c action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.escu.how_to_implement = No extra steps needed to implement this search. action.escu.known_false_positives = None identified @@ -4324,7 +4324,7 @@ search = index=_internal sourcetype=splunk_web_access return_to="/%09/*" | `open action.escu = 0 action.escu.enabled = 1 description = This search looks for ColdRoot events from the osx-attacks osquery pack. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} action.escu.eli5 = This search looks for ColdRoot events from the osx-attacks osquery pack. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model action.escu.known_false_positives = There are no known false positives. @@ -4358,7 +4358,7 @@ search = | from datamodel Alerts.Alerts | search app=osquery:results (name=pack_ action.escu = 0 action.escu.enabled = 1 description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -4394,7 +4394,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched via WMI. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} action.escu.eli5 = This search looks for processes launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. @@ -4429,7 +4429,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"]} action.escu.eli5 = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. action.escu.known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. @@ -4463,7 +4463,7 @@ search = | from datamodel Alerts.Alerts | search app=osquery:results name=pack_o action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -4499,7 +4499,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model @@ -4535,7 +4535,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. @@ -4570,7 +4570,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as prohibited. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. @@ -4606,7 +4606,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "PR.AC"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. @@ -4641,7 +4641,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. @@ -4677,7 +4677,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} action.escu.eli5 = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. @@ -4712,7 +4712,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for command-line arguments used to hide a file or directory using the reg add command. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -4748,7 +4748,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} action.escu.eli5 = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. @@ -4783,7 +4783,7 @@ search = | tstats `security_content_summariesonly` count values(Registry.registr action.escu = 0 action.escu.enabled = 1 description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. @@ -4818,7 +4818,7 @@ search = | tstats `security_content_summariesonly` count values(Registry.registr action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. action.escu.how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications @@ -4852,7 +4852,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. @@ -4888,7 +4888,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. @@ -4924,7 +4924,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. @@ -4960,7 +4960,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -4996,7 +4996,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search monitors for remote modifications to registry keys. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = This search monitors for remote modifications to registry keys. action.escu.how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. @@ -5031,7 +5031,7 @@ search = | tstats `security_content_summariesonly` count values(Registry.registr action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to operate on remote systems. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5067,7 +5067,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1085"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5103,7 +5103,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. @@ -5139,7 +5139,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ @@ -5178,7 +5178,7 @@ search = | tstats `security_content_summariesonly` count values(All_Traffic.dest action.escu = 0 action.escu.enabled = 1 description = This search looks for long URLs that have several SQL commands visible within them. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} action.escu.data_models = [Web] action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. @@ -5214,7 +5214,7 @@ search = | tstats `security_content_summariesonly` count from datamodel=Web wher action.escu = 0 action.escu.enabled = 1 description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -5250,7 +5250,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5286,7 +5286,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5322,7 +5322,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5358,7 +5358,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5394,7 +5394,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -5430,7 +5430,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search looks for scripts launched via WMI. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} action.escu.eli5 = This search looks for scripts launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. @@ -5465,7 +5465,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} action.escu.eli5 = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. @@ -5500,7 +5500,7 @@ search = | tstats `security_content_summariesonly` count values(Filesystem.actio action.escu = 0 action.escu.enabled = 1 description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5536,7 +5536,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search detects accounts that were created and deleted in a short time period. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} action.escu.data_models = [Change] action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ @@ -5572,7 +5572,7 @@ search = | tstats `security_content_summariesonly` values(All_Changes.result_id) action.escu = 0 action.escu.enabled = 1 description = This search looks for process names that consist only of a single letter. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for process names that consist only of a single letter. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5607,7 +5607,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} action.escu.data_models = [Vulnerabilities] action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. @@ -5642,7 +5642,7 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_ action.escu = 0 action.escu.enabled = 1 description = The search looks for a sharp increase in the number of files written to a particular host -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} action.escu.eli5 = The search looks for a sharp increase in the number of files written to a particular host action.escu.how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, such as Carbon Black or endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the file system. action.escu.known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. @@ -5677,7 +5677,7 @@ search = | tstats `security_content_summariesonly` count FROM datamodel=Endpoint action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. action.escu.how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. action.escu.known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. @@ -5712,7 +5712,7 @@ search = index=_internal sourcetype=splunkd_ui_access server-info | search clien action.escu = 0 action.escu.enabled = 1 description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} action.escu.eli5 = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. @@ -5747,7 +5747,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} action.escu.data_models = [UEBA] action.escu.eli5 = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. @@ -5783,7 +5783,7 @@ search = |tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for emails that have attachments with suspicious file extensions. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ @@ -5820,7 +5820,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names that have been linked to malicious activity. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = The search looks for files created with names that have been linked to malicious activity. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. action.escu.known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. @@ -5855,7 +5855,7 @@ search = | tstats `security_content_summariesonly` count values(Filesystem.actio action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"]} action.escu.eli5 = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. action.escu.known_false_positives = There are no known false positives. @@ -5890,7 +5890,7 @@ search = `stream_http` http_method=POST http_content_length>1 | regex form_data= action.escu = 0 action.escu.enabled = 1 description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} action.escu.eli5 = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. @@ -5925,7 +5925,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112", "T1089"], "nist": ["DE.CM"]} action.escu.eli5 = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. @@ -5960,7 +5960,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -5996,7 +5996,7 @@ search = | tstats `security_content_summariesonly` values(Processes.process) as action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the 'System Volume Information' folder by something other than the System process. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} action.escu.eli5 = This search detects writes to the 'System Volume Information' folder by something other than the System process. action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. @@ -6030,7 +6030,7 @@ search = (`sysmon` OR tag=process) EventCode=11 process_id!=4 file_path=*System\ action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the recycle bin by a process other than explorer.exe. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} action.escu.eli5 = This search detects writes to the recycle bin by a process other than explorer.exe. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. action.escu.known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. @@ -6065,7 +6065,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. action.escu.how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. action.escu.known_false_positives = None identified @@ -6100,7 +6100,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE"]} action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. @@ -6135,7 +6135,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} action.escu.data_models = [Endpoint] action.escu.eli5 = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -6171,7 +6171,7 @@ search = | tstats `security_content_summariesonly` count values(Processes.proces action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as uncommon. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["ID.AM", "PR.DS"]} action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. @@ -6207,7 +6207,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["DE.CM"]} action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. @@ -6243,7 +6243,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search detects loading of unsigned images by LSASS. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} action.escu.eli5 = This search detects loading of unsigned images by LSASS. action.escu.how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. @@ -6276,7 +6276,7 @@ search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_tim action.escu = 0 action.escu.enabled = 1 description = This search gives you the hosts where a backup was attempted and then failed. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} action.escu.eli5 = This search gives you the hosts where a backup was attempted and then failed. action.escu.how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. action.escu.known_false_positives = None identified @@ -6310,7 +6310,7 @@ search = `netbackup` | stats latest(_time) as latestTime by COMPUTERNAME, MESSAG action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships, from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some legitimate applications start with long command lines. @@ -6345,7 +6345,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. action.escu.how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. action.escu.known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. @@ -6380,7 +6380,7 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} action.escu.eli5 = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.escu.how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. action.escu.known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. @@ -6414,7 +6414,7 @@ search = `stream_http` | eval cs_content_type_length = len(cs_content_type) | wh action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI permanent event subscriptions. -action.escu.mappings = {} +action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. @@ -6449,7 +6449,7 @@ search = `wmi` EventCode=5861 Binding | rex field=Message "Consumer =\s+(? 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Unauthorized Assets by MAC address", "Get Notable Info", "Get Notable History", "Get First Occurrence and Last Occurrence of a MAC Address"] +searches = ["Detect Unauthorized Assets by MAC address", "Get First Occurrence and Last Occurrence of a MAC Address", "Get Notable History", "Get Notable Info"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse", "Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] +searches = ["Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Started In Previously Unused Region", "Abnormally High AWS Instances Launched by User - MLTK", "Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Investigate Cloud Compute Instance Activities", "Investigate User Activities In Single Cloud Region", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +searches = ["Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Started In Previously Unused Region", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate User Activities In Single Cloud Region", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Investigate Cloud Compute Instance Activities", "Get EC2 Launch Details"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events", "Get Notable History", "Get Risk Modifiers For User", "Investigate Network Traffic From src ip", "Get Authentication Logs For Endpoint", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events", "Get Vulnerability Logs For Endpoint", "Investigate Network Traffic From src ip", "Get User Information from Identity Table", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious writes to System Volume Information", "Email servers sending high volume traffic to hosts", "Suspicious writes to windows Recycle Bin", "Hosts receiving high volume of network traffic from email server", "Email files written outside of the Outlook directory", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to windows Recycle Bin", "Email files written outside of the Outlook directory", "Suspicious writes to System Volume Information", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect Large Outbound ICMP Packets", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detection of DNS Tunnels", "Detect Spike in blocked Outbound Traffic from your AWS", "Prohibited Network Traffic Allowed", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "Protocol or Port Mismatch", "Excessive DNS Failures", "DNS Query Length Outliers - MLTK", "TOR Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "Get Parent Process Info", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +searches = ["Detect Large Outbound ICMP Packets", "DNS Query Length With High Standard Deviation", "Excessive DNS Failures", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detect Spike in blocked Outbound Traffic from your AWS", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "TOR Traffic", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "Detect Long DNS TXT Record Response", "AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["New container uploaded to AWS ECR", "GCP GCR container uploaded", "Investigate AWS ECR container listing activity"] +searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR", "Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect Credential Dumping through LSASS access", "Creation of Shadow Copy with wmic and powershell", "Unsigned Image Loaded by LSASS", "Creation of Shadow Copy", "Attempted Credential Dump From Registry via Reg exe", "Credential Dumping via Symlink to Shadow Copy", "Create Remote Thread into LSASS", "Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Credential Dumping via Copy Command from Shadow Copy", "Dump LSASS via comsvcs DLL", "Detect Mimikatz Using Loaded Images", "Investigate Pass the Ticket Attempts", "Investigate Failed Logins for Multiple Destinations", "Investigate Previous Unseen User", "Investigate Pass the Hash Attempts"] +searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Credential Dumping via Copy Command from Shadow Copy", "Access LSASS Memory for Dump Creation", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Symlink to Shadow Copy", "Unsigned Image Loaded by LSASS", "Dump LSASS via comsvcs DLL", "Create Remote Thread into LSASS", "Attempted Credential Dump From Registry via Reg exe", "Creation of Shadow Copy", "Detect Mimikatz Using Loaded Images", "Detect Credential Dumping through LSASS access", "Investigate Previous Unseen User", "Investigate Failed Logins for Multiple Destinations", "Investigate Pass the Hash Attempts", "Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["SMB Traffic Spike - MLTK", "Malicious PowerShell Process - Execution Policy Bypass", "Single Letter Process On Endpoint", "Registry Keys Used For Persistence", "Scheduled Task Name Used by Dragonfly Threat Actors", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Detect New Local Admin account", "Processes launching netsh", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Sc exe Manipulating Windows Services", "Create local admin accounts using net exe", "Suspicious Reg exe Process", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Registry Activity", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Process File Activity", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["Sc exe Manipulating Windows Services", "First time seen command line argument", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Detect PsExec With accepteula Flag", "Processes launching netsh", "Single Letter Process On Endpoint", "Detect New Local Admin account", "Create local admin accounts using net exe", "Scheduled Task Name Used by Dragonfly Threat Actors", "Malicious PowerShell Process - Execution Policy Bypass", "Registry Keys Used For Persistence", "Detect Outbound SMB Traffic", "Suspicious Reg exe Process", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Process File Activity", "Get Parent Process Info", "Get Process Info", "Get Process Registry Activity", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Large Volume of DNS ANY Queries", "Get Risk Modifiers For User", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +searches = ["Large Volume of DNS ANY Queries", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Clients Connecting to Multiple DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Get DNS Server History for a host"] +searches = ["Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Detection of DNS Tunnels", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] +searches = ["Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Attempt To Add Certificate To Untrusted Store", "Unload Sysmon Filter Driver", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Sc exe Manipulating Windows Services", "Unload Sysmon Filter Driver", "Processes launching netsh", "Attempt To Stop Security Service", "Suspicious Reg exe Process", "Attempt To Add Certificate To Untrusted Store", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Investigate Web Activity From src ip"] +searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers", "Get DNS Server History for a host", "Get Notable Info", "Get DNS traffic ratio", "Investigate Web Activity From src ip", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["SMB Traffic Spike - MLTK", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Registry Keys Used For Persistence", "Prohibited Software On Endpoint", "SMB Traffic Spike", "Detect Rare Executables", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["Detect Rare Executables", "Detection of tools built by NirSoft", "SMB Traffic Spike - MLTK", "Detect Use of cmd exe to Launch Script Interpreters", "Registry Keys Used For Persistence", "Suspicious Email Attachment Extensions", "Prohibited Software On Endpoint", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Length With High Standard Deviation", "SMB Traffic Spike - MLTK", "Suspicious File Write", "Create or delete windows shares using net exe", "First time seen command line argument", "SMB Traffic Spike", "Detect Outbound SMB Traffic", "Remote Desktop Process Running On System", "DNS Query Length Outliers - MLTK", "Remote Desktop Network Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["DNS Query Length With High Standard Deviation", "First time seen command line argument", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "DNS Query Length Outliers - MLTK", "Suspicious File Write", "Remote Desktop Process Running On System", "Create or delete windows shares using net exe", "Remote Desktop Network Traffic", "Detect Outbound SMB Traffic", "Investigate Web Activity From Host", "Get DNS Server History for a host", "Get Notable Info", "Get Vulnerability Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Clients Connecting to Multiple DNS Servers", "Windows hosts file modification", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get DNS Server History for a host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Windows hosts file modification", "Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Get DNS Server History for a host", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers", "Get Notable Info", "Get Notable History", "Investigate Web Activity From Host", "Get Risk Modifiers For Endpoint", "Get Vulnerability Logs For Endpoint"] +searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Get Notable Info", "Get Notable History", "GCP Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint", "Amazon EKS Kubernetes activity by src ip"] +searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "Get Notable Info", "GCP Kubernetes activity by src ip", "Get Notable History", "Amazon EKS Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Schtasks scheduling job on remote system", "Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Process Running On System", "Remote Desktop Network Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system", "Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Malicious PowerShell Process With Obfuscation Techniques", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process With Obfuscation Techniques", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups", "All backup logs for host", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] +searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups", "Get Notable History", "All backup logs for host", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Prohibited Software On Endpoint", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["Prohibited Software On Endpoint", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["No Windows Updates in a time frame", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +searches = ["No Windows Updates in a time frame", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Processes launching netsh", "Processes created by netsh", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Processes launching netsh", "Processes created by netsh", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["First time seen command line argument", "First Time Seen Running Windows Service", "Sc exe Manipulating Windows Services", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "First time seen command line argument", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process", "Get Parent Process Info"] +searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file", "Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["Unusually Long Command Line", "Registry Keys Used For Persistence", "First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Unusually Long Command Line - MLTK", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Unusually Long Command Line - MLTK", "First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Unusually Long Command Line", "Registry Keys Used For Persistence", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Protocol or Port Mismatch", "Prohibited Network Traffic Allowed", "TOR Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Prohibited Network Traffic Allowed", "Detect hosts connecting to dynamic domain providers", "Protocol or Port Mismatch", "TOR Traffic", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Unusually Long Command Line", "Common Ransomware Notes", "Remote Process Instantiation via WMI", "SMB Traffic Spike - MLTK", "USN Journal Deletion", "Spike in File Writes", "Scheduled tasks used in BadRabbit ransomware", "Registry Keys Used For Persistence", "Common Ransomware Extensions", "Suspicious wevtutil Usage", "Prohibited Network Traffic Allowed", "SMB Traffic Spike", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Deleting Shadow Copies", "Schtasks used for forcing a reboot", "Windows Event Log Cleared", "TOR Traffic", "Get Process Information For Port Activity", "Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["Deleting Shadow Copies", "Unusually Long Command Line - MLTK", "SMB Traffic Spike", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "Spike in File Writes", "System Processes Run From Unexpected Locations", "Remote Process Instantiation via WMI", "Registry Keys Used For Persistence", "Schtasks used for forcing a reboot", "USN Journal Deletion", "Suspicious wevtutil Usage", "Unusually Long Command Line", "Common Ransomware Extensions", "TOR Traffic", "Prohibited Network Traffic Allowed", "Common Ransomware Notes", "Scheduled tasks used in BadRabbit ransomware", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get Registry Activities", "Get Risk Modifiers For User", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect New Login Attempts to Routers", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Detect New Login Attempts to Routers", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["SQL Injection with Long URLs", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["SQL Injection with Long URLs", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Common Ransomware Notes", "Spike in File Writes", "Remote Desktop Network Bruteforce", "Detect PsExec With accepteula Flag", "Common Ransomware Extensions", "File with Samsam Extension", "Detect malicious requests to exploit JBoss servers", "Prohibited Software On Endpoint", "Samsam Test File Write", "Deleting Shadow Copies", "Batch File Write to System32", "Detect attackers scanning for vulnerable JBoss servers", "Remote Desktop Network Traffic", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Update Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Backup Logs For Endpoint", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["Deleting Shadow Copies", "Spike in File Writes", "File with Samsam Extension", "Detect attackers scanning for vulnerable JBoss servers", "Batch File Write to System32", "Detect PsExec With accepteula Flag", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Common Ransomware Extensions", "Prohibited Software On Endpoint", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Notes", "Samsam Test File Write", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Spectre and Meltdown Vulnerable Systems", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Spectre and Meltdown Vulnerable Systems", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Open Redirect in Splunk Web", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +searches = ["Open Redirect in Splunk Web", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Splunk Enterprise Information Disclosure", "Get Notable Info", "Get Notable History", "Investigate Network Traffic From src ip", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] +searches = ["Splunk Enterprise Information Disclosure", "Get Notable Info", "Investigate Network Traffic From src ip", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Terminated by User - MLTK", "Abnormally High AWS Instances Terminated by User", "EC2 Instance Started With Previously Unseen User", "Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Get Notable Info", "Get Notable History", "Get EC2 Launch Details", "Investigate AWS activities via region name", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table"] +searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User", "AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Get EC2 Launch Details"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login", "AWS Investigate User Activities By ARN"] +searches = ["Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New Country", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New City", "AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect New Open S3 buckets", "Detect Spike in S3 Bucket deletion", "Detect S3 access from a new IP", "Get Notable Info", "Get Notable History", "Investigate AWS activities via region name", "AWS S3 Bucket details via bucketName", "Get All AWS Activity From IP Address", "AWS Investigate User Activities By ARN", "Get User Information from Identity Table"] +searches = ["Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets", "AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get All AWS Activity From IP Address", "Get Notable History", "Get User Information from Identity Table", "AWS S3 Bucket details via bucketName"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Risk Modifiers For Endpoint", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Authentication Logs For Endpoint", "AWS Network Interface details via resourceId", "AWS Investigate User Activities By ARN", "Get DNS traffic ratio", "Get User Information from Identity Table"] +searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Unusually Long Command Line", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Detect Prohibited Applications Spawning cmd exe", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Unusually Long Command Line - MLTK", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Prohibited Applications Spawning cmd exe", "Unusually Long Command Line", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detection of DNS Tunnels", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "Excessive DNS Failures", "DNS Query Length Outliers - MLTK", "Get Notable Info", "Get Notable History", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For User", "Get Process Info", "Get DNS Server History for a host", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get DNS traffic ratio", "Get User Information from Identity Table"] +searches = ["DNS Query Length With High Standard Deviation", "Excessive DNS Failures", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "Detect Long DNS TXT Record Response", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Suspicious Email - UBA Anomaly", "Monitor Email For Brand Abuse", "Email Attachments With Lots Of Spaces", "Suspicious Email Attachment Extensions", "Get Notable Info", "Get Emails From Specific Sender", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get Email Info"] +searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email Attachment Extensions", "Suspicious Email - UBA Anomaly", "Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Failed SSO Attempts", "Okta Account Lockout Events", "Okta User Logins From Multiple Cities", "Investigate User Activities In Okta", "Investigate Okta Activity by IP Address", "Investigate Okta Activity by app"] +searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta User Logins From Multiple Cities", "Okta Failed SSO Attempts", "Investigate Okta Activity by app", "Investigate User Activities In Okta", "Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription", "Process Execution via WMI", "Script Execution via WMI", "Get Sysmon WMI Activity for Host", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Process Execution via WMI", "WMI Permanent Event Subscription - Sysmon", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "WMI Temporary Event Subscription", "WMI Permanent Event Subscription", "Script Execution via WMI", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Monitor Registry Keys for Print Monitors", "Registry Keys Used For Privilege Escalation", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Registry Keys Used For Persistence", "Suspicious Changes to File Associations", "Registry Keys for Creating SHIM Databases", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Remote Registry Key modifications", "Suspicious Changes to File Associations", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Monitor Registry Keys for Print Monitors", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["EC2 Instance Modified With Previously Unseen User", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId", "Get Notable History"] +searches = ["EC2 Instance Modified With Previously Unseen User", "Get Notable History", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Unusually Long Command Line", "Uncommon Processes On Endpoint", "RunDLL Loading DLL By Ordinal", "Detect processes used for System Network Configuration Discovery", "Detect Rare Executables", "System Processes Run From Unexpected Locations", "Unusually Long Command Line - MLTK", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Uncommon Processes On Endpoint", "Detect Rare Executables", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Protocols passing authentication in cleartext", "Get Process Information For Port Activity", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Protocols passing authentication in cleartext", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Process Information For Port Activity"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["Web Fraud - Password Sharing Across Accounts", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Account Harvesting", "Get Web Session Information via session id", "Get Emails From Specific Sender", "Get Notable History", "Get Notable Info"] +searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Account Harvesting", "Get Notable History", "Get Notable Info", "Get Emails From Specific Sender", "Get Web Session Information via session id"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Hiding Files And Directories With Attrib exe", "Suspicious Reg exe Process", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Remote Registry Key modifications", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Hiding Files And Directories With Attrib exe", "Suspicious Reg exe Process", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Suspicious Changes to File Associations", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Suspicious Changes to File Associations", "Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "Windows Event Log Cleared", "USN Journal Deletion", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table", "Get Vulnerability Logs For Endpoint"] +searches = ["Suspicious wevtutil Usage", "Deleting Shadow Copies", "Windows Event Log Cleared", "USN Journal Deletion", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Registry Keys Used For Persistence", "Shim Database File Creation", "Detect Path Interception By Creation Of program exe", "Shim Database Installation With Suspicious Parameters", "Registry Keys for Creating SHIM Databases", "Sc exe Manipulating Windows Services", "Hiding Files And Directories With Attrib exe", "Schtasks used for forcing a reboot", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Sc exe Manipulating Windows Services", "Detect Path Interception By Creation Of program exe", "Remote Registry Key modifications", "Reg exe Manipulating Windows Services Registry Keys", "Schtasks used for forcing a reboot", "Reg exe used to hide files directories via registry keys", "Shim Database Installation With Suspicious Parameters", "Registry Keys for Creating SHIM Databases", "Hiding Files And Directories With Attrib exe", "Registry Keys Used For Persistence", "Shim Database File Creation", "Monitor Registry Keys for Print Monitors", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Registry Keys Used For Privilege Escalation", "Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Uncommon Processes On Endpoint", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Registry Activities", "Investigate Web Activity From Host", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Uncommon Processes On Endpoint", "Registry Keys Used For Privilege Escalation", "Overwriting Accessibility Binaries", "Child Processes of Spoolsv exe", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For User", "Get Process Info", "Get Parent Process Info", "Get Authentication Logs For Endpoint", "Get Risk Modifiers For Endpoint", "Get User Information from Identity Table"] +searches = ["Sc exe Manipulating Windows Services", "Reg exe Manipulating Windows Services Registry Keys", "First Time Seen Running Windows Service", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. diff --git a/tmp.js b/tmp.js new file mode 100644 index 0000000000..d92c18ed1f --- /dev/null +++ b/tmp.js @@ -0,0 +1,2232 @@ +webpackJsonp([40], { + 0: function(e, t, a) { + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + a.p = function() { + function e() { + for (var e, a, n = "", l = 0, r = arguments.length; l < r; l++) e = arguments[l].toString(), a = e.length, a > 1 && "/" == e.charAt(a - 1) && (e = e.substring(0, a - 1)), n += "/" != e.charAt(0) ? 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p.default.createElement(h.default, { + content: t + }, l) : l; + return r + } + }]), t + }(c.Component); + E.propTypes = { + readiness: _.default.number, + reason: _.default.string + }, E.defaultProps = { + readiness: null, + reason: null + }, t.default = E, e.exports = t.default + }, + 2929: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(1733), + r = n(l), + o = a(3), + i = n(o), + s = a(1353), + u = n(s), + d = a(834), + f = n(d), + c = a(864), + p = n(c), + m = a(865), + h = n(m), + g = a(869), + y = n(g), + v = a(870), + k = n(v), + S = a(1453), + _ = n(S), + C = a(886), + b = a(1358), + E = a(1673), + R = n(E), + M = a(2930), + q = n(M), + O = a(2931), + w = n(O), + A = a(1619), + T = n(A), + D = a(1633), + L = n(D), + U = a(1620), + I = n(U), + B = a(1621), + x = n(B), + F = a(1628), + P = n(F), + j = a(1682), + N = n(j), + z = a(2126), + H = a(1), + K = a(889), + W = a(1684), + V = n(W), + $ = a(1688), + J = n($), + G = a(1618), + Q = n(G), + X = a(1617), + Y = n(X), + Z = a(2935), + ee = n(Z), + te = a(2936), + ae = n(te), + ne = a(1352), + le = a(1610), + re = n(le), + oe = a(888), + ie = a(2199), + se = a(1626); + a(57); + var ue = {}, + de = { + output_mode: "json", + count: -1, + f: "datasets" + }, + fe = { + paddingLeft: 10, + width: 190, + float: "left" + }, + ce = { + marginLeft: 200 + }, + pe = { + padding: "0 10px" + }, + me = { + paddingTop: 10, + paddingBottom: 10, + paddingRight: 10 + }, + he = { + marginLeft: 1, + paddingTop: 10 + }, + ge = function(e) { + function t(e) { + (0, p.default)(this, t); + var a = (0, y.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).call(this, e)); + return a.state = { + useCases: [], + analyticStories: [], + selectedCategories: [], + searchValue: "", + searchTerm: "", + errorMsg: "", + isLoading: !0, + openDiscoverRecStoriesModal: !1, + dataModels: [], + dataSources: [], + apps: [], + modal: "", + optOut: !1, + annotations: [], + filterMetadata: [], + filterApp: "", + filterDataSource: "", + filterDataModel: "", + filterInUse: "", + filterBookmarked: "", + dataModelsSearchesMap: new Map, + dataSourcesSearchesMap: new Map + }, a.handleCategoryClick = a.handleCategoryClick.bind(a), a.handleSearchChange = a.handleSearchChange.bind(a), a.handleAnnotationClick = a.handleAnnotationClick.bind(a), a.handleBookmarkClick = a.handleBookmarkClick.bind(a), a.handleFiltersChange = a.handleFiltersChange.bind(a), a.handleMetadataFilterChange = a.handleMetadataFilterChange.bind(a), a.updateMetadataState = a.updateMetadataState.bind(a), a.setSearchTerm = (0, K.debounce)(a.setSearchTerm, 300), a.fetchSearchContentInfo = a.fetchSearchContentInfo.bind(a), a.currentUser = (0, C.getCurrentUser)(), a.fetchStoryContentInfo = a.fetchStoryContentInfo.bind(a), a.handleCloseESCUModal = a.handleCloseESCUModal.bind(a), a.handleOptOutClick = a.handleOptOutClick.bind(a), a + } + return (0, k.default)(t, e), (0, h.default)(t, [{ + key: "componentWillMount", + value: function() { + var e = (0, C.getURLParameter)("category"); + null !== e && this.setState({ + selectedCategories: [e] + }) + } + }, { + key: "componentDidMount", + value: function() { + var e = this; + Promise.all([(0, z.fetchAnalyticStories)(), (0, z.fetchSavedSearches)(), (0, C.getUserPrefModel)(), (0, z.fetchUseCasesCategories)()]).then(function(t) { + var a = (0, f.default)(t, 4), + n = a[0], + l = a[1], + r = a[2], + o = a[3]; + e.userPrefModel = r; + var i = (0, z.getAnalyticStoriesFromResponse)(n), + s = (0, z.getUseCasesFromResponse)(o), + u = (0, z.getSavedSearchesFromResponse)(l), + d = (0, z.mergeAnalyticStoriesWithSearches)(i, u), + c = (0, z.getMetadataInfo)(d) || {}, + p = { + useCases: s, + analyticStories: d, + isLoading: !1, + annotations: c.annotations + }; + return e.setState(p), d + }).catch(function() { + e.setState({ + errorMsg: (0, H._)("Error fetching the analytic stories."), + isLoading: !1 + }) + }).then(function(t) { + return e.setSavedSearchPropertiesAndInUse(t) + }).then(function(t) { + return e.setBookmarkedStories(t) + }).then(function(e) { + var t = (0, K.uniqBy)(e, "app").map(function(e) { + return e.app + }).concat(["DA-ESS-ContentUpdate"]); + return Promise.all([e, (0, C.getApps)((0, C.getSearchStringByNames)(t))]) + }).then(function(t) { + var a = (0, f.default)(t, 2), + n = a[0], + l = a[1], + r = l.find(function(e) { + return "DA-ESS-ContentUpdate" === e.name + }), + o = !1; + r || (0, b.normalizeBoolean)(e.userPrefModel.entry.content.get("dontShowESCUModal")) || (o = !0); + var i = n.map(function(e) { + var t = l.find(function(t) { + return t.name === e.app + }), + a = t && t.content && t.content.label ? t.content.label : e.app; + return Object.assign(e, { + appLabel: a + }) + }); + e.setState((0, u.default)({ + apps: l.map(function(e) { + return { + name: e.name, + label: e.content.label + } + }) + }, o && { + modal: "escu" + }, { + analyticStories: i + })) + }), this.fetchAndSetDataModelsDataSources() + } + }, { + key: "setSavedSearchPropertiesAndInUse", + value: function(e) { + var t = this; + return new Promise(function(a) { + (0, C.fetchRESTURL)("saved/searches", { + app: oe.app, + owner: "nobody" + }, { + output_mode: "json", + count: 0 + }).then(function(t) { + var n = e.slice().map(function(e) { + return e.searches = e.searches.map(function(e) { + var a = t.entry.find(function(t) { + return e.name === t.name + }); + return Object.assign(e, { + label: void 0 !== a ? a.content["action.correlationsearch.label"] : "", + active: void 0 !== a && a.content.is_scheduled && a.content.disabled === !1, + app: void 0 !== a ? a.acl.app : "", + uri: void 0 !== a ? a.links.edit : "", + isCorrelationSearch: void 0 !== a && (0, b.normalizeBoolean)(a.content["action.correlationsearch.enabled"]) === !0 + }) + }), e.in_use = e.searches.some(function(e) { + return "detection" === e.type && e.active + }), e + }); + a(n) + }).catch(function(n) { + t.setState({ + errorMsg: (0, H._)("Error detecting if analytic stories are in use.") + " " + n + }), a(e) + }) + }) + } + }, { + key: "setBookmarkedStories", + value: function(e) { + var t = this.getCurrentBookmarks(); + if (t.length > 0) { + var a = e.slice().map(function(e) { + return e.bookmarked = Boolean(t.indexOf(e.name) !== -1), e + }); + return a + } + return e.map(function(e) { + return e.bookmarked = !1, e + }) + } + }, { + key: "getFilteredStories", + value: function(e, t, a) { + var n = arguments.length > 3 && void 0 !== arguments[3] ? arguments[3] : {}, + l = this.state, + r = l.dataModelsSearchesMap, + o = l.dataSourcesSearchesMap, + i = e; + if (a.length > 0) { + var s = a.map(function(e) { + return e.toLowerCase() + }); + i = i.filter(function(e) { + return (0, K.includes)(s, e.category.toLowerCase()) + }) + } + if (t.length > 0) { + var u = t.toLowerCase(); + i = i.filter(function(e) { + return e.category.toLowerCase().includes(u) || e.name.toLowerCase().includes(u) || e.narrative.toLowerCase().includes(u) || e.description.toLowerCase().includes(u) || (0, z.isAnnotationContainedInStory)(e, t) + }) + } + if (void 0 !== n.filterApp && "" !== n.filterApp && (i = i.filter(function(e) { + return e.app === n.filterApp + })), void 0 !== n.filterInUse && "" !== n.filterInUse) { + var d = Splunk.util.normalizeBoolean(n.filterInUse); + i = i.filter(function(e) { + return e.in_use === d + }) + } + if (void 0 !== n.filterBookmarked && "" !== n.filterBookmarked) { + var f = Splunk.util.normalizeBoolean(n.filterBookmarked); + i = i.filter(function(e) { + return e.bookmarked === f + }) + } + if (void 0 !== n.filterMetadata && n.filterMetadata.length > 0 && (i = i.filter(function(e) { + return n.filterMetadata.some(function(t) { + return (0, z.isAnnotationContainedInStory)(e, t) + }) + })), void 0 !== n.filterDataModel && n.filterDataModel.length > 0) { + var c = r.get(n.filterDataModel); + void 0 === c ? i = [] : c.length > 0 && (i = i.filter(function(e) { + return e.searches.some(function(e) { + return c.indexOf(e.name) !== -1 + }) + })) + } + if (void 0 !== n.filterDataSource && n.filterDataSource.length > 0) { + var p = o.get(n.filterDataSource); + void 0 === p ? i = [] : p.length > 0 && (i = i.filter(function(e) { + return e.searches.some(function(e) { + return p.indexOf(e.name) !== -1 + }) + })) + } + return i + } + }, { + key: "setSearchTerm", + value: function(e) { + this.setState({ + searchTerm: e + }) + } + }, { + key: "getCurrentBookmarks", + value: function() { + var e = void 0; + try { + e = this.userPrefModel.entry.content.get("analyticStoryBookmarks") || "[]", e = JSON.parse(e) + } catch (t) { + e = [] + } + return e + } + }, { + key: "getAnalyticStoriesLabel", + value: function(e, t) { + if (0 === e.length) return "" + (0, H._)("0 Analytic Stories found in the selected categories"); + var a = t.join(", "), + n = 1 === t.length ? (0, H._)("category") + ": " + a : (0, H._)("categories") + ": " + a, + l = 1 === e.length ? "" + (0, H._)("Analytic Story found in") : "" + (0, H._)("Analytic Stories found in"); + return e.length + " " + l + " " + n + } + }, { + key: "getUseCaseCards", + value: function(e) { + var t = this, + a = this.state.selectedCategories; + return e.map(function(e) { + return _.default.createElement(q.default, { + key: e.id, + id: e.name, + name: e.name, + description: e.description, + icon: e.icon, + selected: (0, K.includes)(a, e.name), + onClick: t.handleCategoryClick + }) + }) + } + }, { + key: "handleAnnotationClick", + value: function(e, t) { + var a = this.state.filterMetadata, + n = a.slice(); + n.indexOf(t) === -1 ? n.push(t) : n.splice(n.indexOf(t), 1), this.updateMetadataState(n) + } + }, { + key: "updateMetadataState", + value: function(e) { + this.setState({ + filterMetadata: e.slice() + }) + } + }, { + key: "handleCloseESCUModal", + value: function() { + var e = this.state.optOut; + this.userPrefModel.entry.content.set({ + dontShowESCUModal: e + }), this.userPrefModel.save(), this.setState({ + modal: "" + }) + } + }, { + key: "handleOptOutClick", + value: function(e, t) { + var a = t.value; + this.setState({ + optOut: !a + }) + } + }, { + key: "fetchSearchContentInfo", + value: function(e) { + return ue[e] ? Promise.resolve(ue[e]) : new Promise(function(t) { + (0, ie.fetchContentInfo)("savedsearch", e, "nobody", oe.app, de).then(function(a) { + if (a && a.entry && a.entry.length > 0 && a.entry[0].content && a.entry[0].content.datasets) { + var n = (0, ie.parseDatasets)(a.entry[0].content.datasets); + ue[e] = n, t(n) + } + t({}) + }).catch(function() { + t({}) + }) + }) + } + }, { + key: "fetchStoryContentInfo", + value: function(e) { + var t = this; + return new Promise(function(a) { + var n = e.searches.filter(function(e) { + return "detection" === e.type + }).map(function(e) { + return t.fetchSearchContentInfo(e.name) + }); + Promise.all(n).then(function(n) { + var l = (0, z.getMetadataInfo)([e]), + r = l.technologies.map(function(e) { + return { + label: e, + id: e + } + }), + o = n.filter(function(e) { + return e.size > 0 + }), + s = o.map(function(e) { + return e.get("sourcetype") + }), + u = o.map(function(e) { + return e.get("datamodel") + }), + d = o.map(function(e) { + return e.get("lookup") + }); + a({ + providingTechnologies: r, + sourcetypes: t.addReadinessToItems("sourcetype", K.unionBy.apply(void 0, (0, i.default)(s).concat(["id"]))), + dataModels: t.addReadinessToItems("datamodel", K.unionBy.apply(void 0, (0, i.default)(u).concat(["id"]))), + lookups: t.addReadinessToItems("lookup", K.unionBy.apply(void 0, (0, i.default)(d).concat(["id"]))) + }) + }) + }) + } + }, { + key: "addReadinessToItems", + value: function(e, t) { + return t.map(function(t) { + return t.reason = (0, ie.getReasonForReadiness)(e, t.readiness), t + }) + } + }, { + key: "fetchAndSetDataModelsDataSources", + value: function() { + var e = this; + (0, ie.fetchContentInfo)("datamodel", void 0, "nobody", oe.app).then(function(t) { + e.setState({ + dataModels: t.entry.map(function(e) { + return e.name + }) + }) + }).catch(function() { + e.setState({ + errorMsg: (0, H._)("Error fetching the data models.") + }) + }); + var t = { + output_mode: "json", + count: -1 + }; + (0, C.fetchRESTURL)("storage/collections/data/dataset_cache", { + app: "SA-Utils", + owner: "nobody" + }, t).then(function(t) { + var a = t.filter(function(e) { + return "datamodel" === e.type && e.usedby && e.usedby.savedsearch + }).map(function(e) { + return [e.name, e.usedby.savedsearch] + }), + n = new Map(a); + e.setState({ + dataModelsSearchesMap: n + }) + }).catch(function() {}) + } + }, { + key: "handleBookmarkClick", + value: function(e, t) { + var a = t.value, + n = this.state.analyticStories, + l = this.getCurrentBookmarks(); + l.indexOf(a) === -1 ? l.push(a) : l = l.filter(function(e) { + return e !== a + }), this.userPrefModel.entry.content.set({ + analyticStoryBookmarks: JSON.stringify(l) + }), this.userPrefModel.save(); + var r = n.slice().map(function(e) { + return e.name === a && (e.bookmarked = !e.bookmarked), e + }); + this.setState({ + analyticStories: r + }) + } + }, { + key: "handleMetadataFilterChange", + value: function(e, t) { + var a = t.values; + this.updateMetadataState(a) + } + }, { + key: "handleFiltersChange", + value: function(e, t) { + var a = t.name, + n = t.value; + this.setState((0, r.default)({}, a, n)) + } + }, { + key: "handleCategoryClick", + value: function(e, t) { + var a = t.value, + n = this.state.selectedCategories, + l = n; + (0, K.includes)(l, a) ? this.setState({ + selectedCategories: (0, K.without)(l, a) + }): this.setState({ + selectedCategories: l.concat(a) + }) + } + }, { + key: "handleSearchChange", + value: function(e, t) { + var a = t.value; + this.setState({ + searchValue: a + }), this.setSearchTerm(a) + } + }, { + key: "render", + value: function() { + var e = this, + t = this.state, + a = t.errorMsg, + n = t.isLoading, + l = t.analyticStories, + r = t.searchTerm, + o = t.selectedCategories, + i = t.filterMetadata, + s = t.filterApp, + u = t.filterDataSource, + d = t.filterDataModel, + f = t.filterInUse, + c = t.filterBookmarked, + p = t.useCases, + m = t.modal, + h = t.optOut, + g = t.apps, + y = t.annotations, + v = t.dataModels, + k = t.dataSources, + S = t.searchValue, + C = t.openDiscoverRecStoriesModal, + b = { + searchTerm: r, + metadata: i, + app: s, + dataSource: u, + dataModel: d, + inUse: f, + bookmarked: c + }, + E = a.length > 0; + if (n) return _.default.createElement(Y.default, { + size: "medium", + style: se.spinnerStyle + }); + var M = this.getFilteredStories(l, r, o, { + filterMetadata: i, + filterApp: s, + filterDataSource: u, + filterDataModel: d, + filterInUse: f, + filterBookmarked: c + }), + q = (0, K.uniq)(M.map(function(e) { + return e.category + })), + O = this.getAnalyticStoriesLabel(M, q), + A = (0, ne.makeURLfromArgs)("manager", oe.app, "appsremote", { + count: 1, + query: "Splunk ES Content Update" + }); + return _.default.createElement(_.default.Fragment, null, _.default.createElement(Q.default, { + pageTitle: (0, H._)("Use Case Library"), + pageDescr: (0, H._)("Explore the Analytic Stories included with Enterprise Security that provide analysis guidance on how to investigate and take actions on threats that ES detects."), + descriptionPadding: "0 200px 0 0", + border: !0 + }), E && _.default.createElement(re.default, { + fill: !0, + type: "error", + style: se.marginLeftRight20 + }, a), _.default.createElement("div", null, _.default.createElement("div", { + "data-test": "use-cases-column", + style: fe + }, _.default.createElement(T.default, { + style: se.marginTop20, + level: 2 + }, (0, H._)("Use Cases")), _.default.createElement(V.default, null, this.getUseCaseCards(p))), _.default.createElement("div", { + style: ce + }, _.default.createElement("div", { + style: me + }, _.default.createElement(R.default, null, _.default.createElement(R.default.Row, null, _.default.createElement(R.default.Column, null, _.default.createElement(R.default.Row, null, _.default.createElement(R.default.Column, { + style: se.noMargin, + span: 10, + "data-test": "use-case-filters" + }, _.default.createElement(ae.default, { + apps: g, + annotations: y, + dataModels: v, + dataSources: k, + onFilterChanged: this.handleFiltersChange, + onMetadataChanged: this.handleMetadataFilterChange, + filterMetadata: i, + filterInUse: f, + filterDataModel: d, + filterDataSource: u, + filterApp: s, + filterBookmarked: c + })), _.default.createElement(R.default.Column, { + style: pe, + span: 2 + }, _.default.createElement(J.default, { + appearance: "search", + value: S, + placeholder: (0, H._)("filter..."), + onChange: this.handleSearchChange, + "data-test": "filterText" + }))), _.default.createElement(R.default.Row, null, _.default.createElement(R.default.Column, { + span: 12, + style: he + }, O)))))), _.default.createElement("div", null, _.default.createElement(w.default, { + filters: b, + analyticStories: M, + onAnnotationClick: this.handleAnnotationClick, + fetchStoryContentInfo: this.fetchStoryContentInfo, + handleBookmarkClick: this.handleBookmarkClick + })))), _.default.createElement(ee.default, { + open: C, + onRequestClose: function() { + return e.setState({ + openDiscoverRecStoriesModal: !1 + }) + }, + onClick: function() { + return e.setState({ + openDiscoverRecStoriesModal: !1 + }) + } + }), _.default.createElement(L.default, { + onRequestClose: this.handleCloseESCUModal, + open: "escu" === m, + style: se.modalStyle450 + }, _.default.createElement(L.default.Header, { + title: (0, H._)("ES Content Update Recommended"), + onRequestClose: this.handleCloseESCUModal + }), _.default.createElement(L.default.Body, null, _.default.createElement(I.default, null, (0, H._)("Download and install the ES Content Update add-on for access to common security analytic stories.")), _.default.createElement(I.default, null, _.default.createElement(x.default, { + to: A, + openInNewContext: !0 + }, "Install ES Content Update App from Splunk")), _.default.createElement(I.default, null, _.default.createElement(x.default, { + to: "https://splunkbase.splunk.com/app/3449", + openInNewContext: !0 + }, "ES Content Update App on Splunkbase"))), _.default.createElement(L.default.Footer, null, _.default.createElement(N.default, { + style: se.floatLeft, + onClick: this.handleOptOutClick, + selected: h, + value: h + }, _.default.createElement("span", { + style: se.fontSize12 + }, (0, H._)("Don't show this modal again."))), _.default.createElement(P.default, { + onClick: this.handleCloseESCUModal, + label: (0, H._)("Close") + })))) + } + }]), t + }(S.Component); + t.default = ge, e.exports = t.default + }, + 2930: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(864), + r = n(l), + o = a(865), + i = n(o), + s = a(869), + u = n(s), + d = a(870), + f = n(d), + c = a(1453), + p = n(c), + m = a(1461), + h = n(m), + g = a(2178), + y = n(g), + v = a(1652), + k = n(v); + a(57); + var S = function(e) { + return { + width: 180, + minWidth: 100, + marginBottom: 10, + background: e ? "#ECF8FF" : "#FFF" + } + }, + _ = { + fontWeight: "bold" + }, + C = { + textAlign: "center" + }, + b = function(e) { + function t() { + return (0, r.default)(this, t), (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).apply(this, arguments)) + } + return (0, f.default)(t, e), (0, i.default)(t, [{ + key: "render", + value: function() { + var e = this.props, + t = e.id, + a = e.description, + n = e.onClick, + l = e.selected, + r = e.name, + o = e.icon, + i = { + height: 72, + width: 72, + marginTop: -111 + }, + s = { + height: 76, + width: 76, + borderRadius: "50%", + display: "inline-block", + border: "solid 1px " + (l ? "#007ABD" : "#ffffff") + }; + return p.default.createElement(k.default, { + content: a, + defaultPlacement: "right" + }, p.default.createElement(y.default, { + style: S(l), + value: t, + onClick: n, + selected: l + }, p.default.createElement(y.default.Header, { + title: r, + truncateTitle: !1, + style: _ + }), p.default.createElement(y.default.Body, { + style: C + }, p.default.createElement("div", { + style: s + }), p.default.createElement("img", { + src: o, + style: i, + alt: r + })))) + } + }]), t + }(c.Component); + b.propTypes = { + name: h.default.string.isRequired, + id: h.default.string.isRequired, + description: h.default.string.isRequired, + icon: h.default.string.isRequired, + selected: h.default.bool.isRequired, + onClick: h.default.func.isRequired + }, t.default = b, e.exports = t.default + }, + 2931: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(864), + r = n(l), + o = a(865), + i = n(o), + s = a(869), + u = n(s), + d = a(870), + f = n(d), + c = a(1453), + p = n(c), + m = a(1), + h = a(1352), + g = a(888), + y = a(2932), + v = n(y), + k = a(1621), + S = n(k), + _ = a(1909), + C = n(_), + b = a(1461), + E = n(b), + R = a(1847), + M = n(R), + q = a(1814), + O = n(q), + w = a(1652), + A = n(w), + T = a(1859), + D = n(T), + L = a(1682), + U = n(L), + I = a(1701), + B = n(I), + x = a(1626); + a(57); + var F = function(e) { + function t(e, a) { + (0, r.default)(this, t); + var n = (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).call(this, e, a)); + return n.handleSort = n.handleSort.bind(n), n.state = { + sortKey: "name", + sortDir: "asc" + }, n + } + return (0, f.default)(t, e), (0, i.default)(t, [{ + key: "getExpansionRow", + value: function(e) { + var t = this.props, + a = t.onAnnotationClick, + n = t.fetchStoryContentInfo; + return p.default.createElement(C.default.Row, { + key: e.name + "-expansion" + }, p.default.createElement(C.default.Cell, { + style: x.noBorderTop, + colSpan: 7 + }, p.default.createElement(v.default, { + anStory: e, + onAnnotationClick: a, + fetchStoryContentInfo: n + }))) + } + }, { + key: "getStoryInUseComponent", + value: function(e) { + return void 0 === e.in_use ? p.default.createElement(D.default, null) : p.default.createElement(A.default, { + content: e.in_use ? (0, m._)("Story is in use") : (0, m._)("No searches are active") + }, e.in_use ? p.default.createElement(O.default, { + "data-test": "in-use", + screenReaderText: "" + }) : p.default.createElement(M.default, { + "data-test": "not-in-use", + screenReaderText: "" + })) + } + }, { + key: "sortAnalyticStoriesWithKey", + value: function(e, t, a) { + var n = "asc" === a ? 1 : -1; + return e.sort(function(e, a) { + return e[t] < a[t] ? -1 * n : e[t] > a[t] ? 1 * n : 0 + }) + } + }, { + key: "handleSort", + value: function(e, t) { + var a = t.sortKey, + n = this.state.sortDir, + l = this.state.sortKey, + r = l === a ? n : "none", + o = "asc" === r ? "desc" : "asc"; + this.setState({ + sortKey: a, + sortDir: o + }) + } + }, { + key: "renderAnalyticStoryRow", + value: function(e) { + var t = this.props.handleBookmarkClick, + a = e.name, + n = (0, h.makeURLfromArgs)("app", g.app, "ess_analytic_story_details", { + analytic_story: a + }); + return p.default.createElement(C.default.Row, { + key: e.id, + expansionRow: this.getExpansionRow(e) + }, p.default.createElement(C.default.Cell, { + align: "center", + "data-test": "in-use-section", + "data-test-value": e.in_use + }, this.getStoryInUseComponent(e)), p.default.createElement(C.default.Cell, { + data: e, + "data-test": "analytic-story-section", + "data-test-value": a + }, p.default.createElement(S.default, { + to: n + }, a)), p.default.createElement(C.default.Cell, { + data: e, + "data-test": "use-case-section", + "data-test-value": e.category + }, e.category), p.default.createElement(C.default.Cell, { + "data-test": "description-section" + }, e.description), p.default.createElement(C.default.Cell, { + "data-test": "app-section" + }, e.appLabel), p.default.createElement(C.default.Cell, { + "data-test": "last-updated-section" + }, B.default.newSplunkTime({ + time: e.last_updated + }).format("ll")), p.default.createElement(C.default.Cell, { + "data-test": "bookmarked-section", + "data-test-value": e.bookmarked + }, void 0 !== e.bookmarked && p.default.createElement(U.default, { + key: e.id, + value: e.name, + onClick: t, + selected: e.bookmarked, + selectedLabel: (0, m._)("Bookmark enabled"), + unselectedLabel: (0, m._)("Bookmark disabled"), + appearance: "toggle", + size: "small" + }))) + } + }, { + key: "render", + value: function() { + var e = this, + t = this.state, + a = t.sortKey, + n = t.sortDir, + l = this.props, + r = l.analyticStories, + o = l.filters, + i = o.searchTerm, + s = o.metadata, + u = o.app, + d = o.dataSource, + f = o.dataModel, + c = o.inUse, + h = o.bookmarked, + g = this.sortAnalyticStoriesWithKey(r, a, n); + return p.default.createElement(C.default, { + stripeRows: !0, + rowExpansion: "single", + innerStyle: x.tableStyle, + "data-test-filter-metadata": s.join(","), + "data-test-filter-app": u, + "data-test-filter-datasource": d, + "data-test-filter-datamodel": f, + "data-test-filter-inuse": c, + "data-test-filter-bookmarked": h, + "data-test-search-term": i + }, p.default.createElement(C.default.Head, null, p.default.createElement(C.default.HeadCell, { + width: 30 + }, (0, m._)("In use")), p.default.createElement(C.default.HeadCell, { + width: 180, + onSort: this.handleSort, + sortKey: "name", + sortDir: "name" === a ? n : "none" + }, (0, m._)("Analytic Story")), p.default.createElement(C.default.HeadCell, { + width: 140, + onSort: this.handleSort, + sortKey: "category", + sortDir: "category" === a ? n : "none" + }, (0, m._)("Use Case")), p.default.createElement(C.default.HeadCell, null, (0, m._)("Description")), p.default.createElement(C.default.HeadCell, { + width: 110, + onSort: this.handleSort, + sortKey: "app", + sortDir: "app" === a ? n : "none" + }, (0, m._)("App")), p.default.createElement(C.default.HeadCell, { + width: 90, + onSort: this.handleSort, + sortKey: "last_updated", + sortDir: "last_updated" === a ? n : "none" + }, (0, m._)("Last Updated")), p.default.createElement(C.default.HeadCell, { + width: 90, + onSort: this.handleSort, + sortKey: "bookmarked", + sortDir: "bookmarked" === a ? n : "none" + }, (0, m._)("Bookmark"))), p.default.createElement(C.default.Body, null, g.map(function(t) { + return e.renderAnalyticStoryRow(t) + }))) + } + }]), t + }(c.Component); + F.propTypes = { + analyticStories: E.default.arrayOf(E.default.shape({ + name: E.default.string.isRequired, + description: E.default.string.isRequired, + app: E.default.string.isRequired, + category: E.default.string.isRequired, + in_use: E.default.bool, + bookmarked: E.default.bool, + last_updated: E.default.string.isRequired, + annotations: E.default.arrayOf(E.default.shape({ + name: E.default.string.isRequired, + items: E.default.arrayOf(E.default.string).isRequired + })).isRequired, + searches: E.default.arrayOf(E.default.shape({ + type: E.default.string.isRequired, + name: E.default.string.isRequired + })).isRequired + }).isRequired).isRequired, + onAnnotationClick: E.default.func.isRequired, + fetchStoryContentInfo: E.default.func.isRequired, + handleBookmarkClick: E.default.func.isRequired, + filters: E.default.shape({ + searchTerm: E.default.string.isRequired, + metadata: E.default.arrayOf(E.default.string).isRequired, + app: E.default.string.isRequired, + dataSource: E.default.string.isRequired, + dataModel: E.default.string.isRequired, + inUse: E.default.string.isRequired, + bookmarked: E.default.string.isRequired + }).isRequired + }, t.default = F, e.exports = t.default + }, + 2932: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(864), + r = n(l), + o = a(865), + i = n(o), + s = a(869), + u = n(s), + d = a(870), + f = n(d), + c = a(1453), + p = n(c), + m = a(1461), + h = n(m), + g = a(1673), + y = n(g), + v = a(1), + k = a(1674), + S = n(k), + _ = a(1621), + C = n(_), + b = a(1352), + E = a(888), + R = a(2933), + M = n(R), + q = a(1652), + O = n(q), + w = a(1619), + A = n(w), + T = a(1620), + D = n(T), + L = a(1847), + U = n(L), + I = a(1814), + B = n(I), + x = a(2934), + F = n(x); + a(57); + var P = function(e) { + function t(e, a) { + (0, r.default)(this, t); + var n = (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).call(this, e, a)); + return n.state = { + dataModels: [], + providingTechnologies: [], + sourcetypes: [], + lookups: [], + loading: !1 + }, n + } + return (0, f.default)(t, e), (0, i.default)(t, [{ + key: "componentDidMount", + value: function() { + var e = this.props.anStory; + this.fetchData(e) + } + }, { + key: "componentDidUpdate", + value: function(e) { + var t = this.props.anStory; + t.id !== e.anStory.id && this.fetchData(t) + } + }, { + key: "fetchData", + value: function(e) { + var t = this, + a = this.props.fetchStoryContentInfo; + this.setState({ + loading: !0 + }), a(e).then(function(e) { + t.setState({ + providingTechnologies: e.providingTechnologies, + sourcetypes: e.sourcetypes, + dataModels: e.dataModels, + lookups: e.lookups, + loading: !1 + }) + }) + } + }, { + key: "genEditLink", + value: function(e) { + if (e.isCorrelationSearch) { + var t = (0, b.makeURLfromArgs)("app", E.app, "correlation_search_edit", { + search: e.name + }); + return p.default.createElement(C.default, { + to: t + }, (0, v._)("edit"), " ") + } + var a = (0, b.makeURLfromArgs)("manager", E.app, "saved", "searches", e.name, { + search: e.name, + app: e.app, + uri: e.uri, + action: "edit" + }); + return p.default.createElement(C.default, { + to: a + }, (0, v._)("edit saved search"), " ") + } + }, { + key: "render", + value: function() { + var e = this, + t = this.props, + a = t.anStory, + n = t.onAnnotationClick, + l = this.state, + r = l.sourcetypes, + o = l.dataModels, + i = l.providingTechnologies, + s = l.lookups, + u = l.loading, + d = { + padding: 5 + }, + f = { + borderStyle: "solid", + paddingRight: 5, + paddingLeft: 5, + borderWidth: .5, + borderColor: "#C3CBD4" + }, + c = (0, v._)("See all %d Lookups").replace("%d", s.length), + m = (0, v._)("See all %d Sourcetypes").replace("%d", r.length), + h = (0, v._)("See all %d Data Models").replace("%d", o.length), + g = (0, v._)("See all %d Data Sources").replace("%d", i.length), + k = a.searches.filter(function(e) { + return "detection" === e.type + }).map(function(t) { + return p.default.createElement(S.default.Item, { + "data-test-value": t.active, + "data-test-search": t.name, + key: t.name + }, p.default.createElement(O.default, { + content: t.active ? (0, v._)("Search is active") : (0, v._)("Search is not active") + }, t.active ? p.default.createElement(B.default, { + screenReaderText: "" + }) : p.default.createElement(U.default, { + screenReaderText: "" + })), " ", " ", t.name, " - ", e.genEditLink(t)) + }); + return p.default.createElement(y.default, { + style: f, + gutter: 0 + }, p.default.createElement(y.default.Row, null, p.default.createElement(y.default.Column, { + style: d, + span: 6 + }, p.default.createElement(O.default, { + content: (0, v._)("See all the searches by clicking on the Analytic Story name.") + }, p.default.createElement(A.default, null, (0, v._)("Detection Searches"))), 0 === k.length ? p.default.createElement(D.default, null, (0, v._)("No items found.")) : p.default.createElement(S.default, { + "data-test": "detection-searches-section" + }, k)), p.default.createElement(F.default, { + heading: (0, v._)("Recommended Data Sources"), + loading: u, + items: i, + anchorButtonLabel: g, + modalTitle: (0, v._)("All Data Sources"), + testString: "recommended-data-sources-section" + }), p.default.createElement(F.default, { + heading: (0, v._)("Sourcetypes"), + loading: u, + items: r, + anchorButtonLabel: m, + modalTitle: (0, v._)("All Sourcetypes"), + testString: "sourcetypes-section" + }), p.default.createElement(F.default, { + heading: (0, v._)("Data Models"), + loading: u, + items: o, + anchorButtonLabel: h, + modalTitle: (0, v._)("All Data Models"), + testString: "data-models-section" + }), p.default.createElement(F.default, { + heading: (0, v._)("Lookups"), + loading: u, + items: s, + anchorButtonLabel: c, + modalTitle: (0, v._)("All Lookups"), + testString: "lookups-section" + })), p.default.createElement(y.default.Row, null, p.default.createElement(y.default.Column, { + style: d, + span: 12, + "data-test": "framework-mapping-section" + }, p.default.createElement(A.default, null, (0, v._)("Framework Mapping")), p.default.createElement(M.default, { + data: a.annotations, + onItemClick: n + })))) + } + }]), t + }(c.Component); + P.propTypes = { + anStory: h.default.shape({ + id: h.default.string.isRequired, + annotations: h.default.arrayOf(h.default.shape({ + name: h.default.string.isRequired, + items: h.default.arrayOf(h.default.string).isRequired + })).isRequired, + searches: h.default.arrayOf(h.default.shape({ + type: h.default.string.isRequired, + name: h.default.string.isRequired, + isCorrelationSearch: h.default.bool.isRequired + })).isRequired + }).isRequired, + onAnnotationClick: h.default.func.isRequired, + fetchStoryContentInfo: h.default.func.isRequired + }, t.default = P, e.exports = t.default + }, + 2933: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(864), + r = n(l), + o = a(865), + i = n(o), + s = a(869), + u = n(s), + d = a(870), + f = n(d), + c = a(1453), + p = n(c), + m = a(2161), + h = n(m), + g = a(1461), + y = n(g); + a(57); + var v = function(e) { + function t() { + return (0, r.default)(this, t), (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).apply(this, arguments)) + } + return (0, f.default)(t, e), (0, i.default)(t, [{ + key: "render", + value: function() { + var e = this.props, + t = e.data, + a = e.onItemClick; + return t.map(function(e) { + return p.default.createElement(h.default, { + key: e.name, + name: e.name, + label: e.label || e.name, + color: e.color, + items: e.items, + onItemClick: a, + clickable: !0 + }) + }) + } + }]), t + }(c.Component); + v.propTypes = { + data: y.default.arrayOf(y.default.shape({ + color: y.default.string, + name: y.default.string.isRequired, + label: y.default.string.isRequired, + items: y.default.arrayOf(y.default.string).isRequired + })).isRequired, + onItemClick: y.default.func.isRequired + }, t.default = v, e.exports = t.default + }, + 2934: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(864), + r = n(l), + o = a(865), + i = n(o), + s = a(869), + u = n(s), + d = a(870), + f = n(d), + c = a(1453), + p = n(c), + m = a(1461), + h = n(m), + g = a(1673), + y = n(g), + v = a(1), + k = a(1619), + S = n(k), + _ = a(1617), + C = n(_), + b = a(1620), + E = n(b), + R = a(2203), + M = n(R); + a(57); + var q = { + padding: 5 + }, + O = function(e) { + function t() { + return (0, r.default)(this, t), (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).apply(this, arguments)) + } + return (0, f.default)(t, e), (0, i.default)(t, [{ + key: "render", + value: function() { + var e = this.props, + t = e.heading, + a = e.loading, + n = e.items, + l = e.anchorButtonLabel, + r = e.modalTitle, + o = e.testString; + return p.default.createElement(y.default.Column, { + style: q, + span: 2, + "data-test": o + }, p.default.createElement(S.default, { + level: 3 + }, t), a && p.default.createElement(C.default, { + size: "medium" + }), !a && 0 === n.length && p.default.createElement(E.default, null, (0, v._)("No items found.")), p.default.createElement(M.default, { + items: n, + anchorButtonLabel: l, + modalTitle: r + })) + } + }]), t + }(c.Component); + O.defaultProps = { + testString: "expanded-row-section" + }, O.propTypes = { + heading: h.default.string.isRequired, + loading: h.default.bool.isRequired, + anchorButtonLabel: h.default.string.isRequired, + modalTitle: h.default.string.isRequired, + items: h.default.arrayOf(h.default.shape({ + id: h.default.string.isRequired, + label: h.default.string.isRequired, + readiness: h.default.number + })).isRequired, + testString: h.default.string + }, t.default = O, e.exports = t.default + }, + 2935: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(864), + r = n(l), + o = a(865), + i = n(o), + s = a(869), + u = n(s), + d = a(870), + f = n(d), + c = a(1453), + p = n(c), + m = a(1461), + h = n(m), + g = a(1620), + y = n(g), + v = a(1633), + k = n(v), + S = a(1628), + _ = n(S), + C = a(1), + b = a(1626); + a(57); + var E = function(e) { + function t() { + return (0, r.default)(this, t), (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).apply(this, arguments)) + } + return (0, f.default)(t, e), (0, i.default)(t, [{ + key: "render", + value: function() { + var e = this.props, + t = e.onRequestClose, + a = e.open, + n = e.onClick; + return p.default.createElement(k.default, { + onRequestClose: t, + open: a, + style: b.modalStyle750 + }, p.default.createElement(k.default.Header, { + title: (0, C._)("Discover Recommended Stories Wizard"), + onRequestClose: t + }), p.default.createElement(k.default.Body, null, p.default.createElement(y.default, null, (0, C._)("ES will be able to identify your ingested data and recommend stories you should review and determine if they apply and decide if you want to monitor in your environment."))), p.default.createElement(k.default.Footer, null, p.default.createElement(_.default, { + appearance: "primary", + onClick: n, + label: (0, C._)("Close") + }))) + } + }]), t + }(c.Component); + E.propTypes = { + open: h.default.bool.isRequired, + onClick: h.default.func.isRequired, + onRequestClose: h.default.func.isRequired + }, t.default = E, e.exports = t.default + }, + 2936: function(e, t, a) { + "use strict"; + + function n(e) { + return e && e.__esModule ? e : { + default: e + } + } + Object.defineProperty(t, "__esModule", { + value: !0 + }); + var l = a(864), + r = n(l), + o = a(865), + i = n(o), + s = a(869), + u = n(s), + d = a(870), + f = n(d), + c = a(1453), + p = n(c), + m = a(1461), + h = n(m), + g = a(1), + y = a(1703), + v = n(y), + k = a(1679), + S = n(k), + _ = a(1673), + C = n(_); + a(57); + var b = { + width: "100%" + }, + E = function(e) { + function t() { + return (0, r.default)(this, t), (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).apply(this, arguments)) + } + return (0, f.default)(t, e), (0, i.default)(t, [{ + key: "getMetadataFilterSelect", + value: function() { + var e = this.props, + t = e.annotations, + a = e.filterMetadata, + n = e.onMetadataChanged, + l = t.reduce(function(e, t) { + return e.push(p.default.createElement(S.default.Heading, { + key: t.name, + level: 2 + }, t.label)), e.push(t.items.map(function(e) { + return p.default.createElement(S.default.Option, { + key: e, + label: e, + value: e + }) + })), e + }, []); + return p.default.createElement(S.default, { + style: b, + inline: !0, + values: a, + compact: !0, + name: "filterMetadata", + onChange: n, + placeholder: (0, g._)("Framework Mapping: All"), + "data-test": "filterMetadata" + }, l) + } + }, { + key: "getAppFilterSelect", + value: function() { + var e = this.props, + t = e.filterApp, + a = e.onFilterChanged, + n = e.apps; + return p.default.createElement(v.default, { + 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label: (0, g._)("True"), + value: "true" + }), p.default.createElement(v.default.Option, { + key: "false", + label: (0, g._)("False"), + value: "false" + })) + } + }, { + key: "getBookmarkedFilterSelect", + value: function() { + var e = this.props, + t = e.filterBookmarked, + a = e.onFilterChanged; + return p.default.createElement(v.default, { + style: b, + prefixLabel: (0, g._)("Bookmarked"), + name: "filterBookmarked", + value: t, + onChange: a, + "data-test": "filterBookmarked" + }, p.default.createElement(v.default.Option, { + key: "all", + label: (0, g._)("All"), + value: "" + }), p.default.createElement(v.default.Option, { + key: "true", + label: (0, g._)("True"), + value: "true" + }), p.default.createElement(v.default.Option, { + key: "false", + label: (0, g._)("False"), + value: "false" + })) + } + }, { + key: "render", + value: function() { + return p.default.createElement(C.default, { + gutter: 8 + }, p.default.createElement(C.default.Row, null, p.default.createElement(C.default.Column, { + span: 2.4 + }, this.getMetadataFilterSelect()), p.default.createElement(C.default.Column, { + span: 2.4 + }, this.getDataModelFilterSelect()), p.default.createElement(C.default.Column, { + span: 2.4 + }, this.getAppFilterSelect()), p.default.createElement(C.default.Column, { + span: 2.4 + }, this.getInUseFilterSelect()), p.default.createElement(C.default.Column, { + span: 2.4 + }, this.getBookmarkedFilterSelect()))) + } + }]), t + }(c.Component); + E.propTypes = { + apps: h.default.arrayOf(h.default.shape({ + name: h.default.string.isRequired, + label: h.default.string.isRequired + })).isRequired, + annotations: h.default.arrayOf(h.default.shape({ + name: h.default.string.isRequired, + label: h.default.string.isRequired, + items: h.default.arrayOf(h.default.string).isRequired + })).isRequired, + dataModels: h.default.arrayOf(h.default.string).isRequired, + dataSources: h.default.arrayOf(h.default.string).isRequired, + onFilterChanged: h.default.func.isRequired, + onMetadataChanged: h.default.func.isRequired, + filterMetadata: h.default.arrayOf(h.default.string).isRequired, + filterInUse: h.default.string.isRequired, + filterDataModel: h.default.string.isRequired, + filterDataSource: h.default.string.isRequired, + filterApp: h.default.string.isRequired, + filterBookmarked: h.default.string.isRequired + }, t.default = E, e.exports = t.default + } +}); From d684530ed3170d85bb642cfd41214ece451e3483 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 18:27:18 +0200 Subject: [PATCH 28/93] bug in generate --- bin/generate.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 08b0b2b50e..45ad505841 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -149,8 +149,6 @@ def generate_use_case_library_conf(stories, detections, response_tasks, baseline for story in stories: if story['name'] in sto_det: - detetions_new = [] - for detection in story['detections'] = list(sto_det[story['name']]) if story['name'] in sto_res: story['response_tasks'] = list(sto_res[story['name']]) From b1bdb137ffbacb1030d29c6550d7c2882da9623e Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Fri, 8 May 2020 18:32:18 +0200 Subject: [PATCH 29/93] bug in generate --- bin/generate.py | 4 +- package/default/analytic_stories.conf | 132 ++++----- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 395 +++++++++++++++++++------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 132 ++++----- 6 files changed, 428 insertions(+), 239 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 45ad505841..a5affea313 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -253,9 +253,9 @@ def map_detection_to_stories(detections): if 'analytics_story' in detection['tags']: for story in detection['tags']['analytics_story']: if not (story in sto_det): - sto_det[story] = {str('ESCU - ' + detection['name'] + '- Rule')} + sto_det[story] = {str('ESCU - ' + detection['name'] + ' - Rule')} else: - sto_det[story].add(str('ESCU - ' + detection['name'] + '- Rule')) + sto_det[story].add(str('ESCU - ' + detection['name'] + ' - Rule')) return sto_det def map_response_tasks_to_stories(response_tasks): diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 5e7e7e30b8..b714e9abe8 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T13:13:04 UTC +# On Date: 2020-05-08T16:27:32 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["AWS Cross Account Activity From Previously Unseen Account"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["AWS Investigate User Activities By AccessKeyId", "Get Notable History", "AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] support_searches = [] data_models = none providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started With Previously Unseen User"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Get EC2 Launch Details"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = none providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["AWS Network Access Control List Created with All Open Ports", "AWS Network Access Control List Deleted", "Detect Spike in Network ACL Activity", "Detect Spike in blocked Outbound Traffic from your AWS"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = none providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["Get All AWS Activity From IP Address", "Get All AWS Activity From City", "Get All AWS Activity From Region", "Get All AWS Activity From Country"] +investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City"] support_searches = [] data_models = none providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["Detect API activity from users without MFA", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in AWS API Activity", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["Get Notable History", "Get Notable Info", "Investigate AWS User Activities by user field"] +investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = none providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["Detect Excessive Account Lockouts From Endpoint", "Detect Excessive User Account Lockouts", "Identify New User Accounts", "Short Lived Windows Accounts"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["Get Notable Info", "Get Logon Rights Modifications For User", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Logon Rights Modifications For Endpoint", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["Get Notable Info", "Investigate Suspicious Strings in HTTP Header", "Investigate Web POSTs From src", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["Detect Unauthorized Assets by MAC address"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["Get First Occurrence and Last Occurrence of a MAC Address", "Get Notable History", "Get Notable Info"] +investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Started In Previously Unused Region"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate User Activities In Single Cloud Region", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Investigate Cloud Compute Instance Activities", "Get EC2 Launch Details"] +investigative_searches = ["ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["Get Vulnerability Logs For Endpoint", "Investigate Network Traffic From src ip", "Get User Information from Identity Table", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = none providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -256,7 +256,7 @@ version = 1 reference = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] detection_searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1192"], "nist": ["DE.CM"]} -investigative_searches = ["Get Certificate logs for a domain"] +investigative_searches = ["ESCU - Get Certificate logs for a domain"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -273,7 +273,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] mappings = {} -investigative_searches = ["Investigate AWS ECR container listing activity"] +investigative_searches = ["ESCU - Investigate AWS ECR container listing activity"] support_searches = [] data_models = none providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Attempted Credential Dump From Registry via Reg exe", "Create Remote Thread into LSASS", "Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["Investigate Previous Unseen User", "Investigate Failed Logins for Multiple Destinations", "Investigate Pass the Hash Attempts", "Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["Create local admin accounts using net exe", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Malicious PowerShell Process - Execution Policy Bypass", "Processes launching netsh", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Sc exe Manipulating Windows Services", "Scheduled Task Name Used by Dragonfly Threat Actors", "Single Letter Process On Endpoint", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Process File Activity", "Get Parent Process Info", "Get Process Info", "Get Process Registry Activity", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["Large Volume of DNS ANY Queries"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -343,7 +343,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get DNS Server History for a host"] +investigative_searches = ["ESCU - Get DNS Server History for a host"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["Detect USB device insertion", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Unload Sysmon Filter Driver"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get DNS traffic ratio", "Investigate Web Activity From src ip", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["Detect Rare Executables", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Email Attachments With Lots Of Spaces", "Prohibited Software On Endpoint", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["Create or delete windows shares using net exe", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "Detect Outbound SMB Traffic", "First time seen command line argument", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious File Write"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get DNS Server History for a host", "Get Notable Info", "Get Vulnerability Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["Get Notable Info", "GCP Kubernetes activity by src ip", "Get Notable History", "Amazon EKS Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] support_searches = [] data_models = none providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["Get Notable History", "All backup logs for host", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] support_searches = [] data_models = none providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["Prohibited Software On Endpoint"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["No Windows Updates in a time frame"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["Processes created by netsh", "Processes launching netsh"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["First Time Seen Running Windows Service", "First time seen command line argument", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -647,7 +647,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] detection_searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} -investigative_searches = ["Get Parent Process Info"] +investigative_searches = ["ESCU - Get Parent Process Info"] support_searches = [] data_models = none providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Registry Keys Used For Persistence", "Remote Process Instantiation via WMI", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Scheduled tasks used in BadRabbit ransomware", "Schtasks used for forcing a reboot", "Spike in File Writes", "Suspicious wevtutil Usage", "System Processes Run From Unexpected Locations", "TOR Traffic", "USN Journal Deletion", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get Registry Activities", "Get Risk Modifiers For User", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["Detect New Login Attempts to Routers"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["SQL Injection with Long URLs"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["Batch File Write to System32", "Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Detect PsExec With accepteula Flag", "Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers", "File with Samsam Extension", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Samsam Test File Write", "Spike in File Writes"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["Spectre and Meltdown Vulnerable Systems"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["Open Redirect in Splunk Web"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = none providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["Splunk Enterprise Information Disclosure"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["Get Notable Info", "Investigate Network Traffic From src ip", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] support_searches = [] data_models = none providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Get EC2 Launch Details"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = none providing_technologies = none @@ -876,7 +876,7 @@ version = 1 reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] detection_searches = ["Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP"]} -investigative_searches = ["AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = none providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["Detect New Open S3 buckets", "Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get All AWS Activity From IP Address", "Get Notable History", "Get User Information from Identity Table", "AWS S3 Bucket details via bucketName"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = none providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = none providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts", "Okta User Logins From Multiple Cities"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["Investigate Okta Activity by app", "Investigate User Activities In Okta", "Investigate Okta Activity by IP Address"] +investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] support_searches = [] data_models = none providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["Process Execution via WMI", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["Disabling Remote User Account Control", "Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["EC2 Instance Modified With Previously Unseen User"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["Get Notable History", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] support_searches = [] data_models = none providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["Detect Rare Executables", "Detect processes used for System Network Configuration Discovery", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Uncommon Processes On Endpoint", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["Protocols passing authentication in cleartext"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Process Information For Port Activity"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["Web Fraud - Account Harvesting", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["Get Notable History", "Get Notable Info", "Get Emails From Specific Sender", "Get Web Session Information via session id"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] support_searches = [] data_models = none providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Suspicious Reg exe Process"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions", "Suspicious Changes to File Associations"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["Detect Path Interception By Creation Of program exe", "Hiding Files And Directories With Attrib exe", "Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 1ad01626ec..8cc2636b3e 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T13:13:04 UTC +# On Date: 2020-05-08T16:27:32 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 4976edf7fc..8e3d676d60 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T13:13:04 UTC +# On Date: 2020-05-08T16:27:32 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -21,6 +21,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -57,6 +58,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -93,6 +95,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -129,6 +132,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -164,6 +168,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Cross Account Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -199,6 +204,7 @@ action.escu.modification_date = 2017-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Network Access Control List Created with All Open Ports - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Network ACL Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -234,6 +240,7 @@ action.escu.modification_date = 2017-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Network Access Control List Deleted - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Network ACL Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -269,6 +276,7 @@ action.escu.modification_date = 2018-02-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -303,6 +311,7 @@ action.escu.modification_date = 2019-11-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -338,6 +347,7 @@ action.escu.modification_date = 2018-02-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -372,6 +382,7 @@ action.escu.modification_date = 2019-11-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -407,6 +418,7 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Access LSASS Memory for Dump Creation - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -440,6 +452,7 @@ action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Amazon EKS Kubernetes Pod scan detection - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Kubernetes Scanning Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -474,6 +487,7 @@ action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Amazon EKS Kubernetes cluster scan detection - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Kubernetes Scanning Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -500,7 +514,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attempt to add a certificate to the untrusted certificate store action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. @@ -509,6 +523,7 @@ action.escu.modification_date = 2018-11-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Add Certificate To Untrusted Store - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -536,7 +551,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. action.escu.known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. @@ -545,6 +560,7 @@ action.escu.modification_date = 2019-12-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping", "Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -572,7 +588,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for attempts to stop security-related services on the endpoint. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., action.escu.known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. @@ -581,6 +597,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Stop Security Service - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -608,7 +625,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -617,6 +634,7 @@ action.escu.modification_date = 2019-12-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -642,7 +660,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. @@ -651,6 +669,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Batch File Write to System32 - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -678,7 +697,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.mappings = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. action.escu.known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. @@ -687,6 +706,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Child Processes of Spoolsv exe - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Privilege Escalation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -714,7 +734,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ @@ -725,6 +745,7 @@ action.escu.modification_date = 2020-01-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Clients Connecting to Multiple DNS Servers - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -752,7 +773,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances created by users who have not created them before. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = Cloud_Infrastructure action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. action.escu.known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. @@ -761,6 +782,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -788,7 +810,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = Cloud_Infrastructure action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. action.escu.known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. @@ -797,6 +819,7 @@ action.escu.modification_date = 2018-10-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -824,7 +847,7 @@ action.escu = 0 action.escu.enabled = 1 description = Find EC2 instances being created with previously unseen instance types. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = Cloud_Infrastructure action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. @@ -833,6 +856,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -860,7 +884,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = Cloud_Infrastructure action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. @@ -869,6 +893,7 @@ action.escu.modification_date = 2019-10-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -896,7 +921,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file modifications with extensions commonly used by Ransomware action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ @@ -909,6 +934,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Common Ransomware Extensions - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -936,7 +962,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. @@ -945,6 +971,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Common Ransomware Notes - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -980,6 +1007,7 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Create Remote Thread into LSASS - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -1005,7 +1033,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of local administrator accounts using net.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create admin accounts. @@ -1014,6 +1042,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Create local admin accounts using net exe - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1041,7 +1070,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. @@ -1050,6 +1079,7 @@ action.escu.modification_date = 2020-01-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Create or delete windows shares using net exe - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1077,7 +1107,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. @@ -1086,6 +1116,7 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Creation of Shadow Copy - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -1119,6 +1150,7 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Creation of Shadow Copy with wmic and powershell - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -1144,7 +1176,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects credential dumping using copy command from a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1153,6 +1185,7 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -1178,7 +1211,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the creation of a symlink to a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1187,6 +1220,7 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -1212,7 +1246,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -1227,6 +1261,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length Outliers - MLTK - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1254,7 +1289,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It's possible there can be long domain names that are legitimate. @@ -1263,6 +1298,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length With High Standard Deviation - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1289,7 +1325,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. action.escu.known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. @@ -1298,6 +1334,7 @@ action.escu.modification_date = 2020-01-17 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1325,7 +1362,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ **Splunk>Phantom Playbook Integration**\ @@ -1338,6 +1375,7 @@ action.escu.modification_date = 2020-01-16 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS record changed - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1365,7 +1403,7 @@ action.escu = 0 action.escu.enabled = 1 description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.mappings = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. @@ -1374,6 +1412,7 @@ action.escu.modification_date = 2020-04-17 action.escu.confidence = high action.escu.full_search_name = ESCU - Deleting Shadow Copies - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1415,6 +1454,7 @@ action.escu.modification_date = 2018-05-17 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect API activity from users without MFA - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1456,6 +1496,7 @@ action.escu.modification_date = 2018-03-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS API Activities From Unapproved Accounts - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1491,6 +1532,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New City - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1526,6 +1568,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Country - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1561,6 +1604,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Region - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1596,6 +1640,7 @@ action.escu.modification_date = 2020-01-09 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Activity Related to Pass the Hash Attacks - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1631,6 +1676,7 @@ action.escu.modification_date = 2019-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Credential Dumping through LSASS access - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -1656,7 +1702,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.mappings = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ **Splunk>Phantom Playbook Integration**\ @@ -1669,6 +1715,7 @@ action.escu.modification_date = 2019-04-29 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Common Phishing Frameworks"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1696,7 +1743,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = [Change] +action.escu.data_models = Change action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ **Splunk>Phantom Playbook Integration**\ @@ -1709,6 +1756,7 @@ action.escu.modification_date = 2019-04-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Excessive Account Lockouts From Endpoint - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1736,7 +1784,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = [Change] +action.escu.data_models = Change action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. action.escu.known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. @@ -1745,6 +1793,7 @@ action.escu.modification_date = 2019-03-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Excessive User Account Lockouts - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1772,7 +1821,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. @@ -1781,6 +1830,7 @@ action.escu.modification_date = 2018-06-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Large Outbound ICMP Packets - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1807,7 +1857,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. action.escu.known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. @@ -1816,6 +1866,7 @@ action.escu.modification_date = 2017-09-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Long DNS TXT Record Response - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1851,6 +1902,7 @@ action.escu.modification_date = 2019-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Mimikatz Using Loaded Images - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -1884,6 +1936,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule action.escu.search_type = detection +action.escu.providing_technologies = none cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now @@ -1922,6 +1975,7 @@ action.escu.modification_date = 2019-02-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Local Admin account - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1949,7 +2003,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} -action.escu.data_models = [Authentication] +action.escu.data_models = Authentication action.escu.eli5 = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. action.escu.known_false_positives = Legitimate router connections may appear as new connections @@ -1958,6 +2012,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Login Attempts to Routers - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Router and Infrastructure Security"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1993,6 +2048,7 @@ action.escu.modification_date = 2018-07-25 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Open S3 buckets - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS S3 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2028,6 +2084,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Oulook exe writing a zip file - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Phishing Payloads"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2055,7 +2112,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. @@ -2064,6 +2121,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Outbound SMB Traffic - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2090,7 +2148,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. action.escu.known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. @@ -2099,6 +2157,7 @@ action.escu.modification_date = 2018-11-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Path Interception By Creation Of program exe - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2126,7 +2185,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. action.escu.known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. @@ -2135,6 +2194,7 @@ action.escu.modification_date = 2020-02-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2162,7 +2222,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine @@ -2171,6 +2231,7 @@ action.escu.modification_date = 2019-02-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect PsExec With accepteula Flag - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2198,7 +2259,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. action.escu.known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. @@ -2207,6 +2268,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Rare Executables - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2242,6 +2304,7 @@ action.escu.modification_date = 2018-06-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect S3 access from a new IP - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS S3 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2282,6 +2345,7 @@ action.escu.modification_date = 2018-04-09 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in AWS API Activity - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2317,6 +2381,7 @@ action.escu.modification_date = 2018-05-21 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in Network ACL Activity - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Network ACL Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2352,6 +2417,7 @@ action.escu.modification_date = 2018-11-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in S3 Bucket deletion - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS S3 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2387,6 +2453,7 @@ action.escu.modification_date = 2018-04-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in Security Group Activity - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2422,6 +2489,7 @@ action.escu.modification_date = 2018-05-07 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2448,7 +2516,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = [Change_Analysis] +action.escu.data_models = Change_Analysis action.escu.eli5 = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. action.escu.known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. @@ -2457,6 +2525,7 @@ action.escu.modification_date = 2017-11-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect USB device insertion - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Data Protection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2484,7 +2553,7 @@ action.escu = 0 action.escu.enabled = 1 description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Network_Sessions] +action.escu.data_models = Network_Sessions action.escu.eli5 = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. action.escu.known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. @@ -2493,6 +2562,7 @@ action.escu.modification_date = 2017-09-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Unauthorized Assets by MAC address - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Asset Tracking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2519,7 +2589,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Some legitimate applications may exhibit this behavior. @@ -2528,6 +2598,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2555,7 +2626,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} -action.escu.data_models = [Web] +action.escu.data_models = Web action.escu.eli5 = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. action.escu.known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. @@ -2564,6 +2635,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2591,7 +2663,7 @@ action.escu = 0 action.escu.enabled = 1 description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -2606,6 +2678,7 @@ action.escu.modification_date = 2020-01-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect hosts connecting to dynamic domain providers - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2632,7 +2705,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.mappings = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -action.escu.data_models = [Web] +action.escu.data_models = Web action.escu.eli5 = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model action.escu.known_false_positives = No known false positives for this detection. @@ -2641,6 +2714,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect malicious requests to exploit JBoss servers - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2668,7 +2742,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. @@ -2677,6 +2751,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect mshta exe running scripts in command-line arguments - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious MSHTA Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2712,6 +2787,7 @@ action.escu.modification_date = 2018-04-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect new API calls from user roles - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2747,6 +2823,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect new user AWS Console Login - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2774,7 +2851,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. action.escu.known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. @@ -2783,6 +2860,7 @@ action.escu.modification_date = 2018-11-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect processes used for System Network Configuration Discovery - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2810,7 +2888,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for web connections to dynamic DNS providers. action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"]} -action.escu.data_models = [Web] +action.escu.data_models = Web action.escu.eli5 = This search looks for web connections to dynamic DNS providers. action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ @@ -2821,6 +2899,7 @@ action.escu.modification_date = 2018-09-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect web traffic to dynamic domain providers - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Dynamic DNS"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2848,7 +2927,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. action.escu.known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. @@ -2857,6 +2936,7 @@ action.escu.modification_date = 2017-09-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of DNS Tunnels - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Data Protection", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2884,7 +2964,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072", "T1087"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. @@ -2893,6 +2973,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of tools built by NirSoft - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2928,6 +3009,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Disabling Remote User Account Control - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2955,7 +3037,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -2964,6 +3046,7 @@ action.escu.modification_date = 2020-02-21 action.escu.confidence = high action.escu.full_search_name = ESCU - Dump LSASS via comsvcs DLL - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -2997,6 +3080,7 @@ action.escu.modification_date = 2018-04-09 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Modified With Previously Unseen User - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3032,6 +3116,7 @@ action.escu.modification_date = 2018-02-23 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started In Previously Unseen Region - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3066,6 +3151,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen AMI - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3100,6 +3186,7 @@ action.escu.modification_date = 2020-02-07 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3135,6 +3222,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen User - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3162,7 +3250,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [Email] +action.escu.data_models = Email action.escu.eli5 = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ **Splunk Phantom Playbook Integration**\ @@ -3173,6 +3261,7 @@ action.escu.modification_date = 2017-09-19 action.escu.confidence = high action.escu.full_search_name = ESCU - Email Attachments With Lots Of Spaces - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3199,7 +3288,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. @@ -3208,6 +3297,7 @@ action.escu.modification_date = 2020-03-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Email files written outside of the Outlook directory - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3235,7 +3325,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -3244,6 +3334,7 @@ action.escu.modification_date = 2017-12-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Email servers sending high volume traffic to hosts - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3270,7 +3361,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.mappings = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. @@ -3279,6 +3370,7 @@ action.escu.modification_date = 2017-09-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Excessive DNS Failures - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3305,7 +3397,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = None identified. @@ -3314,6 +3406,7 @@ action.escu.modification_date = 2018-01-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Execution of File With Spaces Before Extension - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows File Extension and Association Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3341,7 +3434,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. action.escu.known_false_positives = None identified. @@ -3350,6 +3443,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Execution of File with Multiple Extensions - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows File Extension and Association Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3385,6 +3479,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Extended Period Without Successful Netbackup Backups - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Monitor Backup Solution"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3412,7 +3507,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. @@ -3421,6 +3516,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - File with Samsam Extension - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3456,6 +3552,7 @@ action.escu.modification_date = 2020-01-13 action.escu.confidence = high action.escu.full_search_name = ESCU - First Time Seen Running Windows Service - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3483,7 +3580,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. action.escu.known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name @@ -3492,6 +3589,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - First time seen command line argument - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3526,6 +3624,7 @@ action.escu.modification_date = 2020-02-20 action.escu.confidence = high action.escu.full_search_name = ESCU - GCP GCR container uploaded - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3561,6 +3660,7 @@ action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - GCP Kubernetes cluster scan detection - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Kubernetes Scanning Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3587,7 +3687,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. @@ -3596,6 +3696,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Hiding Files And Directories With Attrib exe - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3623,7 +3724,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -3632,6 +3733,7 @@ action.escu.modification_date = 2017-12-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Hosts receiving high volume of network traffic from email server - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3666,6 +3768,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Identify New User Accounts - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3692,7 +3795,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. @@ -3701,6 +3804,7 @@ action.escu.modification_date = 2017-09-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Large Volume of DNS ANY Queries - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DNS Amplification Attacks"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3727,7 +3831,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. action.escu.known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. @@ -3736,6 +3840,7 @@ action.escu.modification_date = 2020-02-07 action.escu.confidence = high action.escu.full_search_name = ESCU - MacOS - Re-opened Applications - Rule action.escu.search_type = detection +action.escu.providing_technologies = none cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3762,7 +3867,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -3771,6 +3876,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3798,7 +3904,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = System administrators may use this option, but it's not common. @@ -3807,6 +3913,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Encoded Command - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3834,7 +3941,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. @@ -3843,6 +3950,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3870,7 +3978,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -3879,6 +3987,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3906,7 +4015,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = These characters might be legitimately on the command-line, but it is not common. @@ -3915,6 +4024,7 @@ action.escu.modification_date = 2020-01-17 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3942,7 +4052,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.mappings = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = Network_Resolution action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -3951,6 +4061,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor DNS For Brand Abuse - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Brand Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3977,7 +4088,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [Email] +action.escu.data_models = Email action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -3986,6 +4097,7 @@ action.escu.modification_date = 2018-01-05 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Email For Brand Abuse - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Emails", "Brand Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4020,6 +4132,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Registry Keys for Print Monitors - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4047,7 +4160,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [Web] +action.escu.data_models = Web action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4056,6 +4169,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Web Traffic For Brand Abuse - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Brand Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4091,6 +4205,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4125,6 +4240,7 @@ action.escu.modification_date = 2020-02-20 action.escu.confidence = high action.escu.full_search_name = ESCU - New container uploaded to AWS ECR - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4152,7 +4268,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.mappings = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} -action.escu.data_models = [Updates] +action.escu.data_models = Updates action.escu.eli5 = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. action.escu.known_false_positives = None identified @@ -4161,6 +4277,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - No Windows Updates in a time frame - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Monitor for Updates"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4196,6 +4313,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta Account Lockout Events - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4230,6 +4348,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta Failed SSO Attempts - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4264,6 +4383,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta User Logins From Multiple Cities - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4299,6 +4419,7 @@ action.escu.modification_date = 2017-09-19 action.escu.confidence = high action.escu.full_search_name = ESCU - Open Redirect in Splunk Web - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Splunk Enterprise Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4333,6 +4454,7 @@ action.escu.modification_date = 2019-01-29 action.escu.confidence = high action.escu.full_search_name = ESCU - Osquery pack - ColdRoot detection - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["ColdRoot MacOS RAT"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4359,7 +4481,7 @@ action.escu = 0 action.escu.enabled = 1 description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. @@ -4368,6 +4490,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Overwriting Accessibility Binaries - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Privilege Escalation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4403,6 +4526,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Process Execution via WMI - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4438,6 +4562,7 @@ action.escu.modification_date = 2019-01-25 action.escu.confidence = high action.escu.full_search_name = ESCU - Processes Tapping Keyboard Events - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["ColdRoot MacOS RAT"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4464,7 +4589,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. @@ -4473,6 +4598,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Processes created by netsh - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Netsh Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4500,7 +4626,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model action.escu.known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. @@ -4509,6 +4635,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Processes launching netsh - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4536,7 +4663,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None identified @@ -4545,6 +4672,7 @@ action.escu.modification_date = 2017-09-11 action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Network Traffic Allowed - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4571,7 +4699,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. action.escu.known_false_positives = None identified @@ -4580,6 +4708,7 @@ action.escu.modification_date = 2019-10-11 action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Software On Endpoint - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4607,7 +4736,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. action.escu.known_false_positives = None identified @@ -4616,6 +4745,7 @@ action.escu.modification_date = 2017-09-11 action.escu.confidence = high action.escu.full_search_name = ESCU - Protocol or Port Mismatch - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4642,7 +4772,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.mappings = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. action.escu.known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. @@ -4651,6 +4781,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Protocols passing authentication in cleartext - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Use of Cleartext Protocols"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4686,6 +4817,7 @@ action.escu.modification_date = 2019-03-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Service Abuse", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4713,7 +4845,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None at the moment @@ -4722,6 +4854,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe used to hide files directories via registry keys - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4757,6 +4890,7 @@ action.escu.modification_date = 2017-10-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Persistence - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4792,6 +4926,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Privilege Escalation - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4827,6 +4962,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys for Creating SHIM Databases - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4853,7 +4989,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.mappings = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. action.escu.known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. @@ -4862,6 +4998,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Bruteforce - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4889,7 +5026,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -4898,6 +5035,7 @@ action.escu.modification_date = 2020-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Traffic - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4925,7 +5063,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -4934,6 +5072,7 @@ action.escu.modification_date = 2020-01-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Process Running On System - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4961,7 +5100,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. @@ -4970,6 +5109,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Process Instantiation via WMI - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious WMI Use", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5005,6 +5145,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Registry Key modifications - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5032,7 +5173,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may use this legitimately to gather info from remote systems. @@ -5041,6 +5182,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote WMI Command Attempt - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5068,7 +5210,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1085"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process @@ -5077,6 +5219,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - RunDLL Loading DLL By Ordinal - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5104,7 +5247,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. action.escu.known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. @@ -5113,6 +5256,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5140,7 +5284,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ @@ -5152,6 +5296,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - MLTK - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5179,7 +5324,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for long URLs that have several SQL commands visible within them. action.escu.mappings = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} -action.escu.data_models = [Web] +action.escu.data_models = Web action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. action.escu.known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. @@ -5188,6 +5333,7 @@ action.escu.modification_date = 2017-09-19 action.escu.confidence = high action.escu.full_search_name = ESCU - SQL Injection with Long URLs - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SQL Injection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5215,7 +5361,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = No false positives have been identified. @@ -5224,6 +5370,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Samsam Test File Write - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5251,7 +5398,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. @@ -5260,6 +5407,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Sc exe Manipulating Windows Services - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5287,7 +5435,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -5296,6 +5444,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5323,7 +5472,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -5332,6 +5481,7 @@ action.escu.modification_date = 2019-02-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Scheduled tasks used in BadRabbit ransomware - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5359,7 +5509,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. @@ -5368,6 +5518,7 @@ action.escu.modification_date = 2020-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Schtasks scheduling job on remote system - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5395,7 +5546,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. @@ -5404,6 +5555,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Schtasks used for forcing a reboot - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Persistence Techniques", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5439,6 +5591,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Script Execution via WMI - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5474,6 +5627,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Shim Database File Creation - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5501,7 +5655,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -5510,6 +5664,7 @@ action.escu.modification_date = 2019-03-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Shim Database Installation With Suspicious Parameters - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5537,7 +5692,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects accounts that were created and deleted in a short time period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} -action.escu.data_models = [Change] +action.escu.data_models = Change action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ action.escu.known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. @@ -5546,6 +5701,7 @@ action.escu.modification_date = 2018-01-05 action.escu.confidence = high action.escu.full_search_name = ESCU - Short Lived Windows Accounts - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5573,7 +5729,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for process names that consist only of a single letter. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for process names that consist only of a single letter. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. @@ -5582,6 +5738,7 @@ action.escu.modification_date = 2019-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Single Letter Process On Endpoint - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5608,7 +5765,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.mappings = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} -action.escu.data_models = [Vulnerabilities] +action.escu.data_models = Vulnerabilities action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. action.escu.known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. @@ -5617,6 +5774,7 @@ action.escu.modification_date = 2017-01-07 action.escu.confidence = high action.escu.full_search_name = ESCU - Spectre and Meltdown Vulnerable Systems - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5651,6 +5809,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Spike in File Writes - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5686,6 +5845,7 @@ action.escu.modification_date = 2018-06-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Splunk Enterprise Information Disclosure - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Splunk Enterprise Vulnerability CVE-2018-11409"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5721,6 +5881,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Changes to File Associations - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5748,7 +5909,7 @@ action.escu = 0 action.escu.enabled = 1 description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [UEBA] +action.escu.data_models = UEBA action.escu.eli5 = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. action.escu.known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. @@ -5757,6 +5918,7 @@ action.escu.modification_date = 2019-07-21 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Email - UBA Anomaly - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Emails"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5784,7 +5946,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails that have attachments with suspicious file extensions. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -action.escu.data_models = [Email] +action.escu.data_models = Email action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ **Splunk Phantom Playbook Integration**\ @@ -5795,6 +5957,7 @@ action.escu.modification_date = 2020-01-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Email Attachment Extensions - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5829,6 +5992,7 @@ action.escu.modification_date = 2019-04-25 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious File Write - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5864,6 +6028,7 @@ action.escu.modification_date = 2018-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Java Classes - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Apache Struts Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5899,6 +6064,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious LNK file launching a process - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Phishing Payloads"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5934,6 +6100,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Reg exe Process - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5961,7 +6128,7 @@ action.escu = 0 action.escu.enabled = 1 description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. @@ -5970,6 +6137,7 @@ action.escu.modification_date = 2019-02-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious wevtutil Usage - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6005,6 +6173,7 @@ action.escu.modification_date = 2018-01-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious writes to System Volume Information - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6039,6 +6208,7 @@ action.escu.modification_date = 2020-02-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious writes to windows Recycle Bin - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6074,6 +6244,7 @@ action.escu.modification_date = 2020-02-04 action.escu.confidence = high action.escu.full_search_name = ESCU - System Processes Run From Unexpected Locations - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6101,7 +6272,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = Network_Traffic action.escu.eli5 = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None at this time @@ -6110,6 +6281,7 @@ action.escu.modification_date = 2017-09-11 action.escu.confidence = high action.escu.full_search_name = ESCU - TOR Traffic - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6136,7 +6308,7 @@ action.escu = 0 action.escu.enabled = 1 description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.mappings = {"cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -6145,6 +6317,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - USN Journal Deletion - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6172,7 +6345,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. action.escu.known_false_positives = None identified @@ -6181,6 +6354,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Uncommon Processes On Endpoint - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Privilege Escalation", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6208,7 +6382,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. action.escu.known_false_positives = @@ -6217,6 +6391,7 @@ action.escu.modification_date = 2020-01-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Unload Sysmon Filter Driver - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6252,6 +6427,7 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Unsigned Image Loaded by LSASS - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Credential Dumping"] cron_schedule = */60 * * * * dispatch.earliest_time = -60m @@ -6285,6 +6461,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Unsuccessful Netbackup backups - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Monitor Backup Solution"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6319,6 +6496,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6354,6 +6532,7 @@ action.escu.modification_date = 2019-05-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - MLTK - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6389,6 +6568,7 @@ action.escu.modification_date = 2017-10-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Content-Type Length - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Apache Struts Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6423,6 +6603,7 @@ action.escu.modification_date = 2018-10-23 action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6458,6 +6639,7 @@ action.escu.modification_date = 2018-10-23 action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Sysmon - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6493,6 +6675,7 @@ action.escu.modification_date = 2018-10-23 action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Temporary Event Subscription - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6527,6 +6710,7 @@ action.escu.modification_date = 2018-10-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Account Harvesting - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Web Fraud Detection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6562,6 +6746,7 @@ action.escu.modification_date = 2018-10-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Anomalous User Clickspeed - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Web Fraud Detection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6596,6 +6781,7 @@ action.escu.modification_date = 2018-10-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Password Sharing Across Accounts - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Web Fraud Detection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6623,7 +6809,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious processes on all systems labeled as web servers. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = Endpoint action.escu.eli5 = This search looks for suspicious processes on all systems labeled as web servers. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. action.escu.known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. @@ -6632,6 +6818,7 @@ action.escu.modification_date = 2019-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Servers Executing Suspicious Processes - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Apache Struts Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6667,6 +6854,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Windows Event Log Cleared - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6702,6 +6890,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Windows hosts file modification - Rule action.escu.search_type = detection +action.escu.providing_technologies = none action.escu.analytic_story = ["Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 1f16d00f61..b85d0fecce 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T13:13:04 UTC +# On Date: 2020-05-08T16:27:32 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index ba00389691..3e06987ba9 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T13:13:04 UTC +# On Date: 2020-05-08T16:27:32 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["AWS Cross Account Activity From Previously Unseen Account", "AWS Investigate User Activities By AccessKeyId", "Get Notable History", "AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account- Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["EC2 Instance Started With Previously Unseen AMI", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User", "EC2 Instance Started With Previously Unseen Instance Type", "AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User- Rule", "ESCU - EC2 Instance Started In Previously Unseen Region- Rule", "ESCU - Abnormally High AWS Instances Launched by User- Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type- Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["AWS Network Access Control List Deleted", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect Spike in Network ACL Activity", "AWS Network Access Control List Created with All Open Ports", "AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS- Rule", "ESCU - AWS Network Access Control List Created with All Open Ports- Rule", "ESCU - Detect Spike in Network ACL Activity- Rule", "ESCU - AWS Network Access Control List Deleted- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Region", "Get All AWS Activity From IP Address", "Get All AWS Activity From City", "Get All AWS Activity From Region", "Get All AWS Activity From Country"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City- Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address- Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region- Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country- Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect API activity from users without MFA", "Detect Spike in Security Group Activity", "Detect Spike in AWS API Activity", "Detect new API calls from user roles", "Detect AWS API Activities From Unapproved Accounts", "Get Notable History", "Get Notable Info", "Investigate AWS User Activities by user field"] +searches = ["ESCU - Detect Spike in AWS API Activity- Rule", "ESCU - Detect new API calls from user roles- Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts- Rule", "ESCU - Detect API activity from users without MFA- Rule", "ESCU - Detect Spike in Security Group Activity- Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Identify New User Accounts", "Detect Excessive User Account Lockouts", "Detect Excessive Account Lockouts From Endpoint", "Short Lived Windows Accounts", "Get Notable Info", "Get Logon Rights Modifications For User", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Logon Rights Modifications For Endpoint", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Excessive User Account Lockouts- Rule", "ESCU - Short Lived Windows Accounts- Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint- Rule", "ESCU - Identify New User Accounts- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Web Servers Executing Suspicious Processes", "Suspicious Java Classes", "Unusually Long Content-Type Length", "Get Notable Info", "Investigate Suspicious Strings in HTTP Header", "Investigate Web POSTs From src", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Suspicious Java Classes- Rule", "ESCU - Unusually Long Content-Type Length- Rule", "ESCU - Web Servers Executing Suspicious Processes- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Unauthorized Assets by MAC address", "Get First Occurrence and Last Occurrence of a MAC Address", "Get Notable History", "Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address- Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Monitor Web Traffic For Brand Abuse", "Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse- Rule", "ESCU - Monitor Email For Brand Abuse- Rule", "ESCU - Monitor DNS For Brand Abuse- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Cloud Compute Instance Created With Previously Unseen Instance Type", "Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Started In Previously Unused Region", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate User Activities In Single Cloud Region", "Investigate AWS activities via region name", "Investigate User Activities In All Cloud Regions", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Investigate Cloud Compute Instance Activities", "Get EC2 Launch Details"] +searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type- Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image- Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK- Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region- Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User- Rule", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events", "Get Vulnerability Logs For Endpoint", "Investigate Network Traffic From src ip", "Get User Information from Identity Table", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Osquery pack - ColdRoot detection- Rule", "ESCU - Processes Tapping Keyboard Events- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to windows Recycle Bin", "Email files written outside of the Outlook directory", "Suspicious writes to System Volume Information", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Suspicious writes to windows Recycle Bin- Rule", "ESCU - Email files written outside of the Outlook directory- Rule", "ESCU - Hosts receiving high volume of network traffic from email server- Rule", "ESCU - Email servers sending high volume traffic to hosts- Rule", "ESCU - Suspicious writes to System Volume Information- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Detect Large Outbound ICMP Packets", "DNS Query Length With High Standard Deviation", "Excessive DNS Failures", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detect Spike in blocked Outbound Traffic from your AWS", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "TOR Traffic", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "Detect Long DNS TXT Record Response", "AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - DNS Query Length With High Standard Deviation- Rule", "ESCU - Detect Large Outbound ICMP Packets- Rule", "ESCU - Protocol or Port Mismatch- Rule", "ESCU - DNS Query Length Outliers - MLTK- Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS- Rule", "ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detection of DNS Tunnels- Rule", "ESCU - Prohibited Network Traffic Allowed- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Detect Long DNS TXT Record Response- Rule", "ESCU - Excessive DNS Failures- Rule", "ESCU - TOR Traffic- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -189,7 +189,7 @@ version = 1 references = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2", "Get Certificate logs for a domain"] +searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2- Rule", "ESCU - Get Certificate logs for a domain"] description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. narrative = As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR", "Investigate AWS ECR container listing activity"] +searches = ["ESCU - GCP GCR container uploaded- Rule", "ESCU - New container uploaded to AWS ECR- Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Credential Dumping via Copy Command from Shadow Copy", "Access LSASS Memory for Dump Creation", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Symlink to Shadow Copy", "Unsigned Image Loaded by LSASS", "Dump LSASS via comsvcs DLL", "Create Remote Thread into LSASS", "Attempted Credential Dump From Registry via Reg exe", "Creation of Shadow Copy", "Detect Mimikatz Using Loaded Images", "Detect Credential Dumping through LSASS access", "Investigate Previous Unseen User", "Investigate Failed Logins for Multiple Destinations", "Investigate Pass the Hash Attempts", "Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Attempted Credential Dump From Registry via Reg exe- Rule", "ESCU - Access LSASS Memory for Dump Creation- Rule", "ESCU - Unsigned Image Loaded by LSASS- Rule", "ESCU - Creation of Shadow Copy with wmic and powershell- Rule", "ESCU - Creation of Shadow Copy- Rule", "ESCU - Dump LSASS via comsvcs DLL- Rule", "ESCU - Detect Mimikatz Using Loaded Images- Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy- Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy- Rule", "ESCU - Create Remote Thread into LSASS- Rule", "ESCU - Detect Credential Dumping through LSASS access- Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass- Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "First time seen command line argument", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Detect PsExec With accepteula Flag", "Processes launching netsh", "Single Letter Process On Endpoint", "Detect New Local Admin account", "Create local admin accounts using net exe", "Scheduled Task Name Used by Dragonfly Threat Actors", "Malicious PowerShell Process - Execution Policy Bypass", "Registry Keys Used For Persistence", "Detect Outbound SMB Traffic", "Suspicious Reg exe Process", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Process File Activity", "Get Parent Process Info", "Get Process Info", "Get Process Registry Activity", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Create local admin accounts using net exe- Rule", "ESCU - Detect New Local Admin account- Rule", "ESCU - Single Letter Process On Endpoint- Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass- Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors- Rule", "ESCU - Detect Outbound SMB Traffic- Rule", "ESCU - Detect PsExec With accepteula Flag- Rule", "ESCU - Processes launching netsh- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Suspicious Reg exe Process- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Large Volume of DNS ANY Queries", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] +searches = ["ESCU - Large Volume of DNS ANY Queries- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Get DNS Server History for a host"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - DNS record changed- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Detect USB device insertion", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detection of DNS Tunnels- Rule", "ESCU - Detect USB device insertion- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "Unload Sysmon Filter Driver", "Processes launching netsh", "Attempt To Stop Security Service", "Suspicious Reg exe Process", "Attempt To Add Certificate To Untrusted Store", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Unload Sysmon Filter Driver- Rule", "ESCU - Attempt To Add Certificate To Untrusted Store- Rule", "ESCU - Attempt To Stop Security Service- Rule", "ESCU - Processes launching netsh- Rule", "ESCU - Suspicious Reg exe Process- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers", "Get DNS Server History for a host", "Get Notable Info", "Get DNS traffic ratio", "Investigate Web Activity From src ip", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detect web traffic to dynamic domain providers- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Rare Executables", "Detection of tools built by NirSoft", "SMB Traffic Spike - MLTK", "Detect Use of cmd exe to Launch Script Interpreters", "Registry Keys Used For Persistence", "Suspicious Email Attachment Extensions", "Prohibited Software On Endpoint", "Email Attachments With Lots Of Spaces", "SMB Traffic Spike", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Process Information For Port Activity", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Rare Executables- Rule", "ESCU - Suspicious Email Attachment Extensions- Rule", "ESCU - Detection of tools built by NirSoft- Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters- Rule", "ESCU - Email Attachments With Lots Of Spaces- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Prohibited Software On Endpoint- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Length With High Standard Deviation", "First time seen command line argument", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "DNS Query Length Outliers - MLTK", "Suspicious File Write", "Remote Desktop Process Running On System", "Create or delete windows shares using net exe", "Remote Desktop Network Traffic", "Detect Outbound SMB Traffic", "Investigate Web Activity From Host", "Get DNS Server History for a host", "Get Notable Info", "Get Vulnerability Logs For Endpoint", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - DNS Query Length With High Standard Deviation- Rule", "ESCU - Create or delete windows shares using net exe- Rule", "ESCU - DNS Query Length Outliers - MLTK- Rule", "ESCU - Detect Outbound SMB Traffic- Rule", "ESCU - Remote Desktop Process Running On System- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - Remote Desktop Network Traffic- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Suspicious File Write- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Windows hosts file modification", "Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Get DNS Server History for a host", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Windows hosts file modification- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect malicious requests to exploit JBoss servers", "Detect attackers scanning for vulnerable JBoss servers", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Notable History", "Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers- Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["GCP Kubernetes cluster scan detection", "Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "Get Notable Info", "GCP Kubernetes activity by src ip", "Get Notable History", "Amazon EKS Kubernetes activity by src ip", "Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection- Rule", "ESCU - GCP Kubernetes cluster scan detection- Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Remote Desktop Network Traffic", "Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system", "Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Remote Desktop Process Running On System- Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks- Rule", "ESCU - Schtasks scheduling job on remote system- Rule", "ESCU - Remote Desktop Network Traffic- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process With Obfuscation Techniques", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments- Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window- Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques- Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass- Rule", "ESCU - Malicious PowerShell Process - Encoded Command- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups", "Get Notable History", "All backup logs for host", "Get Risk Modifiers For Endpoint", "Get Risk Modifiers For User"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups- Rule", "ESCU - Unsuccessful Netbackup backups- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Prohibited Software On Endpoint", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Prohibited Software On Endpoint- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["No Windows Updates in a time frame", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] +searches = ["ESCU - No Windows Updates in a time frame- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Processes launching netsh", "Processes created by netsh", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Processes created by netsh- Rule", "ESCU - Processes launching netsh- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "First Time Seen Running Windows Service", "First time seen command line argument", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - First time seen command line argument- Rule", "ESCU - First Time Seen Running Windows Service- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["Suspicious LNK file launching a process", "Detect Oulook exe writing a zip file", "Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file- Rule", "ESCU - Suspicious LNK file launching a process- Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["Unusually Long Command Line - MLTK", "First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Unusually Long Command Line", "Registry Keys Used For Persistence", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Prohibited Network Traffic Allowed", "Detect hosts connecting to dynamic domain providers", "Protocol or Port Mismatch", "TOR Traffic", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - TOR Traffic- Rule", "ESCU - Prohibited Network Traffic Allowed- Rule", "ESCU - Protocol or Port Mismatch- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Deleting Shadow Copies", "Unusually Long Command Line - MLTK", "SMB Traffic Spike", "Windows Event Log Cleared", "SMB Traffic Spike - MLTK", "Spike in File Writes", "System Processes Run From Unexpected Locations", "Remote Process Instantiation via WMI", "Registry Keys Used For Persistence", "Schtasks used for forcing a reboot", "USN Journal Deletion", "Suspicious wevtutil Usage", "Unusually Long Command Line", "Common Ransomware Extensions", "TOR Traffic", "Prohibited Network Traffic Allowed", "Common Ransomware Notes", "Scheduled tasks used in BadRabbit ransomware", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get Registry Activities", "Get Risk Modifiers For User", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Remote Process Instantiation via WMI- Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware- Rule", "ESCU - Spike in File Writes- Rule", "ESCU - TOR Traffic- Rule", "ESCU - Windows Event Log Cleared- Rule", "ESCU - Prohibited Network Traffic Allowed- Rule", "ESCU - Suspicious wevtutil Usage- Rule", "ESCU - Common Ransomware Extensions- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - System Processes Run From Unexpected Locations- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Common Ransomware Notes- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - USN Journal Deletion- Rule", "ESCU - Schtasks used for forcing a reboot- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - Deleting Shadow Copies- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect New Login Attempts to Routers", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect New Login Attempts to Routers- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["SQL Injection with Long URLs", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Deleting Shadow Copies", "Spike in File Writes", "File with Samsam Extension", "Detect attackers scanning for vulnerable JBoss servers", "Batch File Write to System32", "Detect PsExec With accepteula Flag", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Common Ransomware Extensions", "Prohibited Software On Endpoint", "Detect malicious requests to exploit JBoss servers", "Common Ransomware Notes", "Samsam Test File Write", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Investigate Successful Remote Desktop Authentications", "Get Parent Process Info", "Get Process Info", "Get Update Logs For Endpoint", "Get Notable History", "Get Backup Logs For Endpoint", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Samsam Test File Write- Rule", "ESCU - Spike in File Writes- Rule", "ESCU - Batch File Write to System32- Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers- Rule", "ESCU - Detect PsExec With accepteula Flag- Rule", "ESCU - Remote Desktop Network Bruteforce- Rule", "ESCU - Detect malicious requests to exploit JBoss servers- Rule", "ESCU - Common Ransomware Extensions- Rule", "ESCU - File with Samsam Extension- Rule", "ESCU - Remote Desktop Network Traffic- Rule", "ESCU - Common Ransomware Notes- Rule", "ESCU - Prohibited Software On Endpoint- Rule", "ESCU - Deleting Shadow Copies- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Spectre and Meltdown Vulnerable Systems", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Open Redirect in Splunk Web", "Get Notable History", "Get Notable Info", "Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Open Redirect in Splunk Web- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Splunk Enterprise Information Disclosure", "Get Notable Info", "Investigate Network Traffic From src ip", "Get Notable History", "Investigate Web Activity From src ip", "Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Splunk Enterprise Information Disclosure- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started With Previously Unseen User", "AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get Notable History", "Get EC2 Instance Details by instanceId", "Get User Information from Identity Table", "Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User- Rule", "ESCU - EC2 Instance Started In Previously Unseen Region- Rule", "ESCU - Abnormally High AWS Instances Launched by User- Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK- Rule", "ESCU - Abnormally High AWS Instances Terminated by User- Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect AWS Console Login by User from New Region", "Detect AWS Console Login by User from New Country", "Detect new user AWS Console Login", "Detect AWS Console Login by User from New City", "AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New Region- Rule", "ESCU - Detect new user AWS Console Login- Rule", "ESCU - Detect AWS Console Login by User from New City- Rule", "ESCU - Detect AWS Console Login by User from New Country- Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion", "Detect New Open S3 buckets", "AWS Investigate User Activities By ARN", "Get Notable Info", "Investigate AWS activities via region name", "Get All AWS Activity From IP Address", "Get Notable History", "Get User Information from Identity Table", "AWS S3 Bucket details via bucketName"] +searches = ["ESCU - Detect New Open S3 buckets- Rule", "ESCU - Detect S3 access from a new IP- Rule", "ESCU - Detect Spike in S3 Bucket deletion- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect Spike in blocked Outbound Traffic from your AWS", "AWS Investigate User Activities By ARN", "Get DNS Server History for a host", "Get Notable Info", "Get Process Info", "AWS Network Interface details via resourceId", "Get DNS traffic ratio", "AWS Network ACL Details from ID", "Get All AWS Activity From IP Address", "Get Notable History", "Get Process Information For Port Activity", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Unusually Long Command Line - MLTK", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Detect Use of cmd exe to Launch Script Interpreters", "Detect Prohibited Applications Spawning cmd exe", "Unusually Long Command Line", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe- Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - System Processes Run From Unexpected Locations- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["DNS Query Length With High Standard Deviation", "Excessive DNS Failures", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS Query Length Outliers - MLTK", "Detection of DNS Tunnels", "Detect hosts connecting to dynamic domain providers", "Clients Connecting to Multiple DNS Servers", "Detect Long DNS TXT Record Response", "Get DNS Server History for a host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get DNS traffic ratio", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Process Responsible For The DNS Traffic", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - DNS Query Length With High Standard Deviation- Rule", "ESCU - DNS Query Length Outliers - MLTK- Rule", "ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detection of DNS Tunnels- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Detect Long DNS TXT Record Response- Rule", "ESCU - Excessive DNS Failures- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email Attachment Extensions", "Suspicious Email - UBA Anomaly", "Investigate Web Activity From Host", "Get Notable Info", "Get Email Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Emails From Specific Sender", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Email Attachments With Lots Of Spaces- Rule", "ESCU - Suspicious Email - UBA Anomaly- Rule", "ESCU - Monitor Email For Brand Abuse- Rule", "ESCU - Suspicious Email Attachment Extensions- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence", "Detect Prohibited Applications Spawning cmd exe", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe- Rule", "ESCU - Detect mshta exe running scripts in command-line arguments- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta User Logins From Multiple Cities", "Okta Failed SSO Attempts", "Investigate Okta Activity by app", "Investigate User Activities In Okta", "Investigate Okta Activity by IP Address"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP- Rule", "ESCU - Okta Failed SSO Attempts- Rule", "ESCU - Okta Account Lockout Events- Rule", "ESCU - Okta User Logins From Multiple Cities- Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Process Execution via WMI", "WMI Permanent Event Subscription - Sysmon", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "WMI Temporary Event Subscription", "WMI Permanent Event Subscription", "Script Execution via WMI", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Sysmon WMI Activity for Host", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Process Execution via WMI- Rule", "ESCU - WMI Permanent Event Subscription - Sysmon- Rule", "ESCU - Remote Process Instantiation via WMI- Rule", "ESCU - WMI Permanent Event Subscription- Rule", "ESCU - Script Execution via WMI- Rule", "ESCU - Remote WMI Command Attempt- Rule", "ESCU - WMI Temporary Event Subscription- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Remote Registry Key modifications", "Suspicious Changes to File Associations", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Registry Keys Used For Persistence", "Monitor Registry Keys for Print Monitors", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation- Rule", "ESCU - Registry Keys for Creating SHIM Databases- Rule", "ESCU - Disabling Remote User Account Control- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Reg exe used to hide files directories via registry keys- Rule", "ESCU - Suspicious Changes to File Associations- Rule", "ESCU - Remote Registry Key modifications- Rule", "ESCU - Monitor Registry Keys for Print Monitors- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["EC2 Instance Modified With Previously Unseen User", "Get Notable History", "AWS Investigate User Activities By ARN", "Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Uncommon Processes On Endpoint", "Detect Rare Executables", "Unusually Long Command Line - MLTK", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Detect processes used for System Network Configuration Discovery", "Unusually Long Command Line", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect processes used for System Network Configuration Discovery- Rule", "ESCU - Detect Rare Executables- Rule", "ESCU - RunDLL Loading DLL By Ordinal- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - System Processes Run From Unexpected Locations- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - Uncommon Processes On Endpoint- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Protocols passing authentication in cleartext", "Get Notable Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Process Information For Port Activity"] +searches = ["ESCU - Protocols passing authentication in cleartext- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts", "Web Fraud - Account Harvesting", "Get Notable History", "Get Notable Info", "Get Emails From Specific Sender", "Get Web Session Information via session id"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts- Rule", "ESCU - Web Fraud - Anomalous User Clickspeed- Rule", "ESCU - Web Fraud - Account Harvesting- Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Remote Registry Key modifications", "Disabling Remote User Account Control", "Reg exe used to hide files directories via registry keys", "Hiding Files And Directories With Attrib exe", "Suspicious Reg exe Process", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Hiding Files And Directories With Attrib exe- Rule", "ESCU - Disabling Remote User Account Control- Rule", "ESCU - Reg exe used to hide files directories via registry keys- Rule", "ESCU - Suspicious Reg exe Process- Rule", "ESCU - Remote Registry Key modifications- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious Changes to File Associations", "Execution of File with Multiple Extensions", "Execution of File With Spaces Before Extension", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Execution of File with Multiple Extensions- Rule", "ESCU - Suspicious Changes to File Associations- Rule", "ESCU - Execution of File With Spaces Before Extension- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Suspicious wevtutil Usage", "Deleting Shadow Copies", "Windows Event Log Cleared", "USN Journal Deletion", "Investigate Web Activity From Host", "Get Vulnerability Logs For Endpoint", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Suspicious wevtutil Usage- Rule", "ESCU - Windows Event Log Cleared- Rule", "ESCU - Deleting Shadow Copies- Rule", "ESCU - USN Journal Deletion- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "Detect Path Interception By Creation Of program exe", "Remote Registry Key modifications", "Reg exe Manipulating Windows Services Registry Keys", "Schtasks used for forcing a reboot", "Reg exe used to hide files directories via registry keys", "Shim Database Installation With Suspicious Parameters", "Registry Keys for Creating SHIM Databases", "Hiding Files And Directories With Attrib exe", "Registry Keys Used For Persistence", "Shim Database File Creation", "Monitor Registry Keys for Print Monitors", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases- Rule", "ESCU - Detect Path Interception By Creation Of program exe- Rule", "ESCU - Schtasks used for forcing a reboot- Rule", "ESCU - Hiding Files And Directories With Attrib exe- Rule", "ESCU - Shim Database Installation With Suspicious Parameters- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Reg exe used to hide files directories via registry keys- Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Remote Registry Key modifications- Rule", "ESCU - Shim Database File Creation- Rule", "ESCU - Monitor Registry Keys for Print Monitors- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["Uncommon Processes On Endpoint", "Registry Keys Used For Privilege Escalation", "Overwriting Accessibility Binaries", "Child Processes of Spoolsv exe", "Investigate Web Activity From Host", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get Registry Activities", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Uncommon Processes On Endpoint- Rule", "ESCU - Overwriting Accessibility Binaries- Rule", "ESCU - Child Processes of Spoolsv exe- Rule", "ESCU - Registry Keys Used For Privilege Escalation- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["Sc exe Manipulating Windows Services", "Reg exe Manipulating Windows Services Registry Keys", "First Time Seen Running Windows Service", "Get Notable Info", "Get Parent Process Info", "Get Process Info", "Get Notable History", "Get User Information from Identity Table", "Get Risk Modifiers For User", "Get Risk Modifiers For Endpoint", "Get Authentication Logs For Endpoint"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys- Rule", "ESCU - First Time Seen Running Windows Service- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From a14b16bf14aada317dd3473c78d231702574f15c Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 08:52:31 +0200 Subject: [PATCH 30/93] bug in generate --- bin/generate.py | 4 +- bin/jinja2_templates/analytic_stories.j2 | 2 +- package/default/analytic_stories.conf | 290 +++++++++++------------ package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 132 +++++------ 7 files changed, 217 insertions(+), 217 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index a5affea313..ca27cfde35 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -295,9 +295,9 @@ def prepare_stories(stories, detections): if 'analytics_story' in detection['tags']: for story in detection['tags']['analytics_story']: if story in sto_to_det.keys(): - sto_to_det[story].add(detection['name']) + sto_to_det[story].add(str('ESCU - ' + detection['name'] + ' - Rule')) else: - sto_to_det[story] = {detection['name']} + sto_to_det[story] = {str('ESCU - ' + detection['name'] + ' - Rule')} data_model = parse_data_models_from_search(detection['search']) if data_model: diff --git a/bin/jinja2_templates/analytic_stories.j2 b/bin/jinja2_templates/analytic_stories.j2 index 47e3efbbf8..5cef46332e 100644 --- a/bin/jinja2_templates/analytic_stories.j2 +++ b/bin/jinja2_templates/analytic_stories.j2 @@ -28,7 +28,7 @@ support_searches = [] {% if story.data_models is defined %} data_models = {{ story.data_models | tojson }} {% else %} -data_models = none +data_models = [] {% endif %} providing_technologies = none description = {{ story.description }} diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index b714e9abe8..b4f742eec6 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T16:27:32 UTC +# On Date: 2020-05-11T06:52:21 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,11 +14,11 @@ modification_date = 2018-06-04 id = 2f2f610a-d64d-48c2-b57c-967a2b49ab5a version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] -detection_searches = ["AWS Cross Account Activity From Previously Unseen Account"] +detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ @@ -32,11 +32,11 @@ modification_date = 2018-03-08 id = ced74200-8465-4bc3-bd2c-9a782eec6750 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["Abnormally High AWS Instances Launched by User", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen AMI", "EC2 Instance Started With Previously Unseen Instance Type", "EC2 Instance Started With Previously Unseen User"] +detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ @@ -51,11 +51,11 @@ modification_date = 2018-05-21 id = 2e8948a5-5239-406b-b56b-6c50ff268af4 version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] -detection_searches = ["AWS Network Access Control List Created with All Open Ports", "AWS Network Access Control List Deleted", "Detect Spike in Network ACL Activity", "Detect Spike in blocked Outbound Traffic from your AWS"] +detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -67,11 +67,11 @@ modification_date = 2018-03-16 id = 3338b567-3804-4261-9889-cf0ca4753c7f version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["AWS Cloud Provisioning From Previously Unseen City", "AWS Cloud Provisioning From Previously Unseen Country", "AWS Cloud Provisioning From Previously Unseen IP Address", "AWS Cloud Provisioning From Previously Unseen Region"] +detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City"] +investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ @@ -84,11 +84,11 @@ modification_date = 2018-03-12 id = 2e8948a5-5239-406b-b56b-6c50f1269af3 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] -detection_searches = ["Detect API activity from users without MFA", "Detect AWS API Activities From Unapproved Accounts", "Detect Spike in AWS API Activity", "Detect Spike in Security Group Activity", "Detect new API calls from user roles"] +detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ @@ -103,9 +103,9 @@ modification_date = 2017-09-06 id = 8892a655-6205-55f7-abba-06460e38c8ae version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] -detection_searches = ["Detect Excessive Account Lockouts From Endpoint", "Detect Excessive User Account Lockouts", "Identify New User Accounts", "Short Lived Windows Accounts"] +detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -119,9 +119,9 @@ modification_date = 2018-12-06 id = 2dcfd6a2-e7d2-4873-b6ba-adaf819d2a1e version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] -detection_searches = ["Suspicious Java Classes", "Unusually Long Content-Type Length", "Web Servers Executing Suspicious Processes"] +detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -148,9 +148,9 @@ modification_date = 2017-09-13 id = 91c676cf-0b23-438d-abee-f6335e1fce77 version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] -detection_searches = ["Detect Unauthorized Assets by MAC address"] +detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -164,9 +164,9 @@ modification_date = 2017-12-19 id = 91c676cf-0b23-438d-abee-f6335e1fce78 version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] -detection_searches = ["Monitor DNS For Brand Abuse", "Monitor Email For Brand Abuse", "Monitor Web Traffic For Brand Abuse"] +detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -182,9 +182,9 @@ modification_date = 2019-10-02 id = 3b96d13c-fdc7-45dd-b3ad-c132b31cdd2a version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["Abnormally High AWS Instances Launched by User - MLTK", "Cloud Compute Instance Created By Previously Unseen User", "Cloud Compute Instance Created With Previously Unseen Image", "Cloud Compute Instance Created With Previously Unseen Instance Type", "Cloud Compute Instance Started In Previously Unused Region"] +detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -201,11 +201,11 @@ modification_date = 2019-01-09 id = bd91a2bc-d20b-4f44-a982-1bea98e86390 version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] -detection_searches = ["Osquery pack - ColdRoot detection", "Processes Tapping Keyboard Events"] +detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ @@ -219,9 +219,9 @@ modification_date = 2020-02-03 id = 8e03c61e-13c4-4dcd-bfbe-5ce5a8dc031a version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] -detection_searches = ["Email files written outside of the Outlook directory", "Email servers sending high volume traffic to hosts", "Hosts receiving high volume of network traffic from email server", "Suspicious writes to System Volume Information", "Suspicious writes to windows Recycle Bin"] +detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -237,9 +237,9 @@ modification_date = 2018-06-01 id = 943773c6-c4de-4f38-89a8-0b92f98804d8 version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] -detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Large Outbound ICMP Packets", "Detect Long DNS TXT Record Response", "Detect Spike in blocked Outbound Traffic from your AWS", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] +detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -254,7 +254,7 @@ modification_date = 2019-04-29 id = 9a64ab44-9214-4639-8163-7eaa2621bd61 version = 1 reference = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] -detection_searches = ["Detect DNS requests to Phishing Sites leveraging EvilGinx2"] +detection_searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1192"], "nist": ["DE.CM"]} investigative_searches = ["ESCU - Get Certificate logs for a domain"] support_searches = [] @@ -271,11 +271,11 @@ modification_date = 2020-02-20 id = aa0e28b1-0521-4b6f-9d2a-7b87e34af246 version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["GCP GCR container uploaded", "New container uploaded to AWS ECR"] +detection_searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule"] mappings = {} investigative_searches = ["ESCU - Investigate AWS ECR container listing activity"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -287,9 +287,9 @@ modification_date = 2020-02-04 id = 854d78bf-d0e2-4f4e-b05c-640905f86d7a version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] -detection_searches = ["Access LSASS Memory for Dump Creation", "Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Attempted Credential Dump From Registry via Reg exe", "Create Remote Thread into LSASS", "Creation of Shadow Copy", "Creation of Shadow Copy with wmic and powershell", "Credential Dumping via Copy Command from Shadow Copy", "Credential Dumping via Symlink to Shadow Copy", "Detect Credential Dumping through LSASS access", "Detect Mimikatz Using Loaded Images", "Dump LSASS via comsvcs DLL", "Unsigned Image Loaded by LSASS"] +detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations"] +investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -305,9 +305,9 @@ modification_date = 2020-01-22 id = 0c016e5c-88be-4e2c-8c6c-c2b55b4fb4ef version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] -detection_searches = ["Create local admin accounts using net exe", "Detect New Local Admin account", "Detect Outbound SMB Traffic", "Detect PsExec With accepteula Flag", "First time seen command line argument", "Malicious PowerShell Process - Execution Policy Bypass", "Processes launching netsh", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Sc exe Manipulating Windows Services", "Scheduled Task Name Used by Dragonfly Threat Actors", "Single Letter Process On Endpoint", "Suspicious Reg exe Process"] +detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -324,9 +324,9 @@ modification_date = 2016-09-13 id = e8afd39e-3294-11e6-b39d-a45e60c6700 version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] -detection_searches = ["Large Volume of DNS ANY Queries"] +detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -341,7 +341,7 @@ modification_date = 2020-02-04 id = 8169f17b-ef68-4b59-aa28-586907301221 version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "DNS record changed", "Detect hosts connecting to dynamic domain providers"] +detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} investigative_searches = ["ESCU - Get DNS Server History for a host"] support_searches = [] @@ -365,9 +365,9 @@ modification_date = 2017-09-14 id = 91c676cf-0b23-438d-abee-f6335e1fce33 version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] -detection_searches = ["Detect USB device insertion", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels"] +detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -381,9 +381,9 @@ modification_date = 2020-02-04 id = fcc27099-46a0-46b0-a271-5c7dab56b6f1 version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] -detection_searches = ["Attempt To Add Certificate To Untrusted Store", "Attempt To Stop Security Service", "Processes launching netsh", "Sc exe Manipulating Windows Services", "Suspicious Reg exe Process", "Unload Sysmon Filter Driver"] +detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -397,9 +397,9 @@ modification_date = 2018-09-06 id = 8169f17b-ef68-4b59-aae8-586907301221 version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "Detect web traffic to dynamic domain providers"] +detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -413,9 +413,9 @@ modification_date = 2020-01-27 id = bb9f5ed2-916e-4364-bb6d-91c310efcf52 version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] -detection_searches = ["Detect Rare Executables", "Detect Use of cmd exe to Launch Script Interpreters", "Detection of tools built by NirSoft", "Email Attachments With Lots Of Spaces", "Prohibited Software On Endpoint", "Registry Keys Used For Persistence", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious Email Attachment Extensions"] +detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -431,9 +431,9 @@ modification_date = 2020-01-22 id = baf7580b-d4b4-4774-8173-7d198e9da335 version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] -detection_searches = ["Create or delete windows shares using net exe", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "Detect Outbound SMB Traffic", "First time seen command line argument", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Suspicious File Write"] +detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -450,9 +450,9 @@ modification_date = 2017-09-14 id = 2e8948a5-5239-406b-b56b-6c50fe268af4 version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] -detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Windows hosts file modification"] +detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -466,9 +466,9 @@ modification_date = 2017-09-14 id = 1f5294cb-b85f-4c2d-9c58-ffcf248f52bd version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] -detection_searches = ["Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers"] +detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -496,11 +496,11 @@ modification_date = 2020-04-15 id = a9ef59cf-e981-4e66-9eef-bb049f695c09 version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] -detection_searches = ["Amazon EKS Kubernetes Pod scan detection", "Amazon EKS Kubernetes cluster scan detection", "GCP Kubernetes cluster scan detection"] +detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -512,9 +512,9 @@ modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] -detection_searches = ["Detect Activity Related to Pass the Hash Attacks", "Remote Desktop Network Traffic", "Remote Desktop Process Running On System", "Schtasks scheduling job on remote system"] +detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -532,9 +532,9 @@ modification_date = 2017-08-23 id = 2c8ff66e-0b57-42af-8ad7-912438a403fc version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -detection_searches = ["Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Malicious PowerShell Process - Encoded Command", "Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments", "Malicious PowerShell Process With Obfuscation Techniques"] +detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -557,11 +557,11 @@ modification_date = 2017-09-12 id = abe807c7-1eb6-4304-ac32-6e7aacdb891d version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] -detection_searches = ["Extended Period Without Successful Netbackup Backups", "Unsuccessful Netbackup backups"] +detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -573,9 +573,9 @@ modification_date = 2017-09-15 id = 8892a655-6205-43f7-abba-06460e38c8ae version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] -detection_searches = ["Prohibited Software On Endpoint"] +detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -590,9 +590,9 @@ modification_date = 2017-09-15 id = 9ef8d677-7b52-4213-a038-99cfc7acc2d8 version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] -detection_searches = ["No Windows Updates in a time frame"] +detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -608,9 +608,9 @@ modification_date = 2017-01-05 id = 2b1800dd-92f9-47ec-a981-fdf1351e5f65 version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] -detection_searches = ["Processes created by netsh", "Processes launching netsh"] +detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -625,9 +625,9 @@ modification_date = 2020-01-22 id = bb9f5ed2-916e-4364-bb6d-97c370efcf52 version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] -detection_searches = ["First Time Seen Running Windows Service", "First time seen command line argument", "Sc exe Manipulating Windows Services"] +detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -645,11 +645,11 @@ modification_date = 2019-04-29 id = 57226b40-94f3-4ce5-b101-a75f67759c27 version = 1 reference = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] -detection_searches = ["Detect Oulook exe writing a zip file", "Suspicious LNK file launching a process"] +detection_searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} investigative_searches = ["ESCU - Get Parent Process Info"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ @@ -668,9 +668,9 @@ modification_date = 2020-01-22 id = 988C59C5-0A1C-45B6-A555-0C62276E327E version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] -detection_searches = ["First time seen command line argument", "Malicious PowerShell Process - Connect To Internet With Hidden Window", "Registry Keys Used For Persistence", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] +detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -711,9 +711,9 @@ modification_date = 2017-09-11 id = 6d13121c-90f3-446d-8ac3-27efbbc65218 version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] -detection_searches = ["Detect hosts connecting to dynamic domain providers", "Prohibited Network Traffic Allowed", "Protocol or Port Mismatch", "TOR Traffic"] +detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -727,9 +727,9 @@ modification_date = 2020-02-04 id = cf309d0d-d4aa-4fbb-963d-1e79febd3756 version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] -detection_searches = ["Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Prohibited Network Traffic Allowed", "Registry Keys Used For Persistence", "Remote Process Instantiation via WMI", "SMB Traffic Spike", "SMB Traffic Spike - MLTK", "Scheduled tasks used in BadRabbit ransomware", "Schtasks used for forcing a reboot", "Spike in File Writes", "Suspicious wevtutil Usage", "System Processes Run From Unexpected Locations", "TOR Traffic", "USN Journal Deletion", "Unusually Long Command Line", "Unusually Long Command Line - MLTK", "Windows Event Log Cleared"] +detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -743,9 +743,9 @@ modification_date = 2017-09-12 id = 91c676cf-0b23-438d-abee-f6335e177e77 version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] -detection_searches = ["Detect New Login Attempts to Routers"] +detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -760,9 +760,9 @@ modification_date = 2017-09-19 id = 4f6632f5-449c-4686-80df-57625f59bab3 version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] -detection_searches = ["SQL Injection with Long URLs"] +detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -777,9 +777,9 @@ modification_date = 2018-12-13 id = c4b89506-fbcf-4cb7-bfd6-527e54789604 version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] -detection_searches = ["Batch File Write to System32", "Common Ransomware Extensions", "Common Ransomware Notes", "Deleting Shadow Copies", "Detect PsExec With accepteula Flag", "Detect attackers scanning for vulnerable JBoss servers", "Detect malicious requests to exploit JBoss servers", "File with Samsam Extension", "Prohibited Software On Endpoint", "Remote Desktop Network Bruteforce", "Remote Desktop Network Traffic", "Samsam Test File Write", "Spike in File Writes"] +detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -798,9 +798,9 @@ modification_date = 2018-01-08 id = 6d3306f6-bb2b-4219-8609-8efad64032f2 version = 1 reference = ["https://meltdownattack.com/"] -detection_searches = ["Spectre and Meltdown Vulnerable Systems"] +detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -814,11 +814,11 @@ modification_date = 2017-09-19 id = 4e692b96-de2d-4bd1-9105-37e2368a8db1 version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] -detection_searches = ["Open Redirect in Splunk Web"] +detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ @@ -839,11 +839,11 @@ modification_date = 2018-06-14 id = 1fc34cbc-34e9-43ba-87ab-6811c9e95400 version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] -detection_searches = ["Splunk Enterprise Information Disclosure"] +detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From src ip"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ @@ -858,11 +858,11 @@ modification_date = 2018-02-09 id = 2e8948a5-5239-406b-b56b-6c50f1268af3 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["Abnormally High AWS Instances Launched by User", "Abnormally High AWS Instances Launched by User - MLTK", "Abnormally High AWS Instances Terminated by User", "Abnormally High AWS Instances Terminated by User - MLTK", "EC2 Instance Started In Previously Unseen Region", "EC2 Instance Started With Previously Unseen User"] +detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -874,11 +874,11 @@ modification_date = 2019-05-01 id = 2e8948a5-5239-406b-b56b-6c59f1268af3 version = 1 reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] -detection_searches = ["Detect AWS Console Login by User from New City", "Detect AWS Console Login by User from New Country", "Detect AWS Console Login by User from New Region", "Detect new user AWS Console Login"] +detection_searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -890,11 +890,11 @@ modification_date = 2018-07-24 id = 2e8948a5-5239-406b-b56b-6c50w3168af3 version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] -detection_searches = ["Detect New Open S3 buckets", "Detect S3 access from a new IP", "Detect Spike in S3 Bucket deletion"] +detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ @@ -908,11 +908,11 @@ modification_date = 2018-05-07 id = 2e8948a5-5239-406b-b56b-6c50f2168af3 version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] -detection_searches = ["Detect Spike in blocked Outbound Traffic from your AWS"] +detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ @@ -927,9 +927,9 @@ modification_date = 2020-02-03 id = f4368ddf-d59f-4192-84f6-778ac5a3ffc7 version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] -detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect Use of cmd exe to Launch Script Interpreters", "First time seen command line argument", "System Processes Run From Unexpected Locations", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] +detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -943,9 +943,9 @@ modification_date = 2017-09-18 id = 3c3835c0-255d-4f9e-ab84-e29ec9ec9b56 version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] -detection_searches = ["Clients Connecting to Multiple DNS Servers", "DNS Query Length Outliers - MLTK", "DNS Query Length With High Standard Deviation", "DNS Query Requests Resolved by Unauthorized DNS Servers", "Detect Long DNS TXT Record Response", "Detect hosts connecting to dynamic domain providers", "Detection of DNS Tunnels", "Excessive DNS Failures"] +detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -959,9 +959,9 @@ modification_date = 2020-01-27 id = 2b1800dd-92f9-47ec-a981-fdf1351e5d55 version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] -detection_searches = ["Email Attachments With Lots Of Spaces", "Monitor Email For Brand Abuse", "Suspicious Email - UBA Anomaly", "Suspicious Email Attachment Extensions"] +detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -979,9 +979,9 @@ modification_date = 2020-02-03 id = 2b1800dd-92f9-47dd-a981-fdf13w1q5d55 version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] -detection_searches = ["Detect Prohibited Applications Spawning cmd exe", "Detect mshta exe running scripts in command-line arguments", "Registry Keys Used For Persistence"] +detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -997,11 +997,11 @@ modification_date = 2020-04-02 id = 9cbd34af-8f39-4476-a423-bacd126c750b version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] -detection_searches = ["Multiple Okta Users With Invalid Credentails From The Same IP", "Okta Account Lockout Events", "Okta Failed SSO Attempts", "Okta User Logins From Multiple Cities"] +detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ @@ -1015,9 +1015,9 @@ modification_date = 2018-10-23 id = c8ddc5be-69bc-4202-b3ab-4010b27d7ad5 version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] -detection_searches = ["Process Execution via WMI", "Remote Process Instantiation via WMI", "Remote WMI Command Attempt", "Script Execution via WMI", "WMI Permanent Event Subscription", "WMI Permanent Event Subscription - Sysmon", "WMI Temporary Event Subscription"] +detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1033,9 +1033,9 @@ modification_date = 2018-05-31 id = 2b1800dd-92f9-47dd-a981-fdf1351e5d55 version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] -detection_searches = ["Disabling Remote User Account Control", "Monitor Registry Keys for Print Monitors", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys Used For Privilege Escalation", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Suspicious Changes to File Associations"] +detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1051,11 +1051,11 @@ modification_date = 2018-04-09 id = 73de57ef-0dfc-411f-b1e7-fa24428aeae0 version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] -detection_searches = ["EC2 Instance Modified With Previously Unseen User"] +detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ @@ -1068,9 +1068,9 @@ modification_date = 2020-02-04 id = f4368e3f-d59f-4192-84f6-748ac5a3ddb6 version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] -detection_searches = ["Detect Rare Executables", "Detect processes used for System Network Configuration Discovery", "RunDLL Loading DLL By Ordinal", "System Processes Run From Unexpected Locations", "Uncommon Processes On Endpoint", "Unusually Long Command Line", "Unusually Long Command Line - MLTK"] +detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1086,9 +1086,9 @@ modification_date = 2017-09-15 id = 826e6431-aeef-41b4-9fc0-6d0985d65a21 version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] -detection_searches = ["Protocols passing authentication in cleartext"] +detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1102,11 +1102,11 @@ modification_date = 2018-10-08 id = 31337aaa-bc22-4752-b599-ef112dq1dq7a version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] -detection_searches = ["Web Fraud - Account Harvesting", "Web Fraud - Anomalous User Clickspeed", "Web Fraud - Password Sharing Across Accounts"] +detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] support_searches = [] -data_models = none +data_models = [] providing_technologies = none description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ @@ -1123,9 +1123,9 @@ modification_date = 2018-05-31 id = 56e24a28-5003-4047-b2db-e8f3c4618064 version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] -detection_searches = ["Disabling Remote User Account Control", "Hiding Files And Directories With Attrib exe", "Reg exe used to hide files directories via registry keys", "Remote Registry Key modifications", "Suspicious Reg exe Process"] +detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1139,9 +1139,9 @@ modification_date = 2018-01-26 id = 30552a76-ac78-48e4-b3c0-de4e34e9563d version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] -detection_searches = ["Execution of File With Spaces Before Extension", "Execution of File with Multiple Extensions", "Suspicious Changes to File Associations"] +detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1159,9 +1159,9 @@ modification_date = 2017-09-12 id = b6db2c60-a281-48b4-95f1-2cd99ed56835 version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] -detection_searches = ["Deleting Shadow Copies", "Suspicious wevtutil Usage", "USN Journal Deletion", "Windows Event Log Cleared"] +detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1176,9 +1176,9 @@ modification_date = 2018-05-31 id = 30874d4f-20a1-488f-85ec-5d52ef74e3f9 version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] -detection_searches = ["Detect Path Interception By Creation Of program exe", "Hiding Files And Directories With Attrib exe", "Monitor Registry Keys for Print Monitors", "Reg exe Manipulating Windows Services Registry Keys", "Reg exe used to hide files directories via registry keys", "Registry Keys Used For Persistence", "Registry Keys for Creating SHIM Databases", "Remote Registry Key modifications", "Sc exe Manipulating Windows Services", "Schtasks used for forcing a reboot", "Shim Database File Creation", "Shim Database Installation With Suspicious Parameters"] +detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1192,9 +1192,9 @@ modification_date = 2020-02-04 id = 644e22d3-598a-429c-a007-16fdb802cae5 version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] -detection_searches = ["Child Processes of Spoolsv exe", "Overwriting Accessibility Binaries", "Registry Keys Used For Privilege Escalation", "Uncommon Processes On Endpoint"] +detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1208,9 +1208,9 @@ modification_date = 2017-11-02 id = 6dbd810e-f66d-414b-8dfc-e46de55cbfe2 version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] -detection_searches = ["First Time Seen Running Windows Service", "Reg exe Manipulating Windows Services Registry Keys", "Sc exe Manipulating Windows Services"] +detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 8cc2636b3e..f0d569c3a0 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T16:27:32 UTC +# On Date: 2020-05-11T06:52:21 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 8e3d676d60..60e152fa6e 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T16:27:32 UTC +# On Date: 2020-05-11T06:52:21 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index b85d0fecce..3f7798e265 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T16:27:32 UTC +# On Date: 2020-05-11T06:52:21 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 3e06987ba9..5cbba9bc28 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-08T16:27:32 UTC +# On Date: 2020-05-11T06:52:21 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account- Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User- Rule", "ESCU - EC2 Instance Started In Previously Unseen Region- Rule", "ESCU - Abnormally High AWS Instances Launched by User- Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type- Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS- Rule", "ESCU - AWS Network Access Control List Created with All Open Ports- Rule", "ESCU - Detect Spike in Network ACL Activity- Rule", "ESCU - AWS Network Access Control List Deleted- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City- Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address- Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region- Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country- Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity- Rule", "ESCU - Detect new API calls from user roles- Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts- Rule", "ESCU - Detect API activity from users without MFA- Rule", "ESCU - Detect Spike in Security Group Activity- Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive User Account Lockouts- Rule", "ESCU - Short Lived Windows Accounts- Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint- Rule", "ESCU - Identify New User Accounts- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Java Classes- Rule", "ESCU - Unusually Long Content-Type Length- Rule", "ESCU - Web Servers Executing Suspicious Processes- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address- Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse- Rule", "ESCU - Monitor Email For Brand Abuse- Rule", "ESCU - Monitor DNS For Brand Abuse- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type- Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image- Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK- Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region- Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User- Rule", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection- Rule", "ESCU - Processes Tapping Keyboard Events- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin- Rule", "ESCU - Email files written outside of the Outlook directory- Rule", "ESCU - Hosts receiving high volume of network traffic from email server- Rule", "ESCU - Email servers sending high volume traffic to hosts- Rule", "ESCU - Suspicious writes to System Volume Information- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation- Rule", "ESCU - Detect Large Outbound ICMP Packets- Rule", "ESCU - Protocol or Port Mismatch- Rule", "ESCU - DNS Query Length Outliers - MLTK- Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS- Rule", "ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detection of DNS Tunnels- Rule", "ESCU - Prohibited Network Traffic Allowed- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Detect Long DNS TXT Record Response- Rule", "ESCU - Excessive DNS Failures- Rule", "ESCU - TOR Traffic- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -189,7 +189,7 @@ version = 1 references = ["https://github.com/kgretzky/evilginx2", "https://attack.mitre.org/techniques/T1192/", "https://breakdev.org/evilginx-advanced-phishing-with-two-factor-authentication-bypass/"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2- Rule", "ESCU - Get Certificate logs for a domain"] +searches = ["ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule", "ESCU - Get Certificate logs for a domain"] description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. narrative = As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Because phishing is a technique that relies on human psychology, you will never be able to eliminate this vulnerability 100%. But you can use automated detection to significantly reduce the risks.\ This Analytic Story focuses on detecting signs of MiTM attacks enabled by [EvilGinx2](https://github.com/kgretzky/evilginx2), a toolkit that sets up a transparent proxy between the targeted site and the user. In this way, the attacker is able to intercept credentials and two-factor identification tokens. It employs a proxy template to allow a registered domain to impersonate targeted sites, such as Linkedin, Amazon, Okta, Github, Twitter, Instagram, Reddit, Office 365, and others. It can even register SSL certificates and camouflage them via a URL shortener, making them difficult to detect. Searches in this story look for signs of MiTM attacks enabled by EvilGinx2. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - GCP GCR container uploaded- Rule", "ESCU - New container uploaded to AWS ECR- Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempted Credential Dump From Registry via Reg exe- Rule", "ESCU - Access LSASS Memory for Dump Creation- Rule", "ESCU - Unsigned Image Loaded by LSASS- Rule", "ESCU - Creation of Shadow Copy with wmic and powershell- Rule", "ESCU - Creation of Shadow Copy- Rule", "ESCU - Dump LSASS via comsvcs DLL- Rule", "ESCU - Detect Mimikatz Using Loaded Images- Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy- Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy- Rule", "ESCU - Create Remote Thread into LSASS- Rule", "ESCU - Detect Credential Dumping through LSASS access- Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass- Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations"] +searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Create local admin accounts using net exe- Rule", "ESCU - Detect New Local Admin account- Rule", "ESCU - Single Letter Process On Endpoint- Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass- Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors- Rule", "ESCU - Detect Outbound SMB Traffic- Rule", "ESCU - Detect PsExec With accepteula Flag- Rule", "ESCU - Processes launching netsh- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Suspicious Reg exe Process- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - DNS record changed- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detection of DNS Tunnels- Rule", "ESCU - Detect USB device insertion- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unload Sysmon Filter Driver- Rule", "ESCU - Attempt To Add Certificate To Untrusted Store- Rule", "ESCU - Attempt To Stop Security Service- Rule", "ESCU - Processes launching netsh- Rule", "ESCU - Suspicious Reg exe Process- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detect web traffic to dynamic domain providers- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables- Rule", "ESCU - Suspicious Email Attachment Extensions- Rule", "ESCU - Detection of tools built by NirSoft- Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters- Rule", "ESCU - Email Attachments With Lots Of Spaces- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Prohibited Software On Endpoint- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation- Rule", "ESCU - Create or delete windows shares using net exe- Rule", "ESCU - DNS Query Length Outliers - MLTK- Rule", "ESCU - Detect Outbound SMB Traffic- Rule", "ESCU - Remote Desktop Process Running On System- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - Remote Desktop Network Traffic- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Suspicious File Write- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Windows hosts file modification- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers- Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection- Rule", "ESCU - GCP Kubernetes cluster scan detection- Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] +searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System- Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks- Rule", "ESCU - Schtasks scheduling job on remote system- Rule", "ESCU - Remote Desktop Network Traffic- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments- Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window- Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques- Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass- Rule", "ESCU - Malicious PowerShell Process - Encoded Command- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups- Rule", "ESCU - Unsuccessful Netbackup backups- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh- Rule", "ESCU - Processes launching netsh- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument- Rule", "ESCU - First Time Seen Running Windows Service- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file- Rule", "ESCU - Suspicious LNK file launching a process- Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - TOR Traffic- Rule", "ESCU - Prohibited Network Traffic Allowed- Rule", "ESCU - Protocol or Port Mismatch- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Process Instantiation via WMI- Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware- Rule", "ESCU - Spike in File Writes- Rule", "ESCU - TOR Traffic- Rule", "ESCU - Windows Event Log Cleared- Rule", "ESCU - Prohibited Network Traffic Allowed- Rule", "ESCU - Suspicious wevtutil Usage- Rule", "ESCU - Common Ransomware Extensions- Rule", "ESCU - SMB Traffic Spike - MLTK- Rule", "ESCU - System Processes Run From Unexpected Locations- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Common Ransomware Notes- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - USN Journal Deletion- Rule", "ESCU - Schtasks used for forcing a reboot- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - Deleting Shadow Copies- Rule", "ESCU - SMB Traffic Spike- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Samsam Test File Write- Rule", "ESCU - Spike in File Writes- Rule", "ESCU - Batch File Write to System32- Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers- Rule", "ESCU - Detect PsExec With accepteula Flag- Rule", "ESCU - Remote Desktop Network Bruteforce- Rule", "ESCU - Detect malicious requests to exploit JBoss servers- Rule", "ESCU - Common Ransomware Extensions- Rule", "ESCU - File with Samsam Extension- Rule", "ESCU - Remote Desktop Network Traffic- Rule", "ESCU - Common Ransomware Notes- Rule", "ESCU - Prohibited Software On Endpoint- Rule", "ESCU - Deleting Shadow Copies- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From src ip"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User- Rule", "ESCU - EC2 Instance Started In Previously Unseen Region- Rule", "ESCU - Abnormally High AWS Instances Launched by User- Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK- Rule", "ESCU - Abnormally High AWS Instances Terminated by User- Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New Region- Rule", "ESCU - Detect new user AWS Console Login- Rule", "ESCU - Detect AWS Console Login by User from New City- Rule", "ESCU - Detect AWS Console Login by User from New Country- Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets- Rule", "ESCU - Detect S3 access from a new IP- Rule", "ESCU - Detect Spike in S3 Bucket deletion- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe- Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - System Processes Run From Unexpected Locations- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - First time seen command line argument- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation- Rule", "ESCU - DNS Query Length Outliers - MLTK- Rule", "ESCU - Detect hosts connecting to dynamic domain providers- Rule", "ESCU - Detection of DNS Tunnels- Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers- Rule", "ESCU - Clients Connecting to Multiple DNS Servers- Rule", "ESCU - Detect Long DNS TXT Record Response- Rule", "ESCU - Excessive DNS Failures- Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Email Attachments With Lots Of Spaces- Rule", "ESCU - Suspicious Email - UBA Anomaly- Rule", "ESCU - Monitor Email For Brand Abuse- Rule", "ESCU - Suspicious Email Attachment Extensions- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe- Rule", "ESCU - Detect mshta exe running scripts in command-line arguments- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP- Rule", "ESCU - Okta Failed SSO Attempts- Rule", "ESCU - Okta Account Lockout Events- Rule", "ESCU - Okta User Logins From Multiple Cities- Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI- Rule", "ESCU - WMI Permanent Event Subscription - Sysmon- Rule", "ESCU - Remote Process Instantiation via WMI- Rule", "ESCU - WMI Permanent Event Subscription- Rule", "ESCU - Script Execution via WMI- Rule", "ESCU - Remote WMI Command Attempt- Rule", "ESCU - WMI Temporary Event Subscription- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation- Rule", "ESCU - Registry Keys for Creating SHIM Databases- Rule", "ESCU - Disabling Remote User Account Control- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Reg exe used to hide files directories via registry keys- Rule", "ESCU - Suspicious Changes to File Associations- Rule", "ESCU - Remote Registry Key modifications- Rule", "ESCU - Monitor Registry Keys for Print Monitors- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User- Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect processes used for System Network Configuration Discovery- Rule", "ESCU - Detect Rare Executables- Rule", "ESCU - RunDLL Loading DLL By Ordinal- Rule", "ESCU - Unusually Long Command Line - MLTK- Rule", "ESCU - System Processes Run From Unexpected Locations- Rule", "ESCU - Unusually Long Command Line- Rule", "ESCU - Uncommon Processes On Endpoint- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts- Rule", "ESCU - Web Fraud - Anomalous User Clickspeed- Rule", "ESCU - Web Fraud - Account Harvesting- Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Hiding Files And Directories With Attrib exe- Rule", "ESCU - Disabling Remote User Account Control- Rule", "ESCU - Reg exe used to hide files directories via registry keys- Rule", "ESCU - Suspicious Reg exe Process- Rule", "ESCU - Remote Registry Key modifications- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions- Rule", "ESCU - Suspicious Changes to File Associations- Rule", "ESCU - Execution of File With Spaces Before Extension- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious wevtutil Usage- Rule", "ESCU - Windows Event Log Cleared- Rule", "ESCU - Deleting Shadow Copies- Rule", "ESCU - USN Journal Deletion- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys for Creating SHIM Databases- Rule", "ESCU - Detect Path Interception By Creation Of program exe- Rule", "ESCU - Schtasks used for forcing a reboot- Rule", "ESCU - Hiding Files And Directories With Attrib exe- Rule", "ESCU - Shim Database Installation With Suspicious Parameters- Rule", "ESCU - Registry Keys Used For Persistence- Rule", "ESCU - Reg exe used to hide files directories via registry keys- Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Remote Registry Key modifications- Rule", "ESCU - Shim Database File Creation- Rule", "ESCU - Monitor Registry Keys for Print Monitors- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint- Rule", "ESCU - Overwriting Accessibility Binaries- Rule", "ESCU - Child Processes of Spoolsv exe- Rule", "ESCU - Registry Keys Used For Privilege Escalation- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys- Rule", "ESCU - First Time Seen Running Windows Service- Rule", "ESCU - Sc exe Manipulating Windows Services- Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 9ec01d97ddbbc4a62e94edfb56ea5156f650be2e Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 08:58:58 +0200 Subject: [PATCH 31/93] bug in generate --- stories/lateral_movement.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/stories/lateral_movement.yml b/stories/lateral_movement.yml index ac9b5e0ebc..9d7d1efff9 100644 --- a/stories/lateral_movement.yml +++ b/stories/lateral_movement.yml @@ -32,7 +32,6 @@ narrative: "Once attackers gain a foothold within an enterprise, they will seek author: David Dorsey, Splunk type: ESCU references: -- https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis - https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html tags: analytics_story: Lateral Movement From 9510b61c07d256eee1dc77e28cf73a57a7ad6317 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 09:14:25 +0200 Subject: [PATCH 32/93] bug in generate --- bin/jinja2_templates/savedsearches.j2 | 2 +- package/default/analytic_stories.conf | 124 ++++----- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 380 +++++++++++++------------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 132 ++++----- 6 files changed, 321 insertions(+), 321 deletions(-) diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 3d1c186551..95de48cd70 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -44,7 +44,7 @@ cron_schedule = {{ detection.deployment.scheduling.cron_schedule }} dispatch.earliest_time = {{ detection.deployment.scheduling.earliest_time }} dispatch.latest_time = {{ detection.deployment.scheduling.latest_time }} action.correlationsearch.enabled = 1 -action.correlationsearch.label = {{ detection.name }} +action.correlationsearch.label = ESCU - {{ detection.name }} - Rule {% if detection.deployment.scheduling.schedule_window is defined %} schedule_window = {{ detection.deployment.scheduling.schedule_window }} {% endif %} diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index b4f742eec6..066a09786a 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T06:52:21 UTC +# On Date: 2020-05-11T07:14:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] +investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] +investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] +investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -511,10 +511,10 @@ creation_date = 2020-02-04 modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 -reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] +investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index f0d569c3a0..3e3556041d 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T06:52:21 UTC +# On Date: 2020-05-11T07:14:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 60e152fa6e..95c6f8579d 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T06:52:21 UTC +# On Date: 2020-05-11T07:14:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -27,7 +27,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen City +action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -64,7 +64,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen Country +action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -101,7 +101,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen IP Address +action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -138,7 +138,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen Region +action.correlationsearch.label = ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -174,7 +174,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Cross Account Activity From Previously Unseen Account +action.correlationsearch.label = ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -210,7 +210,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Network Access Control List Created with All Open Ports +action.correlationsearch.label = ESCU - AWS Network Access Control List Created with All Open Ports - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['src'] @@ -246,7 +246,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Network Access Control List Deleted +action.correlationsearch.label = ESCU - AWS Network Access Control List Deleted - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['src'] @@ -282,7 +282,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Abnormally High AWS Instances Launched by User +action.correlationsearch.label = ESCU - Abnormally High AWS Instances Launched by User - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. @@ -317,7 +317,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Abnormally High AWS Instances Launched by User - MLTK +action.correlationsearch.label = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -353,7 +353,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Abnormally High AWS Instances Terminated by User +action.correlationsearch.label = ESCU - Abnormally High AWS Instances Terminated by User - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window @@ -388,7 +388,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Abnormally High AWS Instances Terminated by User - MLTK +action.correlationsearch.label = ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -424,7 +424,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Access LSASS Memory for Dump Creation +action.correlationsearch.label = ESCU - Access LSASS Memory for Dump Creation - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -458,7 +458,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Amazon EKS Kubernetes Pod scan detection +action.correlationsearch.label = ESCU - Amazon EKS Kubernetes Pod scan detection - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API @@ -493,7 +493,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Amazon EKS Kubernetes cluster scan detection +action.correlationsearch.label = ESCU - Amazon EKS Kubernetes cluster scan detection - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS @@ -529,7 +529,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Attempt To Add Certificate To Untrusted Store +action.correlationsearch.label = ESCU - Attempt To Add Certificate To Untrusted Store - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -566,7 +566,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass +action.correlationsearch.label = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -603,7 +603,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Attempt To Stop Security Service +action.correlationsearch.label = ESCU - Attempt To Stop Security Service - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -640,7 +640,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Attempted Credential Dump From Registry via Reg exe +action.correlationsearch.label = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -675,7 +675,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Batch File Write to System32 +action.correlationsearch.label = ESCU - Batch File Write to System32 - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -712,7 +712,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Child Processes of Spoolsv exe +action.correlationsearch.label = ESCU - Child Processes of Spoolsv exe - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -751,7 +751,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Clients Connecting to Multiple DNS Servers +action.correlationsearch.label = ESCU - Clients Connecting to Multiple DNS Servers - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -788,7 +788,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Cloud Compute Instance Created By Previously Unseen User +action.correlationsearch.label = ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -825,7 +825,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Cloud Compute Instance Created With Previously Unseen Image +action.correlationsearch.label = ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -862,7 +862,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Cloud Compute Instance Created With Previously Unseen Instance Type +action.correlationsearch.label = ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -899,7 +899,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Cloud Compute Instance Started In Previously Unused Region +action.correlationsearch.label = ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -940,7 +940,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Common Ransomware Extensions +action.correlationsearch.label = ESCU - Common Ransomware Extensions - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -977,7 +977,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Common Ransomware Notes +action.correlationsearch.label = ESCU - Common Ransomware Notes - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -1013,7 +1013,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Create Remote Thread into LSASS +action.correlationsearch.label = ESCU - Create Remote Thread into LSASS - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1048,7 +1048,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Create local admin accounts using net exe +action.correlationsearch.label = ESCU - Create local admin accounts using net exe - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -1085,7 +1085,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Create or delete windows shares using net exe +action.correlationsearch.label = ESCU - Create or delete windows shares using net exe - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -1122,7 +1122,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Creation of Shadow Copy +action.correlationsearch.label = ESCU - Creation of Shadow Copy - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1156,7 +1156,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Creation of Shadow Copy with wmic and powershell +action.correlationsearch.label = ESCU - Creation of Shadow Copy with wmic and powershell - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1191,7 +1191,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Credential Dumping via Copy Command from Shadow Copy +action.correlationsearch.label = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1226,7 +1226,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Credential Dumping via Symlink to Shadow Copy +action.correlationsearch.label = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1267,7 +1267,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = DNS Query Length Outliers - MLTK +action.correlationsearch.label = ESCU - DNS Query Length Outliers - MLTK - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -1304,7 +1304,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = DNS Query Length With High Standard Deviation +action.correlationsearch.label = ESCU - DNS Query Length With High Standard Deviation - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. @@ -1340,7 +1340,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = DNS Query Requests Resolved by Unauthorized DNS Servers +action.correlationsearch.label = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -1381,7 +1381,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = DNS record changed +action.correlationsearch.label = ESCU - DNS record changed - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['src'] @@ -1418,7 +1418,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Deleting Shadow Copies +action.correlationsearch.label = ESCU - Deleting Shadow Copies - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -1460,7 +1460,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect API activity from users without MFA +action.correlationsearch.label = ESCU - Detect API activity from users without MFA - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -1502,7 +1502,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect AWS API Activities From Unapproved Accounts +action.correlationsearch.label = ESCU - Detect AWS API Activities From Unapproved Accounts - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -1538,7 +1538,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect AWS Console Login by User from New City +action.correlationsearch.label = ESCU - Detect AWS Console Login by User from New City - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -1574,7 +1574,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect AWS Console Login by User from New Country +action.correlationsearch.label = ESCU - Detect AWS Console Login by User from New Country - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -1610,7 +1610,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect AWS Console Login by User from New Region +action.correlationsearch.label = ESCU - Detect AWS Console Login by User from New Region - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -1646,7 +1646,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Activity Related to Pass the Hash Attacks +action.correlationsearch.label = ESCU - Detect Activity Related to Pass the Hash Attacks - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -1682,7 +1682,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Credential Dumping through LSASS access +action.correlationsearch.label = ESCU - Detect Credential Dumping through LSASS access - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1721,7 +1721,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect DNS requests to Phishing Sites leveraging EvilGinx2 +action.correlationsearch.label = ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -1762,7 +1762,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Excessive Account Lockouts From Endpoint +action.correlationsearch.label = ESCU - Detect Excessive Account Lockouts From Endpoint - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -1799,7 +1799,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Excessive User Account Lockouts +action.correlationsearch.label = ESCU - Detect Excessive User Account Lockouts - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -1836,7 +1836,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Large Outbound ICMP Packets +action.correlationsearch.label = ESCU - Detect Large Outbound ICMP Packets - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. @@ -1872,7 +1872,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Long DNS TXT Record Response +action.correlationsearch.label = ESCU - Detect Long DNS TXT Record Response - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -1908,7 +1908,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Mimikatz Using Loaded Images +action.correlationsearch.label = ESCU - Detect Mimikatz Using Loaded Images - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1941,7 +1941,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Mimikatz Via PowerShell And EventCode 4703 +action.correlationsearch.label = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -1981,7 +1981,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect New Local Admin account +action.correlationsearch.label = ESCU - Detect New Local Admin account - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -2018,7 +2018,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect New Login Attempts to Routers +action.correlationsearch.label = ESCU - Detect New Login Attempts to Routers - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -2054,7 +2054,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect New Open S3 buckets +action.correlationsearch.label = ESCU - Detect New Open S3 buckets - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -2090,7 +2090,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Oulook exe writing a zip file +action.correlationsearch.label = ESCU - Detect Oulook exe writing a zip file - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -2127,7 +2127,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Outbound SMB Traffic +action.correlationsearch.label = ESCU - Detect Outbound SMB Traffic - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. @@ -2163,7 +2163,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Path Interception By Creation Of program exe +action.correlationsearch.label = ESCU - Detect Path Interception By Creation Of program exe - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -2200,7 +2200,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Prohibited Applications Spawning cmd exe +action.correlationsearch.label = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -2237,7 +2237,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect PsExec With accepteula Flag +action.correlationsearch.label = ESCU - Detect PsExec With accepteula Flag - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -2274,7 +2274,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Rare Executables +action.correlationsearch.label = ESCU - Detect Rare Executables - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -2310,7 +2310,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect S3 access from a new IP +action.correlationsearch.label = ESCU - Detect S3 access from a new IP - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. @@ -2351,7 +2351,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Spike in AWS API Activity +action.correlationsearch.label = ESCU - Detect Spike in AWS API Activity - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -2387,7 +2387,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Spike in Network ACL Activity +action.correlationsearch.label = ESCU - Detect Spike in Network ACL Activity - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -2423,7 +2423,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Spike in S3 Bucket deletion +action.correlationsearch.label = ESCU - Detect Spike in S3 Bucket deletion - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -2459,7 +2459,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Spike in Security Group Activity +action.correlationsearch.label = ESCU - Detect Spike in Security Group Activity - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -2495,7 +2495,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Spike in blocked Outbound Traffic from your AWS +action.correlationsearch.label = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. @@ -2531,7 +2531,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect USB device insertion +action.correlationsearch.label = ESCU - Detect USB device insertion - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -2568,7 +2568,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Unauthorized Assets by MAC address +action.correlationsearch.label = ESCU - Detect Unauthorized Assets by MAC address - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. @@ -2604,7 +2604,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect Use of cmd exe to Launch Script Interpreters +action.correlationsearch.label = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -2641,7 +2641,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect attackers scanning for vulnerable JBoss servers +action.correlationsearch.label = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -2684,7 +2684,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect hosts connecting to dynamic domain providers +action.correlationsearch.label = ESCU - Detect hosts connecting to dynamic domain providers - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. @@ -2720,7 +2720,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect malicious requests to exploit JBoss servers +action.correlationsearch.label = ESCU - Detect malicious requests to exploit JBoss servers - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -2757,7 +2757,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect mshta exe running scripts in command-line arguments +action.correlationsearch.label = ESCU - Detect mshta exe running scripts in command-line arguments - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -2793,7 +2793,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect new API calls from user roles +action.correlationsearch.label = ESCU - Detect new API calls from user roles - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -2829,7 +2829,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect new user AWS Console Login +action.correlationsearch.label = ESCU - Detect new user AWS Console Login - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -2866,7 +2866,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect processes used for System Network Configuration Discovery +action.correlationsearch.label = ESCU - Detect processes used for System Network Configuration Discovery - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -2905,7 +2905,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detect web traffic to dynamic domain providers +action.correlationsearch.label = ESCU - Detect web traffic to dynamic domain providers - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -2942,7 +2942,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detection of DNS Tunnels +action.correlationsearch.label = ESCU - Detection of DNS Tunnels - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['src'] @@ -2979,7 +2979,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Detection of tools built by NirSoft +action.correlationsearch.label = ESCU - Detection of tools built by NirSoft - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -3015,7 +3015,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Disabling Remote User Account Control +action.correlationsearch.label = ESCU - Disabling Remote User Account Control - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -3052,7 +3052,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Dump LSASS via comsvcs DLL +action.correlationsearch.label = ESCU - Dump LSASS via comsvcs DLL - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -3086,7 +3086,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = EC2 Instance Modified With Previously Unseen User +action.correlationsearch.label = ESCU - EC2 Instance Modified With Previously Unseen User - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3122,7 +3122,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = EC2 Instance Started In Previously Unseen Region +action.correlationsearch.label = ESCU - EC2 Instance Started In Previously Unseen Region - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started @@ -3157,7 +3157,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = EC2 Instance Started With Previously Unseen AMI +action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen AMI - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen AMIs. @@ -3192,7 +3192,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = EC2 Instance Started With Previously Unseen Instance Type +action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3228,7 +3228,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = EC2 Instance Started With Previously Unseen User +action.correlationsearch.label = ESCU - EC2 Instance Started With Previously Unseen User - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -3267,7 +3267,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Email Attachments With Lots Of Spaces +action.correlationsearch.label = ESCU - Email Attachments With Lots Of Spaces - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. @@ -3303,7 +3303,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Email files written outside of the Outlook directory +action.correlationsearch.label = ESCU - Email files written outside of the Outlook directory - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -3340,7 +3340,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Email servers sending high volume traffic to hosts +action.correlationsearch.label = ESCU - Email servers sending high volume traffic to hosts - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. @@ -3376,7 +3376,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Excessive DNS Failures +action.correlationsearch.label = ESCU - Excessive DNS Failures - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. @@ -3412,7 +3412,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Execution of File With Spaces Before Extension +action.correlationsearch.label = ESCU - Execution of File With Spaces Before Extension - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3449,7 +3449,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Execution of File with Multiple Extensions +action.correlationsearch.label = ESCU - Execution of File with Multiple Extensions - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3485,7 +3485,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Extended Period Without Successful Netbackup Backups +action.correlationsearch.label = ESCU - Extended Period Without Successful Netbackup Backups - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -3522,7 +3522,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = File with Samsam Extension +action.correlationsearch.label = ESCU - File with Samsam Extension - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3558,7 +3558,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = First Time Seen Running Windows Service +action.correlationsearch.label = ESCU - First Time Seen Running Windows Service - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -3595,7 +3595,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = First time seen command line argument +action.correlationsearch.label = ESCU - First time seen command line argument - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. @@ -3630,7 +3630,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = GCP GCR container uploaded +action.correlationsearch.label = ESCU - GCP GCR container uploaded - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -3666,7 +3666,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = GCP Kubernetes cluster scan detection +action.correlationsearch.label = ESCU - GCP Kubernetes cluster scan detection - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster @@ -3702,7 +3702,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Hiding Files And Directories With Attrib exe +action.correlationsearch.label = ESCU - Hiding Files And Directories With Attrib exe - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -3739,7 +3739,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Hosts receiving high volume of network traffic from email server +action.correlationsearch.label = ESCU - Hosts receiving high volume of network traffic from email server - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. @@ -3774,7 +3774,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Identify New User Accounts +action.correlationsearch.label = ESCU - Identify New User Accounts - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. @@ -3810,7 +3810,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Large Volume of DNS ANY Queries +action.correlationsearch.label = ESCU - Large Volume of DNS ANY Queries - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. @@ -3845,7 +3845,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = MacOS - Re-opened Applications +action.correlationsearch.label = ESCU - MacOS - Re-opened Applications - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3882,7 +3882,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Malicious PowerShell Process - Connect To Internet With Hidden Window +action.correlationsearch.label = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3919,7 +3919,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Malicious PowerShell Process - Encoded Command +action.correlationsearch.label = ESCU - Malicious PowerShell Process - Encoded Command - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -3956,7 +3956,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Malicious PowerShell Process - Execution Policy Bypass +action.correlationsearch.label = ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -3993,7 +3993,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments +action.correlationsearch.label = ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4030,7 +4030,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Malicious PowerShell Process With Obfuscation Techniques +action.correlationsearch.label = ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4067,7 +4067,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Monitor DNS For Brand Abuse +action.correlationsearch.label = ESCU - Monitor DNS For Brand Abuse - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. @@ -4103,7 +4103,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Monitor Email For Brand Abuse +action.correlationsearch.label = ESCU - Monitor Email For Brand Abuse - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. @@ -4138,7 +4138,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Monitor Registry Keys for Print Monitors +action.correlationsearch.label = ESCU - Monitor Registry Keys for Print Monitors - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -4175,7 +4175,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Monitor Web Traffic For Brand Abuse +action.correlationsearch.label = ESCU - Monitor Web Traffic For Brand Abuse - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['src'] @@ -4211,7 +4211,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Multiple Okta Users With Invalid Credentails From The Same IP +action.correlationsearch.label = ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. @@ -4246,7 +4246,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = New container uploaded to AWS ECR +action.correlationsearch.label = ESCU - New container uploaded to AWS ECR - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'src'] @@ -4283,7 +4283,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = No Windows Updates in a time frame +action.correlationsearch.label = ESCU - No Windows Updates in a time frame - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -4319,7 +4319,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Okta Account Lockout Events +action.correlationsearch.label = ESCU - Okta Account Lockout Events - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = Detect Okta user lockout events @@ -4354,7 +4354,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Okta Failed SSO Attempts +action.correlationsearch.label = ESCU - Okta Failed SSO Attempts - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = Detect failed Okta SSO events @@ -4389,7 +4389,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Okta User Logins From Multiple Cities +action.correlationsearch.label = ESCU - Okta User Logins From Multiple Cities - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -4425,7 +4425,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Open Redirect in Splunk Web +action.correlationsearch.label = ESCU - Open Redirect in Splunk Web - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. @@ -4460,7 +4460,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Osquery pack - ColdRoot detection +action.correlationsearch.label = ESCU - Osquery pack - ColdRoot detection - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for ColdRoot events from the osx-attacks osquery pack. @@ -4496,7 +4496,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Overwriting Accessibility Binaries +action.correlationsearch.label = ESCU - Overwriting Accessibility Binaries - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4532,7 +4532,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Process Execution via WMI +action.correlationsearch.label = ESCU - Process Execution via WMI - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4568,7 +4568,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Processes Tapping Keyboard Events +action.correlationsearch.label = ESCU - Processes Tapping Keyboard Events - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input @@ -4604,7 +4604,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Processes created by netsh +action.correlationsearch.label = ESCU - Processes created by netsh - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4641,7 +4641,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Processes launching netsh +action.correlationsearch.label = ESCU - Processes launching netsh - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4678,7 +4678,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Prohibited Network Traffic Allowed +action.correlationsearch.label = ESCU - Prohibited Network Traffic Allowed - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. @@ -4714,7 +4714,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Prohibited Software On Endpoint +action.correlationsearch.label = ESCU - Prohibited Software On Endpoint - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4751,7 +4751,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Protocol or Port Mismatch +action.correlationsearch.label = ESCU - Protocol or Port Mismatch - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. @@ -4787,7 +4787,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Protocols passing authentication in cleartext +action.correlationsearch.label = ESCU - Protocols passing authentication in cleartext - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest', 'src'] @@ -4823,7 +4823,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Reg exe Manipulating Windows Services Registry Keys +action.correlationsearch.label = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -4860,7 +4860,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Reg exe used to hide files directories via registry keys +action.correlationsearch.label = ESCU - Reg exe used to hide files directories via registry keys - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -4896,7 +4896,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Registry Keys Used For Persistence +action.correlationsearch.label = ESCU - Registry Keys Used For Persistence - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4932,7 +4932,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Registry Keys Used For Privilege Escalation +action.correlationsearch.label = ESCU - Registry Keys Used For Privilege Escalation - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -4968,7 +4968,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Registry Keys for Creating SHIM Databases +action.correlationsearch.label = ESCU - Registry Keys for Creating SHIM Databases - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. @@ -5004,7 +5004,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Remote Desktop Network Bruteforce +action.correlationsearch.label = ESCU - Remote Desktop Network Bruteforce - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -5041,7 +5041,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Remote Desktop Network Traffic +action.correlationsearch.label = ESCU - Remote Desktop Network Traffic - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -5078,7 +5078,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Remote Desktop Process Running On System +action.correlationsearch.label = ESCU - Remote Desktop Process Running On System - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5115,7 +5115,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Remote Process Instantiation via WMI +action.correlationsearch.label = ESCU - Remote Process Instantiation via WMI - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5151,7 +5151,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Remote Registry Key modifications +action.correlationsearch.label = ESCU - Remote Registry Key modifications - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5188,7 +5188,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Remote WMI Command Attempt +action.correlationsearch.label = ESCU - Remote WMI Command Attempt - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5225,7 +5225,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = RunDLL Loading DLL By Ordinal +action.correlationsearch.label = ESCU - RunDLL Loading DLL By Ordinal - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5262,7 +5262,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = SMB Traffic Spike +action.correlationsearch.label = ESCU - SMB Traffic Spike - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['src'] @@ -5302,7 +5302,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = SMB Traffic Spike - MLTK +action.correlationsearch.label = ESCU - SMB Traffic Spike - MLTK - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -5339,7 +5339,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = SQL Injection with Long URLs +action.correlationsearch.label = ESCU - SQL Injection with Long URLs - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -5376,7 +5376,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Samsam Test File Write +action.correlationsearch.label = ESCU - Samsam Test File Write - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5413,7 +5413,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Sc exe Manipulating Windows Services +action.correlationsearch.label = ESCU - Sc exe Manipulating Windows Services - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5450,7 +5450,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Scheduled Task Name Used by Dragonfly Threat Actors +action.correlationsearch.label = ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5487,7 +5487,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Scheduled tasks used in BadRabbit ransomware +action.correlationsearch.label = ESCU - Scheduled tasks used in BadRabbit ransomware - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -5524,7 +5524,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Schtasks scheduling job on remote system +action.correlationsearch.label = ESCU - Schtasks scheduling job on remote system - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5561,7 +5561,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Schtasks used for forcing a reboot +action.correlationsearch.label = ESCU - Schtasks used for forcing a reboot - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5597,7 +5597,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Script Execution via WMI +action.correlationsearch.label = ESCU - Script Execution via WMI - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5633,7 +5633,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Shim Database File Creation +action.correlationsearch.label = ESCU - Shim Database File Creation - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -5670,7 +5670,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Shim Database Installation With Suspicious Parameters +action.correlationsearch.label = ESCU - Shim Database Installation With Suspicious Parameters - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5707,7 +5707,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Short Lived Windows Accounts +action.correlationsearch.label = ESCU - Short Lived Windows Accounts - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5744,7 +5744,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Single Letter Process On Endpoint +action.correlationsearch.label = ESCU - Single Letter Process On Endpoint - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for process names that consist only of a single letter. @@ -5780,7 +5780,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Spectre and Meltdown Vulnerable Systems +action.correlationsearch.label = ESCU - Spectre and Meltdown Vulnerable Systems - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. @@ -5815,7 +5815,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Spike in File Writes +action.correlationsearch.label = ESCU - Spike in File Writes - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -5851,7 +5851,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Splunk Enterprise Information Disclosure +action.correlationsearch.label = ESCU - Splunk Enterprise Information Disclosure - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -5887,7 +5887,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious Changes to File Associations +action.correlationsearch.label = ESCU - Suspicious Changes to File Associations - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -5924,7 +5924,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious Email - UBA Anomaly +action.correlationsearch.label = ESCU - Suspicious Email - UBA Anomaly - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -5963,7 +5963,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious Email Attachment Extensions +action.correlationsearch.label = ESCU - Suspicious Email Attachment Extensions - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for emails that have attachments with suspicious file extensions. @@ -5998,7 +5998,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious File Write +action.correlationsearch.label = ESCU - Suspicious File Write - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -6034,7 +6034,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious Java Classes +action.correlationsearch.label = ESCU - Suspicious Java Classes - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] @@ -6070,7 +6070,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious LNK file launching a process +action.correlationsearch.label = ESCU - Suspicious LNK file launching a process - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6106,7 +6106,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious Reg exe Process +action.correlationsearch.label = ESCU - Suspicious Reg exe Process - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6143,7 +6143,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious wevtutil Usage +action.correlationsearch.label = ESCU - Suspicious wevtutil Usage - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -6179,7 +6179,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious writes to System Volume Information +action.correlationsearch.label = ESCU - Suspicious writes to System Volume Information - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search detects writes to the 'System Volume Information' folder by something other than the System process. @@ -6214,7 +6214,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Suspicious writes to windows Recycle Bin +action.correlationsearch.label = ESCU - Suspicious writes to windows Recycle Bin - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6250,7 +6250,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = System Processes Run From Unexpected Locations +action.correlationsearch.label = ESCU - System Processes Run From Unexpected Locations - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6287,7 +6287,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = TOR Traffic +action.correlationsearch.label = ESCU - TOR Traffic - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. @@ -6323,7 +6323,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = USN Journal Deletion +action.correlationsearch.label = ESCU - USN Journal Deletion - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6360,7 +6360,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Uncommon Processes On Endpoint +action.correlationsearch.label = ESCU - Uncommon Processes On Endpoint - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6397,7 +6397,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Unload Sysmon Filter Driver +action.correlationsearch.label = ESCU - Unload Sysmon Filter Driver - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6433,7 +6433,7 @@ cron_schedule = */60 * * * * dispatch.earliest_time = -60m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Unsigned Image Loaded by LSASS +action.correlationsearch.label = ESCU - Unsigned Image Loaded by LSASS - Rule schedule_window = auto action.email.subject.alert = Splunk Alert: $name$ action.email.to = test@test.de @@ -6467,7 +6467,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Unsuccessful Netbackup backups +action.correlationsearch.label = ESCU - Unsuccessful Netbackup backups - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search gives you the hosts where a backup was attempted and then failed. @@ -6502,7 +6502,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Unusually Long Command Line +action.correlationsearch.label = ESCU - Unusually Long Command Line - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6538,7 +6538,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Unusually Long Command Line - MLTK +action.correlationsearch.label = ESCU - Unusually Long Command Line - MLTK - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] @@ -6574,7 +6574,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Unusually Long Content-Type Length +action.correlationsearch.label = ESCU - Unusually Long Content-Type Length - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. @@ -6609,7 +6609,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = WMI Permanent Event Subscription +action.correlationsearch.label = ESCU - WMI Permanent Event Subscription - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -6645,7 +6645,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = WMI Permanent Event Subscription - Sysmon +action.correlationsearch.label = ESCU - WMI Permanent Event Subscription - Sysmon - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -6681,7 +6681,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = WMI Temporary Event Subscription +action.correlationsearch.label = ESCU - WMI Temporary Event Subscription - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for the creation of WMI temporary event subscriptions. @@ -6716,7 +6716,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Web Fraud - Account Harvesting +action.correlationsearch.label = ESCU - Web Fraud - Account Harvesting - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -6752,7 +6752,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Web Fraud - Anomalous User Clickspeed +action.correlationsearch.label = ESCU - Web Fraud - Anomalous User Clickspeed - Rule schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. @@ -6787,7 +6787,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Web Fraud - Password Sharing Across Accounts +action.correlationsearch.label = ESCU - Web Fraud - Password Sharing Across Accounts - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['user'] @@ -6824,7 +6824,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Web Servers Executing Suspicious Processes +action.correlationsearch.label = ESCU - Web Servers Executing Suspicious Processes - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -6860,7 +6860,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Windows Event Log Cleared +action.correlationsearch.label = ESCU - Windows Event Log Cleared - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] @@ -6896,7 +6896,7 @@ cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 -action.correlationsearch.label = Windows hosts file modification +action.correlationsearch.label = ESCU - Windows hosts file modification - Rule schedule_window = auto action.notable = 1 action.notable.param.nes_fields = ['dest'] diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 3f7798e265..ced5fe6487 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T06:52:21 UTC +# On Date: 2020-05-11T07:14:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 5cbba9bc28..12f1c40b9e 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T06:52:21 UTC +# On Date: 2020-05-11T07:14:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] +searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] +searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip"] +searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -374,10 +374,10 @@ narrative = Kubernetes is the most used container orchestration platform, this o category = Adversary Tactics last_updated = 2020-02-04 version = 2 -references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 3c7b2dfc6d756e19defcc2644911a0092acacdbb Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 09:31:35 +0200 Subject: [PATCH 33/93] bug in generate --- bin/jinja2_templates/savedsearches.j2 | 4 +- deployments/deployment_example_2.yml | 17 - package/default/analytic_stories.conf | 120 ++-- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 901 +++++++++++++------------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 128 ++-- 7 files changed, 590 insertions(+), 584 deletions(-) delete mode 100644 deployments/deployment_example_2.yml diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 95de48cd70..4a2a229a33 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -35,7 +35,7 @@ action.escu.search_type = detection {% if detection.providing_technologies is defined %} action.escu.providing_technologies = {{ detection.providing_technologies | tojson }} {% else %} -action.escu.providing_technologies = none +action.escu.providing_technologies = [] {% endif %} {% if detection.tags.analytics_story is defined %} action.escu.analytic_story = {{ detection.tags.analytics_story | tojson }} @@ -55,7 +55,7 @@ action.notable.param.nes_fields = {{ detection.nes_fields }} {% endif %} action.notable.param.rule_description = {{ detection.deployment.alert_action.notable.rule_description | custom_jinja2_enrichment_filter(detection) }} action.notable.param.rule_title = {{ detection.deployment.alert_action.notable.rule_title | custom_jinja2_enrichment_filter(detection) }} -action.notable.param.security_domain = {{ detection.security_domain }} +action.notable.param.security_domain = {{ detection.tags.security_domain }} action.notable.param.severity = medium {% endif %} {% if detection.deployment.alert_action.email is defined %} diff --git a/deployments/deployment_example_2.yml b/deployments/deployment_example_2.yml deleted file mode 100644 index e6408ab6a8..0000000000 --- a/deployments/deployment_example_2.yml +++ /dev/null @@ -1,17 +0,0 @@ -name: Enterprise Security deployment configuration -id: bc91a8cd-35e7-4bb2-6140-e756cc46f212 -date: '2020-04-27' -description: This configuration file applies to all correlation searches that are used for detection -author: Bhavin Patel -scheduling: - cron_schedule: '*/60 * * * *' - earliest_time: -60m - latest_time: now - schedule_window: auto -alert_action: - email: - to: 'test@test.de' - subject: 'Splunk Alert: $name$' - message: 'Splunk Alert $name$ triggered' -tags: - mitre_attack_id: T1003 diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 066a09786a..63488ac6ae 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:14:19 UTC +# On Date: 2020-05-11T07:31:11 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 3e3556041d..ac2e3b18f5 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:14:19 UTC +# On Date: 2020-05-11T07:31:11 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 95c6f8579d..ab305181e8 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:14:19 UTC +# On Date: 2020-05-11T07:31:11 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -21,7 +21,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -33,7 +33,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen City -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -58,7 +58,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -70,7 +70,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Country -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -95,7 +95,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -107,7 +107,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen IP Address -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -132,7 +132,7 @@ action.escu.modification_date = 2018-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -144,7 +144,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Region -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -168,7 +168,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Cross Account Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -180,7 +180,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. action.notable.param.rule_title = AWS Cross Account Activity From Previously Unseen Account -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -204,7 +204,7 @@ action.escu.modification_date = 2017-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Network Access Control List Created with All Open Ports - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Network ACL Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -216,7 +216,7 @@ action.notable = 1 action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. action.notable.param.rule_title = AWS Network Access Control List Created with All Open Ports -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -240,7 +240,7 @@ action.escu.modification_date = 2017-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - AWS Network Access Control List Deleted - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Network ACL Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -252,7 +252,7 @@ action.notable = 1 action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. action.notable.param.rule_title = AWS Network Access Control List Deleted -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -276,7 +276,7 @@ action.escu.modification_date = 2018-02-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -287,7 +287,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.notable.param.rule_title = Abnormally High AWS Instances Launched by User -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -311,7 +311,7 @@ action.escu.modification_date = 2019-11-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -323,7 +323,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.notable.param.rule_title = Abnormally High AWS Instances Launched by User - MLTK -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -347,7 +347,7 @@ action.escu.modification_date = 2018-02-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -358,7 +358,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -382,7 +382,7 @@ action.escu.modification_date = 2019-11-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -394,7 +394,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User - MLTK -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -418,18 +418,20 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Access LSASS Memory for Dump Creation - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Access LSASS Memory for Dump Creation - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = Detect memory dumping of the LSASS process. +action.notable.param.rule_title = Access LSASS Memory for Dump Creation +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -452,7 +454,7 @@ action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Amazon EKS Kubernetes Pod scan detection - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Kubernetes Scanning Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -463,7 +465,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.notable.param.rule_title = Amazon EKS Kubernetes Pod scan detection -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -487,7 +489,7 @@ action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Amazon EKS Kubernetes cluster scan detection - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Kubernetes Scanning Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -498,7 +500,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.notable.param.rule_title = Amazon EKS Kubernetes cluster scan detection -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -523,7 +525,7 @@ action.escu.modification_date = 2018-11-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Add Certificate To Untrusted Store - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -535,7 +537,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = Attempt to add a certificate to the untrusted certificate store action.notable.param.rule_title = Attempt To Add Certificate To Untrusted Store -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -560,7 +562,7 @@ action.escu.modification_date = 2019-12-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping", "Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -572,7 +574,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.notable.param.rule_title = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -597,7 +599,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Stop Security Service - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -609,7 +611,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for attempts to stop security-related services on the endpoint. action.notable.param.rule_title = Attempt To Stop Security Service -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -634,18 +636,20 @@ action.escu.modification_date = 2019-12-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Attempted Credential Dump From Registry via Reg exe - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. +action.notable.param.rule_title = Attempted Credential Dump From Registry via Reg exe +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -669,7 +673,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Batch File Write to System32 - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -681,7 +685,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for a batch file (.bat) written to the Windows system directory tree. action.notable.param.rule_title = Batch File Write to System32 -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -706,7 +710,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Child Processes of Spoolsv exe - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Privilege Escalation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -718,7 +722,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.notable.param.rule_title = Child Processes of Spoolsv exe -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -745,7 +749,7 @@ action.escu.modification_date = 2020-01-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Clients Connecting to Multiple DNS Servers - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -757,7 +761,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.notable.param.rule_title = Clients Connecting to Multiple DNS Servers -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -782,7 +786,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -794,7 +798,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for cloud compute instances created by users who have not created them before. action.notable.param.rule_title = Cloud Compute Instance Created By Previously Unseen User -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -819,7 +823,7 @@ action.escu.modification_date = 2018-10-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -831,7 +835,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for cloud compute instances being created with previously unseen image IDs. action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Image -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -856,7 +860,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -868,7 +872,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Find EC2 instances being created with previously unseen instance types. action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Instance Type -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -893,7 +897,7 @@ action.escu.modification_date = 2019-10-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Cloud Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -905,7 +909,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.notable.param.rule_title = Cloud Compute Instance Started In Previously Unused Region -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -934,7 +938,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Common Ransomware Extensions - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -946,7 +950,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for file modifications with extensions commonly used by Ransomware action.notable.param.rule_title = Common Ransomware Extensions -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -971,7 +975,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Common Ransomware Notes - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -983,7 +987,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.notable.param.rule_title = Common Ransomware Notes -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1007,18 +1011,20 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Create Remote Thread into LSASS - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Create Remote Thread into LSASS - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = Detect remote thread creation into LSASS consistent with credential dumping. +action.notable.param.rule_title = Create Remote Thread into LSASS +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1042,7 +1048,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Create local admin accounts using net exe - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1054,7 +1060,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the creation of local administrator accounts using net.exe. action.notable.param.rule_title = Create local admin accounts using net exe -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1079,7 +1085,7 @@ action.escu.modification_date = 2020-01-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Create or delete windows shares using net exe - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1091,7 +1097,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the creation or deletion of hidden shares using net.exe. action.notable.param.rule_title = Create or delete windows shares using net exe -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1116,18 +1122,20 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Creation of Shadow Copy - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Creation of Shadow Copy - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. +action.notable.param.rule_title = Creation of Shadow Copy +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1150,18 +1158,20 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Creation of Shadow Copy with wmic and powershell - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Creation of Shadow Copy with wmic and powershell - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search detects the use of wmic and Powershell to create a shadow copy. +action.notable.param.rule_title = Creation of Shadow Copy with wmic and powershell +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1185,18 +1195,20 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects credential dumping using copy command from a shadow copy. +action.notable.param.rule_title = Credential Dumping via Copy Command from Shadow Copy +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1220,18 +1232,20 @@ action.escu.modification_date = 2019-12-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Credential Dumping via Symlink to Shadow Copy - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = This search detects the creation of a symlink to a shadow copy. +action.notable.param.rule_title = Credential Dumping via Symlink to Shadow Copy +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1261,7 +1275,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length Outliers - MLTK - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1273,7 +1287,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.notable.param.rule_title = DNS Query Length Outliers - MLTK -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1298,7 +1312,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length With High Standard Deviation - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1309,7 +1323,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.notable.param.rule_title = DNS Query Length With High Standard Deviation -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1334,7 +1348,7 @@ action.escu.modification_date = 2020-01-17 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1346,7 +1360,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.notable.param.rule_title = DNS Query Requests Resolved by Unauthorized DNS Servers -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1375,7 +1389,7 @@ action.escu.modification_date = 2020-01-16 action.escu.confidence = high action.escu.full_search_name = ESCU - DNS record changed - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1387,7 +1401,7 @@ action.notable = 1 action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.notable.param.rule_title = DNS record changed -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1412,7 +1426,7 @@ action.escu.modification_date = 2020-04-17 action.escu.confidence = high action.escu.full_search_name = ESCU - Deleting Shadow Copies - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1424,7 +1438,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.notable.param.rule_title = Deleting Shadow Copies -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1454,7 +1468,7 @@ action.escu.modification_date = 2018-05-17 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect API activity from users without MFA - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1466,7 +1480,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. action.notable.param.rule_title = Detect API activity from users without MFA -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1496,7 +1510,7 @@ action.escu.modification_date = 2018-03-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS API Activities From Unapproved Accounts - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1508,7 +1522,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. action.notable.param.rule_title = Detect AWS API Activities From Unapproved Accounts -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1532,7 +1546,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New City - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1544,7 +1558,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect AWS Console Login by User from New City -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1568,7 +1582,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Country - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1580,7 +1594,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect AWS Console Login by User from New Country -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1604,7 +1618,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect AWS Console Login by User from New Region - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1616,7 +1630,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect AWS Console Login by User from New Region -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1640,7 +1654,7 @@ action.escu.modification_date = 2020-01-09 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Activity Related to Pass the Hash Attacks - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1652,7 +1666,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. action.notable.param.rule_title = Detect Activity Related to Pass the Hash Attacks -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1676,18 +1690,20 @@ action.escu.modification_date = 2019-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Credential Dumping through LSASS access - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Credential Dumping through LSASS access - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for reading lsass memory consistent with credential dumping. +action.notable.param.rule_title = Detect Credential Dumping through LSASS access +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1715,7 +1731,7 @@ action.escu.modification_date = 2019-04-29 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Common Phishing Frameworks"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1727,7 +1743,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.notable.param.rule_title = Detect DNS requests to Phishing Sites leveraging EvilGinx2 -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1756,7 +1772,7 @@ action.escu.modification_date = 2019-04-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Excessive Account Lockouts From Endpoint - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1768,7 +1784,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.notable.param.rule_title = Detect Excessive Account Lockouts From Endpoint -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1793,7 +1809,7 @@ action.escu.modification_date = 2019-03-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Excessive User Account Lockouts - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1805,7 +1821,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.notable.param.rule_title = Detect Excessive User Account Lockouts -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1830,7 +1846,7 @@ action.escu.modification_date = 2018-06-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Large Outbound ICMP Packets - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1841,7 +1857,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.notable.param.rule_title = Detect Large Outbound ICMP Packets -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1866,7 +1882,7 @@ action.escu.modification_date = 2017-09-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Long DNS TXT Record Response - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1878,7 +1894,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.notable.param.rule_title = Detect Long DNS TXT Record Response -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -1902,18 +1918,20 @@ action.escu.modification_date = 2019-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Mimikatz Using Loaded Images - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Mimikatz Using Loaded Images - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. +action.notable.param.rule_title = Detect Mimikatz Using Loaded Images +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1936,17 +1954,18 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule action.escu.search_type = detection -action.escu.providing_technologies = none -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +action.escu.providing_technologies = [] +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.rule_description = This search looks for PowerShell requesting privileges consistent with credential dumping. +action.notable.param.rule_title = Detect Mimikatz Via PowerShell And EventCode 4703 +action.notable.param.security_domain = access +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -1975,7 +1994,7 @@ action.escu.modification_date = 2019-02-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Local Admin account - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -1987,7 +2006,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for newly created accounts that have been elevated to local administrators. action.notable.param.rule_title = Detect New Local Admin account -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2012,7 +2031,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Login Attempts to Routers - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Router and Infrastructure Security"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2024,7 +2043,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.notable.param.rule_title = Detect New Login Attempts to Routers -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2048,7 +2067,7 @@ action.escu.modification_date = 2018-07-25 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect New Open S3 buckets - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS S3 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2060,7 +2079,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. action.notable.param.rule_title = Detect New Open S3 buckets -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2084,7 +2103,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Oulook exe writing a zip file - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Phishing Payloads"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2096,7 +2115,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. action.notable.param.rule_title = Detect Oulook exe writing a zip file -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2121,7 +2140,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Outbound SMB Traffic - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2132,7 +2151,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.notable.param.rule_title = Detect Outbound SMB Traffic -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2157,7 +2176,7 @@ action.escu.modification_date = 2018-11-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Path Interception By Creation Of program exe - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2169,7 +2188,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.notable.param.rule_title = Detect Path Interception By Creation Of program exe -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2194,7 +2213,7 @@ action.escu.modification_date = 2020-02-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2206,7 +2225,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.notable.param.rule_title = Detect Prohibited Applications Spawning cmd exe -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2231,7 +2250,7 @@ action.escu.modification_date = 2019-02-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect PsExec With accepteula Flag - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2243,7 +2262,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.notable.param.rule_title = Detect PsExec With accepteula Flag -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2268,7 +2287,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Rare Executables - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2280,7 +2299,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.notable.param.rule_title = Detect Rare Executables -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2304,7 +2323,7 @@ action.escu.modification_date = 2018-06-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect S3 access from a new IP - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS S3 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2315,7 +2334,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. action.notable.param.rule_title = Detect S3 access from a new IP -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2345,7 +2364,7 @@ action.escu.modification_date = 2018-04-09 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in AWS API Activity - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2357,7 +2376,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in AWS API Activity -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2381,7 +2400,7 @@ action.escu.modification_date = 2018-05-21 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in Network ACL Activity - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Network ACL Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2393,7 +2412,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. action.notable.param.rule_title = Detect Spike in Network ACL Activity -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2417,7 +2436,7 @@ action.escu.modification_date = 2018-11-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in S3 Bucket deletion - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS S3 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2429,7 +2448,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in S3 Bucket deletion -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2453,7 +2472,7 @@ action.escu.modification_date = 2018-04-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in Security Group Activity - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2465,7 +2484,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in Security Group Activity -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2489,7 +2508,7 @@ action.escu.modification_date = 2018-05-07 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2500,7 +2519,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in blocked Outbound Traffic from your AWS -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2525,7 +2544,7 @@ action.escu.modification_date = 2017-11-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect USB device insertion - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Data Protection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2537,7 +2556,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.notable.param.rule_title = Detect USB device insertion -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2562,7 +2581,7 @@ action.escu.modification_date = 2017-09-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Unauthorized Assets by MAC address - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Asset Tracking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2573,7 +2592,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.notable.param.rule_title = Detect Unauthorized Assets by MAC address -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2598,7 +2617,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2610,7 +2629,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.notable.param.rule_title = Detect Use of cmd exe to Launch Script Interpreters -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2635,7 +2654,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2647,7 +2666,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.notable.param.rule_title = Detect attackers scanning for vulnerable JBoss servers -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2678,7 +2697,7 @@ action.escu.modification_date = 2020-01-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect hosts connecting to dynamic domain providers - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2689,7 +2708,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.notable.param.rule_title = Detect hosts connecting to dynamic domain providers -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2714,7 +2733,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect malicious requests to exploit JBoss servers - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2726,7 +2745,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.notable.param.rule_title = Detect malicious requests to exploit JBoss servers -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2751,7 +2770,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect mshta exe running scripts in command-line arguments - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious MSHTA Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2763,7 +2782,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.notable.param.rule_title = Detect mshta exe running scripts in command-line arguments -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2787,7 +2806,7 @@ action.escu.modification_date = 2018-04-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect new API calls from user roles - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS User Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2799,7 +2818,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. action.notable.param.rule_title = Detect new API calls from user roles -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2823,7 +2842,7 @@ action.escu.modification_date = 2018-04-30 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect new user AWS Console Login - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS Login Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2835,7 +2854,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect new user AWS Console Login -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2860,7 +2879,7 @@ action.escu.modification_date = 2018-11-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect processes used for System Network Configuration Discovery - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2872,7 +2891,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.notable.param.rule_title = Detect processes used for System Network Configuration Discovery -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2899,7 +2918,7 @@ action.escu.modification_date = 2018-09-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Detect web traffic to dynamic domain providers - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Dynamic DNS"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2911,7 +2930,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for web connections to dynamic DNS providers. action.notable.param.rule_title = Detect web traffic to dynamic domain providers -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2936,7 +2955,7 @@ action.escu.modification_date = 2017-09-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of DNS Tunnels - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Data Protection", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2948,7 +2967,7 @@ action.notable = 1 action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.notable.param.rule_title = Detection of DNS Tunnels -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -2973,7 +2992,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of tools built by NirSoft - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -2985,7 +3004,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.notable.param.rule_title = Detection of tools built by NirSoft -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3009,7 +3028,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Disabling Remote User Account Control - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3021,7 +3040,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). action.notable.param.rule_title = Disabling Remote User Account Control -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3046,18 +3065,20 @@ action.escu.modification_date = 2020-02-21 action.escu.confidence = high action.escu.full_search_name = ESCU - Dump LSASS via comsvcs DLL - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Dump LSASS via comsvcs DLL - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['user', 'dest'] +action.notable.param.rule_description = Detect the usage of comsvcs.dll for dumping the lsass process. +action.notable.param.rule_title = Dump LSASS via comsvcs DLL +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -3080,7 +3101,7 @@ action.escu.modification_date = 2018-04-09 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Modified With Previously Unseen User - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3092,7 +3113,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for EC2 instances being modified by users who have not previously modified them. action.notable.param.rule_title = EC2 Instance Modified With Previously Unseen User -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3116,7 +3137,7 @@ action.escu.modification_date = 2018-02-23 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started In Previously Unseen Region - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3127,7 +3148,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started action.notable.param.rule_title = EC2 Instance Started In Previously Unseen Region -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3151,7 +3172,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen AMI - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3162,7 +3183,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen AMIs. action.notable.param.rule_title = EC2 Instance Started With Previously Unseen AMI -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3186,7 +3207,7 @@ action.escu.modification_date = 2020-02-07 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3198,7 +3219,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen instance types. action.notable.param.rule_title = EC2 Instance Started With Previously Unseen Instance Type -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3222,7 +3243,7 @@ action.escu.modification_date = 2018-03-12 action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen User - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3234,7 +3255,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for EC2 instances being created by users who have not created them before. action.notable.param.rule_title = EC2 Instance Started With Previously Unseen User -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3261,7 +3282,7 @@ action.escu.modification_date = 2017-09-19 action.escu.confidence = high action.escu.full_search_name = ESCU - Email Attachments With Lots Of Spaces - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3272,7 +3293,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.notable.param.rule_title = Email Attachments With Lots Of Spaces -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3297,7 +3318,7 @@ action.escu.modification_date = 2020-03-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Email files written outside of the Outlook directory - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3309,7 +3330,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.notable.param.rule_title = Email files written outside of the Outlook directory -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3334,7 +3355,7 @@ action.escu.modification_date = 2017-12-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Email servers sending high volume traffic to hosts - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3345,7 +3366,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.notable.param.rule_title = Email servers sending high volume traffic to hosts -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3370,7 +3391,7 @@ action.escu.modification_date = 2017-09-18 action.escu.confidence = high action.escu.full_search_name = ESCU - Excessive DNS Failures - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3381,7 +3402,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.notable.param.rule_title = Excessive DNS Failures -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3406,7 +3427,7 @@ action.escu.modification_date = 2018-01-26 action.escu.confidence = high action.escu.full_search_name = ESCU - Execution of File With Spaces Before Extension - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows File Extension and Association Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3418,7 +3439,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.notable.param.rule_title = Execution of File With Spaces Before Extension -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3443,7 +3464,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Execution of File with Multiple Extensions - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows File Extension and Association Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3455,7 +3476,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.notable.param.rule_title = Execution of File with Multiple Extensions -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3479,7 +3500,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Extended Period Without Successful Netbackup Backups - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Monitor Backup Solution"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3491,7 +3512,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search returns a list of hosts that have not successfully completed a backup in over a week. action.notable.param.rule_title = Extended Period Without Successful Netbackup Backups -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3516,7 +3537,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - File with Samsam Extension - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3528,7 +3549,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.notable.param.rule_title = File with Samsam Extension -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3552,7 +3573,7 @@ action.escu.modification_date = 2020-01-13 action.escu.confidence = high action.escu.full_search_name = ESCU - First Time Seen Running Windows Service - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3564,7 +3585,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for the first time a Windows service is seen running in your environment. action.notable.param.rule_title = First Time Seen Running Windows Service -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3589,7 +3610,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - First time seen command line argument - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3600,7 +3621,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.notable.param.rule_title = First time seen command line argument -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3624,7 +3645,7 @@ action.escu.modification_date = 2020-02-20 action.escu.confidence = high action.escu.full_search_name = ESCU - GCP GCR container uploaded - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3636,7 +3657,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. action.notable.param.rule_title = GCP GCR container uploaded -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3660,7 +3681,7 @@ action.escu.modification_date = 2020-04-15 action.escu.confidence = high action.escu.full_search_name = ESCU - GCP Kubernetes cluster scan detection - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Kubernetes Scanning Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3671,7 +3692,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.notable.param.rule_title = GCP Kubernetes cluster scan detection -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3696,7 +3717,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Hiding Files And Directories With Attrib exe - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3708,7 +3729,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.notable.param.rule_title = Hiding Files And Directories With Attrib exe -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3733,7 +3754,7 @@ action.escu.modification_date = 2017-12-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Hosts receiving high volume of network traffic from email server - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3744,7 +3765,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.notable.param.rule_title = Hosts receiving high volume of network traffic from email server -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3768,7 +3789,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Identify New User Accounts - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3779,7 +3800,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. action.notable.param.rule_title = Identify New User Accounts -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3804,7 +3825,7 @@ action.escu.modification_date = 2017-09-20 action.escu.confidence = high action.escu.full_search_name = ESCU - Large Volume of DNS ANY Queries - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DNS Amplification Attacks"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3815,7 +3836,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.notable.param.rule_title = Large Volume of DNS ANY Queries -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3840,7 +3861,7 @@ action.escu.modification_date = 2020-02-07 action.escu.confidence = high action.escu.full_search_name = ESCU - MacOS - Re-opened Applications - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3851,7 +3872,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.notable.param.rule_title = MacOS - Re-opened Applications -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3876,7 +3897,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3888,7 +3909,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.notable.param.rule_title = Malicious PowerShell Process - Connect To Internet With Hidden Window -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3913,7 +3934,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Encoded Command - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3925,7 +3946,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.notable.param.rule_title = Malicious PowerShell Process - Encoded Command -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3950,7 +3971,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3962,7 +3983,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.notable.param.rule_title = Malicious PowerShell Process - Execution Policy Bypass -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -3987,7 +4008,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -3999,7 +4020,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.notable.param.rule_title = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4024,7 +4045,7 @@ action.escu.modification_date = 2020-01-17 action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4036,7 +4057,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.notable.param.rule_title = Malicious PowerShell Process With Obfuscation Techniques -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4061,7 +4082,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor DNS For Brand Abuse - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Brand Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4072,7 +4093,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.notable.param.rule_title = Monitor DNS For Brand Abuse -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4097,7 +4118,7 @@ action.escu.modification_date = 2018-01-05 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Email For Brand Abuse - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Emails", "Brand Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4108,7 +4129,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.notable.param.rule_title = Monitor Email For Brand Abuse -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4132,7 +4153,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Registry Keys for Print Monitors - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4144,7 +4165,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. action.notable.param.rule_title = Monitor Registry Keys for Print Monitors -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4169,7 +4190,7 @@ action.escu.modification_date = 2017-09-23 action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Web Traffic For Brand Abuse - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Brand Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4181,7 +4202,7 @@ action.notable = 1 action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.notable.param.rule_title = Monitor Web Traffic For Brand Abuse -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4205,7 +4226,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4216,7 +4237,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. action.notable.param.rule_title = Multiple Okta Users With Invalid Credentails From The Same IP -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4240,7 +4261,7 @@ action.escu.modification_date = 2020-02-20 action.escu.confidence = high action.escu.full_search_name = ESCU - New container uploaded to AWS ECR - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4252,7 +4273,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'src'] action.notable.param.rule_description = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. action.notable.param.rule_title = New container uploaded to AWS ECR -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4277,7 +4298,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - No Windows Updates in a time frame - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Monitor for Updates"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4289,7 +4310,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.notable.param.rule_title = No Windows Updates in a time frame -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4313,7 +4334,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta Account Lockout Events - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4324,7 +4345,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = Detect Okta user lockout events action.notable.param.rule_title = Okta Account Lockout Events -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4348,7 +4369,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta Failed SSO Attempts - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4359,7 +4380,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = Detect failed Okta SSO events action.notable.param.rule_title = Okta Failed SSO Attempts -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4383,7 +4404,7 @@ action.escu.modification_date = 2020-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Okta User Logins From Multiple Cities - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Okta Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4395,7 +4416,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects logins from the same user from different states in a 24 hour period. action.notable.param.rule_title = Okta User Logins From Multiple Cities -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4419,7 +4440,7 @@ action.escu.modification_date = 2017-09-19 action.escu.confidence = high action.escu.full_search_name = ESCU - Open Redirect in Splunk Web - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Splunk Enterprise Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4430,7 +4451,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.notable.param.rule_title = Open Redirect in Splunk Web -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4454,7 +4475,7 @@ action.escu.modification_date = 2019-01-29 action.escu.confidence = high action.escu.full_search_name = ESCU - Osquery pack - ColdRoot detection - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["ColdRoot MacOS RAT"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4465,7 +4486,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for ColdRoot events from the osx-attacks osquery pack. action.notable.param.rule_title = Osquery pack - ColdRoot detection -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4490,7 +4511,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Overwriting Accessibility Binaries - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Privilege Escalation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4502,7 +4523,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.notable.param.rule_title = Overwriting Accessibility Binaries -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4526,7 +4547,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Process Execution via WMI - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4538,7 +4559,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launched via WMI. action.notable.param.rule_title = Process Execution via WMI -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4562,7 +4583,7 @@ action.escu.modification_date = 2019-01-25 action.escu.confidence = high action.escu.full_search_name = ESCU - Processes Tapping Keyboard Events - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["ColdRoot MacOS RAT"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4573,7 +4594,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input action.notable.param.rule_title = Processes Tapping Keyboard Events -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4598,7 +4619,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Processes created by netsh - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Netsh Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4610,7 +4631,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.notable.param.rule_title = Processes created by netsh -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4635,7 +4656,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Processes launching netsh - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4647,7 +4668,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.notable.param.rule_title = Processes launching netsh -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4672,7 +4693,7 @@ action.escu.modification_date = 2017-09-11 action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Network Traffic Allowed - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4683,7 +4704,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.notable.param.rule_title = Prohibited Network Traffic Allowed -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4708,7 +4729,7 @@ action.escu.modification_date = 2019-10-11 action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Software On Endpoint - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4720,7 +4741,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as prohibited. action.notable.param.rule_title = Prohibited Software On Endpoint -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4745,7 +4766,7 @@ action.escu.modification_date = 2017-09-11 action.escu.confidence = high action.escu.full_search_name = ESCU - Protocol or Port Mismatch - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4756,7 +4777,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.notable.param.rule_title = Protocol or Port Mismatch -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4781,7 +4802,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Protocols passing authentication in cleartext - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Use of Cleartext Protocols"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4793,7 +4814,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest', 'src'] action.notable.param.rule_description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.notable.param.rule_title = Protocols passing authentication in cleartext -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4817,7 +4838,7 @@ action.escu.modification_date = 2019-03-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Service Abuse", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4829,7 +4850,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.notable.param.rule_title = Reg exe Manipulating Windows Services Registry Keys -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4854,7 +4875,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe used to hide files directories via registry keys - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4866,7 +4887,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.notable.param.rule_title = Reg exe used to hide files directories via registry keys -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4890,7 +4911,7 @@ action.escu.modification_date = 2017-10-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Persistence - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4902,7 +4923,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. action.notable.param.rule_title = Registry Keys Used For Persistence -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4926,7 +4947,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Privilege Escalation - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4938,7 +4959,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. action.notable.param.rule_title = Registry Keys Used For Privilege Escalation -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4962,7 +4983,7 @@ action.escu.modification_date = 2017-09-15 action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys for Creating SHIM Databases - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -4973,7 +4994,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. action.notable.param.rule_title = Registry Keys for Creating SHIM Databases -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -4998,7 +5019,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Bruteforce - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5010,7 +5031,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.notable.param.rule_title = Remote Desktop Network Bruteforce -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5035,7 +5056,7 @@ action.escu.modification_date = 2020-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Traffic - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5047,7 +5068,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.notable.param.rule_title = Remote Desktop Network Traffic -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5072,7 +5093,7 @@ action.escu.modification_date = 2020-01-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Process Running On System - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5084,7 +5105,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.notable.param.rule_title = Remote Desktop Process Running On System -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5109,7 +5130,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Process Instantiation via WMI - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious WMI Use", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5121,7 +5142,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.notable.param.rule_title = Remote Process Instantiation via WMI -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5145,7 +5166,7 @@ action.escu.modification_date = 2020-03-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Registry Key modifications - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5157,7 +5178,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search monitors for remote modifications to registry keys. action.notable.param.rule_title = Remote Registry Key modifications -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5182,7 +5203,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Remote WMI Command Attempt - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5194,7 +5215,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.notable.param.rule_title = Remote WMI Command Attempt -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5219,7 +5240,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - RunDLL Loading DLL By Ordinal - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5231,7 +5252,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.notable.param.rule_title = RunDLL Loading DLL By Ordinal -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5256,7 +5277,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5268,7 +5289,7 @@ action.notable = 1 action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.notable.param.rule_title = SMB Traffic Spike -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5296,7 +5317,7 @@ action.escu.modification_date = 2020-01-22 action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - MLTK - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5308,7 +5329,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.notable.param.rule_title = SMB Traffic Spike - MLTK -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5333,7 +5354,7 @@ action.escu.modification_date = 2017-09-19 action.escu.confidence = high action.escu.full_search_name = ESCU - SQL Injection with Long URLs - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SQL Injection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5345,7 +5366,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for long URLs that have several SQL commands visible within them. action.notable.param.rule_title = SQL Injection with Long URLs -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5370,7 +5391,7 @@ action.escu.modification_date = 2018-12-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Samsam Test File Write - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5382,7 +5403,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.notable.param.rule_title = Samsam Test File Write -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5407,7 +5428,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Sc exe Manipulating Windows Services - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5419,7 +5440,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.notable.param.rule_title = Sc exe Manipulating Windows Services -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5444,7 +5465,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5456,7 +5477,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.notable.param.rule_title = Scheduled Task Name Used by Dragonfly Threat Actors -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5481,7 +5502,7 @@ action.escu.modification_date = 2019-02-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Scheduled tasks used in BadRabbit ransomware - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5493,7 +5514,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.notable.param.rule_title = Scheduled tasks used in BadRabbit ransomware -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5518,7 +5539,7 @@ action.escu.modification_date = 2020-01-10 action.escu.confidence = high action.escu.full_search_name = ESCU - Schtasks scheduling job on remote system - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5530,7 +5551,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.notable.param.rule_title = Schtasks scheduling job on remote system -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5555,7 +5576,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Schtasks used for forcing a reboot - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Persistence Techniques", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5567,7 +5588,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.notable.param.rule_title = Schtasks used for forcing a reboot -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5591,7 +5612,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Script Execution via WMI - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5603,7 +5624,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for scripts launched via WMI. action.notable.param.rule_title = Script Execution via WMI -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5627,7 +5648,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Shim Database File Creation - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5639,7 +5660,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.notable.param.rule_title = Shim Database File Creation -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5664,7 +5685,7 @@ action.escu.modification_date = 2019-03-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Shim Database Installation With Suspicious Parameters - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5676,7 +5697,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.notable.param.rule_title = Shim Database Installation With Suspicious Parameters -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5701,7 +5722,7 @@ action.escu.modification_date = 2018-01-05 action.escu.confidence = high action.escu.full_search_name = ESCU - Short Lived Windows Accounts - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Account Monitoring and Controls"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5713,7 +5734,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects accounts that were created and deleted in a short time period. action.notable.param.rule_title = Short Lived Windows Accounts -action.notable.param.security_domain = +action.notable.param.security_domain = access action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5738,7 +5759,7 @@ action.escu.modification_date = 2019-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Single Letter Process On Endpoint - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5749,7 +5770,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for process names that consist only of a single letter. action.notable.param.rule_title = Single Letter Process On Endpoint -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5774,7 +5795,7 @@ action.escu.modification_date = 2017-01-07 action.escu.confidence = high action.escu.full_search_name = ESCU - Spectre and Meltdown Vulnerable Systems - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5785,7 +5806,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.notable.param.rule_title = Spectre and Meltdown Vulnerable Systems -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5809,7 +5830,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Spike in File Writes - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["SamSam Ransomware", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5821,7 +5842,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for a sharp increase in the number of files written to a particular host action.notable.param.rule_title = Spike in File Writes -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5845,7 +5866,7 @@ action.escu.modification_date = 2018-06-14 action.escu.confidence = high action.escu.full_search_name = ESCU - Splunk Enterprise Information Disclosure - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Splunk Enterprise Vulnerability CVE-2018-11409"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5857,7 +5878,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. action.notable.param.rule_title = Splunk Enterprise Information Disclosure -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5881,7 +5902,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Changes to File Associations - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5893,7 +5914,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.notable.param.rule_title = Suspicious Changes to File Associations -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5918,7 +5939,7 @@ action.escu.modification_date = 2019-07-21 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Email - UBA Anomaly - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Emails"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5930,7 +5951,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.notable.param.rule_title = Suspicious Email - UBA Anomaly -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5957,7 +5978,7 @@ action.escu.modification_date = 2020-01-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Email Attachment Extensions - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -5968,7 +5989,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for emails that have attachments with suspicious file extensions. action.notable.param.rule_title = Suspicious Email Attachment Extensions -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -5992,7 +6013,7 @@ action.escu.modification_date = 2019-04-25 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious File Write - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6004,7 +6025,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for files created with names that have been linked to malicious activity. action.notable.param.rule_title = Suspicious File Write -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6028,7 +6049,7 @@ action.escu.modification_date = 2018-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Java Classes - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Apache Struts Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6040,7 +6061,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. action.notable.param.rule_title = Suspicious Java Classes -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6064,7 +6085,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious LNK file launching a process - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Phishing Payloads"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6076,7 +6097,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. action.notable.param.rule_title = Suspicious LNK file launching a process -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6100,7 +6121,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Reg exe Process - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6112,7 +6133,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. action.notable.param.rule_title = Suspicious Reg exe Process -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6137,7 +6158,7 @@ action.escu.modification_date = 2019-02-28 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious wevtutil Usage - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6149,7 +6170,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.notable.param.rule_title = Suspicious wevtutil Usage -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6173,7 +6194,7 @@ action.escu.modification_date = 2018-01-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious writes to System Volume Information - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6184,7 +6205,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search detects writes to the 'System Volume Information' folder by something other than the System process. action.notable.param.rule_title = Suspicious writes to System Volume Information -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6208,7 +6229,7 @@ action.escu.modification_date = 2020-02-03 action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious writes to windows Recycle Bin - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Collection and Staging"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6220,7 +6241,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects writes to the recycle bin by a process other than explorer.exe. action.notable.param.rule_title = Suspicious writes to windows Recycle Bin -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6244,7 +6265,7 @@ action.escu.modification_date = 2020-02-04 action.escu.confidence = high action.escu.full_search_name = ESCU - System Processes Run From Unexpected Locations - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6256,7 +6277,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. action.notable.param.rule_title = System Processes Run From Unexpected Locations -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6281,7 +6302,7 @@ action.escu.modification_date = 2017-09-11 action.escu.confidence = high action.escu.full_search_name = ESCU - TOR Traffic - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6292,7 +6313,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.notable.param.rule_title = TOR Traffic -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6317,7 +6338,7 @@ action.escu.modification_date = 2018-12-03 action.escu.confidence = high action.escu.full_search_name = ESCU - USN Journal Deletion - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6329,7 +6350,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.notable.param.rule_title = USN Journal Deletion -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6354,7 +6375,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Uncommon Processes On Endpoint - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Privilege Escalation", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6366,7 +6387,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as uncommon. action.notable.param.rule_title = Uncommon Processes On Endpoint -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6391,7 +6412,7 @@ action.escu.modification_date = 2020-01-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Unload Sysmon Filter Driver - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6403,7 +6424,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.notable.param.rule_title = Unload Sysmon Filter Driver -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6427,18 +6448,20 @@ action.escu.modification_date = 2019-12-06 action.escu.confidence = high action.escu.full_search_name = ESCU - Unsigned Image Loaded by LSASS - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Credential Dumping"] -cron_schedule = */60 * * * * -dispatch.earliest_time = -60m +cron_schedule = */30 * * * * +dispatch.earliest_time = -30m dispatch.latest_time = now action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Unsigned Image Loaded by LSASS - Rule schedule_window = auto -action.email.subject.alert = Splunk Alert: $name$ -action.email.to = test@test.de -action.email.message.alert = Splunk Alert $name$ triggered -action.email.useNSSubject = 1 +action.notable = 1 +action.notable.param.nes_fields = ['dest'] +action.notable.param.rule_description = This search detects loading of unsigned images by LSASS. +action.notable.param.rule_title = Unsigned Image Loaded by LSASS +action.notable.param.security_domain = endpoint +action.notable.param.severity = medium disabled = true enableSched = 1 counttype = number of events @@ -6461,7 +6484,7 @@ action.escu.modification_date = 2017-09-12 action.escu.confidence = high action.escu.full_search_name = ESCU - Unsuccessful Netbackup backups - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Monitor Backup Solution"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6472,7 +6495,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search gives you the hosts where a backup was attempted and then failed. action.notable.param.rule_title = Unsuccessful Netbackup backups -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6496,7 +6519,7 @@ action.escu.modification_date = 2020-03-16 action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6508,7 +6531,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. action.notable.param.rule_title = Unusually Long Command Line -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6532,7 +6555,7 @@ action.escu.modification_date = 2019-05-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - MLTK - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6544,7 +6567,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. action.notable.param.rule_title = Unusually Long Command Line - MLTK -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6568,7 +6591,7 @@ action.escu.modification_date = 2017-10-13 action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Content-Type Length - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Apache Struts Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6579,7 +6602,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.notable.param.rule_title = Unusually Long Content-Type Length -action.notable.param.security_domain = +action.notable.param.security_domain = network action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6603,7 +6626,7 @@ action.escu.modification_date = 2018-10-23 action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6615,7 +6638,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. action.notable.param.rule_title = WMI Permanent Event Subscription -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6639,7 +6662,7 @@ action.escu.modification_date = 2018-10-23 action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Permanent Event Subscription - Sysmon - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6651,7 +6674,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. action.notable.param.rule_title = WMI Permanent Event Subscription - Sysmon -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6675,7 +6698,7 @@ action.escu.modification_date = 2018-10-23 action.escu.confidence = high action.escu.full_search_name = ESCU - WMI Temporary Event Subscription - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6686,7 +6709,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search looks for the creation of WMI temporary event subscriptions. action.notable.param.rule_title = WMI Temporary Event Subscription -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6710,7 +6733,7 @@ action.escu.modification_date = 2018-10-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Account Harvesting - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Web Fraud Detection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6722,7 +6745,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search is used to identify the creation of multiple user accounts using the same email domain name. action.notable.param.rule_title = Web Fraud - Account Harvesting -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6746,7 +6769,7 @@ action.escu.modification_date = 2018-10-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Anomalous User Clickspeed - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Web Fraud Detection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6757,7 +6780,7 @@ schedule_window = auto action.notable = 1 action.notable.param.rule_description = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. action.notable.param.rule_title = Web Fraud - Anomalous User Clickspeed -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6781,7 +6804,7 @@ action.escu.modification_date = 2018-10-08 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Fraud - Password Sharing Across Accounts - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Web Fraud Detection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6793,7 +6816,7 @@ action.notable = 1 action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search is used to identify user accounts that share a common password. action.notable.param.rule_title = Web Fraud - Password Sharing Across Accounts -action.notable.param.security_domain = +action.notable.param.security_domain = threat action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6818,7 +6841,7 @@ action.escu.modification_date = 2019-04-01 action.escu.confidence = high action.escu.full_search_name = ESCU - Web Servers Executing Suspicious Processes - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Apache Struts Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6830,7 +6853,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for suspicious processes on all systems labeled as web servers. action.notable.param.rule_title = Web Servers Executing Suspicious Processes -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6854,7 +6877,7 @@ action.escu.modification_date = 2019-02-27 action.escu.confidence = high action.escu.full_search_name = ESCU - Windows Event Log Cleared - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Windows Log Manipulation", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6866,7 +6889,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for Windows events that indicate one of the Windows event logs has been purged. action.notable.param.rule_title = Windows Event Log Cleared -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 @@ -6890,7 +6913,7 @@ action.escu.modification_date = 2018-11-02 action.escu.confidence = high action.escu.full_search_name = ESCU - Windows hosts file modification - Rule action.escu.search_type = detection -action.escu.providing_technologies = none +action.escu.providing_technologies = [] action.escu.analytic_story = ["Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m @@ -6902,7 +6925,7 @@ action.notable = 1 action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for modifications to the hosts file on all Windows endpoints across your environment. action.notable.param.rule_title = Windows hosts file modification -action.notable.param.security_domain = +action.notable.param.security_domain = endpoint action.notable.param.severity = medium disabled = true enableSched = 1 diff --git a/package/default/transforms.conf b/package/default/transforms.conf index ced5fe6487..7d223c85d5 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:14:19 UTC +# On Date: 2020-05-11T07:31:11 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 12f1c40b9e..82661903ad 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:14:19 UTC +# On Date: 2020-05-11T07:31:11 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] +searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable History"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History"] +searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Process File Activity", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS Server History for a host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] +searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Registry Activities", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From d87824bf64651acff3e08a98afb71460ab6ae38a Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 10:08:49 +0200 Subject: [PATCH 34/93] bug in generate --- bin/jinja2_templates/savedsearches.j2 | 29 +- package/default/analytic_stories.conf | 112 +- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 1373 ++++++++++++++++++++----- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 122 +-- 6 files changed, 1284 insertions(+), 356 deletions(-) diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 4a2a229a33..07f11de854 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -14,7 +14,9 @@ action.escu.enabled = 1 description = {{ detection.description }} action.escu.mappings = {{ detection.mappings | tojson }} {% if detection.data_model is defined %} -action.escu.data_models = {{ detection.data_model }} +action.escu.data_models = [{{ detection.data_model }}] +{% else %} +action.escu.data_models = [] {% endif %} action.escu.eli5 = {{ detection.description }} {% if detection.how_to_implement is defined %} @@ -71,6 +73,8 @@ action.risk.param._risk_object_type = action.risk.param._risk_score = action.risk.param.verbose = 0 {% endif %} +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -91,15 +95,19 @@ search = {{ detection.search }} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - {{ baseline.name }} - Baseline +action.escu.full_search_name = ESCU - {{ baseline.name }} description = {{ baseline.description }} action.escu.creation_date = {{ baseline.date }} action.escu.modification_date = {{ baseline.date }} {% if baseline.tags.analytics_story is defined %} action.escu.analytic_story = {{ baseline.tags.analytics_story | tojson }} +{% else %} +action.escu.analytic_story = [] {% endif %} {% if baseline.data_model is defined %} -action.escu.data_models = {{ baseline.data_model }} +action.escu.data_models = [{{ baseline.data_model }}] +{% else %} +action.escu.data_models = [] {% endif %} dispatch.earliest_time = {{ baseline.deployment.scheduling.earliest_time }} dispatch.latest_time = {{ baseline.deployment.scheduling.latest_time }} @@ -108,6 +116,8 @@ schedule_window = {{ baseline.deployment.scheduling.schedule_window }} {% endif %} {% if baseline.providing_technologies is defined %} action.escu.providing_technologies = {{ baseline.providing_technologies | tojson }} +{% else %} +action.escu.providing_technologies = [] {% endif %} action.escu.eli5 = {{ baseline.description }} {% if baseline.how_to_implement is defined %} @@ -130,17 +140,26 @@ search = {{ baseline.search }} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - {{ response_task.name }} - Response Task +action.escu.full_search_name = ESCU - {{ response_task.name }} description = {{ response_task.description }} action.escu.creation_date = {{ response_task.date }} action.escu.modification_date = {{ response_task.date }} {% if response_task.tags is defined %} action.escu.analytic_story = {{ response_task.tags.analytics_story | tojson }} +{% else %} +action.escu.analytic_story = [] {% endif %} +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] {% if response_task.data_model is defined %} -action.escu.data_models = {{ response_task.data_model }} +action.escu.data_models = [{{ response_task.data_model }}] +{% else %} +action.escu.data_models = [] {% endif %} action.escu.eli5 = {{ response_task.description }} +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 63488ac6ae..4e6bda4a58 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:31:11 UTC +# On Date: 2020-05-11T08:08:29 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] +investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src"] +investigative_searches = ["ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index ac2e3b18f5..5e3fcd0822 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:31:11 UTC +# On Date: 2020-05-11T08:08:29 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index ab305181e8..85d17e936e 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:31:11 UTC +# On Date: 2020-05-11T08:08:29 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -12,6 +12,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -35,6 +36,8 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen City action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -49,6 +52,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -72,6 +76,8 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Country action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -86,6 +92,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -109,6 +116,8 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen IP Address action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -123,6 +132,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ @@ -146,6 +156,8 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Region action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -160,6 +172,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. action.escu.known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. @@ -182,6 +195,8 @@ action.notable.param.rule_description = This search looks for AssumeRole events action.notable.param.rule_title = AWS Cross Account Activity From Previously Unseen Account action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -196,6 +211,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. @@ -218,6 +234,8 @@ action.notable.param.rule_description = The search looks for CloudTrail events t action.notable.param.rule_title = AWS Network Access Control List Created with All Open Ports action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -232,6 +250,7 @@ action.escu = 0 action.escu.enabled = 1 description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = It's possible that a user has legitimately deleted a network ACL. @@ -254,6 +273,8 @@ action.notable.param.rule_description = Enforcing network-access controls is one action.notable.param.rule_title = AWS Network Access Control List Deleted action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -268,6 +289,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -289,6 +311,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Launched by User action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -303,6 +327,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -325,6 +350,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Launched by User - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -339,6 +366,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. action.escu.known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. @@ -360,6 +388,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -374,6 +404,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. @@ -396,6 +427,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -410,6 +443,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect memory dumping of the LSASS process. action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = Detect memory dumping of the LSASS process. action.escu.how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. @@ -432,6 +466,8 @@ action.notable.param.rule_description = Detect memory dumping of the LSASS proce action.notable.param.rule_title = Access LSASS Memory for Dump Creation action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -446,6 +482,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} +action.escu.data_models = [] action.escu.eli5 = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. @@ -467,6 +504,8 @@ action.notable.param.rule_description = This search provides detection informati action.notable.param.rule_title = Amazon EKS Kubernetes Pod scan detection action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -481,6 +520,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} +action.escu.data_models = [] action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. @@ -502,6 +542,8 @@ action.notable.param.rule_description = This search provides information of unau action.notable.param.rule_title = Amazon EKS Kubernetes cluster scan detection action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -516,7 +558,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attempt to add a certificate to the untrusted certificate store action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. @@ -539,6 +581,8 @@ action.notable.param.rule_description = Attempt to add a certificate to the untr action.notable.param.rule_title = Attempt To Add Certificate To Untrusted Store action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -553,7 +597,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. action.escu.known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. @@ -576,6 +620,8 @@ action.notable.param.rule_description = Monitor for changes of the ExecutionPoli action.notable.param.rule_title = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -590,7 +636,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for attempts to stop security-related services on the endpoint. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., action.escu.known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. @@ -613,6 +659,8 @@ action.notable.param.rule_description = This search looks for attempts to stop s action.notable.param.rule_title = Attempt To Stop Security Service action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -627,7 +675,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -650,6 +698,8 @@ action.notable.param.rule_description = Monitor for execution of reg.exe with pa action.notable.param.rule_title = Attempted Credential Dump From Registry via Reg exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -664,7 +714,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. @@ -687,6 +737,8 @@ action.notable.param.rule_description = The search looks for a batch file (.bat) action.notable.param.rule_title = Batch File Write to System32 action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -701,7 +753,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.mappings = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. action.escu.known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. @@ -724,6 +776,8 @@ action.notable.param.rule_description = This search looks for child processes of action.notable.param.rule_title = Child Processes of Spoolsv exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -738,7 +792,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ @@ -763,6 +817,8 @@ action.notable.param.rule_description = This search allows you to identify the e action.notable.param.rule_title = Clients Connecting to Multiple DNS Servers action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -777,7 +833,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances created by users who have not created them before. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. action.escu.known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. @@ -800,6 +856,8 @@ action.notable.param.rule_description = This search looks for cloud compute inst action.notable.param.rule_title = Cloud Compute Instance Created By Previously Unseen User action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -814,7 +872,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. action.escu.known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. @@ -837,6 +895,8 @@ action.notable.param.rule_description = This search looks for cloud compute inst action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Image action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -851,7 +911,7 @@ action.escu = 0 action.escu.enabled = 1 description = Find EC2 instances being created with previously unseen instance types. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. @@ -874,6 +934,8 @@ action.notable.param.rule_description = Find EC2 instances being created with pr action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Instance Type action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -888,7 +950,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. @@ -911,6 +973,8 @@ action.notable.param.rule_description = This search looks at cloud-infrastructur action.notable.param.rule_title = Cloud Compute Instance Started In Previously Unused Region action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -925,7 +989,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file modifications with extensions commonly used by Ransomware action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ @@ -952,6 +1016,8 @@ action.notable.param.rule_description = The search looks for file modifications action.notable.param.rule_title = Common Ransomware Extensions action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -966,7 +1032,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. @@ -989,6 +1055,8 @@ action.notable.param.rule_description = The search looks for files created with action.notable.param.rule_title = Common Ransomware Notes action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1003,6 +1071,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect remote thread creation into LSASS consistent with credential dumping. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = Detect remote thread creation into LSASS consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. @@ -1025,6 +1094,8 @@ action.notable.param.rule_description = Detect remote thread creation into LSASS action.notable.param.rule_title = Create Remote Thread into LSASS action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1039,7 +1110,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of local administrator accounts using net.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create admin accounts. @@ -1062,6 +1133,8 @@ action.notable.param.rule_description = This search looks for the creation of lo action.notable.param.rule_title = Create local admin accounts using net exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1076,7 +1149,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. @@ -1099,6 +1172,8 @@ action.notable.param.rule_description = This search looks for the creation or de action.notable.param.rule_title = Create or delete windows shares using net exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1113,7 +1188,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. @@ -1136,6 +1211,8 @@ action.notable.param.rule_description = Monitor for signs that Ntdsutil, Vssadmi action.notable.param.rule_title = Creation of Shadow Copy action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1150,6 +1227,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the use of wmic and Powershell to create a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search detects the use of wmic and Powershell to create a shadow copy. action.escu.how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. @@ -1172,6 +1250,8 @@ action.notable.param.rule_description = This search detects the use of wmic and action.notable.param.rule_title = Creation of Shadow Copy with wmic and powershell action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1186,7 +1266,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects credential dumping using copy command from a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1209,6 +1289,8 @@ action.notable.param.rule_description = This search detects credential dumping u action.notable.param.rule_title = Credential Dumping via Copy Command from Shadow Copy action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1223,7 +1305,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the creation of a symlink to a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1246,6 +1328,8 @@ action.notable.param.rule_description = This search detects the creation of a sy action.notable.param.rule_title = Credential Dumping via Symlink to Shadow Copy action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1260,7 +1344,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -1289,6 +1373,8 @@ action.notable.param.rule_description = This search allows you to identify DNS r action.notable.param.rule_title = DNS Query Length Outliers - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1303,7 +1389,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It's possible there can be long domain names that are legitimate. @@ -1325,6 +1411,8 @@ action.notable.param.rule_description = This search allows you to identify DNS r action.notable.param.rule_title = DNS Query Length With High Standard Deviation action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1339,7 +1427,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. action.escu.known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. @@ -1362,6 +1450,8 @@ action.notable.param.rule_description = This search will detect DNS requests res action.notable.param.rule_title = DNS Query Requests Resolved by Unauthorized DNS Servers action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1376,7 +1466,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ **Splunk>Phantom Playbook Integration**\ @@ -1403,6 +1493,8 @@ action.notable.param.rule_description = The search takes the DNS records and the action.notable.param.rule_title = DNS record changed action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1417,7 +1509,7 @@ action.escu = 0 action.escu.enabled = 1 description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.mappings = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. @@ -1440,6 +1532,8 @@ action.notable.param.rule_description = The vssadmin.exe utility is used to inte action.notable.param.rule_title = Deleting Shadow Copies action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1454,6 +1548,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. action.escu.mappings = {"cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -1482,6 +1577,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect API activity from users without MFA action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1496,6 +1593,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -1524,6 +1622,8 @@ action.notable.param.rule_description = This search looks for successful CloudTr action.notable.param.rule_title = Detect AWS API Activities From Unapproved Accounts action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1538,6 +1638,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1560,6 +1661,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect AWS Console Login by User from New City action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1574,6 +1677,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1596,6 +1700,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect AWS Console Login by User from New Country action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1610,6 +1716,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -1632,6 +1739,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect AWS Console Login by User from New Region action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1646,6 +1755,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. action.escu.how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. action.escu.known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. @@ -1668,6 +1778,8 @@ action.notable.param.rule_description = This search looks for specific authentic action.notable.param.rule_title = Detect Activity Related to Pass the Hash Attacks action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1682,6 +1794,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for reading lsass memory consistent with credential dumping. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for reading lsass memory consistent with credential dumping. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. @@ -1704,6 +1817,8 @@ action.notable.param.rule_description = This search looks for reading lsass memo action.notable.param.rule_title = Detect Credential Dumping through LSASS access action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1718,7 +1833,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.mappings = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ **Splunk>Phantom Playbook Integration**\ @@ -1745,6 +1860,8 @@ action.notable.param.rule_description = This search looks for DNS requests for p action.notable.param.rule_title = Detect DNS requests to Phishing Sites leveraging EvilGinx2 action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1759,7 +1876,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = Change +action.escu.data_models = [Change] action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ **Splunk>Phantom Playbook Integration**\ @@ -1786,6 +1903,8 @@ action.notable.param.rule_description = This search identifies endpoints that ha action.notable.param.rule_title = Detect Excessive Account Lockouts From Endpoint action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1800,7 +1919,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = Change +action.escu.data_models = [Change] action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. action.escu.known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. @@ -1823,6 +1942,8 @@ action.notable.param.rule_description = This search detects user accounts that h action.notable.param.rule_title = Detect Excessive User Account Lockouts action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1837,7 +1958,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. @@ -1859,6 +1980,8 @@ action.notable.param.rule_description = This search looks for outbound ICMP pack action.notable.param.rule_title = Detect Large Outbound ICMP Packets action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1873,7 +1996,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. action.escu.known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. @@ -1896,6 +2019,8 @@ action.notable.param.rule_description = This search is used to detect attempts t action.notable.param.rule_title = Detect Long DNS TXT Record Response action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1910,6 +2035,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. action.escu.mappings = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.AE", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for reading loaded Images unique to credential dumping with Mimikatz. action.escu.how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. @@ -1932,6 +2058,8 @@ action.notable.param.rule_description = This search looks for reading loaded Ima action.notable.param.rule_title = Detect Mimikatz Using Loaded Images action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1946,6 +2074,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell requesting privileges consistent with credential dumping. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for PowerShell requesting privileges consistent with credential dumping. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. action.escu.known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. @@ -1966,6 +2095,8 @@ action.notable.param.rule_description = This search looks for PowerShell request action.notable.param.rule_title = Detect Mimikatz Via PowerShell And EventCode 4703 action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -1980,6 +2111,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for newly created accounts that have been elevated to local administrators. action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1078"], "nist": ["PR.AC", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for newly created accounts that have been elevated to local administrators. action.escu.how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Security ID, **Field:** Security_ID\ @@ -2008,6 +2140,8 @@ action.notable.param.rule_description = This search looks for newly created acco action.notable.param.rule_title = Detect New Local Admin account action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2022,7 +2156,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} -action.escu.data_models = Authentication +action.escu.data_models = [Authentication] action.escu.eli5 = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. action.escu.known_false_positives = Legitimate router connections may appear as new connections @@ -2045,6 +2179,8 @@ action.notable.param.rule_description = The search queries the authentication lo action.notable.param.rule_title = Detect New Login Attempts to Routers action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2059,6 +2195,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events where a user has created an open/public S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. action.escu.known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. @@ -2081,6 +2218,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect New Open S3 buckets action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2095,6 +2234,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. @@ -2117,6 +2257,8 @@ action.notable.param.rule_description = This search looks for execution of proce action.notable.param.rule_title = Detect Oulook exe writing a zip file action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2131,7 +2273,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. @@ -2153,6 +2295,8 @@ action.notable.param.rule_description = This search looks for outbound SMB conne action.notable.param.rule_title = Detect Outbound SMB Traffic action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2167,7 +2311,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. action.escu.known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. @@ -2190,6 +2334,8 @@ action.notable.param.rule_description = The search is looking for the creation o action.notable.param.rule_title = Detect Path Interception By Creation Of program exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2204,7 +2350,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. action.escu.known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. @@ -2227,6 +2373,8 @@ action.notable.param.rule_description = This search looks for executions of cmd. action.notable.param.rule_title = Detect Prohibited Applications Spawning cmd exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2241,7 +2389,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine @@ -2264,6 +2412,8 @@ action.notable.param.rule_description = This search looks for events where `PsEx action.notable.param.rule_title = Detect PsExec With accepteula Flag action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2278,7 +2428,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. action.escu.known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. @@ -2301,6 +2451,8 @@ action.notable.param.rule_description = This search will return a table of rare action.notable.param.rule_title = Detect Rare Executables action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2315,6 +2467,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. action.escu.mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access logs' inputs. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. action.escu.known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour @@ -2336,6 +2489,8 @@ action.notable.param.rule_description = This search looks at S3 bucket-access lo action.notable.param.rule_title = Detect S3 access from a new IP action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2350,6 +2505,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +action.escu.data_models = [] action.escu.eli5 = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** AWS Event Name, **Field:** eventName\ @@ -2378,6 +2534,8 @@ action.notable.param.rule_description = This search will detect users creating s action.notable.param.rule_title = Detect Spike in AWS API Activity action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2392,6 +2550,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. action.escu.mappings = {"cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +action.escu.data_models = [] action.escu.eli5 = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. @@ -2414,6 +2573,8 @@ action.notable.param.rule_description = This search will detect users creating s action.notable.param.rule_title = Detect Spike in Network ACL Activity action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2428,6 +2589,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +action.escu.data_models = [] action.escu.eli5 = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. @@ -2450,6 +2612,8 @@ action.notable.param.rule_description = This search detects users creating spike action.notable.param.rule_title = Detect Spike in S3 Bucket deletion action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2464,6 +2628,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} +action.escu.data_models = [] action.escu.eli5 = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. action.escu.known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. @@ -2486,6 +2651,8 @@ action.notable.param.rule_description = This search will detect users creating s action.notable.param.rule_title = Detect Spike in Security Group Activity action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2500,6 +2667,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} +action.escu.data_models = [] action.escu.eli5 = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. action.escu.known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. @@ -2521,6 +2689,8 @@ action.notable.param.rule_description = This search will detect spike in blocked action.notable.param.rule_title = Detect Spike in blocked Outbound Traffic from your AWS action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2535,7 +2705,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = Change_Analysis +action.escu.data_models = [Change_Analysis] action.escu.eli5 = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. action.escu.known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. @@ -2558,6 +2728,8 @@ action.notable.param.rule_description = The search is used to detect hosts that action.notable.param.rule_title = Detect USB device insertion action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2572,7 +2744,7 @@ action.escu = 0 action.escu.enabled = 1 description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = Network_Sessions +action.escu.data_models = [Network_Sessions] action.escu.eli5 = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. action.escu.known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. @@ -2594,6 +2766,8 @@ action.notable.param.rule_description = By populating the organization's assets action.notable.param.rule_title = Detect Unauthorized Assets by MAC address action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2608,7 +2782,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Some legitimate applications may exhibit this behavior. @@ -2631,6 +2805,8 @@ action.notable.param.rule_description = This search looks for the execution of t action.notable.param.rule_title = Detect Use of cmd exe to Launch Script Interpreters action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2645,7 +2821,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. action.escu.known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. @@ -2668,6 +2844,8 @@ action.notable.param.rule_description = This search looks for specific GET or HE action.notable.param.rule_title = Detect attackers scanning for vulnerable JBoss servers action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2682,7 +2860,7 @@ action.escu = 0 action.escu.enabled = 1 description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -2710,6 +2888,8 @@ action.notable.param.rule_description = Malicious actors often abuse legitimate action.notable.param.rule_title = Detect hosts connecting to dynamic domain providers action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2724,7 +2904,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.mappings = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model action.escu.known_false_positives = No known false positives for this detection. @@ -2747,6 +2927,8 @@ action.notable.param.rule_description = This search is used to detect malicious action.notable.param.rule_title = Detect malicious requests to exploit JBoss servers action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2761,7 +2943,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. @@ -2784,6 +2966,8 @@ action.notable.param.rule_description = This search looks for the execution of " action.notable.param.rule_title = Detect mshta exe running scripts in command-line arguments action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2798,6 +2982,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. action.escu.known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. @@ -2820,6 +3005,8 @@ action.notable.param.rule_description = This search detects new API calls that h action.notable.param.rule_title = Detect new API calls from user roles action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2834,6 +3021,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. action.escu.known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. @@ -2856,6 +3044,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect new user AWS Console Login action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2870,7 +3060,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. action.escu.known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. @@ -2893,6 +3083,8 @@ action.notable.param.rule_description = This search looks for fast execution of action.notable.param.rule_title = Detect processes used for System Network Configuration Discovery action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2907,7 +3099,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for web connections to dynamic DNS providers. action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"]} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for web connections to dynamic DNS providers. action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ @@ -2932,6 +3124,8 @@ action.notable.param.rule_description = This search looks for web connections to action.notable.param.rule_title = Detect web traffic to dynamic domain providers action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2946,7 +3140,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. action.escu.known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. @@ -2969,6 +3163,8 @@ action.notable.param.rule_description = This search is used to detect DNS tunnel action.notable.param.rule_title = Detection of DNS Tunnels action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -2983,7 +3179,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072", "T1087"], "nist": ["PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. @@ -3006,6 +3202,8 @@ action.notable.param.rule_description = This search looks for specific command-l action.notable.param.rule_title = Detection of tools built by NirSoft action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3020,6 +3218,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. @@ -3042,6 +3241,8 @@ action.notable.param.rule_description = The search looks for modifications to re action.notable.param.rule_title = Disabling Remote User Account Control action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3056,7 +3257,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -3079,6 +3280,8 @@ action.notable.param.rule_description = Detect the usage of comsvcs.dll for dump action.notable.param.rule_title = Dump LSASS via comsvcs DLL action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3093,6 +3296,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being modified by users who have not previously modified them. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for EC2 instances being modified by users who have not previously modified them. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. action.escu.known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. @@ -3115,6 +3319,8 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Modified With Previously Unseen User action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3129,6 +3335,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. @@ -3150,6 +3357,8 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = EC2 Instance Started In Previously Unseen Region action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3164,6 +3373,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen AMIs. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for EC2 instances being created with previously unseen AMIs. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. action.escu.known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. @@ -3185,6 +3395,8 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Started With Previously Unseen AMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3199,6 +3411,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created with previously unseen instance types. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. @@ -3221,6 +3434,8 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Started With Previously Unseen Instance Type action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3235,6 +3450,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for EC2 instances being created by users who have not created them before. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for EC2 instances being created by users who have not created them before. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. action.escu.known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. @@ -3257,6 +3473,8 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Started With Previously Unseen User action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3271,7 +3489,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = Email +action.escu.data_models = [Email] action.escu.eli5 = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ **Splunk Phantom Playbook Integration**\ @@ -3295,6 +3513,8 @@ action.notable.param.rule_description = Attackers often use spaces as a means to action.notable.param.rule_title = Email Attachments With Lots Of Spaces action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3309,7 +3529,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. @@ -3332,6 +3552,8 @@ action.notable.param.rule_description = The search looks at the change-analysis action.notable.param.rule_title = Email files written outside of the Outlook directory action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3346,7 +3568,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -3368,6 +3590,8 @@ action.notable.param.rule_description = This search looks for an increase of dat action.notable.param.rule_title = Email servers sending high volume traffic to hosts action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3382,7 +3606,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.mappings = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. @@ -3404,6 +3628,8 @@ action.notable.param.rule_description = This search identifies DNS query failure action.notable.param.rule_title = Excessive DNS Failures action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3418,7 +3644,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = None identified. @@ -3441,6 +3667,8 @@ action.notable.param.rule_description = This search looks for processes launched action.notable.param.rule_title = Execution of File With Spaces Before Extension action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3455,7 +3683,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. action.escu.known_false_positives = None identified. @@ -3478,6 +3706,8 @@ action.notable.param.rule_description = This search looks for processes launched action.notable.param.rule_title = Execution of File with Multiple Extensions action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3492,6 +3722,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search returns a list of hosts that have not successfully completed a backup in over a week. action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search returns a list of hosts that have not successfully completed a backup in over a week. action.escu.how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. action.escu.known_false_positives = None identified @@ -3514,6 +3745,8 @@ action.notable.param.rule_description = This search returns a list of hosts that action.notable.param.rule_title = Extended Period Without Successful Netbackup Backups action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3528,7 +3761,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. @@ -3551,6 +3784,8 @@ action.notable.param.rule_description = The search looks for file writes with ex action.notable.param.rule_title = File with Samsam Extension action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3565,6 +3800,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the first time a Windows service is seen running in your environment. action.escu.mappings = {"cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for the first time a Windows service is seen running in your environment. action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. action.escu.known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. @@ -3587,6 +3823,8 @@ action.notable.param.rule_description = This search looks for the first time a W action.notable.param.rule_title = First Time Seen Running Windows Service action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3601,7 +3839,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. action.escu.known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name @@ -3623,6 +3861,8 @@ action.notable.param.rule_description = This search looks for command-line argum action.notable.param.rule_title = First time seen command line argument action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3637,6 +3877,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. action.escu.mappings = {} +action.escu.data_models = [] action.escu.eli5 = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. @@ -3659,6 +3900,8 @@ action.notable.param.rule_description = This search show information on uploaded action.notable.param.rule_title = GCP GCR container uploaded action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3673,6 +3916,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"]} +action.escu.data_models = [] action.escu.eli5 = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.escu.how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. action.escu.known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. @@ -3694,6 +3938,8 @@ action.notable.param.rule_description = This search provides information of unau action.notable.param.rule_title = GCP Kubernetes cluster scan detection action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3708,7 +3954,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. @@ -3731,6 +3977,8 @@ action.notable.param.rule_description = Attackers leverage an existing Windows b action.notable.param.rule_title = Hiding Files And Directories With Attrib exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3745,7 +3993,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -3767,6 +4015,8 @@ action.notable.param.rule_description = This search looks for an increase of dat action.notable.param.rule_title = Hosts receiving high volume of network traffic from email server action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3781,6 +4031,7 @@ action.escu = 0 action.escu.enabled = 1 description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. action.escu.how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. action.escu.known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. @@ -3802,6 +4053,8 @@ action.notable.param.rule_description = This detection search will help profile action.notable.param.rule_title = Identify New User Accounts action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3816,7 +4069,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. @@ -3838,6 +4091,8 @@ action.notable.param.rule_description = The search is used to identify attempts action.notable.param.rule_title = Large Volume of DNS ANY Queries action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3852,7 +4107,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. action.escu.known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. @@ -3874,6 +4129,8 @@ action.notable.param.rule_description = This search looks for processes referenc action.notable.param.rule_title = MacOS - Re-opened Applications action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3888,7 +4145,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -3911,6 +4168,8 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Connect To Internet With Hidden Window action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3925,7 +4184,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = System administrators may use this option, but it's not common. @@ -3948,6 +4207,8 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Encoded Command action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3962,7 +4223,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. @@ -3985,6 +4246,8 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Execution Policy Bypass action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -3999,7 +4262,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -4022,6 +4285,8 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4036,7 +4301,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = These characters might be legitimately on the command-line, but it is not common. @@ -4059,6 +4324,8 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process With Obfuscation Techniques action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4073,7 +4340,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.mappings = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4095,6 +4362,8 @@ action.notable.param.rule_description = This search looks for DNS requests for f action.notable.param.rule_title = Monitor DNS For Brand Abuse action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4109,7 +4378,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = Email +action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4131,6 +4400,8 @@ action.notable.param.rule_description = This search looks for emails claiming to action.notable.param.rule_title = Monitor Email For Brand Abuse action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4145,6 +4416,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. action.escu.mappings = {"cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. action.escu.known_false_positives = You will encounter noise from legitimate print-monitor registry entries. @@ -4167,6 +4439,8 @@ action.notable.param.rule_description = This search looks for registry activity action.notable.param.rule_title = Monitor Registry Keys for Print Monitors action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4181,7 +4455,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4204,6 +4478,8 @@ action.notable.param.rule_description = This search looks for Web requests to fa action.notable.param.rule_title = Monitor Web Traffic For Brand Abuse action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4218,6 +4494,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. @@ -4239,6 +4516,8 @@ action.notable.param.rule_description = This search detects Okta login failures action.notable.param.rule_title = Multiple Okta Users With Invalid Credentails From The Same IP action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4253,6 +4532,7 @@ action.escu = 0 action.escu.enabled = 1 description = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. action.escu.mappings = {} +action.escu.data_models = [] action.escu.eli5 = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. action.escu.known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. @@ -4275,6 +4555,8 @@ action.notable.param.rule_description = This searches show information on upload action.notable.param.rule_title = New container uploaded to AWS ECR action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4289,7 +4571,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.mappings = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} -action.escu.data_models = Updates +action.escu.data_models = [Updates] action.escu.eli5 = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. action.escu.known_false_positives = None identified @@ -4312,6 +4594,8 @@ action.notable.param.rule_description = This search looks for Windows endpoints action.notable.param.rule_title = No Windows Updates in a time frame action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4326,6 +4610,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect Okta user lockout events action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = Detect Okta user lockout events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. @@ -4347,6 +4632,8 @@ action.notable.param.rule_description = Detect Okta user lockout events action.notable.param.rule_title = Okta Account Lockout Events action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4361,6 +4648,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect failed Okta SSO events action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = Detect failed Okta SSO events action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. @@ -4382,6 +4670,8 @@ action.notable.param.rule_description = Detect failed Okta SSO events action.notable.param.rule_title = Okta Failed SSO Attempts action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4396,6 +4686,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects logins from the same user from different states in a 24 hour period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search detects logins from the same user from different states in a 24 hour period. action.escu.how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. action.escu.known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. @@ -4418,6 +4709,8 @@ action.notable.param.rule_description = This search detects logins from the same action.notable.param.rule_title = Okta User Logins From Multiple Cities action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4432,6 +4725,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.escu.how_to_implement = No extra steps needed to implement this search. action.escu.known_false_positives = None identified @@ -4453,6 +4747,8 @@ action.notable.param.rule_description = This search allows you to look for evide action.notable.param.rule_title = Open Redirect in Splunk Web action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4467,6 +4763,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for ColdRoot events from the osx-attacks osquery pack. action.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for ColdRoot events from the osx-attacks osquery pack. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model action.escu.known_false_positives = There are no known false positives. @@ -4488,6 +4785,8 @@ action.notable.param.rule_description = This search looks for ColdRoot events fr action.notable.param.rule_title = Osquery pack - ColdRoot detection action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4502,7 +4801,7 @@ action.escu = 0 action.escu.enabled = 1 description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. @@ -4525,6 +4824,8 @@ action.notable.param.rule_description = Microsoft Windows contains accessibility action.notable.param.rule_title = Overwriting Accessibility Binaries action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4539,6 +4840,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched via WMI. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for processes launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. @@ -4561,6 +4863,8 @@ action.notable.param.rule_description = This search looks for processes launched action.notable.param.rule_title = Process Execution via WMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4575,6 +4879,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input action.escu.mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. action.escu.known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. @@ -4596,6 +4901,8 @@ action.notable.param.rule_description = This search looks for processes in an Ma action.notable.param.rule_title = Processes Tapping Keyboard Events action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4610,7 +4917,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. @@ -4633,6 +4940,8 @@ action.notable.param.rule_description = This search looks for processes launchin action.notable.param.rule_title = Processes created by netsh action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4647,7 +4956,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model action.escu.known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. @@ -4670,6 +4979,8 @@ action.notable.param.rule_description = This search looks for processes launchin action.notable.param.rule_title = Processes launching netsh action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4684,7 +4995,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None identified @@ -4706,6 +5017,8 @@ action.notable.param.rule_description = This search looks for network traffic de action.notable.param.rule_title = Prohibited Network Traffic Allowed action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4720,7 +5033,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. action.escu.known_false_positives = None identified @@ -4743,6 +5056,8 @@ action.notable.param.rule_description = This search looks for applications on th action.notable.param.rule_title = Prohibited Software On Endpoint action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4757,7 +5072,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. action.escu.known_false_positives = None identified @@ -4779,6 +5094,8 @@ action.notable.param.rule_description = This search looks for network traffic on action.notable.param.rule_title = Protocol or Port Mismatch action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4793,7 +5110,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.mappings = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. action.escu.known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. @@ -4816,6 +5133,8 @@ action.notable.param.rule_description = This search looks for cleartext protocol action.notable.param.rule_title = Protocols passing authentication in cleartext action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4830,6 +5149,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. @@ -4852,6 +5172,8 @@ action.notable.param.rule_description = The search looks for reg.exe modifying r action.notable.param.rule_title = Reg exe Manipulating Windows Services Registry Keys action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4866,7 +5188,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None at the moment @@ -4889,6 +5211,8 @@ action.notable.param.rule_description = The search looks for command-line argume action.notable.param.rule_title = Reg exe used to hide files directories via registry keys action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4903,6 +5227,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. @@ -4925,6 +5250,8 @@ action.notable.param.rule_description = The search looks for modifications to re action.notable.param.rule_title = Registry Keys Used For Persistence action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4939,6 +5266,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. @@ -4961,6 +5289,8 @@ action.notable.param.rule_description = This search looks for modifications to r action.notable.param.rule_title = Registry Keys Used For Privilege Escalation action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -4975,6 +5305,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. action.escu.how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications @@ -4996,6 +5327,8 @@ action.notable.param.rule_description = This search looks for registry activity action.notable.param.rule_title = Registry Keys for Creating SHIM Databases action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5010,7 +5343,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.mappings = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. action.escu.known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. @@ -5033,6 +5366,8 @@ action.notable.param.rule_description = This search looks for RDP application ne action.notable.param.rule_title = Remote Desktop Network Bruteforce action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5047,7 +5382,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -5070,6 +5405,8 @@ action.notable.param.rule_description = This search looks for network traffic on action.notable.param.rule_title = Remote Desktop Network Traffic action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5084,7 +5421,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -5107,6 +5444,8 @@ action.notable.param.rule_description = This search looks for the remote desktop action.notable.param.rule_title = Remote Desktop Process Running On System action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5121,7 +5460,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. @@ -5144,6 +5483,8 @@ action.notable.param.rule_description = This search looks for wmic.exe being lau action.notable.param.rule_title = Remote Process Instantiation via WMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5158,6 +5499,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search monitors for remote modifications to registry keys. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search monitors for remote modifications to registry keys. action.escu.how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. action.escu.known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. @@ -5180,6 +5522,8 @@ action.notable.param.rule_description = This search monitors for remote modifica action.notable.param.rule_title = Remote Registry Key modifications action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5194,7 +5538,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may use this legitimately to gather info from remote systems. @@ -5217,6 +5561,8 @@ action.notable.param.rule_description = This search looks for wmic.exe being lau action.notable.param.rule_title = Remote WMI Command Attempt action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5231,7 +5577,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1085"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process @@ -5254,6 +5600,8 @@ action.notable.param.rule_description = This search looks for DLLs under %AppDat action.notable.param.rule_title = RunDLL Loading DLL By Ordinal action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5268,7 +5616,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. action.escu.known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. @@ -5291,6 +5639,8 @@ action.notable.param.rule_description = This search looks for spikes in the numb action.notable.param.rule_title = SMB Traffic Spike action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5305,7 +5655,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ @@ -5331,6 +5681,8 @@ action.notable.param.rule_description = This search uses the Machine Learning To action.notable.param.rule_title = SMB Traffic Spike - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5345,7 +5697,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for long URLs that have several SQL commands visible within them. action.escu.mappings = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} -action.escu.data_models = Web +action.escu.data_models = [Web] action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. action.escu.known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. @@ -5368,6 +5720,8 @@ action.notable.param.rule_description = This search looks for long URLs that hav action.notable.param.rule_title = SQL Injection with Long URLs action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5382,7 +5736,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = No false positives have been identified. @@ -5405,6 +5759,8 @@ action.notable.param.rule_description = The search looks for a file named "test. action.notable.param.rule_title = Samsam Test File Write action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5419,7 +5775,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. @@ -5442,6 +5798,8 @@ action.notable.param.rule_description = This search looks for arguments to sc.ex action.notable.param.rule_title = Sc exe Manipulating Windows Services action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5456,7 +5814,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -5479,6 +5837,8 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Scheduled Task Name Used by Dragonfly Threat Actors action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5493,7 +5853,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -5516,6 +5876,8 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Scheduled tasks used in BadRabbit ransomware action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5530,7 +5892,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. @@ -5553,6 +5915,8 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Schtasks scheduling job on remote system action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5567,7 +5931,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. @@ -5590,6 +5954,8 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Schtasks used for forcing a reboot action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5604,6 +5970,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for scripts launched via WMI. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for scripts launched via WMI. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. @@ -5626,6 +5993,8 @@ action.notable.param.rule_description = This search looks for scripts launched v action.notable.param.rule_title = Script Execution via WMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5640,6 +6009,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. @@ -5662,6 +6032,8 @@ action.notable.param.rule_description = This search looks for shim database file action.notable.param.rule_title = Shim Database File Creation action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5676,7 +6048,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -5699,6 +6071,8 @@ action.notable.param.rule_description = This search detects the process executio action.notable.param.rule_title = Shim Database Installation With Suspicious Parameters action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5713,7 +6087,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects accounts that were created and deleted in a short time period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} -action.escu.data_models = Change +action.escu.data_models = [Change] action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ action.escu.known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. @@ -5736,6 +6110,8 @@ action.notable.param.rule_description = This search detects accounts that were c action.notable.param.rule_title = Short Lived Windows Accounts action.notable.param.security_domain = access action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5750,7 +6126,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for process names that consist only of a single letter. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for process names that consist only of a single letter. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. @@ -5772,6 +6148,8 @@ action.notable.param.rule_description = This search looks for process names that action.notable.param.rule_title = Single Letter Process On Endpoint action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5786,7 +6164,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.mappings = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} -action.escu.data_models = Vulnerabilities +action.escu.data_models = [Vulnerabilities] action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. action.escu.known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. @@ -5808,6 +6186,8 @@ action.notable.param.rule_description = The search is used to detect systems tha action.notable.param.rule_title = Spectre and Meltdown Vulnerable Systems action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5822,6 +6202,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a sharp increase in the number of files written to a particular host action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = The search looks for a sharp increase in the number of files written to a particular host action.escu.how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, such as Carbon Black or endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the file system. action.escu.known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. @@ -5844,6 +6225,8 @@ action.notable.param.rule_description = The search looks for a sharp increase in action.notable.param.rule_title = Spike in File Writes action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5858,6 +6241,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. action.escu.how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. action.escu.known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. @@ -5880,6 +6264,8 @@ action.notable.param.rule_description = This search allows you to look for evide action.notable.param.rule_title = Splunk Enterprise Information Disclosure action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5894,6 +6280,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. action.escu.known_false_positives = There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. @@ -5916,6 +6303,8 @@ action.notable.param.rule_description = This search looks for changes to registr action.notable.param.rule_title = Suspicious Changes to File Associations action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5930,7 +6319,7 @@ action.escu = 0 action.escu.enabled = 1 description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = UEBA +action.escu.data_models = [UEBA] action.escu.eli5 = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. action.escu.known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. @@ -5953,6 +6342,8 @@ action.notable.param.rule_description = This detection looks for emails that are action.notable.param.rule_title = Suspicious Email - UBA Anomaly action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -5967,7 +6358,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails that have attachments with suspicious file extensions. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -action.escu.data_models = Email +action.escu.data_models = [Email] action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ **Splunk Phantom Playbook Integration**\ @@ -5991,6 +6382,8 @@ action.notable.param.rule_description = This search looks for emails that have a action.notable.param.rule_title = Suspicious Email Attachment Extensions action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6005,6 +6398,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names that have been linked to malicious activity. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = The search looks for files created with names that have been linked to malicious activity. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. action.escu.known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. @@ -6027,6 +6421,8 @@ action.notable.param.rule_description = The search looks for files created with action.notable.param.rule_title = Suspicious File Write action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6041,6 +6437,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. action.escu.mappings = {"cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. action.escu.known_false_positives = There are no known false positives. @@ -6063,6 +6460,8 @@ action.notable.param.rule_description = This search looks for suspicious Java cl action.notable.param.rule_title = Suspicious Java Classes action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6077,6 +6476,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. action.escu.how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. action.escu.known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. @@ -6099,6 +6499,8 @@ action.notable.param.rule_description = This search looks for a ``*.lnk` file un action.notable.param.rule_title = Suspicious LNK file launching a process action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6113,6 +6515,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112", "T1089"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. @@ -6135,6 +6538,8 @@ action.notable.param.rule_description = This search looks for reg.exe being laun action.notable.param.rule_title = Suspicious Reg exe Process action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6149,7 +6554,7 @@ action.escu = 0 action.escu.enabled = 1 description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. @@ -6172,6 +6577,8 @@ action.notable.param.rule_description = The wevtutil.exe application is the wind action.notable.param.rule_title = Suspicious wevtutil Usage action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6186,6 +6593,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the 'System Volume Information' folder by something other than the System process. action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search detects writes to the 'System Volume Information' folder by something other than the System process. action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. @@ -6207,6 +6615,8 @@ action.notable.param.rule_description = This search detects writes to the 'Syste action.notable.param.rule_title = Suspicious writes to System Volume Information action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6221,6 +6631,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects writes to the recycle bin by a process other than explorer.exe. action.escu.mappings = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search detects writes to the recycle bin by a process other than explorer.exe. action.escu.how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. action.escu.known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. @@ -6243,6 +6654,8 @@ action.notable.param.rule_description = This search detects writes to the recycl action.notable.param.rule_title = Suspicious writes to windows Recycle Bin action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6257,6 +6670,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. action.escu.how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. action.escu.known_false_positives = None identified @@ -6279,6 +6693,8 @@ action.notable.param.rule_description = This search looks for system processes t action.notable.param.rule_title = System Processes Run From Unexpected Locations action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6293,7 +6709,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE"]} -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None at this time @@ -6315,6 +6731,8 @@ action.notable.param.rule_description = This search looks for network traffic id action.notable.param.rule_title = TOR Traffic action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6329,7 +6747,7 @@ action.escu = 0 action.escu.enabled = 1 description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.mappings = {"cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -6352,6 +6770,8 @@ action.notable.param.rule_description = The fsutil.exe application is a legitima action.notable.param.rule_title = USN Journal Deletion action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6366,7 +6786,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. action.escu.known_false_positives = None identified @@ -6389,6 +6809,8 @@ action.notable.param.rule_description = This search looks for applications on th action.notable.param.rule_title = Uncommon Processes On Endpoint action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6403,7 +6825,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["DE.CM"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. action.escu.known_false_positives = @@ -6426,6 +6848,8 @@ action.notable.param.rule_description = Attackers often disable security tools t action.notable.param.rule_title = Unload Sysmon Filter Driver action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6440,6 +6864,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects loading of unsigned images by LSASS. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search detects loading of unsigned images by LSASS. action.escu.how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. action.escu.known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. @@ -6462,6 +6887,8 @@ action.notable.param.rule_description = This search detects loading of unsigned action.notable.param.rule_title = Unsigned Image Loaded by LSASS action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6476,6 +6903,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search gives you the hosts where a backup was attempted and then failed. action.escu.mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search gives you the hosts where a backup was attempted and then failed. action.escu.how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. action.escu.known_false_positives = None identified @@ -6497,6 +6925,8 @@ action.notable.param.rule_description = This search gives you the hosts where a action.notable.param.rule_title = Unsuccessful Netbackup backups action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6511,6 +6941,7 @@ action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships, from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some legitimate applications start with long command lines. @@ -6533,6 +6964,8 @@ action.notable.param.rule_description = Command lines that are extremely long ma action.notable.param.rule_title = Unusually Long Command Line action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6547,6 +6980,7 @@ action.escu = 0 action.escu.enabled = 1 description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. action.escu.how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. action.escu.known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. @@ -6569,6 +7003,8 @@ action.notable.param.rule_description = Command lines that are extremely long ma action.notable.param.rule_title = Unusually Long Command Line - MLTK action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6583,6 +7019,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.escu.mappings = {"cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.escu.how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. action.escu.known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. @@ -6604,6 +7041,8 @@ action.notable.param.rule_description = This search looks for unusually long str action.notable.param.rule_title = Unusually Long Content-Type Length action.notable.param.security_domain = network action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6618,6 +7057,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI permanent event subscriptions. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. @@ -6640,6 +7080,8 @@ action.notable.param.rule_description = This search looks for the creation of WM action.notable.param.rule_title = WMI Permanent Event Subscription action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6654,6 +7096,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI permanent event subscriptions. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for the creation of WMI permanent event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. action.escu.known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. @@ -6676,6 +7119,8 @@ action.notable.param.rule_description = This search looks for the creation of WM action.notable.param.rule_title = WMI Permanent Event Subscription - Sysmon action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6690,6 +7135,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of WMI temporary event subscriptions. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for the creation of WMI temporary event subscriptions. action.escu.how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. action.escu.known_false_positives = Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events. @@ -6711,6 +7157,8 @@ action.notable.param.rule_description = This search looks for the creation of WM action.notable.param.rule_title = WMI Temporary Event Subscription action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6725,6 +7173,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to identify the creation of multiple user accounts using the same email domain name. action.escu.mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136"], "nist": ["DE.CM", "DE.DP"]} +action.escu.data_models = [] action.escu.eli5 = This search is used to identify the creation of multiple user accounts using the same email domain name. action.escu.how_to_implement = We start with a dataset that provides visibility into the email address used for the account creation. In this example, we are narrowing our search down to the single web page that hosts the Magento2 e-commerce platform (via URI) used for account creation, the single http content-type to grab only the user's clicks, and the http field that provides the username (form_data), for performance reasons. After we have the username and email domain, we look for numerous account creations per email domain. Common data sources used for this detection are customized Apache logs or Splunk Stream. action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamolous behavior. This search will need to be customized to fit your environment—improving its fidelity by counting based on something much more specific, such as a device ID that may be present in your dataset. Consideration for whether the large number of registrations are occuring from a first-time seen domain may also be important. Extending the search window to look further back in time, or even calculating the average per hour/day for each email domain to look for an anomalous spikes, will improve this search. You can also use Shannon entropy or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness or similarity of the email name or email domain, as the names are often machine-generated. @@ -6747,6 +7196,8 @@ action.notable.param.rule_description = This search is used to identify the crea action.notable.param.rule_title = Web Fraud - Account Harvesting action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6761,6 +7212,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. action.escu.mappings = {"cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078"], "nist": ["DE.AE", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. action.escu.how_to_implement = Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior. @@ -6782,6 +7234,8 @@ action.notable.param.rule_description = This search is used to examine web sessi action.notable.param.rule_title = Web Fraud - Anomalous User Clickspeed action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6796,6 +7250,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to identify user accounts that share a common password. action.escu.mappings = {"cis20": ["CIS 16"], "nist": ["DE.DP"]} +action.escu.data_models = [] action.escu.eli5 = This search is used to identify user accounts that share a common password. action.escu.how_to_implement = We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. action.escu.known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior. @@ -6818,6 +7273,8 @@ action.notable.param.rule_description = This search is used to identify user acc action.notable.param.rule_title = Web Fraud - Password Sharing Across Accounts action.notable.param.security_domain = threat action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6832,7 +7289,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious processes on all systems labeled as web servers. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["PR.IP"]} -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] action.escu.eli5 = This search looks for suspicious processes on all systems labeled as web servers. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. action.escu.known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. @@ -6855,6 +7312,8 @@ action.notable.param.rule_description = This search looks for suspicious process action.notable.param.rule_title = Web Servers Executing Suspicious Processes action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6869,6 +7328,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows events that indicate one of the Windows event logs has been purged. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"]} +action.escu.data_models = [] action.escu.eli5 = This search looks for Windows events that indicate one of the Windows event logs has been purged. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting Windows event logs from your hosts. action.escu.known_false_positives = It is possible that these logs may be legitimately cleared by Administrators. @@ -6891,6 +7351,8 @@ action.notable.param.rule_description = This search looks for Windows events tha action.notable.param.rule_title = Windows Event Log Cleared action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6905,6 +7367,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for modifications to the hosts file on all Windows endpoints across your environment. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"]} +action.escu.data_models = [] action.escu.eli5 = The search looks for modifications to the hosts file on all Windows endpoints across your environment. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = There may be legitimate reasons for system administrators to add entries to this file. @@ -6927,6 +7390,8 @@ action.notable.param.rule_description = The search looks for modifications to th action.notable.param.rule_title = Windows hosts file modification action.notable.param.security_domain = endpoint action.notable.param.severity = medium +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 disabled = true enableSched = 1 counttype = number of events @@ -6945,14 +7410,16 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security - Baseline +action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security description = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "SamSam Ransomware"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. action.escu.how_to_implement = This search should be run on each new install of ESCU. disabled = true @@ -6963,14 +7430,16 @@ search = | inputlookup interesting_processes_lookup | search note!=ESCU* | input action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of API Calls per User ARN - Baseline +action.escu.full_search_name = ESCU - Baseline of API Calls per User ARN description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.creation_date = 2018-04-09 action.escu.modification_date = 2018-04-09 action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. disabled = true @@ -6981,14 +7450,16 @@ search = `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity. action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Command Line Length - MLTK - Baseline +action.escu.full_search_name = ESCU - Baseline of Command Line Length - MLTK description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. action.escu.creation_date = 2019-05-08 action.escu.modification_date = 2019-05-08 action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Unusual Processes"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. action.escu.how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. disabled = true @@ -6999,15 +7470,16 @@ search = | tstats `security_content_summariesonly` count min(_time) as start_tim action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of DNS Query Length - MLTK - Baseline +action.escu.full_search_name = ESCU - Baseline of DNS Query Length - MLTK description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. action.escu.creation_date = 2019-05-08 action.escu.modification_date = 2019-05-08 action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. disabled = true @@ -7018,14 +7490,16 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK - Baseline +action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. action.escu.creation_date = 2019-11-14 action.escu.modification_date = 2019-11-14 action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ @@ -7038,14 +7512,16 @@ search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_ru action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK - Baseline +action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. action.escu.creation_date = 2019-11-14 action.escu.modification_date = 2019-11-14 action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ @@ -7058,14 +7534,16 @@ search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excess action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Network ACL Activity by ARN - Baseline +action.escu.full_search_name = ESCU - Baseline of Network ACL Activity by ARN description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.creation_date = 2018-05-21 action.escu.modification_date = 2018-05-21 action.escu.analytic_story = ["AWS Network ACL Activity"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. disabled = true @@ -7076,14 +7554,16 @@ search = `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity. action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of S3 Bucket deletion activity by ARN - Baseline +action.escu.full_search_name = ESCU - Baseline of S3 Bucket deletion activity by ARN description = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.creation_date = 2018-07-17 action.escu.modification_date = 2018-07-17 action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. disabled = true @@ -7094,15 +7574,16 @@ search = `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentit action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of SMB Traffic - MLTK - Baseline +action.escu.full_search_name = ESCU - Baseline of SMB Traffic - MLTK description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. action.escu.creation_date = 2019-05-08 action.escu.modification_date = 2019-05-08 action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Netsh Abuse", "Ransomware"] -action.escu.data_models = Network_Traffic +action.escu.data_models = [Network_Traffic] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. action.escu.how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. disabled = true @@ -7113,14 +7594,16 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Security Group Activity by ARN - Baseline +action.escu.full_search_name = ESCU - Baseline of Security Group Activity by ARN description = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.creation_date = 2018-04-17 action.escu.modification_date = 2018-04-17 action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. disabled = true @@ -7131,14 +7614,16 @@ search = `cloudtrail` `security_group_api_calls` | spath output=arn path=userIde action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of blocked outbound traffic from AWS - Baseline +action.escu.full_search_name = ESCU - Baseline of blocked outbound traffic from AWS description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. action.escu.creation_date = 2018-05-07 action.escu.modification_date = 2018-05-07 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. disabled = true @@ -7149,14 +7634,16 @@ search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=17 action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of Unique IPs Connecting to Ports - Baseline +action.escu.full_search_name = ESCU - Count of Unique IPs Connecting to Ports description = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. action.escu.creation_date = 2017-09-13 action.escu.modification_date = 2017-09-13 -action.escu.data_models = Network_Traffic +action.escu.analytic_story = [] +action.escu.data_models = [Network_Traffic] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. action.escu.how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. disabled = true @@ -7167,14 +7654,16 @@ search = | tstats `security_content_summariesonly` count dc(All_Traffic.src) as action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of assets by category - Baseline +action.escu.full_search_name = ESCU - Count of assets by category description = This search shows you every asset category you have and the assets that belong to those categories. action.escu.creation_date = 2017-09-13 action.escu.modification_date = 2017-09-13 action.escu.analytic_story = ["Asset Tracking"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search shows you every asset category you have and the assets that belong to those categories. action.escu.how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. disabled = true @@ -7185,14 +7674,16 @@ search = | from datamodel Identity_Management.All_Assets | stats count values(nt action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Create a list of approved AWS service accounts - Baseline +action.escu.full_search_name = ESCU - Create a list of approved AWS service accounts description = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. action.escu.creation_date = 2018-12-03 action.escu.modification_date = 2018-12-03 action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. disabled = true @@ -7203,14 +7694,16 @@ search = `cloudtrail` errorCode=success | rename userName as identity | search N action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - DNSTwist Domain Names - Baseline +action.escu.full_search_name = ESCU - DNSTwist Domain Names description = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. action.escu.creation_date = 2018-10-08 action.escu.modification_date = 2018-10-08 action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. action.escu.how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. disabled = true @@ -7221,15 +7714,16 @@ search = | dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domai action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Discover DNS records - Baseline +action.escu.full_search_name = ESCU - Discover DNS records description = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup action.escu.creation_date = 2019-02-14 action.escu.modification_date = 2019-02-14 action.escu.analytic_story = ["DNS Hijacking"] -action.escu.data_models = Network_Resolution +action.escu.data_models = [Network_Resolution] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup action.escu.how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation disabled = true @@ -7240,14 +7734,16 @@ search = | inputlookup cim_corporate_email_domains.csv | inputlookup append=T ci action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Creating Remote Desktop Traffic - Baseline +action.escu.full_search_name = ESCU - Identify Systems Creating Remote Desktop Traffic description = This search counts the numbers of times the system has generated remote desktop traffic. action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 -action.escu.data_models = Network_Traffic +action.escu.analytic_story = [] +action.escu.data_models = [Network_Traffic] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search counts the numbers of times the system has generated remote desktop traffic. action.escu.how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. disabled = true @@ -7258,14 +7754,16 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Receiving Remote Desktop Traffic - Baseline +action.escu.full_search_name = ESCU - Identify Systems Receiving Remote Desktop Traffic description = This search counts the numbers of times the system has created remote desktop traffic action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 -action.escu.data_models = Network_Traffic +action.escu.analytic_story = [] +action.escu.data_models = [Network_Traffic] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search counts the numbers of times the system has created remote desktop traffic action.escu.how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. disabled = true @@ -7276,14 +7774,16 @@ search = | tstats `security_content_summariesonly` count from datamodel=Network_ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Using Remote Desktop - Baseline +action.escu.full_search_name = ESCU - Identify Systems Using Remote Desktop description = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 -action.escu.data_models = Endpoint +action.escu.analytic_story = [] +action.escu.data_models = [Endpoint] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. disabled = true @@ -7294,14 +7794,16 @@ search = | tstats `security_content_summariesonly` count from datamodel=Endpoint action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Successful Backups - Baseline +action.escu.full_search_name = ESCU - Monitor Successful Backups description = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.analytic_story = ["Monitor Backup Solution"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. disabled = true @@ -7312,14 +7814,16 @@ search = `netbackup` "Disk/Partition backup completed successfully." | bucket _t action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Unsuccessful Backups - Baseline +action.escu.full_search_name = ESCU - Monitor Unsuccessful Backups description = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.analytic_story = ["Monitor Backup Solution"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. disabled = true @@ -7330,14 +7834,16 @@ search = `netbackup` "An error occurred, failed to backup." | bucket _time span= action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Cross Account Activity - Baseline +action.escu.full_search_name = ESCU - Previously Seen AWS Cross Account Activity description = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. action.escu.creation_date = 2018-06-04 action.escu.modification_date = 2018-06-04 action.escu.analytic_story = ["AWS Cross Account Activity"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. disabled = true @@ -7348,14 +7854,16 @@ search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId pa action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Provisioning Activity Sources - Baseline +action.escu.full_search_name = ESCU - Previously Seen AWS Provisioning Activity Sources description = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. action.escu.creation_date = 2018-03-16 action.escu.modification_date = 2018-03-16 action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. disabled = true @@ -7366,14 +7874,16 @@ search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceI action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Regions - Baseline +action.escu.full_search_name = ESCU - Previously Seen AWS Regions description = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days action.escu.creation_date = 2018-01-08 action.escu.modification_date = 2018-01-08 action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. disabled = true @@ -7384,15 +7894,16 @@ search = `cloudtrail` StartInstances | stats earliest(_time) as earliest latest( action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Creations By User - Baseline +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Creations By User description = This search builds a table of previously seen users that have launched a cloud compute instance. action.escu.creation_date = 2018-03-15 action.escu.modification_date = 2018-03-15 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen users that have launched a cloud compute instance. action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. disabled = true @@ -7403,15 +7914,16 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from d action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Images - Baseline +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Images description = This search builds a table of previously seen images used to launch cloud compute instances action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen images used to launch cloud compute instances action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. disabled = true @@ -7422,15 +7934,16 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from d action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Instance Types - Baseline +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Instance Types description = This search builds a table of previously seen cloud compute instance types action.escu.creation_date = 2019-10-03 action.escu.modification_date = 2019-10-03 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen cloud compute instance types action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. disabled = true @@ -7441,15 +7954,16 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from d action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Regions - Baseline +action.escu.full_search_name = ESCU - Previously Seen Cloud Regions description = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days action.escu.creation_date = 2019-10-02 action.escu.modification_date = 2019-10-02 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = Cloud_Infrastructure +action.escu.data_models = [Cloud_Infrastructure] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. disabled = true @@ -7460,14 +7974,16 @@ search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from d action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 AMIs - Baseline +action.escu.full_search_name = ESCU - Previously Seen EC2 AMIs description = This search builds a table of previously seen AMIs used to launch EC2 instances action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["AWS Cryptomining"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen AMIs used to launch EC2 instances action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. disabled = true @@ -7478,14 +7994,16 @@ search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestP action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Instance Types - Baseline +action.escu.full_search_name = ESCU - Previously Seen EC2 Instance Types description = This search builds a table of previously seen EC2 instance types action.escu.creation_date = 2018-03-08 action.escu.modification_date = 2018-03-08 action.escu.analytic_story = ["AWS Cryptomining"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen EC2 instance types action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. disabled = true @@ -7496,14 +8014,16 @@ search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestP action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Launches By User - Baseline +action.escu.full_search_name = ESCU - Previously Seen EC2 Launches By User description = This search builds a table of previously seen ARNs that have launched a EC2 instance. action.escu.creation_date = 2018-03-15 action.escu.modification_date = 2018-03-15 action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. disabled = true @@ -7514,14 +8034,16 @@ search = `cloudtrail` eventName=RunInstances errorCode=success | rename userIden action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Modifications By User - Baseline +action.escu.full_search_name = ESCU - Previously Seen EC2 Modifications By User description = This search builds a table of previously seen ARNs that have launched a EC2 instance. action.escu.creation_date = 2018-04-05 action.escu.modification_date = 2018-04-05 action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. disabled = true @@ -7532,14 +8054,16 @@ search = `cloudtrail` `ec2_modification_api_calls` errorCode=success | spath out action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Running Windows Services - Baseline +action.escu.full_search_name = ESCU - Previously Seen Running Windows Services description = This collects the services that have been started across your entire enterprise. action.escu.creation_date = 2020-01-13 action.escu.modification_date = 2020-01-13 action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This collects the services that have been started across your entire enterprise. action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. disabled = true @@ -7550,14 +8074,16 @@ search = `wineventlog_system` signature_id=7036 | rename param1 as service_name action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen API call per user roles in CloudTrail - Baseline +action.escu.full_search_name = ESCU - Previously seen API call per user roles in CloudTrail description = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. action.escu.creation_date = 2018-04-16 action.escu.modification_date = 2018-04-16 action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. disabled = true @@ -7568,14 +8094,16 @@ search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=A action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen S3 bucket access by remote IP - Baseline +action.escu.full_search_name = ESCU - Previously seen S3 bucket access by remote IP description = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" action.escu.creation_date = 2018-06-28 action.escu.modification_date = 2018-06-28 action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. disabled = true @@ -7586,15 +8114,16 @@ search = `aws_s3_accesslogs` http_status=200 | stats earliest(_time) as earlie action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen command line arguments - Baseline +action.escu.full_search_name = ESCU - Previously seen command line arguments description = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. action.escu.creation_date = 2019-03-01 action.escu.modification_date = 2019-03-01 action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Hidden Cobra Malware", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] -action.escu.data_models = Endpoint +action.escu.data_models = [Endpoint] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. disabled = true @@ -7605,14 +8134,16 @@ search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen users in CloudTrail - Baseline +action.escu.full_search_name = ESCU - Previously seen users in CloudTrail description = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. action.escu.creation_date = 2018-04-30 action.escu.modification_date = 2018-04-30 action.escu.analytic_story = ["Suspicious AWS Login Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. disabled = true @@ -7623,14 +8154,16 @@ search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Systems Ready for Spectre-Meltdown Windows Patch - Baseline +action.escu.full_search_name = ESCU - Systems Ready for Spectre-Meltdown Windows Patch description = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. action.escu.creation_date = 2018-01-08 action.escu.modification_date = 2018-01-08 action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. disabled = true @@ -7641,14 +8174,16 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Update previously seen users in CloudTrail - Baseline +action.escu.full_search_name = ESCU - Update previously seen users in CloudTrail description = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. action.escu.creation_date = 2018-04-30 action.escu.modification_date = 2018-04-30 action.escu.analytic_story = ["Suspicious AWS Login Activities"] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. disabled = true @@ -7659,13 +8194,16 @@ search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Failures - Baseline +action.escu.full_search_name = ESCU - Windows Updates Install Failures description = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. action.escu.creation_date = 2017-09-14 action.escu.modification_date = 2017-09-14 +action.escu.analytic_story = [] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. action.escu.how_to_implement = You must be ingesting your Windows Update Logs disabled = true @@ -7676,13 +8214,16 @@ search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FRO action.escu = 0 action.escu.enabled = 1 action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Successes - Baseline +action.escu.full_search_name = ESCU - Windows Updates Install Successes description = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. action.escu.creation_date = 2017-09-14 action.escu.modification_date = 2017-09-14 +action.escu.analytic_story = [] +action.escu.data_models = [] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto +action.escu.providing_technologies = [] action.escu.eli5 = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. action.escu.how_to_implement = You must be ingesting your Windows Update Logs disabled = true @@ -7697,12 +8238,18 @@ search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FRO action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN - Response Task +action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. action.escu.creation_date = 2019-04-30 action.escu.modification_date = 2019-04-30 action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Cloud Cryptomining", "Command and Control", "Suspicious AWS EC2 Activities", "Suspicious AWS Login Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Unusual AWS EC2 Modifications"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7712,12 +8259,18 @@ search = | search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _tim action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By AccessKeyId - Response Task +action.escu.full_search_name = ESCU - AWS Investigate User Activities By AccessKeyId description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. action.escu.creation_date = 2018-06-08 action.escu.modification_date = 2018-06-08 action.escu.analytic_story = ["AWS Cross Account Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7727,12 +8280,18 @@ search = | search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyI action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By Source User - Response Task +action.escu.full_search_name = ESCU - AWS Investigate User Activities By Source User description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. action.escu.creation_date = 2018-06-08 action.escu.modification_date = 2018-06-08 action.escu.analytic_story = ["AWS Cross Account Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7742,12 +8301,18 @@ search = | search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network ACL Details from ID - Response Task +action.escu.full_search_name = ESCU - AWS Network ACL Details from ID description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID action.escu.creation_date = 2017-01-22 action.escu.modification_date = 2017-01-22 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7757,12 +8322,18 @@ search = | search sourcetype=aws:description id={networkAclId} | table id accoun action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network Interface details via resourceId - Response Task +action.escu.full_search_name = ESCU - AWS Network Interface details via resourceId description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. action.escu.creation_date = 2018-05-07 action.escu.modification_date = 2018-05-07 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7772,12 +8343,18 @@ search = | search sourcetype=aws:config resourceId={resourceId} | table _time AR action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS S3 Bucket details via bucketName - Response Task +action.escu.full_search_name = ESCU - AWS S3 Bucket details via bucketName description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. action.escu.creation_date = 2018-06-26 action.escu.modification_date = 2018-06-26 action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7787,12 +8364,18 @@ search = | search sourcetype=aws:config resourceId={bucketName} | table resource action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - All backup logs for host - Response Task +action.escu.full_search_name = ESCU - All backup logs for host description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.analytic_story = ["Monitor Backup Solution"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7802,12 +8385,18 @@ search = | search sourcetype="netbackup_logs" dest={dest} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Amazon EKS Kubernetes activity by src ip - Response Task +action.escu.full_search_name = ESCU - Amazon EKS Kubernetes activity by src ip description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address action.escu.creation_date = 2020-04-13 action.escu.modification_date = 2020-04-13 action.escu.analytic_story = ["Kubernetes Scanning Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7817,12 +8406,18 @@ search = sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceI action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - GCP Kubernetes activity by src ip - Response Task +action.escu.full_search_name = ESCU - GCP Kubernetes activity by src ip description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address action.escu.creation_date = 2020-04-13 action.escu.modification_date = 2020-04-13 action.escu.analytic_story = ["Kubernetes Scanning Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7832,12 +8427,18 @@ search = sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadat action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From City - Response Task +action.escu.full_search_name = ESCU - Get All AWS Activity From City description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7847,12 +8448,18 @@ search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Country - Response Task +action.escu.full_search_name = ESCU - Get All AWS Activity From Country description = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7862,12 +8469,18 @@ search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From IP Address - Response Task +action.escu.full_search_name = ESCU - Get All AWS Activity From IP Address description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Network ACL Activity", "AWS Suspicious Provisioning Activities", "Command and Control", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7877,12 +8490,18 @@ search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Region - Response Task +action.escu.full_search_name = ESCU - Get All AWS Activity From Region description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. action.escu.creation_date = 2018-03-19 action.escu.modification_date = 2018-03-19 action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7892,13 +8511,18 @@ search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | searc action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Authentication Logs For Endpoint - Response Task +action.escu.full_search_name = ESCU - Get Authentication Logs For Endpoint description = This search returns all users that have attempted to access a particular endpoint. action.escu.creation_date = 2017-11-01 action.escu.modification_date = 2017-11-01 action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.data_models = Authentication +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] action.escu.eli5 = This search returns all users that have attempted to access a particular endpoint. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7908,12 +8532,18 @@ search = | tstats count from datamodel=Authentication where Authentication.dest= action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Backup Logs For Endpoint - Response Task +action.escu.full_search_name = ESCU - Get Backup Logs For Endpoint description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. action.escu.creation_date = 2017-09-14 action.escu.modification_date = 2017-09-14 action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7923,12 +8553,18 @@ search = | search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPU action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Certificate logs for a domain - Response Task +action.escu.full_search_name = ESCU - Get Certificate logs for a domain description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. action.escu.creation_date = 2019-04-29 action.escu.modification_date = 2019-04-29 action.escu.analytic_story = ["Common Phishing Frameworks"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7938,12 +8574,18 @@ search = | tstats `summariesonly` count min(_time) as firstTime max(_time) as la action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS Server History for a host - Response Task +action.escu.full_search_name = ESCU - Get DNS Server History for a host description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DNS Hijacking", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Host Redirection", "Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7953,13 +8595,18 @@ search = | search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS traffic ratio - Response Task +action.escu.full_search_name = ESCU - Get DNS traffic ratio description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.data_models = Network_Traffic +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Network_Traffic] action.escu.eli5 = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7969,12 +8616,18 @@ search = | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get EC2 Instance Details by instanceId - Response Task +action.escu.full_search_name = ESCU - Get EC2 Instance Details by instanceId description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field action.escu.creation_date = 2018-02-12 action.escu.modification_date = 2018-02-12 action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Unusual AWS EC2 Modifications"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7984,12 +8637,18 @@ search = | search sourcetype="aws:description" source="*:ec2_instances"| dedup i action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get EC2 Launch Details - Response Task +action.escu.full_search_name = ESCU - Get EC2 Launch Details description = This search returns some of the launch details for a EC2 instance. action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns some of the launch details for a EC2 instance. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -7999,12 +8658,18 @@ search = | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Email Info - Response Task +action.escu.full_search_name = ESCU - Get Email Info description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8014,12 +8679,18 @@ search = | from datamodel Email.All_Email | search message_id={message_id} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Emails From Specific Sender - Response Task +action.escu.full_search_name = ESCU - Get Emails From Specific Sender description = This search returns all the emails from a specific sender over the last 24 and next hours. action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails", "Web Fraud Detection"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns all the emails from a specific sender over the last 24 and next hours. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8029,13 +8700,18 @@ search = | from datamodel Email.All_Email | search src_user={src_user} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task +action.escu.full_search_name = ESCU - Get First Occurrence and Last Occurrence of a MAC Address description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. action.escu.creation_date = 2017-09-13 action.escu.modification_date = 2017-09-13 action.escu.analytic_story = ["Asset Tracking"] -action.escu.data_models = Network_Sessions +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Network_Sessions] action.escu.eli5 = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8045,12 +8721,18 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get History Of Email Sources - Response Task +action.escu.full_search_name = ESCU - Get History Of Email Sources description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. action.escu.creation_date = 2019-02-21 action.escu.modification_date = 2019-02-21 -action.escu.data_models = Email +action.escu.analytic_story = [] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Email] action.escu.eli5 = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8060,12 +8742,18 @@ search = |tstats `security_content_summariesonly` values(All_Email.dest) as dest action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For Endpoint - Response Task +action.escu.full_search_name = ESCU - Get Logon Rights Modifications For Endpoint description = This search allows you to retrieve any modifications to logon rights associated with a specific host. action.escu.creation_date = 2017-09-12 action.escu.modification_date = 2017-09-12 action.escu.analytic_story = ["Account Monitoring and Controls"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search allows you to retrieve any modifications to logon rights associated with a specific host. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8075,12 +8763,18 @@ search = | search eventtype=wineventlog_security (signature_id=4718 OR signature action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For User - Response Task +action.escu.full_search_name = ESCU - Get Logon Rights Modifications For User description = This search allows you to retrieve any modifications to logon rights for a specific user account. action.escu.creation_date = 2019-02-27 action.escu.modification_date = 2019-02-27 action.escu.analytic_story = ["Account Monitoring and Controls"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search allows you to retrieve any modifications to logon rights for a specific user account. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8090,12 +8784,18 @@ search = | search eventtype=wineventlog_security (signature_id=4718 OR signature action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable History - Response Task +action.escu.full_search_name = ESCU - Get Notable History description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 action.escu.analytic_story = ["AWS Cross Account Activity", "AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual AWS EC2 Modifications", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8105,12 +8805,18 @@ search = | search `notable` | search dest={dest} | table _time, rule_name, owner action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable Info - Response Task +action.escu.full_search_name = ESCU - Get Notable Info description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8120,11 +8826,18 @@ search = | search `notable_by_id({event_id})` | table time, rule_name, dest, des action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task +action.escu.full_search_name = ESCU - Get Outbound Emails to Hidden Cobra Threat Actors description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. action.escu.creation_date = 2018-06-14 action.escu.modification_date = 2018-06-14 +action.escu.analytic_story = [] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8134,12 +8847,18 @@ search = | from datamodel Email.All_Email | search recipient=misswang8107@gmail. action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Parent Process Info - Response Task +action.escu.full_search_name = ESCU - Get Parent Process Info description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest action.escu.creation_date = 2019-02-28 action.escu.modification_date = 2019-02-28 action.escu.analytic_story = ["Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Phishing Payloads", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8149,13 +8868,18 @@ search = | tstats `summariesonly` count values(Processes.process) as process min action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process File Activity - Response Task +action.escu.full_search_name = ESCU - Get Process File Activity description = This search returns the file activity for a specific process on a specific endpoint action.escu.creation_date = 2019-11-06 action.escu.modification_date = 2019-11-06 action.escu.analytic_story = ["DHS Report TA18-074A"] -action.escu.data_models = Endpoint +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] action.escu.eli5 = This search returns the file activity for a specific process on a specific endpoint +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8165,13 +8889,18 @@ search = | tstats `security_content_summariesonly` values(Filesystem.file_name) action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Info - Response Task +action.escu.full_search_name = ESCU - Get Process Info description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 action.escu.analytic_story = ["AWS Network ACL Activity", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.data_models = Endpoint +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] action.escu.eli5 = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8181,13 +8910,18 @@ search = | tstats `security_content_summariesonly` count min(_time) max(_time) action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Information For Port Activity - Response Task +action.escu.full_search_name = ESCU - Get Process Information For Port Activity description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Use of Cleartext Protocols"] -action.escu.data_models = Endpoint +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] action.escu.eli5 = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8197,13 +8931,18 @@ search = | tstats `security_content_summariesonly` count min(_time) max(_time) action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Registry Activity - Response Task +action.escu.full_search_name = ESCU - Get Process Registry Activity description = This search returns the registry activity for a specific process on a specific endpoint action.escu.creation_date = 2019-11-06 action.escu.modification_date = 2019-11-06 action.escu.analytic_story = ["DHS Report TA18-074A"] -action.escu.data_models = Endpoint +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] action.escu.eli5 = This search returns the registry activity for a specific process on a specific endpoint +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8213,13 +8952,18 @@ search = | tstats `security_content_summariesonly` values(Registry.registry_key_ action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Responsible For The DNS Traffic - Response Task +action.escu.full_search_name = ESCU - Get Process Responsible For The DNS Traffic description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 action.escu.analytic_story = ["AWS Network ACL Activity", "Brand Monitoring", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.data_models = Endpoint +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] action.escu.eli5 = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8229,12 +8973,18 @@ search = | tstats `security_content_summariesonly` count min(_time) max(_time) action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Registry Activities - Response Task +action.escu.full_search_name = ESCU - Get Registry Activities description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. action.escu.creation_date = 2019-03-01 action.escu.modification_date = 2019-03-01 action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Persistence Techniques", "Windows Privilege Escalation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8244,12 +8994,18 @@ search = | tstats `security_content_summariesonly` values(Registry.registry_path action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For Endpoint - Response Task +action.escu.full_search_name = ESCU - Get Risk Modifiers For Endpoint description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) action.escu.creation_date = 2017-10-19 action.escu.modification_date = 2017-10-19 action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8259,12 +9015,18 @@ search = | from datamodel:Risk.All_Risk | search risk_object_type=system risk_ob action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For User - Response Task +action.escu.full_search_name = ESCU - Get Risk Modifiers For User description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user action.escu.creation_date = 2017-10-19 action.escu.modification_date = 2017-10-19 action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8274,12 +9036,18 @@ search = | from datamodel:Risk.All_Risk | search risk_object_type=user risk_obje action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Sysmon WMI Activity for Host - Response Task +action.escu.full_search_name = ESCU - Get Sysmon WMI Activity for Host description = This search queries Sysmon WMI events for the host of interest. action.escu.creation_date = 2018-10-23 action.escu.modification_date = 2018-10-23 action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search queries Sysmon WMI events for the host of interest. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8289,12 +9057,18 @@ search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventC action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Update Logs For Endpoint - Response Task +action.escu.full_search_name = ESCU - Get Update Logs For Endpoint description = This search will tell you give you the update logs for a specific endpoint for the last week. action.escu.creation_date = 2017-08-24 action.escu.modification_date = 2017-08-24 action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search will tell you give you the update logs for a specific endpoint for the last week. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8304,12 +9078,18 @@ search = | from datamodel Updates.Updates | search (vendor_product="Microsoft W action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get User Information from Identity Table - Response Task +action.escu.full_search_name = ESCU - Get User Information from Identity Table description = Gather more information about the user identified in the Notable Event. action.escu.creation_date = 2017-09-20 action.escu.modification_date = 2017-09-20 action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = Gather more information about the user identified in the Notable Event. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8319,12 +9099,18 @@ search = | `identities` | search identity={user} | table _time, identity, first, action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Vulnerability Logs For Endpoint - Response Task +action.escu.full_search_name = ESCU - Get Vulnerability Logs For Endpoint description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. action.escu.creation_date = 2017-09-10 action.escu.modification_date = 2017-09-10 action.escu.analytic_story = ["ColdRoot MacOS RAT", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware", "Windows Log Manipulation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search will show you any vulnerabilities noted for a specific endpoint for the last week. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8334,12 +9120,18 @@ search = | from datamodel Vulnerabilities.Vulnerabilities | search dest={dest} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Web Session Information via session id - Response Task +action.escu.full_search_name = ESCU - Get Web Session Information via session id description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. action.escu.creation_date = 2018-10-08 action.escu.modification_date = 2018-10-08 action.escu.analytic_story = ["Web Fraud Detection"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8349,12 +9141,18 @@ search = | search sourcetype=stream:http {session_id} | stats values(url) values action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS ECR container listing activity - Response Task +action.escu.full_search_name = ESCU - Investigate AWS ECR container listing activity description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. action.escu.creation_date = 2020-02-20 action.escu.modification_date = 2020-02-20 action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8364,12 +9162,18 @@ search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datam action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS User Activities by user field - Response Task +action.escu.full_search_name = ESCU - Investigate AWS User Activities by user field description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8379,12 +9183,18 @@ search = | search sourcetype=aws:cloudtrail user={user} | table _time userIdenti action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS activities via region name - Response Task +action.escu.full_search_name = ESCU - Investigate AWS activities via region name description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user action.escu.creation_date = 2018-02-09 action.escu.modification_date = 2018-02-09 action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8394,12 +9204,18 @@ search = | search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename reques action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Cloud Compute Instance Activities - Response Task +action.escu.full_search_name = ESCU - Investigate Cloud Compute Instance Activities description = This search returns a logs of events that operated on the compute instance. action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns a logs of events that operated on the compute instance. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8409,13 +9225,18 @@ search = | from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fi action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Failed Logins for Multiple Destinations - Response Task +action.escu.full_search_name = ESCU - Investigate Failed Logins for Multiple Destinations description = This search returns failed logins to multiple destinations by user. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] -action.escu.data_models = Authentication +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] action.escu.eli5 = This search returns failed logins to multiple destinations by user. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8425,12 +9246,18 @@ search = | tstats count `security_content_summariesonly` earliest(_time) as firs action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Network Traffic From src ip - Response Task +action.escu.full_search_name = ESCU - Investigate Network Traffic From src ip description = This search allows you to find all the network traffic from a specific IP address. action.escu.creation_date = 2018-06-15 action.escu.modification_date = 2018-06-15 action.escu.analytic_story = ["ColdRoot MacOS RAT", "Splunk Enterprise Vulnerability CVE-2018-11409"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search allows you to find all the network traffic from a specific IP address. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8440,12 +9267,18 @@ search = | from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by IP Address - Response Task +action.escu.full_search_name = ESCU - Investigate Okta Activity by IP Address description = This search returns all okta events from a specific IP address. action.escu.creation_date = 2020-04-02 action.escu.modification_date = 2020-04-02 action.escu.analytic_story = ["Suspicious Okta Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns all okta events from a specific IP address. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8455,12 +9288,18 @@ search = eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext. action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by app - Response Task +action.escu.full_search_name = ESCU - Investigate Okta Activity by app description = This search returns all okta events associated with a specific app action.escu.creation_date = 2020-04-02 action.escu.modification_date = 2020-04-02 action.escu.analytic_story = ["Suspicious Okta Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns all okta events associated with a specific app +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8470,12 +9309,18 @@ search = eventtype=okta_log app={app} | rename client.geographicalContext.countr action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Hash Attempts - Response Task +action.escu.full_search_name = ESCU - Investigate Pass the Hash Attempts description = This search hunts for dumped NTLM hashes used for pass the hash. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search hunts for dumped NTLM hashes used for pass the hash. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8485,12 +9330,18 @@ search = `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackag action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Ticket Attempts - Response Task +action.escu.full_search_name = ESCU - Investigate Pass the Ticket Attempts description = This search hunts for dumped kerberos ticket from LSASS memory. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search hunts for dumped kerberos ticket from LSASS memory. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8500,13 +9351,18 @@ search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=use action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Previous Unseen User - Response Task +action.escu.full_search_name = ESCU - Investigate Previous Unseen User description = This search returns previous unseen user, which didn't log in for 30 days. action.escu.creation_date = 2019-12-10 action.escu.modification_date = 2019-12-10 action.escu.analytic_story = ["Credential Dumping"] -action.escu.data_models = Authentication +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] action.escu.eli5 = This search returns previous unseen user, which didn't log in for 30 days. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8516,13 +9372,18 @@ search = | tstats count `security_content_summariesonly` earliest(_time) as firs action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Successful Remote Desktop Authentications - Response Task +action.escu.full_search_name = ESCU - Investigate Successful Remote Desktop Authentications description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. action.escu.creation_date = 2018-12-14 action.escu.modification_date = 2018-12-14 action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement", "SamSam Ransomware"] -action.escu.data_models = Authentication +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] action.escu.eli5 = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8532,12 +9393,18 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Suspicious Strings in HTTP Header - Response Task +action.escu.full_search_name = ESCU - Investigate Suspicious Strings in HTTP Header description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. action.escu.creation_date = 2017-10-20 action.escu.modification_date = 2017-10-20 action.escu.analytic_story = ["Apache Struts Vulnerability"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8547,12 +9414,18 @@ search = | search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In All Cloud Regions - Response Task +action.escu.full_search_name = ESCU - Investigate User Activities In All Cloud Regions description = This search lists all the logged cloud infrastructure activities by a specific cloud user action.escu.creation_date = 2019-04-30 action.escu.modification_date = 2019-04-30 action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8562,12 +9435,18 @@ search = | from datamodel:Cloud_Infrastructure.Compute | search user={src_user} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Okta - Response Task +action.escu.full_search_name = ESCU - Investigate User Activities In Okta description = This search returns all okta events by a specific user action.escu.creation_date = 2020-04-02 action.escu.modification_date = 2020-04-02 action.escu.analytic_story = ["Suspicious Okta Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search returns all okta events by a specific user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8577,12 +9456,18 @@ search = eventtype=okta_log user={user} | rename client.geographicalContext.coun action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Single Cloud Region - Response Task +action.escu.full_search_name = ESCU - Investigate User Activities In Single Cloud Region description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region action.escu.creation_date = 2019-04-30 action.escu.modification_date = 2019-04-30 action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8592,12 +9477,18 @@ search = | from datamodel:Cloud_Infrastructure.Compute | search region={region} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From Host - Response Task +action.escu.full_search_name = ESCU - Investigate Web Activity From Host description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. action.escu.creation_date = 2017-11-09 action.escu.modification_date = 2017-11-09 action.escu.analytic_story = ["Brand Monitoring", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8607,12 +9498,18 @@ search = | from datamodel Web.Web | search src={dest} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From src ip - Response Task +action.escu.full_search_name = ESCU - Investigate Web Activity From src ip description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. action.escu.creation_date = 2018-06-15 action.escu.modification_date = 2018-06-15 action.escu.analytic_story = ["ColdRoot MacOS RAT", "Dynamic DNS", "Splunk Enterprise Vulnerability CVE-2018-11409"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8622,13 +9519,18 @@ search = | from datamodel Web.Web | search src={src_ip} action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web POSTs From src - Response Task +action.escu.full_search_name = ESCU - Investigate Web POSTs From src description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. action.escu.creation_date = 2018-12-06 action.escu.modification_date = 2018-12-06 action.escu.analytic_story = ["Apache Struts Vulnerability"] -action.escu.data_models = Web +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Web] action.escu.eli5 = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false @@ -8638,11 +9540,18 @@ search = | tstats `security_content_summariesonly` values(Web.url) as url from d action.escu = 0 action.escu.enabled = 1 action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Process Chain Analysis - Response Task +action.escu.full_search_name = ESCU - Process Chain Analysis description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. action.escu.creation_date = 2020-04-29 action.escu.modification_date = 2020-04-29 +action.escu.analytic_story = [] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] action.escu.eli5 = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 7d223c85d5..f884bb7159 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:31:11 UTC +# On Date: 2020-05-11T08:08:29 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 82661903ad..9109b57c41 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T07:31:11 UTC +# On Date: 2020-05-11T08:08:29 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] +searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable History"] +searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities"] +searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host", "ESCU - Get Notable History"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +searches = ["ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] +searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info"] +searches = ["ESCU - File with Samsam Extension - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info"] +searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Shim Database File Creation - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Process Info"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From fa599c2624a92e354beaf7fda1d36330da13ffdc Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 14:21:06 +0200 Subject: [PATCH 35/93] bug in generate --- bin/jinja2_templates/savedsearches.j2 | 82 - bin/jinja2_templates/savedsearches.j2.real | 250 +++ package/default/analytic_stories.conf | 120 +- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2158 +------------------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 126 +- 7 files changed, 376 insertions(+), 2364 deletions(-) create mode 100644 bin/jinja2_templates/savedsearches.j2.real diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 07f11de854..1a01d5a83f 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -88,88 +88,6 @@ search = {{ detection.search }} ### END ESCU DETECTIONS ### -### ESCU BASELINES ### - -{% for baseline in baselines %} -[ESCU - {{ baseline.name }} - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - {{ baseline.name }} -description = {{ baseline.description }} -action.escu.creation_date = {{ baseline.date }} -action.escu.modification_date = {{ baseline.date }} -{% if baseline.tags.analytics_story is defined %} -action.escu.analytic_story = {{ baseline.tags.analytics_story | tojson }} -{% else %} -action.escu.analytic_story = [] -{% endif %} -{% if baseline.data_model is defined %} -action.escu.data_models = [{{ baseline.data_model }}] -{% else %} -action.escu.data_models = [] -{% endif %} -dispatch.earliest_time = {{ baseline.deployment.scheduling.earliest_time }} -dispatch.latest_time = {{ baseline.deployment.scheduling.latest_time }} -{% if baseline.deployment.scheduling.schedule_window is defined %} -schedule_window = {{ baseline.deployment.scheduling.schedule_window }} -{% endif %} -{% if baseline.providing_technologies is defined %} -action.escu.providing_technologies = {{ baseline.providing_technologies | tojson }} -{% else %} -action.escu.providing_technologies = [] -{% endif %} -action.escu.eli5 = {{ baseline.description }} -{% if baseline.how_to_implement is defined %} -action.escu.how_to_implement = {{ baseline.how_to_implement }} -{% else %} -action.escu.how_to_implement = none -{% endif %} -disabled = true -is_visible = false -search = {{ baseline.search }} - -{% endfor %} - - -### ESCU RESPONSE TASKS ### - -{% for response_task in response_tasks %} -{% if response_task.search is defined %} -[ESCU - {{ response_task.name }} - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - {{ response_task.name }} -description = {{ response_task.description }} -action.escu.creation_date = {{ response_task.date }} -action.escu.modification_date = {{ response_task.date }} -{% if response_task.tags is defined %} -action.escu.analytic_story = {{ response_task.tags.analytics_story | tojson }} -{% else %} -action.escu.analytic_story = [] -{% endif %} -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -{% if response_task.data_model is defined %} -action.escu.data_models = [{{ response_task.data_model }}] -{% else %} -action.escu.data_models = [] -{% endif %} -action.escu.eli5 = {{ response_task.description }} -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = {{ response_task.search }} - -{% endif %} -{% endfor %} - - -### END ESCU RESPONSE TASKS ### ### USAGE DASHBOARD CONFIGURATIONS ### diff --git a/bin/jinja2_templates/savedsearches.j2.real b/bin/jinja2_templates/savedsearches.j2.real new file mode 100644 index 0000000000..07f11de854 --- /dev/null +++ b/bin/jinja2_templates/savedsearches.j2.real @@ -0,0 +1,250 @@ +############# +# Automatically generated by generator.py in splunk/security-content +# On Date: {{ time }} UTC +# Author: Splunk Security Research +# Contact: research@splunk.com +############# + +### ESCU DETECTIONS ### + +{% for detection in detections %} +[ESCU - {{ detection.name }} - Rule] +action.escu = 0 +action.escu.enabled = 1 +description = {{ detection.description }} +action.escu.mappings = {{ detection.mappings | tojson }} +{% if detection.data_model is defined %} +action.escu.data_models = [{{ detection.data_model }}] +{% else %} +action.escu.data_models = [] +{% endif %} +action.escu.eli5 = {{ detection.description }} +{% if detection.how_to_implement is defined %} +action.escu.how_to_implement = {{ detection.how_to_implement }} +{% else %} +action.escu.how_to_implement = none +{% endif %} +{% if detection.known_false_positives is defined %} +action.escu.known_false_positives = {{ detection.known_false_positives }} +{% else %} +action.escu.known_false_positives = None +{% endif %} +action.escu.creation_date = {{ detection.date }} +action.escu.modification_date = {{ detection.date }} +action.escu.confidence = high +action.escu.full_search_name = ESCU - {{ detection.name }} - Rule +action.escu.search_type = detection +{% if detection.providing_technologies is defined %} +action.escu.providing_technologies = {{ detection.providing_technologies | tojson }} +{% else %} +action.escu.providing_technologies = [] +{% endif %} +{% if detection.tags.analytics_story is defined %} +action.escu.analytic_story = {{ detection.tags.analytics_story | tojson }} +{% endif %} +cron_schedule = {{ detection.deployment.scheduling.cron_schedule }} +dispatch.earliest_time = {{ detection.deployment.scheduling.earliest_time }} +dispatch.latest_time = {{ detection.deployment.scheduling.latest_time }} +action.correlationsearch.enabled = 1 +action.correlationsearch.label = ESCU - {{ detection.name }} - Rule +{% if detection.deployment.scheduling.schedule_window is defined %} +schedule_window = {{ detection.deployment.scheduling.schedule_window }} +{% endif %} +{% if detection.deployment.alert_action.notable is defined %} +action.notable = 1 +{% if detection.nes_fields is defined %} +action.notable.param.nes_fields = {{ detection.nes_fields }} +{% endif %} +action.notable.param.rule_description = {{ detection.deployment.alert_action.notable.rule_description | custom_jinja2_enrichment_filter(detection) }} +action.notable.param.rule_title = {{ detection.deployment.alert_action.notable.rule_title | custom_jinja2_enrichment_filter(detection) }} +action.notable.param.security_domain = {{ detection.tags.security_domain }} +action.notable.param.severity = medium +{% endif %} +{% if detection.deployment.alert_action.email is defined %} +action.email.subject.alert = {{ detection.deployment.alert_action.email.subject | custom_jinja2_enrichment_filter(detection) }} +action.email.to = {{ detection.deployment.alert_action.email.to }} +action.email.message.alert = {{ detection.deployment.alert_action.email.message | custom_jinja2_enrichment_filter(detection) }} +action.email.useNSSubject = 1 +{% endif %} +{% if detection.deployment.alert_action.risk is defined %} +action.risk = 1 +action.risk.param._risk_object = +action.risk.param._risk_object_type = +action.risk.param._risk_score = +action.risk.param.verbose = 0 +{% endif %} +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +disabled = true +enableSched = 1 +counttype = number of events +relation = greater than +quantity = 0 +realtime_schedule = 0 +is_visible = false +search = {{ detection.search }} + +{% endfor %} +### END ESCU DETECTIONS ### + + +### ESCU BASELINES ### + +{% for baseline in baselines %} +[ESCU - {{ baseline.name }} - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - {{ baseline.name }} +description = {{ baseline.description }} +action.escu.creation_date = {{ baseline.date }} +action.escu.modification_date = {{ baseline.date }} +{% if baseline.tags.analytics_story is defined %} +action.escu.analytic_story = {{ baseline.tags.analytics_story | tojson }} +{% else %} +action.escu.analytic_story = [] +{% endif %} +{% if baseline.data_model is defined %} +action.escu.data_models = [{{ baseline.data_model }}] +{% else %} +action.escu.data_models = [] +{% endif %} +dispatch.earliest_time = {{ baseline.deployment.scheduling.earliest_time }} +dispatch.latest_time = {{ baseline.deployment.scheduling.latest_time }} +{% if baseline.deployment.scheduling.schedule_window is defined %} +schedule_window = {{ baseline.deployment.scheduling.schedule_window }} +{% endif %} +{% if baseline.providing_technologies is defined %} +action.escu.providing_technologies = {{ baseline.providing_technologies | tojson }} +{% else %} +action.escu.providing_technologies = [] +{% endif %} +action.escu.eli5 = {{ baseline.description }} +{% if baseline.how_to_implement is defined %} +action.escu.how_to_implement = {{ baseline.how_to_implement }} +{% else %} +action.escu.how_to_implement = none +{% endif %} +disabled = true +is_visible = false +search = {{ baseline.search }} + +{% endfor %} + + +### ESCU RESPONSE TASKS ### + +{% for response_task in response_tasks %} +{% if response_task.search is defined %} +[ESCU - {{ response_task.name }} - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - {{ response_task.name }} +description = {{ response_task.description }} +action.escu.creation_date = {{ response_task.date }} +action.escu.modification_date = {{ response_task.date }} +{% if response_task.tags is defined %} +action.escu.analytic_story = {{ response_task.tags.analytics_story | tojson }} +{% else %} +action.escu.analytic_story = [] +{% endif %} +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +{% if response_task.data_model is defined %} +action.escu.data_models = [{{ response_task.data_model }}] +{% else %} +action.escu.data_models = [] +{% endif %} +action.escu.eli5 = {{ response_task.description }} +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = {{ response_task.search }} + +{% endif %} +{% endfor %} + + +### END ESCU RESPONSE TASKS ### + +### USAGE DASHBOARD CONFIGURATIONS ### + +[escu-metrics-usage] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +dispatchAs = user +search = index=_audit sourcetype="audittrail" \ +"ESCU - "\ +`comment("Find all the search names in the audittrail.")`\ +| stats count(search) by search savedsearch_name user\ +| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ +`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ +| rex field=search "\"(?.*)\""\ +`comment("Extract the name of the search from the search string")`\ +| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* + +[escu-metrics-search] +action.email.useNSSubject = 1 +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +enableSched = 1 +cron_schedule = 0 0 * * * +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +search = index=_audit action=search | transaction search_id maxspan=3m | search ESCU | stats sum(total_run_time) avg(total_run_time) max(total_run_time) sum(result_count) + +[escu-metrics-search-events] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +cron_schedule = 0 0 * * * +enableSched = 1 +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +search = [search index=_audit sourcetype="audittrail" \"ESCU NOT "index=_audit" | where search !="" | dedup search_id | rex field=search "\"(?.*)\"" | rex field=_raw "user=(?[a-zA-Z0-9_\-]+)" | eval usage=if(savedsearch_name!="", "scheduled", "adhoc") | eval savedsearch_name=if(savedsearch_name != "", savedsearch_name, search_name) | table savedsearch_name search_id user _time usage | outputlookup escu_search_id.csv | table search_id] index=_audit total_run_time event_count result_count NOT "index=_audit" | lookup escu_search_id.csv search_id | stats count(savedsearch_name) AS search_count avg(total_run_time) AS search_avg_run_time sum(total_run_time) AS search_total_run_time sum(result_count) AS search_total_results earliest(_time) AS firsts latest(_time) AS lasts by savedsearch_name user usage| eval first_run=strftime(firsts, "%B %d %Y") | eval last_run=strftime(lasts, "%B %d %Y") + +[escu-metrics-search-longest-runtime] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +enableSched = 1 +cron_schedule = 0 0 * * * +disabled = 1 +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +search = index=_* ESCU [search index=_* action=search latest=-2h earliest=-1d| transaction search_id maxspan=3m | search ESCU | stats values(total_run_time) AS run by search_id | sort -run | head 1| table search_id] | table search search_id + +[escu-metrics-usage-search] +action.email.useNSSubject = 1 +alert.digest_mode = True +alert.suppress = 0 +alert.track = 0 +auto_summarize.dispatch.earliest_time = -1d@h +cron_schedule = 0 0 * * * +dispatch.earliest_time = -4h@h +dispatch.latest_time = -1h@h +enableSched = 1 +dispatchAs = user +search = index=_audit sourcetype="audittrail" \ +"ESCU - "\ +`comment("Find all the search names in the audittrail. Ignore the last few minutes so we can exclude this search's text from the result.")`\ +| stats count(search) by search savedsearch_name user\ +| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ +`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ +| rex field=search "\"(?.*)\""\ +`comment("Extract the name of the search from the search string")`\ +| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* + +### END OF USAGE DASHBOARD CONFIGURATIONS ### diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 4e6bda4a58..fe3cdb4a74 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T08:08:29 UTC +# On Date: 2020-05-11T12:20:56 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] +investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 5e3fcd0822..3bed7c7d85 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T08:08:29 UTC +# On Date: 2020-05-11T12:20:56 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 85d17e936e..3bb7c75e59 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T08:08:29 UTC +# On Date: 2020-05-11T12:20:56 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -7404,2162 +7404,6 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime ### END ESCU DETECTIONS ### -### ESCU BASELINES ### - -[ESCU - Add Prohibited Processes to Enterprise Security - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security -description = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "SamSam Ransomware"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. -action.escu.how_to_implement = This search should be run on each new install of ESCU. -disabled = true -is_visible = false -search = | inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count - -[ESCU - Baseline of API Calls per User ARN - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of API Calls per User ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-04-09 -action.escu.modification_date = 2018-04-09 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count - -[ESCU - Baseline of Command Line Length - MLTK - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Command Line Length - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Unusual Processes"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. -action.escu.how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search user!=unknown | `security_content_ctime(start_time)`| `security_content_ctime(end_time)`| eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel - -[ESCU - Baseline of DNS Query Length - MLTK - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of DNS Query Length - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -action.escu.data_models = [Network_Resolution] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. -action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name("DNS")` | eval query_length = len(query) | fit DensityFunction query_length by record_type into dns_query_pdfmodel - -[ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 - -[ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. -action.escu.creation_date = 2019-11-14 -action.escu.modification_date = 2019-11-14 -action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ -In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ -More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 - -[ESCU - Baseline of Network ACL Activity by ARN - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Network ACL Activity by ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-05-21 -action.escu.modification_date = 2018-05-21 -action.escu.analytic_story = ["AWS Network ACL Activity"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. -disabled = true -is_visible = false -search = `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats count - -[ESCU - Baseline of S3 Bucket deletion activity by ARN - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of S3 Bucket deletion activity by ARN -description = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-07-17 -action.escu.modification_date = 2018-07-17 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count - -[ESCU - Baseline of SMB Traffic - MLTK - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of SMB Traffic - MLTK -description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. -action.escu.creation_date = 2019-05-08 -action.escu.modification_date = 2019-05-08 -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Netsh Abuse", "Ransomware"] -action.escu.data_models = [Network_Traffic] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. -action.escu.how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name("All_Traffic")` | fit DensityFunction count by "HourOfDay,DayOfWeek" into smb_pdfmodel - -[ESCU - Baseline of Security Group Activity by ARN - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of Security Group Activity by ARN -description = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-04-17 -action.escu.modification_date = 2018-04-17 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -disabled = true -is_visible = false -search = `cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats count - -[ESCU - Baseline of blocked outbound traffic from AWS - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Baseline of blocked outbound traffic from AWS -description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. -action.escu.creation_date = 2018-05-07 -action.escu.modification_date = 2018-05-07 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. -disabled = true -is_visible = false -search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | stats count - -[ESCU - Count of Unique IPs Connecting to Ports - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of Unique IPs Connecting to Ports -description = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. -action.escu.creation_date = 2017-09-13 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = [] -action.escu.data_models = [Network_Traffic] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. -action.escu.how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Count of assets by category - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Count of assets by category -description = This search shows you every asset category you have and the assets that belong to those categories. -action.escu.creation_date = 2017-09-13 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = ["Asset Tracking"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search shows you every asset category you have and the assets that belong to those categories. -action.escu.how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. -disabled = true -is_visible = false -search = | from datamodel Identity_Management.All_Assets | stats count values(nt_host) by category | sort -count - -[ESCU - Create a list of approved AWS service accounts - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Create a list of approved AWS service accounts -description = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. -action.escu.creation_date = 2018-12-03 -action.escu.modification_date = 2018-12-03 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. -disabled = true -is_visible = false -search = `cloudtrail` errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count by identity | table identity | outputlookup aws_service_accounts | stats count - -[ESCU - DNSTwist Domain Names - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - DNSTwist Domain Names -description = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. -action.escu.creation_date = 2018-10-08 -action.escu.modification_date = 2018-10-08 -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. -action.escu.how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. -disabled = true -is_visible = false -search = | dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse="true" | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count - -[ESCU - Discover DNS records - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Discover DNS records -description = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup -action.escu.creation_date = 2019-02-14 -action.escu.modification_date = 2019-02-14 -action.escu.analytic_story = ["DNS Hijacking"] -action.escu.data_models = [Network_Resolution] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup -action.escu.how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation -disabled = true -is_visible = false -search = | inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, "\*", "")) | join domain [|tstats `security_content_summariesonly` count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,domain,type,query,answer | outputlookup createinapp=true discovered_dns_records.csv - -[ESCU - Identify Systems Creating Remote Desktop Traffic - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Creating Remote Desktop Traffic -description = This search counts the numbers of times the system has generated remote desktop traffic. -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = [] -action.escu.data_models = [Network_Traffic] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search counts the numbers of times the system has generated remote desktop traffic. -action.escu.how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Identify Systems Receiving Remote Desktop Traffic - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Receiving Remote Desktop Traffic -description = This search counts the numbers of times the system has created remote desktop traffic -action.escu.creation_date = 2017-09-15 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = [] -action.escu.data_models = [Network_Traffic] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search counts the numbers of times the system has created remote desktop traffic -action.escu.how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name("All_Traffic")` | sort - count - -[ESCU - Identify Systems Using Remote Desktop - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Identify Systems Using Remote Desktop -description = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = [] -action.escu.data_models = [Endpoint] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. -action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Endpoint.Processes where Processes.process_name="*mstsc.exe*" by Processes.dest Processes.process_name | `drop_dm_object_name(Processes)` | sort - count - -[ESCU - Monitor Successful Backups - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Successful Backups -description = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. -disabled = true -is_visible = false -search = `netbackup` "Disk/Partition backup completed successfully." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE - -[ESCU - Monitor Unsuccessful Backups - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Monitor Unsuccessful Backups -description = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. -action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. -disabled = true -is_visible = false -search = `netbackup` "An error occurred, failed to backup." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE - -[ESCU - Previously Seen AWS Cross Account Activity - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Cross Account Activity -description = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. -action.escu.creation_date = 2018-06-04 -action.escu.modification_date = 2018-06-04 -action.escu.analytic_story = ["AWS Cross Account Activity"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats count - -[ESCU - Previously Seen AWS Provisioning Activity Sources - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Provisioning Activity Sources -description = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count - -[ESCU - Previously Seen AWS Regions - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen AWS Regions -description = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days -action.escu.creation_date = 2018-01-08 -action.escu.modification_date = 2018-01-08 -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count - -[ESCU - Previously Seen Cloud Compute Creations By User - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Creations By User -description = This search builds a table of previously seen users that have launched a cloud compute instance. -action.escu.creation_date = 2018-03-15 -action.escu.modification_date = 2018-03-15 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen users that have launched a cloud compute instance. -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -disabled = true -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_creations_by_user_input_filter` by Compute.src_user | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_creations_by_user | stats count - -[ESCU - Previously Seen Cloud Compute Images - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Images -description = This search builds a table of previously seen images used to launch cloud compute instances -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen images used to launch cloud compute instances -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -disabled = true -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_images | stats count - -[ESCU - Previously Seen Cloud Compute Instance Types - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Instance Types -description = This search builds a table of previously seen cloud compute instance types -action.escu.creation_date = 2019-10-03 -action.escu.modification_date = 2019-10-03 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen cloud compute instance types -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -disabled = true -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_instance_types | stats count - -[ESCU - Previously Seen Cloud Regions - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Cloud Regions -description = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days -action.escu.creation_date = 2019-10-02 -action.escu.modification_date = 2019-10-02 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days -action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. -disabled = true -is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=start `previously_seen_cloud_regions_input_filter` by Compute.region | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_regions | stats count - -[ESCU - Previously Seen EC2 AMIs - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 AMIs -description = This search builds a table of previously seen AMIs used to launch EC2 instances -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["AWS Cryptomining"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen AMIs used to launch EC2 instances -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | stats count - -[ESCU - Previously Seen EC2 Instance Types - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Instance Types -description = This search builds a table of previously seen EC2 instance types -action.escu.creation_date = 2018-03-08 -action.escu.modification_date = 2018-03-08 -action.escu.analytic_story = ["AWS Cryptomining"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen EC2 instance types -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | stats count - -[ESCU - Previously Seen EC2 Launches By User - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Launches By User -description = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.creation_date = 2018-03-15 -action.escu.modification_date = 2018-03-15 -action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. -disabled = true -is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count - -[ESCU - Previously Seen EC2 Modifications By User - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen EC2 Modifications By User -description = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.creation_date = 2018-04-05 -action.escu.modification_date = 2018-04-05 -action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -disabled = true -is_visible = false -search = `cloudtrail` `ec2_modification_api_calls` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count - -[ESCU - Previously Seen Running Windows Services - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously Seen Running Windows Services -description = This collects the services that have been started across your entire enterprise. -action.escu.creation_date = 2020-01-13 -action.escu.modification_date = 2020-01-13 -action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This collects the services that have been started across your entire enterprise. -action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -disabled = true -is_visible = false -search = `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services | stats count - -[ESCU - Previously seen API call per user roles in CloudTrail - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen API call per user roles in CloudTrail -description = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. -action.escu.creation_date = 2018-04-16 -action.escu.modification_date = 2018-04-16 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles | stats count - -[ESCU - Previously seen S3 bucket access by remote IP - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen S3 bucket access by remote IP -description = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" -action.escu.creation_date = 2018-06-28 -action.escu.modification_date = 2018-06-28 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `aws_s3_accesslogs` http_status=200 | stats earliest(_time) as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip | stats count - -[ESCU - Previously seen command line arguments - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen command line arguments -description = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. -action.escu.creation_date = 2019-03-01 -action.escu.modification_date = 2019-03-01 -action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Hidden Cobra Malware", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] -action.escu.data_models = [Endpoint] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. -action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe AND Processes.process="* /c *" by Processes.process | `drop_dm_object_name(Processes)` - -[ESCU - Previously seen users in CloudTrail - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Previously seen users in CloudTrail -description = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv | stats count - -[ESCU - Systems Ready for Spectre-Meltdown Windows Patch - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Systems Ready for Spectre-Meltdown Windows Patch -description = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. -action.escu.creation_date = 2018-01-08 -action.escu.modification_date = 2018-01-08 -action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. -action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` - -[ESCU - Update previously seen users in CloudTrail - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Update previously seen users in CloudTrail -description = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. -action.escu.creation_date = 2018-04-30 -action.escu.modification_date = 2018-04-30 -action.escu.analytic_story = ["Suspicious AWS Login Activities"] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. -disabled = true -is_visible = false -search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv - -[ESCU - Windows Updates Install Failures - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Failures -description = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.creation_date = 2017-09-14 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = [] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.how_to_implement = You must be ingesting your Windows Update Logs -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=failure by _time span=1d - -[ESCU - Windows Updates Install Successes - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Windows Updates Install Successes -description = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.creation_date = 2017-09-14 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = [] -action.escu.data_models = [] -dispatch.earliest_time = -30m -dispatch.latest_time = now -schedule_window = auto -action.escu.providing_technologies = [] -action.escu.eli5 = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. -action.escu.how_to_implement = You must be ingesting your Windows Update Logs -disabled = true -is_visible = false -search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=installed by _time span=1d - - - -### ESCU RESPONSE TASKS ### - -[ESCU - AWS Investigate User Activities By ARN - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN -description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. -action.escu.creation_date = 2019-04-30 -action.escu.modification_date = 2019-04-30 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Cloud Cryptomining", "Command and Control", "Suspicious AWS EC2 Activities", "Suspicious AWS Login Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Unusual AWS EC2 Modifications"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType - -[ESCU - AWS Investigate User Activities By AccessKeyId - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By AccessKeyId -description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. -action.escu.creation_date = 2018-06-08 -action.escu.modification_date = 2018-06-08 -action.escu.analytic_story = ["AWS Cross Account Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage - -[ESCU - AWS Investigate User Activities By Source User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By Source User -description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. -action.escu.creation_date = 2018-06-08 -action.escu.modification_date = 2018-06-08 -action.escu.analytic_story = ["AWS Cross Account Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage - -[ESCU - AWS Network ACL Details from ID - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network ACL Details from ID -description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID -action.escu.creation_date = 2017-01-22 -action.escu.modification_date = 2017-01-22 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:description id={networkAclId} | table id account_id vpc_id network_acl_entries{}.* - -[ESCU - AWS Network Interface details via resourceId - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Network Interface details via resourceId -description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. -action.escu.creation_date = 2018-05-07 -action.escu.modification_date = 2018-05-07 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:config resourceId={resourceId} | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp - -[ESCU - AWS S3 Bucket details via bucketName - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS S3 Bucket details via bucketName -description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. -action.escu.creation_date = 2018-06-26 -action.escu.modification_date = 2018-06-26 -action.escu.analytic_story = ["Suspicious AWS S3 Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList - -[ESCU - All backup logs for host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - All backup logs for host -description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Monitor Backup Solution"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype="netbackup_logs" dest={dest} - -[ESCU - Amazon EKS Kubernetes activity by src ip - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Amazon EKS Kubernetes activity by src ip -description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address -action.escu.creation_date = 2020-04-13 -action.escu.modification_date = 2020-04-13 -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip - -[ESCU - GCP Kubernetes activity by src ip - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - GCP Kubernetes activity by src ip -description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address -action.escu.creation_date = 2020-04-13 -action.escu.modification_date = 2020-04-13 -action.escu.analytic_story = ["Kubernetes Scanning Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type - -[ESCU - Get All AWS Activity From City - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From City -description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode - -[ESCU - Get All AWS Activity From Country - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Country -description = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode - -[ESCU - Get All AWS Activity From IP Address - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From IP Address -description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "AWS Suspicious Provisioning Activities", "Command and Control", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode - -[ESCU - Get All AWS Activity From Region - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get All AWS Activity From Region -description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.creation_date = 2018-03-19 -action.escu.modification_date = 2018-03-19 -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode - -[ESCU - Get Authentication Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Authentication Logs For Endpoint -description = This search returns all users that have attempted to access a particular endpoint. -action.escu.creation_date = 2017-11-01 -action.escu.modification_date = 2017-11-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] -action.escu.eli5 = This search returns all users that have attempted to access a particular endpoint. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats count from datamodel=Authentication where Authentication.dest={dest} by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` - -[ESCU - Get Backup Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Backup Logs For Endpoint -description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. -action.escu.creation_date = 2017-09-14 -action.escu.modification_date = 2017-09-14 -action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature - -[ESCU - Get Certificate logs for a domain - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Certificate logs for a domain -description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. -action.escu.creation_date = 2019-04-29 -action.escu.modification_date = 2019-04-29 -action.escu.analytic_story = ["Common Phishing Frameworks"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get DNS Server History for a host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS Server History for a host -description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DNS Hijacking", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Host Redirection", "Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count - -[ESCU - Get DNS traffic ratio - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get DNS traffic ratio -description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Network_Traffic] -action.escu.eli5 = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval ratio = (bytes_out/bytes_in) | table ratio - -[ESCU - Get EC2 Instance Details by instanceId - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get EC2 Instance Details by instanceId -description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field -action.escu.creation_date = 2018-02-12 -action.escu.modification_date = 2018-02-12 -action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Unusual AWS EC2 Modifications"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC - -[ESCU - Get EC2 Launch Details - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get EC2 Launch Details -description = This search returns some of the launch details for a EC2 instance. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns some of the launch details for a EC2 instance. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName - -[ESCU - Get Email Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Email Info -description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Email.All_Email | search message_id={message_id} - -[ESCU - Get Emails From Specific Sender - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Emails From Specific Sender -description = This search returns all the emails from a specific sender over the last 24 and next hours. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails", "Web Fraud Detection"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all the emails from a specific sender over the last 24 and next hours. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Email.All_Email | search src_user={src_user} - -[ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get First Occurrence and Last Occurrence of a MAC Address -description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. -action.escu.creation_date = 2017-09-13 -action.escu.modification_date = 2017-09-13 -action.escu.analytic_story = ["Asset Tracking"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Network_Sessions] -action.escu.eli5 = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - -[ESCU - Get History Of Email Sources - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get History Of Email Sources -description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. -action.escu.creation_date = 2019-02-21 -action.escu.modification_date = 2019-02-21 -action.escu.analytic_story = [] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Email] -action.escu.eli5 = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = |tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get Logon Rights Modifications For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For Endpoint -description = This search allows you to retrieve any modifications to logon rights associated with a specific host. -action.escu.creation_date = 2017-09-12 -action.escu.modification_date = 2017-09-12 -action.escu.analytic_story = ["Account Monitoring and Controls"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search allows you to retrieve any modifications to logon rights associated with a specific host. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest={dest} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature - -[ESCU - Get Logon Rights Modifications For User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Logon Rights Modifications For User -description = This search allows you to retrieve any modifications to logon rights for a specific user account. -action.escu.creation_date = 2019-02-27 -action.escu.modification_date = 2019-02-27 -action.escu.analytic_story = ["Account Monitoring and Controls"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search allows you to retrieve any modifications to logon rights for a specific user account. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user={user} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature - -[ESCU - Get Notable History - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable History -description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. -action.escu.creation_date = 2017-09-20 -action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cross Account Activity", "AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual AWS EC2 Modifications", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search `notable` | search dest={dest} | table _time, rule_name, owner, priority, severity, status_description - -[ESCU - Get Notable Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Notable Info -description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. -action.escu.creation_date = 2017-09-20 -action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description - -[ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Outbound Emails to Hidden Cobra Threat Actors -description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. -action.escu.creation_date = 2018-06-14 -action.escu.modification_date = 2018-06-14 -action.escu.analytic_story = [] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get Parent Process Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Parent Process Info -description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest -action.escu.creation_date = 2019-02-28 -action.escu.modification_date = 2019-02-28 -action.escu.analytic_story = ["Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Phishing Payloads", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - -[ESCU - Get Process File Activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process File Activity -description = This search returns the file activity for a specific process on a specific endpoint -action.escu.creation_date = 2019-11-06 -action.escu.modification_date = 2019-11-06 -action.escu.analytic_story = ["DHS Report TA18-074A"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] -action.escu.eli5 = This search returns the file activity for a specific process on a specific endpoint -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path - -[ESCU - Get Process Info - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Info -description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] -action.escu.eli5 = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` - -[ESCU - Get Process Information For Port Activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Information For Port Activity -description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Use of Cleartext Protocols"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] -action.escu.eli5 = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] - -[ESCU - Get Process Registry Activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Registry Activity -description = This search returns the registry activity for a specific process on a specific endpoint -action.escu.creation_date = 2019-11-06 -action.escu.modification_date = 2019-11-06 -action.escu.analytic_story = ["DHS Report TA18-074A"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] -action.escu.eli5 = This search returns the registry activity for a specific process on a specific endpoint -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id={process_id} AND Registry.dest={dest} by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path - -[ESCU - Get Process Responsible For The DNS Traffic - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Process Responsible For The DNS Traffic -description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. -action.escu.creation_date = 2019-04-01 -action.escu.modification_date = 2019-04-01 -action.escu.analytic_story = ["AWS Network ACL Activity", "Brand Monitoring", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] -action.escu.eli5 = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] - -[ESCU - Get Registry Activities - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Registry Activities -description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. -action.escu.creation_date = 2019-03-01 -action.escu.modification_date = 2019-03-01 -action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Persistence Techniques", "Windows Privilege Escalation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "{dest}" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] - -[ESCU - Get Risk Modifiers For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For Endpoint -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) -action.escu.creation_date = 2017-10-19 -action.escu.modification_date = 2017-10-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - -[ESCU - Get Risk Modifiers For User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Risk Modifiers For User -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user -action.escu.creation_date = 2017-10-19 -action.escu.modification_date = 2017-10-19 -action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` - -[ESCU - Get Sysmon WMI Activity for Host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Sysmon WMI Activity for Host -description = This search queries Sysmon WMI events for the host of interest. -action.escu.creation_date = 2018-10-23 -action.escu.modification_date = 2018-10-23 -action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search queries Sysmon WMI events for the host of interest. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter - -[ESCU - Get Update Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Update Logs For Endpoint -description = This search will tell you give you the update logs for a specific endpoint for the last week. -action.escu.creation_date = 2017-08-24 -action.escu.modification_date = 2017-08-24 -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search will tell you give you the update logs for a specific endpoint for the last week. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest} - -[ESCU - Get User Information from Identity Table - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get User Information from Identity Table -description = Gather more information about the user identified in the Notable Event. -action.escu.creation_date = 2017-09-20 -action.escu.modification_date = 2017-09-20 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = Gather more information about the user identified in the Notable Event. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | `identities` | search identity={user} | table _time, identity, first, last, email, category, watchlist - -[ESCU - Get Vulnerability Logs For Endpoint - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Vulnerability Logs For Endpoint -description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. -action.escu.creation_date = 2017-09-10 -action.escu.modification_date = 2017-09-10 -action.escu.analytic_story = ["ColdRoot MacOS RAT", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware", "Windows Log Manipulation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search will show you any vulnerabilities noted for a specific endpoint for the last week. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Vulnerabilities.Vulnerabilities | search dest={dest} - -[ESCU - Get Web Session Information via session id - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Get Web Session Information via session id -description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. -action.escu.creation_date = 2018-10-08 -action.escu.modification_date = 2018-10-08 -action.escu.analytic_story = ["Web Fraud Detection"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) by src_ip status - -[ESCU - Investigate AWS ECR container listing activity - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS ECR container listing activity -description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. -action.escu.creation_date = 2020-02-20 -action.escu.modification_date = 2020-02-20 -action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1 - -[ESCU - Investigate AWS User Activities by user field - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS User Activities by user field -description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["AWS User Monitoring"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType - -[ESCU - Investigate AWS activities via region name - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate AWS activities via region name -description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user -action.escu.creation_date = 2018-02-09 -action.escu.modification_date = 2018-02-09 -action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId - -[ESCU - Investigate Cloud Compute Instance Activities - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Cloud Compute Instance Activities -description = This search returns a logs of events that operated on the compute instance. -action.escu.creation_date = 2018-03-12 -action.escu.modification_date = 2018-03-12 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns a logs of events that operated on the compute instance. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields - _* - -[ESCU - Investigate Failed Logins for Multiple Destinations - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Failed Logins for Multiple Destinations -description = This search returns failed logins to multiple destinations by user. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] -action.escu.eli5 = This search returns failed logins to multiple destinations by user. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` - -[ESCU - Investigate Network Traffic From src ip - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Network Traffic From src ip -description = This search allows you to find all the network traffic from a specific IP address. -action.escu.creation_date = 2018-06-15 -action.escu.modification_date = 2018-06-15 -action.escu.analytic_story = ["ColdRoot MacOS RAT", "Splunk Enterprise Vulnerability CVE-2018-11409"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search allows you to find all the network traffic from a specific IP address. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip} - -[ESCU - Investigate Okta Activity by IP Address - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by IP Address -description = This search returns all okta events from a specific IP address. -action.escu.creation_date = 2020-04-02 -action.escu.modification_date = 2020-04-02 -action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all okta events from a specific IP address. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - -[ESCU - Investigate Okta Activity by app - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Okta Activity by app -description = This search returns all okta events associated with a specific app -action.escu.creation_date = 2020-04-02 -action.escu.modification_date = 2020-04-02 -action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all okta events associated with a specific app -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = eventtype=okta_log app={app} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - -[ESCU - Investigate Pass the Hash Attempts - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Hash Attempts -description = This search hunts for dumped NTLM hashes used for pass the hash. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search hunts for dumped NTLM hashes used for pass the hash. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` - -[ESCU - Investigate Pass the Ticket Attempts - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Pass the Ticket Attempts -description = This search hunts for dumped kerberos ticket from LSASS memory. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search hunts for dumped kerberos ticket from LSASS memory. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user - -[ESCU - Investigate Previous Unseen User - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Previous Unseen User -description = This search returns previous unseen user, which didn't log in for 30 days. -action.escu.creation_date = 2019-12-10 -action.escu.modification_date = 2019-12-10 -action.escu.analytic_story = ["Credential Dumping"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] -action.escu.eli5 = This search returns previous unseen user, which didn't log in for 30 days. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` - -[ESCU - Investigate Successful Remote Desktop Authentications - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Successful Remote Desktop Authentications -description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. -action.escu.creation_date = 2018-12-14 -action.escu.modification_date = 2018-12-14 -action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement", "SamSam Ransomware"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] -action.escu.eli5 = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| table firstTime lastTime src src_nt_domain dest user app count | sort count - -[ESCU - Investigate Suspicious Strings in HTTP Header - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Suspicious Strings in HTTP Header -description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. -action.escu.creation_date = 2017-10-20 -action.escu.modification_date = 2017-10-20 -action.escu.analytic_story = ["Apache Struts Vulnerability"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url - -[ESCU - Investigate User Activities In All Cloud Regions - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In All Cloud Regions -description = This search lists all the logged cloud infrastructure activities by a specific cloud user -action.escu.creation_date = 2019-04-30 -action.escu.modification_date = 2019-04-30 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | fields - _* - -[ESCU - Investigate User Activities In Okta - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Okta -description = This search returns all okta events by a specific user -action.escu.creation_date = 2020-04-02 -action.escu.modification_date = 2020-04-02 -action.escu.analytic_story = ["Suspicious Okta Activity"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search returns all okta events by a specific user -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = eventtype=okta_log user={user} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - -[ESCU - Investigate User Activities In Single Cloud Region - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate User Activities In Single Cloud Region -description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region -action.escu.creation_date = 2019-04-30 -action.escu.modification_date = 2019-04-30 -action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} | fields - _* - -[ESCU - Investigate Web Activity From Host - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From Host -description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -action.escu.creation_date = 2017-11-09 -action.escu.modification_date = 2017-11-09 -action.escu.analytic_story = ["Brand Monitoring", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Web.Web | search src={dest} - -[ESCU - Investigate Web Activity From src ip - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web Activity From src ip -description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -action.escu.creation_date = 2018-06-15 -action.escu.modification_date = 2018-06-15 -action.escu.analytic_story = ["ColdRoot MacOS RAT", "Dynamic DNS", "Splunk Enterprise Vulnerability CVE-2018-11409"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | from datamodel Web.Web | search src={src_ip} - -[ESCU - Investigate Web POSTs From src - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Investigate Web POSTs From src -description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. -action.escu.creation_date = 2018-12-06 -action.escu.modification_date = 2018-12-06 -action.escu.analytic_story = ["Apache Struts Vulnerability"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [Web] -action.escu.eli5 = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "{src}") and like(http_method, "POST") - -[ESCU - Process Chain Analysis - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - Process Chain Analysis -description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. -action.escu.creation_date = 2020-04-29 -action.escu.modification_date = 2020-04-29 -action.escu.analytic_story = [] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -action.escu.data_models = [] -action.escu.eli5 = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = `sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count - - - -### END ESCU RESPONSE TASKS ### ### USAGE DASHBOARD CONFIGURATIONS ### diff --git a/package/default/transforms.conf b/package/default/transforms.conf index f884bb7159..b9325478b5 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T08:08:29 UTC +# On Date: 2020-05-11T12:20:56 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 9109b57c41..b8e297b0d6 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T08:08:29 UTC +# On Date: 2020-05-11T12:20:56 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] +searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] +searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity"] +searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] +searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - All backup logs for host"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - File with Samsam Extension - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Shim Database File Creation - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 7fa4709995206c90820c7645391a3986ae01d53c Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 14:27:43 +0200 Subject: [PATCH 36/93] bug in generate --- bin/jinja2_templates/savedsearches.j2 | 82 +++++++ bin/jinja2_templates/savedsearches.j2.real | 250 --------------------- 2 files changed, 82 insertions(+), 250 deletions(-) delete mode 100644 bin/jinja2_templates/savedsearches.j2.real diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 1a01d5a83f..07f11de854 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -88,6 +88,88 @@ search = {{ detection.search }} ### END ESCU DETECTIONS ### +### ESCU BASELINES ### + +{% for baseline in baselines %} +[ESCU - {{ baseline.name }} - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - {{ baseline.name }} +description = {{ baseline.description }} +action.escu.creation_date = {{ baseline.date }} +action.escu.modification_date = {{ baseline.date }} +{% if baseline.tags.analytics_story is defined %} +action.escu.analytic_story = {{ baseline.tags.analytics_story | tojson }} +{% else %} +action.escu.analytic_story = [] +{% endif %} +{% if baseline.data_model is defined %} +action.escu.data_models = [{{ baseline.data_model }}] +{% else %} +action.escu.data_models = [] +{% endif %} +dispatch.earliest_time = {{ baseline.deployment.scheduling.earliest_time }} +dispatch.latest_time = {{ baseline.deployment.scheduling.latest_time }} +{% if baseline.deployment.scheduling.schedule_window is defined %} +schedule_window = {{ baseline.deployment.scheduling.schedule_window }} +{% endif %} +{% if baseline.providing_technologies is defined %} +action.escu.providing_technologies = {{ baseline.providing_technologies | tojson }} +{% else %} +action.escu.providing_technologies = [] +{% endif %} +action.escu.eli5 = {{ baseline.description }} +{% if baseline.how_to_implement is defined %} +action.escu.how_to_implement = {{ baseline.how_to_implement }} +{% else %} +action.escu.how_to_implement = none +{% endif %} +disabled = true +is_visible = false +search = {{ baseline.search }} + +{% endfor %} + + +### ESCU RESPONSE TASKS ### + +{% for response_task in response_tasks %} +{% if response_task.search is defined %} +[ESCU - {{ response_task.name }} - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - {{ response_task.name }} +description = {{ response_task.description }} +action.escu.creation_date = {{ response_task.date }} +action.escu.modification_date = {{ response_task.date }} +{% if response_task.tags is defined %} +action.escu.analytic_story = {{ response_task.tags.analytics_story | tojson }} +{% else %} +action.escu.analytic_story = [] +{% endif %} +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +{% if response_task.data_model is defined %} +action.escu.data_models = [{{ response_task.data_model }}] +{% else %} +action.escu.data_models = [] +{% endif %} +action.escu.eli5 = {{ response_task.description }} +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = {{ response_task.search }} + +{% endif %} +{% endfor %} + + +### END ESCU RESPONSE TASKS ### ### USAGE DASHBOARD CONFIGURATIONS ### diff --git a/bin/jinja2_templates/savedsearches.j2.real b/bin/jinja2_templates/savedsearches.j2.real deleted file mode 100644 index 07f11de854..0000000000 --- a/bin/jinja2_templates/savedsearches.j2.real +++ /dev/null @@ -1,250 +0,0 @@ -############# -# Automatically generated by generator.py in splunk/security-content -# On Date: {{ time }} UTC -# Author: Splunk Security Research -# Contact: research@splunk.com -############# - -### ESCU DETECTIONS ### - -{% for detection in detections %} -[ESCU - {{ detection.name }} - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = {{ detection.description }} -action.escu.mappings = {{ detection.mappings | tojson }} -{% if detection.data_model is defined %} -action.escu.data_models = [{{ detection.data_model }}] -{% else %} -action.escu.data_models = [] -{% endif %} -action.escu.eli5 = {{ detection.description }} -{% if detection.how_to_implement is defined %} -action.escu.how_to_implement = {{ detection.how_to_implement }} -{% else %} -action.escu.how_to_implement = none -{% endif %} -{% if detection.known_false_positives is defined %} -action.escu.known_false_positives = {{ detection.known_false_positives }} -{% else %} -action.escu.known_false_positives = None -{% endif %} -action.escu.creation_date = {{ detection.date }} -action.escu.modification_date = {{ detection.date }} -action.escu.confidence = high -action.escu.full_search_name = ESCU - {{ detection.name }} - Rule -action.escu.search_type = detection -{% if detection.providing_technologies is defined %} -action.escu.providing_technologies = {{ detection.providing_technologies | tojson }} -{% else %} -action.escu.providing_technologies = [] -{% endif %} -{% if detection.tags.analytics_story is defined %} -action.escu.analytic_story = {{ detection.tags.analytics_story | tojson }} -{% endif %} -cron_schedule = {{ detection.deployment.scheduling.cron_schedule }} -dispatch.earliest_time = {{ detection.deployment.scheduling.earliest_time }} -dispatch.latest_time = {{ detection.deployment.scheduling.latest_time }} -action.correlationsearch.enabled = 1 -action.correlationsearch.label = ESCU - {{ detection.name }} - Rule -{% if detection.deployment.scheduling.schedule_window is defined %} -schedule_window = {{ detection.deployment.scheduling.schedule_window }} -{% endif %} -{% if detection.deployment.alert_action.notable is defined %} -action.notable = 1 -{% if detection.nes_fields is defined %} -action.notable.param.nes_fields = {{ detection.nes_fields }} -{% endif %} -action.notable.param.rule_description = {{ detection.deployment.alert_action.notable.rule_description | custom_jinja2_enrichment_filter(detection) }} -action.notable.param.rule_title = {{ detection.deployment.alert_action.notable.rule_title | custom_jinja2_enrichment_filter(detection) }} -action.notable.param.security_domain = {{ detection.tags.security_domain }} -action.notable.param.severity = medium -{% endif %} -{% if detection.deployment.alert_action.email is defined %} -action.email.subject.alert = {{ detection.deployment.alert_action.email.subject | custom_jinja2_enrichment_filter(detection) }} -action.email.to = {{ detection.deployment.alert_action.email.to }} -action.email.message.alert = {{ detection.deployment.alert_action.email.message | custom_jinja2_enrichment_filter(detection) }} -action.email.useNSSubject = 1 -{% endif %} -{% if detection.deployment.alert_action.risk is defined %} -action.risk = 1 -action.risk.param._risk_object = -action.risk.param._risk_object_type = -action.risk.param._risk_score = -action.risk.param.verbose = 0 -{% endif %} -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -is_visible = false -search = {{ detection.search }} - -{% endfor %} -### END ESCU DETECTIONS ### - - -### ESCU BASELINES ### - -{% for baseline in baselines %} -[ESCU - {{ baseline.name }} - Baseline] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - {{ baseline.name }} -description = {{ baseline.description }} -action.escu.creation_date = {{ baseline.date }} -action.escu.modification_date = {{ baseline.date }} -{% if baseline.tags.analytics_story is defined %} -action.escu.analytic_story = {{ baseline.tags.analytics_story | tojson }} -{% else %} -action.escu.analytic_story = [] -{% endif %} -{% if baseline.data_model is defined %} -action.escu.data_models = [{{ baseline.data_model }}] -{% else %} -action.escu.data_models = [] -{% endif %} -dispatch.earliest_time = {{ baseline.deployment.scheduling.earliest_time }} -dispatch.latest_time = {{ baseline.deployment.scheduling.latest_time }} -{% if baseline.deployment.scheduling.schedule_window is defined %} -schedule_window = {{ baseline.deployment.scheduling.schedule_window }} -{% endif %} -{% if baseline.providing_technologies is defined %} -action.escu.providing_technologies = {{ baseline.providing_technologies | tojson }} -{% else %} -action.escu.providing_technologies = [] -{% endif %} -action.escu.eli5 = {{ baseline.description }} -{% if baseline.how_to_implement is defined %} -action.escu.how_to_implement = {{ baseline.how_to_implement }} -{% else %} -action.escu.how_to_implement = none -{% endif %} -disabled = true -is_visible = false -search = {{ baseline.search }} - -{% endfor %} - - -### ESCU RESPONSE TASKS ### - -{% for response_task in response_tasks %} -{% if response_task.search is defined %} -[ESCU - {{ response_task.name }} - Response Task] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - {{ response_task.name }} -description = {{ response_task.description }} -action.escu.creation_date = {{ response_task.date }} -action.escu.modification_date = {{ response_task.date }} -{% if response_task.tags is defined %} -action.escu.analytic_story = {{ response_task.tags.analytics_story | tojson }} -{% else %} -action.escu.analytic_story = [] -{% endif %} -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = [] -{% if response_task.data_model is defined %} -action.escu.data_models = [{{ response_task.data_model }}] -{% else %} -action.escu.data_models = [] -{% endif %} -action.escu.eli5 = {{ response_task.description }} -action.escu.how_to_implement = none -action.escu.known_false_positives = None at this time -disabled = true -schedule_window = auto -is_visible = false -search = {{ response_task.search }} - -{% endif %} -{% endfor %} - - -### END ESCU RESPONSE TASKS ### - -### USAGE DASHBOARD CONFIGURATIONS ### - -[escu-metrics-usage] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -dispatchAs = user -search = index=_audit sourcetype="audittrail" \ -"ESCU - "\ -`comment("Find all the search names in the audittrail.")`\ -| stats count(search) by search savedsearch_name user\ -| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ -`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ -| rex field=search "\"(?.*)\""\ -`comment("Extract the name of the search from the search string")`\ -| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* - -[escu-metrics-search] -action.email.useNSSubject = 1 -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -enableSched = 1 -cron_schedule = 0 0 * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = index=_audit action=search | transaction search_id maxspan=3m | search ESCU | stats sum(total_run_time) avg(total_run_time) max(total_run_time) sum(result_count) - -[escu-metrics-search-events] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -cron_schedule = 0 0 * * * -enableSched = 1 -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = [search index=_audit sourcetype="audittrail" \"ESCU NOT "index=_audit" | where search !="" | dedup search_id | rex field=search "\"(?.*)\"" | rex field=_raw "user=(?[a-zA-Z0-9_\-]+)" | eval usage=if(savedsearch_name!="", "scheduled", "adhoc") | eval savedsearch_name=if(savedsearch_name != "", savedsearch_name, search_name) | table savedsearch_name search_id user _time usage | outputlookup escu_search_id.csv | table search_id] index=_audit total_run_time event_count result_count NOT "index=_audit" | lookup escu_search_id.csv search_id | stats count(savedsearch_name) AS search_count avg(total_run_time) AS search_avg_run_time sum(total_run_time) AS search_total_run_time sum(result_count) AS search_total_results earliest(_time) AS firsts latest(_time) AS lasts by savedsearch_name user usage| eval first_run=strftime(firsts, "%B %d %Y") | eval last_run=strftime(lasts, "%B %d %Y") - -[escu-metrics-search-longest-runtime] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -enableSched = 1 -cron_schedule = 0 0 * * * -disabled = 1 -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = index=_* ESCU [search index=_* action=search latest=-2h earliest=-1d| transaction search_id maxspan=3m | search ESCU | stats values(total_run_time) AS run by search_id | sort -run | head 1| table search_id] | table search search_id - -[escu-metrics-usage-search] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -cron_schedule = 0 0 * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -enableSched = 1 -dispatchAs = user -search = index=_audit sourcetype="audittrail" \ -"ESCU - "\ -`comment("Find all the search names in the audittrail. Ignore the last few minutes so we can exclude this search's text from the result.")`\ -| stats count(search) by search savedsearch_name user\ -| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ -`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ -| rex field=search "\"(?.*)\""\ -`comment("Extract the name of the search from the search string")`\ -| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* - -### END OF USAGE DASHBOARD CONFIGURATIONS ### From 7ad2bb485c021179c370fbc1338d8064ece3697c Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 14:39:28 +0200 Subject: [PATCH 37/93] bug in generate --- bin/jinja2_templates/savedsearches.j2 | 9 +- package/default/analytic_stories.conf | 116 +- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2349 ++++++++++++++++++++++++- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 122 +- 6 files changed, 2475 insertions(+), 125 deletions(-) diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 07f11de854..cd41ad438d 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -41,6 +41,8 @@ action.escu.providing_technologies = [] {% endif %} {% if detection.tags.analytics_story is defined %} action.escu.analytic_story = {{ detection.tags.analytics_story | tojson }} +{% else %} +action.escu.analytic_story = [] {% endif %} cron_schedule = {{ detection.deployment.scheduling.cron_schedule }} dispatch.earliest_time = {{ detection.deployment.scheduling.earliest_time }} @@ -68,11 +70,12 @@ action.email.useNSSubject = 1 {% endif %} {% if detection.deployment.alert_action.risk is defined %} action.risk = 1 -action.risk.param._risk_object = -action.risk.param._risk_object_type = -action.risk.param._risk_score = +action.risk.param._risk_object = dest +action.risk.param._risk_object_type = system +action.risk.param._risk_score = 30 action.risk.param.verbose = 0 {% endif %} +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index fe3cdb4a74..6441c13abb 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:20:56 UTC +# On Date: 2020-05-11T12:39:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process File Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName"] +investigative_searches = ["ESCU - Investigate AWS activities via region name", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 3bed7c7d85..3471bfab77 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:20:56 UTC +# On Date: 2020-05-11T12:39:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 3bb7c75e59..805673ae90 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:20:56 UTC +# On Date: 2020-05-11T12:39:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -36,6 +36,7 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen City action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -76,6 +77,7 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Country action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -116,6 +118,7 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen IP Address action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -156,6 +159,7 @@ action.notable.param.rule_description = This search looks for AWS provisioning a action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Region action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -195,6 +199,7 @@ action.notable.param.rule_description = This search looks for AssumeRole events action.notable.param.rule_title = AWS Cross Account Activity From Previously Unseen Account action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -234,6 +239,7 @@ action.notable.param.rule_description = The search looks for CloudTrail events t action.notable.param.rule_title = AWS Network Access Control List Created with All Open Ports action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -273,6 +279,7 @@ action.notable.param.rule_description = Enforcing network-access controls is one action.notable.param.rule_title = AWS Network Access Control List Deleted action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -311,6 +318,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Launched by User action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -350,6 +358,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Launched by User - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -388,6 +397,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -427,6 +437,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -466,6 +477,7 @@ action.notable.param.rule_description = Detect memory dumping of the LSASS proce action.notable.param.rule_title = Access LSASS Memory for Dump Creation action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -504,6 +516,7 @@ action.notable.param.rule_description = This search provides detection informati action.notable.param.rule_title = Amazon EKS Kubernetes Pod scan detection action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -542,6 +555,7 @@ action.notable.param.rule_description = This search provides information of unau action.notable.param.rule_title = Amazon EKS Kubernetes cluster scan detection action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -581,6 +595,7 @@ action.notable.param.rule_description = Attempt to add a certificate to the untr action.notable.param.rule_title = Attempt To Add Certificate To Untrusted Store action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -620,6 +635,7 @@ action.notable.param.rule_description = Monitor for changes of the ExecutionPoli action.notable.param.rule_title = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -659,6 +675,7 @@ action.notable.param.rule_description = This search looks for attempts to stop s action.notable.param.rule_title = Attempt To Stop Security Service action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -698,6 +715,7 @@ action.notable.param.rule_description = Monitor for execution of reg.exe with pa action.notable.param.rule_title = Attempted Credential Dump From Registry via Reg exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -737,6 +755,7 @@ action.notable.param.rule_description = The search looks for a batch file (.bat) action.notable.param.rule_title = Batch File Write to System32 action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -776,6 +795,7 @@ action.notable.param.rule_description = This search looks for child processes of action.notable.param.rule_title = Child Processes of Spoolsv exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -817,6 +837,7 @@ action.notable.param.rule_description = This search allows you to identify the e action.notable.param.rule_title = Clients Connecting to Multiple DNS Servers action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -856,6 +877,7 @@ action.notable.param.rule_description = This search looks for cloud compute inst action.notable.param.rule_title = Cloud Compute Instance Created By Previously Unseen User action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -895,6 +917,7 @@ action.notable.param.rule_description = This search looks for cloud compute inst action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Image action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -934,6 +957,7 @@ action.notable.param.rule_description = Find EC2 instances being created with pr action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Instance Type action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -973,6 +997,7 @@ action.notable.param.rule_description = This search looks at cloud-infrastructur action.notable.param.rule_title = Cloud Compute Instance Started In Previously Unused Region action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1016,6 +1041,7 @@ action.notable.param.rule_description = The search looks for file modifications action.notable.param.rule_title = Common Ransomware Extensions action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1055,6 +1081,7 @@ action.notable.param.rule_description = The search looks for files created with action.notable.param.rule_title = Common Ransomware Notes action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1094,6 +1121,7 @@ action.notable.param.rule_description = Detect remote thread creation into LSASS action.notable.param.rule_title = Create Remote Thread into LSASS action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1133,6 +1161,7 @@ action.notable.param.rule_description = This search looks for the creation of lo action.notable.param.rule_title = Create local admin accounts using net exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1172,6 +1201,7 @@ action.notable.param.rule_description = This search looks for the creation or de action.notable.param.rule_title = Create or delete windows shares using net exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1211,6 +1241,7 @@ action.notable.param.rule_description = Monitor for signs that Ntdsutil, Vssadmi action.notable.param.rule_title = Creation of Shadow Copy action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1250,6 +1281,7 @@ action.notable.param.rule_description = This search detects the use of wmic and action.notable.param.rule_title = Creation of Shadow Copy with wmic and powershell action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1289,6 +1321,7 @@ action.notable.param.rule_description = This search detects credential dumping u action.notable.param.rule_title = Credential Dumping via Copy Command from Shadow Copy action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1328,6 +1361,7 @@ action.notable.param.rule_description = This search detects the creation of a sy action.notable.param.rule_title = Credential Dumping via Symlink to Shadow Copy action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1373,6 +1407,7 @@ action.notable.param.rule_description = This search allows you to identify DNS r action.notable.param.rule_title = DNS Query Length Outliers - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1411,6 +1446,7 @@ action.notable.param.rule_description = This search allows you to identify DNS r action.notable.param.rule_title = DNS Query Length With High Standard Deviation action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1450,6 +1486,7 @@ action.notable.param.rule_description = This search will detect DNS requests res action.notable.param.rule_title = DNS Query Requests Resolved by Unauthorized DNS Servers action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1493,6 +1530,7 @@ action.notable.param.rule_description = The search takes the DNS records and the action.notable.param.rule_title = DNS record changed action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1532,6 +1570,7 @@ action.notable.param.rule_description = The vssadmin.exe utility is used to inte action.notable.param.rule_title = Deleting Shadow Copies action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1577,6 +1616,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect API activity from users without MFA action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1622,6 +1662,7 @@ action.notable.param.rule_description = This search looks for successful CloudTr action.notable.param.rule_title = Detect AWS API Activities From Unapproved Accounts action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1661,6 +1702,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect AWS Console Login by User from New City action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1700,6 +1742,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect AWS Console Login by User from New Country action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1739,6 +1782,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect AWS Console Login by User from New Region action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1778,6 +1822,7 @@ action.notable.param.rule_description = This search looks for specific authentic action.notable.param.rule_title = Detect Activity Related to Pass the Hash Attacks action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1817,6 +1862,7 @@ action.notable.param.rule_description = This search looks for reading lsass memo action.notable.param.rule_title = Detect Credential Dumping through LSASS access action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1860,6 +1906,7 @@ action.notable.param.rule_description = This search looks for DNS requests for p action.notable.param.rule_title = Detect DNS requests to Phishing Sites leveraging EvilGinx2 action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1903,6 +1950,7 @@ action.notable.param.rule_description = This search identifies endpoints that ha action.notable.param.rule_title = Detect Excessive Account Lockouts From Endpoint action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1942,6 +1990,7 @@ action.notable.param.rule_description = This search detects user accounts that h action.notable.param.rule_title = Detect Excessive User Account Lockouts action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -1980,6 +2029,7 @@ action.notable.param.rule_description = This search looks for outbound ICMP pack action.notable.param.rule_title = Detect Large Outbound ICMP Packets action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2019,6 +2069,7 @@ action.notable.param.rule_description = This search is used to detect attempts t action.notable.param.rule_title = Detect Long DNS TXT Record Response action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2058,6 +2109,7 @@ action.notable.param.rule_description = This search looks for reading loaded Ima action.notable.param.rule_title = Detect Mimikatz Using Loaded Images action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2084,6 +2136,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule action.escu.search_type = detection action.escu.providing_technologies = [] +action.escu.analytic_story = [] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2095,6 +2148,7 @@ action.notable.param.rule_description = This search looks for PowerShell request action.notable.param.rule_title = Detect Mimikatz Via PowerShell And EventCode 4703 action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2140,6 +2194,7 @@ action.notable.param.rule_description = This search looks for newly created acco action.notable.param.rule_title = Detect New Local Admin account action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2179,6 +2234,7 @@ action.notable.param.rule_description = The search queries the authentication lo action.notable.param.rule_title = Detect New Login Attempts to Routers action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2218,6 +2274,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect New Open S3 buckets action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2257,6 +2314,7 @@ action.notable.param.rule_description = This search looks for execution of proce action.notable.param.rule_title = Detect Oulook exe writing a zip file action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2295,6 +2353,7 @@ action.notable.param.rule_description = This search looks for outbound SMB conne action.notable.param.rule_title = Detect Outbound SMB Traffic action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2334,6 +2393,7 @@ action.notable.param.rule_description = The search is looking for the creation o action.notable.param.rule_title = Detect Path Interception By Creation Of program exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2373,6 +2433,7 @@ action.notable.param.rule_description = This search looks for executions of cmd. action.notable.param.rule_title = Detect Prohibited Applications Spawning cmd exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2412,6 +2473,7 @@ action.notable.param.rule_description = This search looks for events where `PsEx action.notable.param.rule_title = Detect PsExec With accepteula Flag action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2451,6 +2513,7 @@ action.notable.param.rule_description = This search will return a table of rare action.notable.param.rule_title = Detect Rare Executables action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2489,6 +2552,7 @@ action.notable.param.rule_description = This search looks at S3 bucket-access lo action.notable.param.rule_title = Detect S3 access from a new IP action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2534,6 +2598,7 @@ action.notable.param.rule_description = This search will detect users creating s action.notable.param.rule_title = Detect Spike in AWS API Activity action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2573,6 +2638,7 @@ action.notable.param.rule_description = This search will detect users creating s action.notable.param.rule_title = Detect Spike in Network ACL Activity action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2612,6 +2678,7 @@ action.notable.param.rule_description = This search detects users creating spike action.notable.param.rule_title = Detect Spike in S3 Bucket deletion action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2651,6 +2718,7 @@ action.notable.param.rule_description = This search will detect users creating s action.notable.param.rule_title = Detect Spike in Security Group Activity action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2689,6 +2757,7 @@ action.notable.param.rule_description = This search will detect spike in blocked action.notable.param.rule_title = Detect Spike in blocked Outbound Traffic from your AWS action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2728,6 +2797,7 @@ action.notable.param.rule_description = The search is used to detect hosts that action.notable.param.rule_title = Detect USB device insertion action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2766,6 +2836,7 @@ action.notable.param.rule_description = By populating the organization's assets action.notable.param.rule_title = Detect Unauthorized Assets by MAC address action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2805,6 +2876,7 @@ action.notable.param.rule_description = This search looks for the execution of t action.notable.param.rule_title = Detect Use of cmd exe to Launch Script Interpreters action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2844,6 +2916,7 @@ action.notable.param.rule_description = This search looks for specific GET or HE action.notable.param.rule_title = Detect attackers scanning for vulnerable JBoss servers action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2888,6 +2961,7 @@ action.notable.param.rule_description = Malicious actors often abuse legitimate action.notable.param.rule_title = Detect hosts connecting to dynamic domain providers action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2927,6 +3001,7 @@ action.notable.param.rule_description = This search is used to detect malicious action.notable.param.rule_title = Detect malicious requests to exploit JBoss servers action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -2966,6 +3041,7 @@ action.notable.param.rule_description = This search looks for the execution of " action.notable.param.rule_title = Detect mshta exe running scripts in command-line arguments action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3005,6 +3081,7 @@ action.notable.param.rule_description = This search detects new API calls that h action.notable.param.rule_title = Detect new API calls from user roles action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3044,6 +3121,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = Detect new user AWS Console Login action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3083,6 +3161,7 @@ action.notable.param.rule_description = This search looks for fast execution of action.notable.param.rule_title = Detect processes used for System Network Configuration Discovery action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3124,6 +3203,7 @@ action.notable.param.rule_description = This search looks for web connections to action.notable.param.rule_title = Detect web traffic to dynamic domain providers action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3163,6 +3243,7 @@ action.notable.param.rule_description = This search is used to detect DNS tunnel action.notable.param.rule_title = Detection of DNS Tunnels action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3202,6 +3283,7 @@ action.notable.param.rule_description = This search looks for specific command-l action.notable.param.rule_title = Detection of tools built by NirSoft action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3241,6 +3323,7 @@ action.notable.param.rule_description = The search looks for modifications to re action.notable.param.rule_title = Disabling Remote User Account Control action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3280,6 +3363,7 @@ action.notable.param.rule_description = Detect the usage of comsvcs.dll for dump action.notable.param.rule_title = Dump LSASS via comsvcs DLL action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3319,6 +3403,7 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Modified With Previously Unseen User action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3357,6 +3442,7 @@ action.notable.param.rule_description = This search looks for CloudTrail events action.notable.param.rule_title = EC2 Instance Started In Previously Unseen Region action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3395,6 +3481,7 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Started With Previously Unseen AMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3434,6 +3521,7 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Started With Previously Unseen Instance Type action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3473,6 +3561,7 @@ action.notable.param.rule_description = This search looks for EC2 instances bein action.notable.param.rule_title = EC2 Instance Started With Previously Unseen User action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3513,6 +3602,7 @@ action.notable.param.rule_description = Attackers often use spaces as a means to action.notable.param.rule_title = Email Attachments With Lots Of Spaces action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3552,6 +3642,7 @@ action.notable.param.rule_description = The search looks at the change-analysis action.notable.param.rule_title = Email files written outside of the Outlook directory action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3590,6 +3681,7 @@ action.notable.param.rule_description = This search looks for an increase of dat action.notable.param.rule_title = Email servers sending high volume traffic to hosts action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3628,6 +3720,7 @@ action.notable.param.rule_description = This search identifies DNS query failure action.notable.param.rule_title = Excessive DNS Failures action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3667,6 +3760,7 @@ action.notable.param.rule_description = This search looks for processes launched action.notable.param.rule_title = Execution of File With Spaces Before Extension action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3706,6 +3800,7 @@ action.notable.param.rule_description = This search looks for processes launched action.notable.param.rule_title = Execution of File with Multiple Extensions action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3745,6 +3840,7 @@ action.notable.param.rule_description = This search returns a list of hosts that action.notable.param.rule_title = Extended Period Without Successful Netbackup Backups action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3784,6 +3880,7 @@ action.notable.param.rule_description = The search looks for file writes with ex action.notable.param.rule_title = File with Samsam Extension action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3823,6 +3920,7 @@ action.notable.param.rule_description = This search looks for the first time a W action.notable.param.rule_title = First Time Seen Running Windows Service action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3861,6 +3959,7 @@ action.notable.param.rule_description = This search looks for command-line argum action.notable.param.rule_title = First time seen command line argument action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3900,6 +3999,7 @@ action.notable.param.rule_description = This search show information on uploaded action.notable.param.rule_title = GCP GCR container uploaded action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3938,6 +4038,7 @@ action.notable.param.rule_description = This search provides information of unau action.notable.param.rule_title = GCP Kubernetes cluster scan detection action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -3977,6 +4078,7 @@ action.notable.param.rule_description = Attackers leverage an existing Windows b action.notable.param.rule_title = Hiding Files And Directories With Attrib exe action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4015,6 +4117,7 @@ action.notable.param.rule_description = This search looks for an increase of dat action.notable.param.rule_title = Hosts receiving high volume of network traffic from email server action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4053,6 +4156,7 @@ action.notable.param.rule_description = This detection search will help profile action.notable.param.rule_title = Identify New User Accounts action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4091,6 +4195,7 @@ action.notable.param.rule_description = The search is used to identify attempts action.notable.param.rule_title = Large Volume of DNS ANY Queries action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4117,6 +4222,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - MacOS - Re-opened Applications - Rule action.escu.search_type = detection action.escu.providing_technologies = [] +action.escu.analytic_story = [] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4129,6 +4235,7 @@ action.notable.param.rule_description = This search looks for processes referenc action.notable.param.rule_title = MacOS - Re-opened Applications action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4168,6 +4275,7 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Connect To Internet With Hidden Window action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4207,6 +4315,7 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Encoded Command action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4246,6 +4355,7 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Execution Policy Bypass action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4285,6 +4395,7 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4324,6 +4435,7 @@ action.notable.param.rule_description = This search looks for PowerShell process action.notable.param.rule_title = Malicious PowerShell Process With Obfuscation Techniques action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4362,6 +4474,7 @@ action.notable.param.rule_description = This search looks for DNS requests for f action.notable.param.rule_title = Monitor DNS For Brand Abuse action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4400,6 +4513,7 @@ action.notable.param.rule_description = This search looks for emails claiming to action.notable.param.rule_title = Monitor Email For Brand Abuse action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4439,6 +4553,7 @@ action.notable.param.rule_description = This search looks for registry activity action.notable.param.rule_title = Monitor Registry Keys for Print Monitors action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4478,6 +4593,7 @@ action.notable.param.rule_description = This search looks for Web requests to fa action.notable.param.rule_title = Monitor Web Traffic For Brand Abuse action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4516,6 +4632,7 @@ action.notable.param.rule_description = This search detects Okta login failures action.notable.param.rule_title = Multiple Okta Users With Invalid Credentails From The Same IP action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4555,6 +4672,7 @@ action.notable.param.rule_description = This searches show information on upload action.notable.param.rule_title = New container uploaded to AWS ECR action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4594,6 +4712,7 @@ action.notable.param.rule_description = This search looks for Windows endpoints action.notable.param.rule_title = No Windows Updates in a time frame action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4632,6 +4751,7 @@ action.notable.param.rule_description = Detect Okta user lockout events action.notable.param.rule_title = Okta Account Lockout Events action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4670,6 +4790,7 @@ action.notable.param.rule_description = Detect failed Okta SSO events action.notable.param.rule_title = Okta Failed SSO Attempts action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4709,6 +4830,7 @@ action.notable.param.rule_description = This search detects logins from the same action.notable.param.rule_title = Okta User Logins From Multiple Cities action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4747,6 +4869,7 @@ action.notable.param.rule_description = This search allows you to look for evide action.notable.param.rule_title = Open Redirect in Splunk Web action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4785,6 +4908,7 @@ action.notable.param.rule_description = This search looks for ColdRoot events fr action.notable.param.rule_title = Osquery pack - ColdRoot detection action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4824,6 +4948,7 @@ action.notable.param.rule_description = Microsoft Windows contains accessibility action.notable.param.rule_title = Overwriting Accessibility Binaries action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4863,6 +4988,7 @@ action.notable.param.rule_description = This search looks for processes launched action.notable.param.rule_title = Process Execution via WMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4901,6 +5027,7 @@ action.notable.param.rule_description = This search looks for processes in an Ma action.notable.param.rule_title = Processes Tapping Keyboard Events action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4940,6 +5067,7 @@ action.notable.param.rule_description = This search looks for processes launchin action.notable.param.rule_title = Processes created by netsh action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -4979,6 +5107,7 @@ action.notable.param.rule_description = This search looks for processes launchin action.notable.param.rule_title = Processes launching netsh action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5017,6 +5146,7 @@ action.notable.param.rule_description = This search looks for network traffic de action.notable.param.rule_title = Prohibited Network Traffic Allowed action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5056,6 +5186,7 @@ action.notable.param.rule_description = This search looks for applications on th action.notable.param.rule_title = Prohibited Software On Endpoint action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5094,6 +5225,7 @@ action.notable.param.rule_description = This search looks for network traffic on action.notable.param.rule_title = Protocol or Port Mismatch action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5133,6 +5265,7 @@ action.notable.param.rule_description = This search looks for cleartext protocol action.notable.param.rule_title = Protocols passing authentication in cleartext action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5172,6 +5305,7 @@ action.notable.param.rule_description = The search looks for reg.exe modifying r action.notable.param.rule_title = Reg exe Manipulating Windows Services Registry Keys action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5211,6 +5345,7 @@ action.notable.param.rule_description = The search looks for command-line argume action.notable.param.rule_title = Reg exe used to hide files directories via registry keys action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5250,6 +5385,7 @@ action.notable.param.rule_description = The search looks for modifications to re action.notable.param.rule_title = Registry Keys Used For Persistence action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5289,6 +5425,7 @@ action.notable.param.rule_description = This search looks for modifications to r action.notable.param.rule_title = Registry Keys Used For Privilege Escalation action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5327,6 +5464,7 @@ action.notable.param.rule_description = This search looks for registry activity action.notable.param.rule_title = Registry Keys for Creating SHIM Databases action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5366,6 +5504,7 @@ action.notable.param.rule_description = This search looks for RDP application ne action.notable.param.rule_title = Remote Desktop Network Bruteforce action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5405,6 +5544,7 @@ action.notable.param.rule_description = This search looks for network traffic on action.notable.param.rule_title = Remote Desktop Network Traffic action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5444,6 +5584,7 @@ action.notable.param.rule_description = This search looks for the remote desktop action.notable.param.rule_title = Remote Desktop Process Running On System action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5483,6 +5624,7 @@ action.notable.param.rule_description = This search looks for wmic.exe being lau action.notable.param.rule_title = Remote Process Instantiation via WMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5522,6 +5664,7 @@ action.notable.param.rule_description = This search monitors for remote modifica action.notable.param.rule_title = Remote Registry Key modifications action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5561,6 +5704,7 @@ action.notable.param.rule_description = This search looks for wmic.exe being lau action.notable.param.rule_title = Remote WMI Command Attempt action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5600,6 +5744,7 @@ action.notable.param.rule_description = This search looks for DLLs under %AppDat action.notable.param.rule_title = RunDLL Loading DLL By Ordinal action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5639,6 +5784,7 @@ action.notable.param.rule_description = This search looks for spikes in the numb action.notable.param.rule_title = SMB Traffic Spike action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5681,6 +5827,7 @@ action.notable.param.rule_description = This search uses the Machine Learning To action.notable.param.rule_title = SMB Traffic Spike - MLTK action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5720,6 +5867,7 @@ action.notable.param.rule_description = This search looks for long URLs that hav action.notable.param.rule_title = SQL Injection with Long URLs action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5759,6 +5907,7 @@ action.notable.param.rule_description = The search looks for a file named "test. action.notable.param.rule_title = Samsam Test File Write action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5798,6 +5947,7 @@ action.notable.param.rule_description = This search looks for arguments to sc.ex action.notable.param.rule_title = Sc exe Manipulating Windows Services action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5837,6 +5987,7 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Scheduled Task Name Used by Dragonfly Threat Actors action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5876,6 +6027,7 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Scheduled tasks used in BadRabbit ransomware action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5915,6 +6067,7 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Schtasks scheduling job on remote system action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5954,6 +6107,7 @@ action.notable.param.rule_description = This search looks for flags passed to sc action.notable.param.rule_title = Schtasks used for forcing a reboot action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -5993,6 +6147,7 @@ action.notable.param.rule_description = This search looks for scripts launched v action.notable.param.rule_title = Script Execution via WMI action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6032,6 +6187,7 @@ action.notable.param.rule_description = This search looks for shim database file action.notable.param.rule_title = Shim Database File Creation action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6071,6 +6227,7 @@ action.notable.param.rule_description = This search detects the process executio action.notable.param.rule_title = Shim Database Installation With Suspicious Parameters action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6110,6 +6267,7 @@ action.notable.param.rule_description = This search detects accounts that were c action.notable.param.rule_title = Short Lived Windows Accounts action.notable.param.security_domain = access action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6148,6 +6306,7 @@ action.notable.param.rule_description = This search looks for process names that action.notable.param.rule_title = Single Letter Process On Endpoint action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6186,6 +6345,7 @@ action.notable.param.rule_description = The search is used to detect systems tha action.notable.param.rule_title = Spectre and Meltdown Vulnerable Systems action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6225,6 +6385,7 @@ action.notable.param.rule_description = The search looks for a sharp increase in action.notable.param.rule_title = Spike in File Writes action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6264,6 +6425,7 @@ action.notable.param.rule_description = This search allows you to look for evide action.notable.param.rule_title = Splunk Enterprise Information Disclosure action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6303,6 +6465,7 @@ action.notable.param.rule_description = This search looks for changes to registr action.notable.param.rule_title = Suspicious Changes to File Associations action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6342,6 +6505,7 @@ action.notable.param.rule_description = This detection looks for emails that are action.notable.param.rule_title = Suspicious Email - UBA Anomaly action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6382,6 +6546,7 @@ action.notable.param.rule_description = This search looks for emails that have a action.notable.param.rule_title = Suspicious Email Attachment Extensions action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6421,6 +6586,7 @@ action.notable.param.rule_description = The search looks for files created with action.notable.param.rule_title = Suspicious File Write action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6460,6 +6626,7 @@ action.notable.param.rule_description = This search looks for suspicious Java cl action.notable.param.rule_title = Suspicious Java Classes action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6499,6 +6666,7 @@ action.notable.param.rule_description = This search looks for a ``*.lnk` file un action.notable.param.rule_title = Suspicious LNK file launching a process action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6538,6 +6706,7 @@ action.notable.param.rule_description = This search looks for reg.exe being laun action.notable.param.rule_title = Suspicious Reg exe Process action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6577,6 +6746,7 @@ action.notable.param.rule_description = The wevtutil.exe application is the wind action.notable.param.rule_title = Suspicious wevtutil Usage action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6615,6 +6785,7 @@ action.notable.param.rule_description = This search detects writes to the 'Syste action.notable.param.rule_title = Suspicious writes to System Volume Information action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6654,6 +6825,7 @@ action.notable.param.rule_description = This search detects writes to the recycl action.notable.param.rule_title = Suspicious writes to windows Recycle Bin action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6693,6 +6865,7 @@ action.notable.param.rule_description = This search looks for system processes t action.notable.param.rule_title = System Processes Run From Unexpected Locations action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6731,6 +6904,7 @@ action.notable.param.rule_description = This search looks for network traffic id action.notable.param.rule_title = TOR Traffic action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6770,6 +6944,7 @@ action.notable.param.rule_description = The fsutil.exe application is a legitima action.notable.param.rule_title = USN Journal Deletion action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6809,6 +6984,7 @@ action.notable.param.rule_description = This search looks for applications on th action.notable.param.rule_title = Uncommon Processes On Endpoint action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6848,6 +7024,7 @@ action.notable.param.rule_description = Attackers often disable security tools t action.notable.param.rule_title = Unload Sysmon Filter Driver action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6887,6 +7064,7 @@ action.notable.param.rule_description = This search detects loading of unsigned action.notable.param.rule_title = Unsigned Image Loaded by LSASS action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6925,6 +7103,7 @@ action.notable.param.rule_description = This search gives you the hosts where a action.notable.param.rule_title = Unsuccessful Netbackup backups action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -6964,6 +7143,7 @@ action.notable.param.rule_description = Command lines that are extremely long ma action.notable.param.rule_title = Unusually Long Command Line action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7003,6 +7183,7 @@ action.notable.param.rule_description = Command lines that are extremely long ma action.notable.param.rule_title = Unusually Long Command Line - MLTK action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7041,6 +7222,7 @@ action.notable.param.rule_description = This search looks for unusually long str action.notable.param.rule_title = Unusually Long Content-Type Length action.notable.param.security_domain = network action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7080,6 +7262,7 @@ action.notable.param.rule_description = This search looks for the creation of WM action.notable.param.rule_title = WMI Permanent Event Subscription action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7119,6 +7302,7 @@ action.notable.param.rule_description = This search looks for the creation of WM action.notable.param.rule_title = WMI Permanent Event Subscription - Sysmon action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7157,6 +7341,7 @@ action.notable.param.rule_description = This search looks for the creation of WM action.notable.param.rule_title = WMI Temporary Event Subscription action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7196,6 +7381,7 @@ action.notable.param.rule_description = This search is used to identify the crea action.notable.param.rule_title = Web Fraud - Account Harvesting action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7234,6 +7420,7 @@ action.notable.param.rule_description = This search is used to examine web sessi action.notable.param.rule_title = Web Fraud - Anomalous User Clickspeed action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7273,6 +7460,7 @@ action.notable.param.rule_description = This search is used to identify user acc action.notable.param.rule_title = Web Fraud - Password Sharing Across Accounts action.notable.param.security_domain = threat action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7312,6 +7500,7 @@ action.notable.param.rule_description = This search looks for suspicious process action.notable.param.rule_title = Web Servers Executing Suspicious Processes action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7351,6 +7540,7 @@ action.notable.param.rule_description = This search looks for Windows events tha action.notable.param.rule_title = Windows Event Log Cleared action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7390,6 +7580,7 @@ action.notable.param.rule_description = The search looks for modifications to th action.notable.param.rule_title = Windows hosts file modification action.notable.param.security_domain = endpoint action.notable.param.severity = medium +alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 disabled = true @@ -7404,6 +7595,2162 @@ search = | tstats `security_content_summariesonly` count min(_time) as firstTime ### END ESCU DETECTIONS ### +### ESCU BASELINES ### + +[ESCU - Add Prohibited Processes to Enterprise Security - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security +description = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. +action.escu.creation_date = 2017-09-15 +action.escu.modification_date = 2017-09-15 +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "SamSam Ransomware"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. +action.escu.how_to_implement = This search should be run on each new install of ESCU. +disabled = true +is_visible = false +search = | inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count + +[ESCU - Baseline of API Calls per User ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of API Calls per User ARN +description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-04-09 +action.escu.modification_date = 2018-04-09 +action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventType=AwsApiCall | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup api_call_by_user_baseline | stats count + +[ESCU - Baseline of Command Line Length - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Command Line Length - MLTK +description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. +action.escu.creation_date = 2019-05-08 +action.escu.modification_date = 2019-05-08 +action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Unusual Processes"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the command lines observed for each user in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies outliers in the length of the command line. +action.escu.how_to_implement = You must be ingesting endpoint data and populating the Endpoint data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name(Processes)` | search user!=unknown | `security_content_ctime(start_time)`| `security_content_ctime(end_time)`| eval processlen=len(process) | fit DensityFunction processlen by user into cmdline_pdfmodel + +[ESCU - Baseline of DNS Query Length - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of DNS Query Length - MLTK +description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. +action.escu.creation_date = 2019-05-08 +action.escu.modification_date = 2019-05-08 +action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] +action.escu.data_models = [Network_Resolution] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query. +action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name("DNS")` | eval query_length = len(query) | fit DensityFunction query_length by record_type into dns_query_pdfmodel + +[ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK +description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. +action.escu.creation_date = 2019-11-14 +action.escu.modification_date = 2019-11-14 +action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many RunInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of RunInstances performed by a user in a small time window. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ +In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ +More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | fit DensityFunction instances_launched threshold=0.0005 into ec2_excessive_runinstances_v1 + +[ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK +description = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. +action.escu.creation_date = 2019-11-14 +action.escu.modification_date = 2019-11-14 +action.escu.analytic_story = ["Suspicious AWS EC2 Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model for how many TerminateInstances users do in the environment. By default, the search uses the last 90 days of data to build the model. The model created by this search is then used in the corresponding detection search, which identifies subsequent outliers in the number of TerminateInstances performed by a user in a small time window. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs.\ +In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. Depending on the number of users in your environment, you may also need to adjust the value for max_inputs in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data.\ +More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | fit DensityFunction instances_terminated threshold=0.0005 into ec2_excessive_terminateinstances_v1 + +[ESCU - Baseline of Network ACL Activity by ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Network ACL Activity by ARN +description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-05-21 +action.escu.modification_date = 2018-05-21 +action.escu.analytic_story = ["AWS Network ACL Activity"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of API calls that were related to network ACLs made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for network ACLs, edit the macro `network_acl_events`. +disabled = true +is_visible = false +search = `cloudtrail` `network_acl_events` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup network_acl_activity_baseline | stats count + +[ESCU - Baseline of S3 Bucket deletion activity by ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of S3 Bucket deletion activity by ARN +description = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-07-17 +action.escu.modification_date = 2018-07-17 +action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search establishes, on a per-hour basis, the average and standard deviation for the number of API calls related to deleting an S3 bucket by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=DeleteBucket | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup s3_deletion_baseline | stats count + +[ESCU - Baseline of SMB Traffic - MLTK - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of SMB Traffic - MLTK +description = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. +action.escu.creation_date = 2019-05-08 +action.escu.modification_date = 2019-05-08 +action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Netsh Abuse", "Ransomware"] +action.escu.data_models = [Network_Traffic] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the number of SMB connections observed each hour for every day of week. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search to identify outliers in the number of SMB connections for that hour and day of the week. +action.escu.how_to_implement = You must be ingesting network traffic and populating the Network_Traffic data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. To improve your results, you may consider adding "src" to the by clause, which will build the model for each unique source in your enviornment. However, if you have a large number of hosts in your environment, this search may be very resource intensive. In this case, you may need to raise the value of max_inputs and/or max_groups in the MLTK settings for the DensityFunction algorithm, then ensure that the search completes in a reasonable timeframe. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at `https://docs.splunk.com/Documentation/MLApp/4.2.0/User/Algorithms#DensityFunction`. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=10m, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name("All_Traffic")` | fit DensityFunction count by "HourOfDay,DayOfWeek" into smb_pdfmodel + +[ESCU - Baseline of Security Group Activity by ARN - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of Security Group Activity by ARN +description = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-04-17 +action.escu.modification_date = 2018-04-17 +action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation for the number of API calls related to security groups made by each user. Also recorded is the number of data points for each user. This table is then outputted to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. +disabled = true +is_visible = false +search = `cloudtrail` `security_group_api_calls` | spath output=arn path=userIdentity.arn | bucket _time span=1h | stats count as apiCalls by _time, arn | stats count(apiCalls) as numDataPoints, latest(apiCalls) as latestCount, avg(apiCalls) as avgApiCalls, stdev(apiCalls) as stdevApiCalls by arn | table arn, latestCount, numDataPoints, avgApiCalls, stdevApiCalls | outputlookup security_group_activity_baseline | stats count + +[ESCU - Baseline of blocked outbound traffic from AWS - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Baseline of blocked outbound traffic from AWS +description = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. +action.escu.creation_date = 2018-05-07 +action.escu.modification_date = 2018-05-07 +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search establishes, on a per-hour basis, the average and the standard deviation of the number of outbound connections blocked in your VPC flow logs by each source IP address (IP address of your EC2 instances). Also recorded is the number of data points for each source IP. This table outputs to a lookup file to allow the detection search to operate quickly. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your `VPC flow logs.`. +disabled = true +is_visible = false +search = `cloudwatchlogs_vpcflow` action=blocked (src_ip=10.0.0.0/8 OR src_ip=172.16.0.0/12 OR src_ip=192.168.0.0/16) ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | bucket _time span=1h | stats count as numberOfBlockedConnections by _time, src_ip | stats count(numberOfBlockedConnections) as numDataPoints, latest(numberOfBlockedConnections) as latestCount, avg(numberOfBlockedConnections) as avgBlockedConnections, stdev(numberOfBlockedConnections) as stdevBlockedConnections by src_ip | table src_ip, latestCount, numDataPoints, avgBlockedConnections, stdevBlockedConnections | outputlookup baseline_blocked_outbound_connections | stats count + +[ESCU - Count of Unique IPs Connecting to Ports - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Count of Unique IPs Connecting to Ports +description = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. +action.escu.creation_date = 2017-09-13 +action.escu.modification_date = 2017-09-13 +action.escu.analytic_story = [] +action.escu.data_models = [Network_Traffic] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = The search counts the number of times a connection was observed to each destination port, and the number of unique source IPs connecting to them. +action.escu.how_to_implement = To successfully implement this search, you must be ingesting network traffic, and populating the Network_Traffic data model. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count dc(All_Traffic.src) as numberOfUniqueHosts from datamodel=Network_Traffic by All_Traffic.dest_port | `drop_dm_object_name("All_Traffic")` | sort - count + +[ESCU - Count of assets by category - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Count of assets by category +description = This search shows you every asset category you have and the assets that belong to those categories. +action.escu.creation_date = 2017-09-13 +action.escu.modification_date = 2017-09-13 +action.escu.analytic_story = ["Asset Tracking"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search shows you every asset category you have and the assets that belong to those categories. +action.escu.how_to_implement = To successfully implement this search you must first leverage the Assets and Identity framework in Enterprise Security to populate your assets_by_str.csv file which should then be mapped to the Identity_Management data model. The Identity_Management data model will contain a list of known authorized company assets. Ensure that all inventoried systems are constantly vetted and updated. +disabled = true +is_visible = false +search = | from datamodel Identity_Management.All_Assets | stats count values(nt_host) by category | sort -count + +[ESCU - Create a list of approved AWS service accounts - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Create a list of approved AWS service accounts +description = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. +action.escu.creation_date = 2018-12-03 +action.escu.modification_date = 2018-12-03 +action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for successful API activity in CloudTrail within the last 30 days, filters out known users from the identity table, and outputs values of users into `aws_service_accounts.csv` lookup file. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the service account entires in `aws_service_accounts.csv`, which is a lookup file created as a result of running this support search. Please remove the entries of service accounts that are not legitimate. +disabled = true +is_visible = false +search = `cloudtrail` errorCode=success | rename userName as identity | search NOT [inputlookup identity_lookup_expanded | fields identity] | stats count by identity | table identity | outputlookup aws_service_accounts | stats count + +[ESCU - DNSTwist Domain Names - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - DNSTwist Domain Names +description = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. +action.escu.creation_date = 2018-10-08 +action.escu.modification_date = 2018-10-08 +action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search creates permutations of your existing domains, removes the valid domain names and stores them in a specified lookup file so they can be checked for in the associated detection searches. +action.escu.how_to_implement = To successfully implement this search you need to update the file called domains.csv in the DA-ESS-SOC/lookup directory. Or `cim_corporate_email_domains.csv` and `cim_corporate_web_domains.csv` from **Splunk\_SA\_CIM**. +disabled = true +is_visible = false +search = | dnstwist domainlist=domains.csv | `remove_valid_domains` | eval domain_abuse="true" | table domain, domain_abuse | outputlookup brandMonitoring_lookup | stats count + +[ESCU - Discover DNS records - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Discover DNS records +description = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup +action.escu.creation_date = 2019-02-14 +action.escu.modification_date = 2019-02-14 +action.escu.analytic_story = ["DNS Hijacking"] +action.escu.data_models = [Network_Resolution] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Resolution ` datamodel, then stores the output under the `discovered_dns_records.csv` lookup +action.escu.how_to_implement = To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation +disabled = true +is_visible = false +search = | inputlookup cim_corporate_email_domains.csv | inputlookup append=T cim_corporate_web_domains.csv | inputlookup append=T cim_cloud_domains.csv | eval domain = trim(replace(domain, "\*", "")) | join domain [|tstats `security_content_summariesonly` count values(DNS.record_type) as type, values(DNS.answer) as answer from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!="unknown" DNS.answer!="" by DNS.query | rename DNS.query as query | where query!="unknown" | rex field=query "(?\w+\.\w+?)(?:$|/)"] | makemv delim=" " answer | makemv delim=" " type | sort -count | table count,domain,type,query,answer | outputlookup createinapp=true discovered_dns_records.csv + +[ESCU - Identify Systems Creating Remote Desktop Traffic - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Identify Systems Creating Remote Desktop Traffic +description = This search counts the numbers of times the system has generated remote desktop traffic. +action.escu.creation_date = 2017-09-15 +action.escu.modification_date = 2017-09-15 +action.escu.analytic_story = [] +action.escu.data_models = [Network_Traffic] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search counts the numbers of times the system has generated remote desktop traffic. +action.escu.how_to_implement = To successfully implement this search, you must ingest network traffic and populate the Network_Traffic data model. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.src | `drop_dm_object_name("All_Traffic")` | sort - count + +[ESCU - Identify Systems Receiving Remote Desktop Traffic - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Identify Systems Receiving Remote Desktop Traffic +description = This search counts the numbers of times the system has created remote desktop traffic +action.escu.creation_date = 2017-09-15 +action.escu.modification_date = 2017-09-15 +action.escu.analytic_story = [] +action.escu.data_models = [Network_Traffic] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search counts the numbers of times the system has created remote desktop traffic +action.escu.how_to_implement = To successfully implement this search you must ingest network traffic and populate the Network_Traffic data model. If a system receives a lot of remote desktop traffic, you can apply the category common_rdp_destination to it. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Network_Traffic where All_Traffic.dest_port=3389 by All_Traffic.dest | `drop_dm_object_name("All_Traffic")` | sort - count + +[ESCU - Identify Systems Using Remote Desktop - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Identify Systems Using Remote Desktop +description = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. +action.escu.creation_date = 2019-04-01 +action.escu.modification_date = 2019-04-01 +action.escu.analytic_story = [] +action.escu.data_models = [Endpoint] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search counts the numbers of times the remote desktop process, mstsc.exe, has run on each system. +action.escu.how_to_implement = To successfully implement this search you must be ingesting endpoint data that records process activity. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count from datamodel=Endpoint.Processes where Processes.process_name="*mstsc.exe*" by Processes.dest Processes.process_name | `drop_dm_object_name(Processes)` | sort - count + +[ESCU - Monitor Successful Backups - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Monitor Successful Backups +description = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.creation_date = 2017-09-12 +action.escu.modification_date = 2017-09-12 +action.escu.analytic_story = ["Monitor Backup Solution"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is intended to give you a feel for how often successful backups are conducted in your environment. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. +disabled = true +is_visible = false +search = `netbackup` "Disk/Partition backup completed successfully." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE + +[ESCU - Monitor Unsuccessful Backups - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Monitor Unsuccessful Backups +description = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.creation_date = 2017-09-12 +action.escu.modification_date = 2017-09-12 +action.escu.analytic_story = ["Monitor Backup Solution"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is intended to give you a feel for how often backup failures happen in your environments. Fluctuations in these numbers will allow you to determine when you should investigate. +action.escu.how_to_implement = To successfully implement this search you must be ingesting your backup logs. +disabled = true +is_visible = false +search = `netbackup` "An error occurred, failed to backup." | bucket _time span=1d | stats dc(COMPUTERNAME) as count values(COMPUTERNAME) as dest by _time, MESSAGE + +[ESCU - Previously Seen AWS Cross Account Activity - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen AWS Cross Account Activity +description = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. +action.escu.creation_date = 2018-06-04 +action.escu.modification_date = 2018-06-04 +action.escu.analytic_story = ["AWS Cross Account Activity"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for **AssumeRole** events where the requesting account differs from the requested account, then writes these relationships to a lookup file. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Validate the user name entries in `previously_seen_aws_cross_account_activity.csv`, a lookup file created by this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId!=requestedAccountId | stats earliest(_time) as firstTime latest(_time) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity | stats count + +[ESCU - Previously Seen AWS Provisioning Activity Sources - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen AWS Provisioning Activity Sources +description = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. +action.escu.creation_date = 2018-03-16 +action.escu.modification_date = 2018-03-16 +action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of the first and last times seen for every IP address (along with its physical location) previously associated with cloud-provisioning activity. This is broadly defined as any event that runs or creates something. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats count + +[ESCU - Previously Seen AWS Regions - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen AWS Regions +description = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days +action.escu.creation_date = 2018-01-08 +action.escu.modification_date = 2018-01-08 +action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv | stats count + +[ESCU - Previously Seen Cloud Compute Creations By User - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Creations By User +description = This search builds a table of previously seen users that have launched a cloud compute instance. +action.escu.creation_date = 2018-03-15 +action.escu.modification_date = 2018-03-15 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = [Cloud_Infrastructure] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of previously seen users that have launched a cloud compute instance. +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_creations_by_user_input_filter` by Compute.src_user | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_creations_by_user | stats count + +[ESCU - Previously Seen Cloud Compute Images - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Images +description = This search builds a table of previously seen images used to launch cloud compute instances +action.escu.creation_date = 2018-03-12 +action.escu.modification_date = 2018-03-12 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = [Cloud_Infrastructure] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of previously seen images used to launch cloud compute instances +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_images | stats count + +[ESCU - Previously Seen Cloud Compute Instance Types - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Compute Instance Types +description = This search builds a table of previously seen cloud compute instance types +action.escu.creation_date = 2019-10-03 +action.escu.modification_date = 2019-10-03 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = [Cloud_Infrastructure] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of previously seen cloud compute instance types +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_compute_instance_types | stats count + +[ESCU - Previously Seen Cloud Regions - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Cloud Regions +description = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days +action.escu.creation_date = 2019-10-02 +action.escu.modification_date = 2019-10-02 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.data_models = [Cloud_Infrastructure] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for cloud compute events where a compute instance is started and creates a baseline of most recent time, `lastTime` and the first time `firstTime` we've seen this region in our dataset grouped by the region for the last 30 days +action.escu.how_to_implement = You must be ingesting the approrpiate cloud infrastructure logs and have the Security Research cloud data model installed. +disabled = true +is_visible = false +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime from datamodel=Cloud_Infrastructure.Compute where Compute.action=start `previously_seen_cloud_regions_input_filter` by Compute.region | `drop_dm_object_name("Compute")` | outputlookup previously_seen_cloud_regions | stats count + +[ESCU - Previously Seen EC2 AMIs - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 AMIs +description = This search builds a table of previously seen AMIs used to launch EC2 instances +action.escu.creation_date = 2018-03-12 +action.escu.modification_date = 2018-03-12 +action.escu.analytic_story = ["AWS Cryptomining"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of previously seen AMIs used to launch EC2 instances +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instancesSet.items{}.imageId as amiID | stats earliest(_time) as firstTime latest(_time) as lastTime by amiID | outputlookup previously_seen_ec2_amis.csv | stats count + +[ESCU - Previously Seen EC2 Instance Types - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 Instance Types +description = This search builds a table of previously seen EC2 instance types +action.escu.creation_date = 2018-03-08 +action.escu.modification_date = 2018-03-08 +action.escu.analytic_story = ["AWS Cryptomining"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of previously seen EC2 instance types +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success | rename requestParameters.instanceType as instanceType | fillnull value="m1.small" instanceType | stats earliest(_time) as earliest latest(_time) as latest by instanceType | outputlookup previously_seen_ec2_instance_types.csv | stats count + +[ESCU - Previously Seen EC2 Launches By User - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 Launches By User +description = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.creation_date = 2018-03-15 +action.escu.modification_date = 2018-03-15 +action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. +disabled = true +is_visible = false +search = `cloudtrail` eventName=RunInstances errorCode=success | rename userIdentity.arn as arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_launches_by_user.csv | stats count + +[ESCU - Previously Seen EC2 Modifications By User - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen EC2 Modifications By User +description = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.creation_date = 2018-04-05 +action.escu.modification_date = 2018-04-05 +action.escu.analytic_story = ["Unusual AWS EC2 Modifications"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search builds a table of previously seen ARNs that have launched a EC2 instance. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS version (4.4.0 or later), then configure your CloudTrail inputs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. +disabled = true +is_visible = false +search = `cloudtrail` `ec2_modification_api_calls` errorCode=success | spath output=arn userIdentity.arn | stats earliest(_time) as firstTime latest(_time) as lastTime by arn | outputlookup previously_seen_ec2_modifications_by_user | stats count + +[ESCU - Previously Seen Running Windows Services - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously Seen Running Windows Services +description = This collects the services that have been started across your entire enterprise. +action.escu.creation_date = 2020-01-13 +action.escu.modification_date = 2020-01-13 +action.escu.analytic_story = ["Orangeworm Attack Group", "Windows Service Abuse"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This collects the services that have been started across your entire enterprise. +action.escu.how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs for it to execute successfully. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. +disabled = true +is_visible = false +search = `wineventlog_system` signature_id=7036 | rename param1 as service_name | rename param2 as action | search action="running" | stats earliest(_time) as firstTime, latest(_time) as lastTime by service_name | outputlookup previously_seen_running_windows_services | stats count + +[ESCU - Previously seen API call per user roles in CloudTrail - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen API call per user roles in CloudTrail +description = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. +action.escu.creation_date = 2018-04-16 +action.escu.modification_date = 2018-04-16 +action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for successful API calls made by different user roles, then creates a baseline of the earliest and latest times we have encountered this user role. It also returns the name of the API call in our dataset--grouped by user role and name of the API call--that occurred within the last 30 days. In this support search, we are only looking for events where the user identity is Assumed Role. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user role entries in `previously_seen_api_calls_from_user_roles.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventType=AwsApiCall errorCode=success userIdentity.type=AssumedRole | stats earliest(_time) as earliest latest(_time) as latest by userName eventName | outputlookup previously_seen_api_calls_from_user_roles | stats count + +[ESCU - Previously seen S3 bucket access by remote IP - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen S3 bucket access by remote IP +description = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" +action.escu.creation_date = 2018-06-28 +action.escu.modification_date = 2018-06-28 +action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for successful access to S3 buckets from remote IP addresses, then creates a baseline of the earliest and latest times we have encountered this remote IP within the last 30 days. In this support search, we are only looking for S3 access events where the HTTP response code from AWS is "200" +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access-logs inputs. You must validate the remote IP and bucket name entries in `previously_seen_S3_access_from_remote_ip.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `aws_s3_accesslogs` http_status=200 | stats earliest(_time) as earliest latest(_time) as latest by bucket_name remote_ip | outputlookup previously_seen_S3_access_from_remote_ip | stats count + +[ESCU - Previously seen command line arguments - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen command line arguments +description = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. +action.escu.creation_date = 2019-03-01 +action.escu.modification_date = 2019-03-01 +action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Hidden Cobra Malware", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] +action.escu.data_models = [Endpoint] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for command-line arguments where `cmd.exe /c` is used to execute a program, then creates a baseline of the earliest and latest times we have encountered this command-line argument in our dataset within the last 30 days. +action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe AND Processes.process="* /c *" by Processes.process | `drop_dm_object_name(Processes)` + +[ESCU - Previously seen users in CloudTrail - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Previously seen users in CloudTrail +description = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. +action.escu.creation_date = 2018-04-30 +action.escu.modification_date = 2018-04-30 +action.escu.analytic_story = ["Suspicious AWS Login Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then creates a baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last 30 days. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) as firstTime latest(_time) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv | stats count + +[ESCU - Systems Ready for Spectre-Meltdown Windows Patch - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Systems Ready for Spectre-Meltdown Windows Patch +description = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. +action.escu.creation_date = 2018-01-08 +action.escu.modification_date = 2018-01-08 +action.escu.analytic_story = ["Spectre And Meltdown Vulnerabilities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = Some AV applications can cause the Spectre/Meltdown patch for Windows not to install successfully. This registry key is supposed to be created by the AV engine when it has been patched to be able to handle the Windows patch. If this key has been written, the system can then be patched for Spectre and Meltdown. +action.escu.how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Change_Analysis.All_Changes where All_Changes.object_category=registry AND (All_Changes.object_path="HKLM\Software\Microsoft\Windows\CurrentVersion\QualityCompat*") by All_Changes.dest, All_Changes.command, All_Changes.user, All_Changes.object, All_Changes.object_path | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("All_Changes")` + +[ESCU - Update previously seen users in CloudTrail - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Update previously seen users in CloudTrail +description = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. +action.escu.creation_date = 2018-04-30 +action.escu.modification_date = 2018-04-30 +action.escu.analytic_story = ["Suspicious AWS Login Activities"] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search looks for CloudTrail events where a user logs into the console, then updates the baseline of the latest and earliest times, City, Region, and Country we have encountered this user in our dataset, grouped by ARN, within the last hour. +action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Please validate the user name entries in `previously_seen_users_console_logins.csv`, which is a lookup file created as a result of running this support search. +disabled = true +is_visible = false +search = `cloudtrail` eventName=ConsoleLogin | rename userIdentity.arn as user | iplocation src | eval City=if(City LIKE "",src,City),Region=if(Region LIKE "",src,Region) | stats earliest(_time) AS firstTime latest(_time) AS lastTime by user src City Region Country | inputlookup append=t previously_seen_users_console_logins.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by user src City Region Country | outputlookup previously_seen_users_console_logins.csv + +[ESCU - Windows Updates Install Failures - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Windows Updates Install Failures +description = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.creation_date = 2017-09-14 +action.escu.modification_date = 2017-09-14 +action.escu.analytic_story = [] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is intended to give you a feel for how often Windows updates fail to install in your environment. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.how_to_implement = You must be ingesting your Windows Update Logs +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=failure by _time span=1d + +[ESCU - Windows Updates Install Successes - Baseline] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = support +action.escu.full_search_name = ESCU - Windows Updates Install Successes +description = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.creation_date = 2017-09-14 +action.escu.modification_date = 2017-09-14 +action.escu.analytic_story = [] +action.escu.data_models = [] +dispatch.earliest_time = -30m +dispatch.latest_time = now +schedule_window = auto +action.escu.providing_technologies = [] +action.escu.eli5 = This search is intended to give you a feel for how often successful Windows updates are applied in your environments. Fluctuations in these numbers will allow you to determine when you should be concerned. +action.escu.how_to_implement = You must be ingesting your Windows Update Logs +disabled = true +is_visible = false +search = | tstats `security_content_summariesonly` dc(Updates.dest) as count FROM datamodel=Updates where Updates.vendor_product="Microsoft Windows" AND Updates.status=installed by _time span=1d + + + +### ESCU RESPONSE TASKS ### + +[ESCU - AWS Investigate User Activities By ARN - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN +description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. +action.escu.creation_date = 2019-04-30 +action.escu.modification_date = 2019-04-30 +action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Cloud Cryptomining", "Command and Control", "Suspicious AWS EC2 Activities", "Suspicious AWS Login Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Unusual AWS EC2 Modifications"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType + +[ESCU - AWS Investigate User Activities By AccessKeyId - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - AWS Investigate User Activities By AccessKeyId +description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. +action.escu.creation_date = 2018-06-08 +action.escu.modification_date = 2018-06-08 +action.escu.analytic_story = ["AWS Cross Account Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage + +[ESCU - AWS Investigate User Activities By Source User - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - AWS Investigate User Activities By Source User +description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. +action.escu.creation_date = 2018-06-08 +action.escu.modification_date = 2018-06-08 +action.escu.analytic_story = ["AWS Cross Account Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage + +[ESCU - AWS Network ACL Details from ID - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - AWS Network ACL Details from ID +description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID +action.escu.creation_date = 2017-01-22 +action.escu.modification_date = 2017-01-22 +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:description id={networkAclId} | table id account_id vpc_id network_acl_entries{}.* + +[ESCU - AWS Network Interface details via resourceId - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - AWS Network Interface details via resourceId +description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. +action.escu.creation_date = 2018-05-07 +action.escu.modification_date = 2018-05-07 +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Suspicious AWS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:config resourceId={resourceId} | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp + +[ESCU - AWS S3 Bucket details via bucketName - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - AWS S3 Bucket details via bucketName +description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. +action.escu.creation_date = 2018-06-26 +action.escu.modification_date = 2018-06-26 +action.escu.analytic_story = ["Suspicious AWS S3 Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList + +[ESCU - All backup logs for host - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - All backup logs for host +description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. +action.escu.creation_date = 2017-09-12 +action.escu.modification_date = 2017-09-12 +action.escu.analytic_story = ["Monitor Backup Solution"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype="netbackup_logs" dest={dest} + +[ESCU - Amazon EKS Kubernetes activity by src ip - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Amazon EKS Kubernetes activity by src ip +description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address +action.escu.creation_date = 2020-04-13 +action.escu.modification_date = 2020-04-13 +action.escu.analytic_story = ["Kubernetes Scanning Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip + +[ESCU - GCP Kubernetes activity by src ip - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - GCP Kubernetes activity by src ip +description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address +action.escu.creation_date = 2020-04-13 +action.escu.modification_date = 2020-04-13 +action.escu.analytic_story = ["Kubernetes Scanning Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type + +[ESCU - Get All AWS Activity From City - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get All AWS Activity From City +description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.creation_date = 2018-03-19 +action.escu.modification_date = 2018-03-19 +action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode + +[ESCU - Get All AWS Activity From Country - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get All AWS Activity From Country +description = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.creation_date = 2018-03-19 +action.escu.modification_date = 2018-03-19 +action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode + +[ESCU - Get All AWS Activity From IP Address - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get All AWS Activity From IP Address +description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.creation_date = 2018-03-19 +action.escu.modification_date = 2018-03-19 +action.escu.analytic_story = ["AWS Network ACL Activity", "AWS Suspicious Provisioning Activities", "Command and Control", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode + +[ESCU - Get All AWS Activity From Region - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get All AWS Activity From Region +description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.creation_date = 2018-03-19 +action.escu.modification_date = 2018-03-19 +action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode + +[ESCU - Get Authentication Logs For Endpoint - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Authentication Logs For Endpoint +description = This search returns all users that have attempted to access a particular endpoint. +action.escu.creation_date = 2017-11-01 +action.escu.modification_date = 2017-11-01 +action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] +action.escu.eli5 = This search returns all users that have attempted to access a particular endpoint. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats count from datamodel=Authentication where Authentication.dest={dest} by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` + +[ESCU - Get Backup Logs For Endpoint - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Backup Logs For Endpoint +description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. +action.escu.creation_date = 2017-09-14 +action.escu.modification_date = 2017-09-14 +action.escu.analytic_story = ["Ransomware", "SamSam Ransomware"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature + +[ESCU - Get Certificate logs for a domain - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Certificate logs for a domain +description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. +action.escu.creation_date = 2019-04-29 +action.escu.modification_date = 2019-04-29 +action.escu.analytic_story = ["Common Phishing Frameworks"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + +[ESCU - Get DNS Server History for a host - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get DNS Server History for a host +description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. +action.escu.creation_date = 2017-11-09 +action.escu.modification_date = 2017-11-09 +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DNS Hijacking", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Host Redirection", "Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count + +[ESCU - Get DNS traffic ratio - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get DNS traffic ratio +description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. +action.escu.creation_date = 2017-11-09 +action.escu.modification_date = 2017-11-09 +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Network_Traffic] +action.escu.eli5 = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval ratio = (bytes_out/bytes_in) | table ratio + +[ESCU - Get EC2 Instance Details by instanceId - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get EC2 Instance Details by instanceId +description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field +action.escu.creation_date = 2018-02-12 +action.escu.modification_date = 2018-02-12 +action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Unusual AWS EC2 Modifications"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC + +[ESCU - Get EC2 Launch Details - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get EC2 Launch Details +description = This search returns some of the launch details for a EC2 instance. +action.escu.creation_date = 2018-03-12 +action.escu.modification_date = 2018-03-12 +action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns some of the launch details for a EC2 instance. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName + +[ESCU - Get Email Info - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Email Info +description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. +action.escu.creation_date = 2017-11-09 +action.escu.modification_date = 2017-11-09 +action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Email.All_Email | search message_id={message_id} + +[ESCU - Get Emails From Specific Sender - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Emails From Specific Sender +description = This search returns all the emails from a specific sender over the last 24 and next hours. +action.escu.creation_date = 2017-11-09 +action.escu.modification_date = 2017-11-09 +action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails", "Web Fraud Detection"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns all the emails from a specific sender over the last 24 and next hours. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Email.All_Email | search src_user={src_user} + +[ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get First Occurrence and Last Occurrence of a MAC Address +description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. +action.escu.creation_date = 2017-09-13 +action.escu.modification_date = 2017-09-13 +action.escu.analytic_story = ["Asset Tracking"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Network_Sessions] +action.escu.eli5 = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + +[ESCU - Get History Of Email Sources - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get History Of Email Sources +description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. +action.escu.creation_date = 2019-02-21 +action.escu.modification_date = 2019-02-21 +action.escu.analytic_story = [] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Email] +action.escu.eli5 = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = |tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + +[ESCU - Get Logon Rights Modifications For Endpoint - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Logon Rights Modifications For Endpoint +description = This search allows you to retrieve any modifications to logon rights associated with a specific host. +action.escu.creation_date = 2017-09-12 +action.escu.modification_date = 2017-09-12 +action.escu.analytic_story = ["Account Monitoring and Controls"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search allows you to retrieve any modifications to logon rights associated with a specific host. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest={dest} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature + +[ESCU - Get Logon Rights Modifications For User - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Logon Rights Modifications For User +description = This search allows you to retrieve any modifications to logon rights for a specific user account. +action.escu.creation_date = 2019-02-27 +action.escu.modification_date = 2019-02-27 +action.escu.analytic_story = ["Account Monitoring and Controls"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search allows you to retrieve any modifications to logon rights for a specific user account. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user={user} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature + +[ESCU - Get Notable History - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Notable History +description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. +action.escu.creation_date = 2017-09-20 +action.escu.modification_date = 2017-09-20 +action.escu.analytic_story = ["AWS Cross Account Activity", "AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual AWS EC2 Modifications", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search `notable` | search dest={dest} | table _time, rule_name, owner, priority, severity, status_description + +[ESCU - Get Notable Info - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Notable Info +description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. +action.escu.creation_date = 2017-09-20 +action.escu.modification_date = 2017-09-20 +action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "AWS User Monitoring", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Asset Tracking", "Brand Monitoring", "Cloud Cryptomining", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Web Fraud Detection", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description + +[ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Outbound Emails to Hidden Cobra Threat Actors +description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. +action.escu.creation_date = 2018-06-14 +action.escu.modification_date = 2018-06-14 +action.escu.analytic_story = [] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + +[ESCU - Get Parent Process Info - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Parent Process Info +description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest +action.escu.creation_date = 2019-02-28 +action.escu.modification_date = 2019-02-28 +action.escu.analytic_story = ["Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Phishing Payloads", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + +[ESCU - Get Process File Activity - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Process File Activity +description = This search returns the file activity for a specific process on a specific endpoint +action.escu.creation_date = 2019-11-06 +action.escu.modification_date = 2019-11-06 +action.escu.analytic_story = ["DHS Report TA18-074A"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] +action.escu.eli5 = This search returns the file activity for a specific process on a specific endpoint +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path + +[ESCU - Get Process Info - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Process Info +description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. +action.escu.creation_date = 2019-04-01 +action.escu.modification_date = 2019-04-01 +action.escu.analytic_story = ["AWS Network ACL Activity", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] +action.escu.eli5 = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + +[ESCU - Get Process Information For Port Activity - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Process Information For Port Activity +description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. +action.escu.creation_date = 2019-04-01 +action.escu.modification_date = 2019-04-01 +action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Lateral Movement", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "SamSam Ransomware", "Suspicious AWS Traffic", "Use of Cleartext Protocols"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] +action.escu.eli5 = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] + +[ESCU - Get Process Registry Activity - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Process Registry Activity +description = This search returns the registry activity for a specific process on a specific endpoint +action.escu.creation_date = 2019-11-06 +action.escu.modification_date = 2019-11-06 +action.escu.analytic_story = ["DHS Report TA18-074A"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] +action.escu.eli5 = This search returns the registry activity for a specific process on a specific endpoint +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id={process_id} AND Registry.dest={dest} by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path + +[ESCU - Get Process Responsible For The DNS Traffic - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Process Responsible For The DNS Traffic +description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. +action.escu.creation_date = 2019-04-01 +action.escu.modification_date = 2019-04-01 +action.escu.analytic_story = ["AWS Network ACL Activity", "Brand Monitoring", "Command and Control", "Data Protection", "Dynamic DNS", "Hidden Cobra Malware", "Suspicious AWS Traffic", "Suspicious DNS Traffic"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Endpoint] +action.escu.eli5 = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] + +[ESCU - Get Registry Activities - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Registry Activities +description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. +action.escu.creation_date = 2019-03-01 +action.escu.modification_date = 2019-03-01 +action.escu.analytic_story = ["DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Persistence Techniques", "Windows Privilege Escalation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "{dest}" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] + +[ESCU - Get Risk Modifiers For Endpoint - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Risk Modifiers For Endpoint +description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) +action.escu.creation_date = 2017-10-19 +action.escu.modification_date = 2017-10-19 +action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "JBoss Vulnerability", "Kubernetes Scanning Activity", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Monitor for Updates", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SQL Injection", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Splunk Enterprise Vulnerability", "Splunk Enterprise Vulnerability CVE-2018-11409", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + +[ESCU - Get Risk Modifiers For User - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Risk Modifiers For User +description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user +action.escu.creation_date = 2017-10-19 +action.escu.modification_date = 2017-10-19 +action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "DNS Amplification Attacks", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor Backup Solution", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` + +[ESCU - Get Sysmon WMI Activity for Host - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Sysmon WMI Activity for Host +description = This search queries Sysmon WMI events for the host of interest. +action.escu.creation_date = 2018-10-23 +action.escu.modification_date = 2018-10-23 +action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search queries Sysmon WMI events for the host of interest. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter + +[ESCU - Get Update Logs For Endpoint - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Update Logs For Endpoint +description = This search will tell you give you the update logs for a specific endpoint for the last week. +action.escu.creation_date = 2017-08-24 +action.escu.modification_date = 2017-08-24 +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search will tell you give you the update logs for a specific endpoint for the last week. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest} + +[ESCU - Get User Information from Identity Table - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get User Information from Identity Table +description = Gather more information about the user identified in the Notable Event. +action.escu.creation_date = 2017-09-20 +action.escu.modification_date = 2017-09-20 +action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Account Monitoring and Controls", "Apache Struts Vulnerability", "Brand Monitoring", "Cloud Cryptomining", "ColdRoot MacOS RAT", "Collection and Staging", "Command and Control", "DHS Report TA18-074A", "Data Protection", "Disabling Security Tools", "Dynamic DNS", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Host Redirection", "Lateral Movement", "Malicious PowerShell", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Router and Infrastructure Security", "SamSam Ransomware", "Spectre And Meltdown Vulnerabilities", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Suspicious Command-Line Executions", "Suspicious DNS Traffic", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious WMI Use", "Suspicious Windows Registry Activities", "Unusual Processes", "Use of Cleartext Protocols", "Windows Defense Evasion Tactics", "Windows File Extension and Association Abuse", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation", "Windows Service Abuse"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = Gather more information about the user identified in the Notable Event. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | `identities` | search identity={user} | table _time, identity, first, last, email, category, watchlist + +[ESCU - Get Vulnerability Logs For Endpoint - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Vulnerability Logs For Endpoint +description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. +action.escu.creation_date = 2017-09-10 +action.escu.modification_date = 2017-09-10 +action.escu.analytic_story = ["ColdRoot MacOS RAT", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Ransomware", "SamSam Ransomware", "Windows Log Manipulation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search will show you any vulnerabilities noted for a specific endpoint for the last week. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Vulnerabilities.Vulnerabilities | search dest={dest} + +[ESCU - Get Web Session Information via session id - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Get Web Session Information via session id +description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. +action.escu.creation_date = 2018-10-08 +action.escu.modification_date = 2018-10-08 +action.escu.analytic_story = ["Web Fraud Detection"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) by src_ip status + +[ESCU - Investigate AWS ECR container listing activity - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate AWS ECR container listing activity +description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. +action.escu.creation_date = 2020-02-20 +action.escu.modification_date = 2020-02-20 +action.escu.analytic_story = ["Container Implantation Monitoring and Investigation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1 + +[ESCU - Investigate AWS User Activities by user field - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate AWS User Activities by user field +description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. +action.escu.creation_date = 2018-03-12 +action.escu.modification_date = 2018-03-12 +action.escu.analytic_story = ["AWS User Monitoring"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType + +[ESCU - Investigate AWS activities via region name - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate AWS activities via region name +description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user +action.escu.creation_date = 2018-02-09 +action.escu.modification_date = 2018-02-09 +action.escu.analytic_story = ["AWS Cryptomining", "Cloud Cryptomining", "Suspicious AWS EC2 Activities", "Suspicious AWS S3 Activities"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId + +[ESCU - Investigate Cloud Compute Instance Activities - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Cloud Compute Instance Activities +description = This search returns a logs of events that operated on the compute instance. +action.escu.creation_date = 2018-03-12 +action.escu.modification_date = 2018-03-12 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns a logs of events that operated on the compute instance. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields - _* + +[ESCU - Investigate Failed Logins for Multiple Destinations - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Failed Logins for Multiple Destinations +description = This search returns failed logins to multiple destinations by user. +action.escu.creation_date = 2019-12-10 +action.escu.modification_date = 2019-12-10 +action.escu.analytic_story = ["Credential Dumping"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] +action.escu.eli5 = This search returns failed logins to multiple destinations by user. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + +[ESCU - Investigate Network Traffic From src ip - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Network Traffic From src ip +description = This search allows you to find all the network traffic from a specific IP address. +action.escu.creation_date = 2018-06-15 +action.escu.modification_date = 2018-06-15 +action.escu.analytic_story = ["ColdRoot MacOS RAT", "Splunk Enterprise Vulnerability CVE-2018-11409"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search allows you to find all the network traffic from a specific IP address. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip} + +[ESCU - Investigate Okta Activity by IP Address - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Okta Activity by IP Address +description = This search returns all okta events from a specific IP address. +action.escu.creation_date = 2020-04-02 +action.escu.modification_date = 2020-04-02 +action.escu.analytic_story = ["Suspicious Okta Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns all okta events from a specific IP address. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + +[ESCU - Investigate Okta Activity by app - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Okta Activity by app +description = This search returns all okta events associated with a specific app +action.escu.creation_date = 2020-04-02 +action.escu.modification_date = 2020-04-02 +action.escu.analytic_story = ["Suspicious Okta Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns all okta events associated with a specific app +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = eventtype=okta_log app={app} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + +[ESCU - Investigate Pass the Hash Attempts - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Pass the Hash Attempts +description = This search hunts for dumped NTLM hashes used for pass the hash. +action.escu.creation_date = 2019-12-10 +action.escu.modification_date = 2019-12-10 +action.escu.analytic_story = ["Credential Dumping"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search hunts for dumped NTLM hashes used for pass the hash. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` + +[ESCU - Investigate Pass the Ticket Attempts - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Pass the Ticket Attempts +description = This search hunts for dumped kerberos ticket from LSASS memory. +action.escu.creation_date = 2019-12-10 +action.escu.modification_date = 2019-12-10 +action.escu.analytic_story = ["Credential Dumping"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search hunts for dumped kerberos ticket from LSASS memory. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user + +[ESCU - Investigate Previous Unseen User - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Previous Unseen User +description = This search returns previous unseen user, which didn't log in for 30 days. +action.escu.creation_date = 2019-12-10 +action.escu.modification_date = 2019-12-10 +action.escu.analytic_story = ["Credential Dumping"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] +action.escu.eli5 = This search returns previous unseen user, which didn't log in for 30 days. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + +[ESCU - Investigate Successful Remote Desktop Authentications - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Successful Remote Desktop Authentications +description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. +action.escu.creation_date = 2018-12-14 +action.escu.modification_date = 2018-12-14 +action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement", "SamSam Ransomware"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Authentication] +action.escu.eli5 = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| table firstTime lastTime src src_nt_domain dest user app count | sort count + +[ESCU - Investigate Suspicious Strings in HTTP Header - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Suspicious Strings in HTTP Header +description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. +action.escu.creation_date = 2017-10-20 +action.escu.modification_date = 2017-10-20 +action.escu.analytic_story = ["Apache Struts Vulnerability"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url + +[ESCU - Investigate User Activities In All Cloud Regions - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate User Activities In All Cloud Regions +description = This search lists all the logged cloud infrastructure activities by a specific cloud user +action.escu.creation_date = 2019-04-30 +action.escu.modification_date = 2019-04-30 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | fields - _* + +[ESCU - Investigate User Activities In Okta - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate User Activities In Okta +description = This search returns all okta events by a specific user +action.escu.creation_date = 2020-04-02 +action.escu.modification_date = 2020-04-02 +action.escu.analytic_story = ["Suspicious Okta Activity"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search returns all okta events by a specific user +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = eventtype=okta_log user={user} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + +[ESCU - Investigate User Activities In Single Cloud Region - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate User Activities In Single Cloud Region +description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region +action.escu.creation_date = 2019-04-30 +action.escu.modification_date = 2019-04-30 +action.escu.analytic_story = ["Cloud Cryptomining"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} | fields - _* + +[ESCU - Investigate Web Activity From Host - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Web Activity From Host +description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +action.escu.creation_date = 2017-11-09 +action.escu.modification_date = 2017-11-09 +action.escu.analytic_story = ["Brand Monitoring", "DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "JBoss Vulnerability", "Monitor for Unauthorized Software", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "SamSam Ransomware", "Suspicious Command-Line Executions", "Suspicious Emails", "Suspicious MSHTA Activity", "Suspicious Windows Registry Activities", "Unusual Processes", "Windows Log Manipulation", "Windows Persistence Techniques", "Windows Privilege Escalation"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Web.Web | search src={dest} + +[ESCU - Investigate Web Activity From src ip - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Web Activity From src ip +description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +action.escu.creation_date = 2018-06-15 +action.escu.modification_date = 2018-06-15 +action.escu.analytic_story = ["ColdRoot MacOS RAT", "Dynamic DNS", "Splunk Enterprise Vulnerability CVE-2018-11409"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | from datamodel Web.Web | search src={src_ip} + +[ESCU - Investigate Web POSTs From src - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Investigate Web POSTs From src +description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. +action.escu.creation_date = 2018-12-06 +action.escu.modification_date = 2018-12-06 +action.escu.analytic_story = ["Apache Struts Vulnerability"] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [Web] +action.escu.eli5 = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "{src}") and like(http_method, "POST") + +[ESCU - Process Chain Analysis - Response Task] +action.escu = 0 +action.escu.enabled = 1 +action.escu.search_type = investigative +action.escu.full_search_name = ESCU - Process Chain Analysis +description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. +action.escu.creation_date = 2020-04-29 +action.escu.modification_date = 2020-04-29 +action.escu.analytic_story = [] +action.escu.earliest_time_offset = 3600 +action.escu.latest_time_offset = 86400 +action.escu.providing_technologies = [] +action.escu.data_models = [] +action.escu.eli5 = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. +action.escu.how_to_implement = none +action.escu.known_false_positives = None at this time +disabled = true +schedule_window = auto +is_visible = false +search = `sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count + + + +### END ESCU RESPONSE TASKS ### ### USAGE DASHBOARD CONFIGURATIONS ### diff --git a/package/default/transforms.conf b/package/default/transforms.conf index b9325478b5..ab1d2383dd 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:20:56 UTC +# On Date: 2020-05-11T12:39:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index b8e297b0d6..e5e940b564 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:20:56 UTC +# On Date: 2020-05-11T12:39:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +searches = ["ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header"] +searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Creation of Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process File Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info"] +searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] +searches = ["ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName"] +searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Investigate AWS activities via region name", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Notable Info"] +searches = ["ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 804e2e8248ea3ea05099ca888f7cb8abc6a0610a Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 11 May 2020 17:40:06 +0200 Subject: [PATCH 38/93] bug in generate --- bin/generate.py | 15 + bin/jinja2_templates/use_case_library.j2 | 2 +- package/default/analytic_stories.conf | 118 +++--- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 506 +++++++++++------------ 7 files changed, 331 insertions(+), 316 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index ca27cfde35..66868a86cc 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -156,6 +156,21 @@ def generate_use_case_library_conf(stories, detections, response_tasks, baseline else: story['searches'] = story['detections'] + for detection in detections: + + keys = ['mitre_attack', 'kill_chain_phases', 'cis20', 'nist'] + mappings = {} + for key in keys: + if key == 'mitre_attack': + if 'mitre_attack_id' in detection['tags']: + mappings[key] = detection['tags']['mitre_attack_id'] + else: + if key in detection['tags']: + mappings[key] = detection['tags'][key] + + + detection['mappings'] = mappings + utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), diff --git a/bin/jinja2_templates/use_case_library.j2 b/bin/jinja2_templates/use_case_library.j2 index f9af4c57ff..1aa262ca2b 100644 --- a/bin/jinja2_templates/use_case_library.j2 +++ b/bin/jinja2_templates/use_case_library.j2 @@ -37,7 +37,7 @@ how_to_implement = {{ detection.how_to_implement }} {% else %} how_to_implement = none {% endif %} -annotations = {{ detection.tags | tojson }} +annotations = {{ detection.mappings | tojson }} known_false_positives = {{ detection.known_false_positives }} providing_technologies = none diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 6441c13abb..539460661d 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:39:19 UTC +# On Date: 2020-05-11T15:39:38 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] +investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] +investigative_searches = ["ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process File Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Investigate AWS activities via region name", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/macros.conf b/package/default/macros.conf index 3471bfab77..c93e15c0a1 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:39:19 UTC +# On Date: 2020-05-11T15:39:38 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 805673ae90..c53098f2e9 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:39:19 UTC +# On Date: 2020-05-11T15:39:38 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index ab1d2383dd..95e5cd8368 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:39:19 UTC +# On Date: 2020-05-11T15:39:38 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index e5e940b564..f74724152d 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T12:39:19 UTC +# On Date: 2020-05-11T15:39:38 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Creation of Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Process File Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Attempt To Stop Security Service - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Investigate AWS activities via region name", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. @@ -902,7 +902,7 @@ asset_type = confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new city is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. providing_technologies = none @@ -913,7 +913,7 @@ asset_type = confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching over plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new country is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. providing_technologies = none @@ -924,7 +924,7 @@ asset_type = confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new IP address is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your country, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. providing_technologies = none @@ -935,7 +935,7 @@ asset_type = confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -annotations = {"analytics_story": ["AWS Suspicious Provisioning Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ This search will fire any time a new region is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your region, there should be few false positives. If you are located in regions where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. providing_technologies = none @@ -946,7 +946,7 @@ asset_type = confidence = medium explanation = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. -annotations = {"analytics_story": ["AWS Cross Account Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.AC", "PR.DS", "DE.AE"]} known_false_positives = Using multiple AWS accounts and roles is perfectly valid behavior. It's suspicious when an account requests privileges of an account it hasn't before. You should validate with the account owner that this is a legitimate request. providing_technologies = none @@ -956,7 +956,7 @@ asset_type = confidence = medium explanation = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail inputs. -annotations = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = It's possible that an admin has created this ACL with all ports open for some legitimate purpose however, this should be scoped and not allowed in production environment. providing_technologies = none @@ -966,7 +966,7 @@ asset_type = confidence = medium explanation = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -annotations = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = It's possible that a user has legitimately deleted a network ACL. providing_technologies = none @@ -976,7 +976,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. providing_technologies = none @@ -986,7 +986,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. providing_technologies = none @@ -996,7 +996,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -annotations = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = Many service accounts configured with your AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify whether this search alerted on a human user. providing_technologies = none @@ -1006,7 +1006,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"analytics_story": ["Suspicious AWS EC2 Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = Many service accounts configured within an AWS infrastructure are known to exhibit this behavior. Please adjust the threshold values and filter out service accounts from the output. Always verify if this search alerted on a human user. providing_technologies = none @@ -1016,7 +1016,7 @@ asset_type = confidence = medium explanation = Detect memory dumping of the LSASS process. how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual. providing_technologies = none @@ -1026,7 +1026,7 @@ asset_type = confidence = medium explanation = This search provides detection information on unauthenticated requests against Kubernetes' Pods API how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. -annotations = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster Pod", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +annotations = {"kill_chain_phases": ["Reconnaissance"]} known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. providing_technologies = none @@ -1036,7 +1036,7 @@ asset_type = confidence = medium explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs. -annotations = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "Amazon EKS Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +annotations = {"kill_chain_phases": ["Reconnaissance"]} known_false_positives = Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. providing_technologies = none @@ -1046,7 +1046,7 @@ asset_type = confidence = medium explanation = Attempt to add a certificate to the untrusted certificate store how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. providing_technologies = none @@ -1056,7 +1056,7 @@ asset_type = confidence = medium explanation = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. -annotations = {"analytics_story": ["Credential Dumping", "Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["DE.CM"]} known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. providing_technologies = none @@ -1066,7 +1066,7 @@ asset_type = confidence = medium explanation = This search looks for attempts to stop security-related services on the endpoint. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., -annotations = {"analytics_story": ["Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. providing_technologies = none @@ -1076,7 +1076,7 @@ asset_type = confidence = medium explanation = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = None identified. providing_technologies = none @@ -1086,7 +1086,7 @@ asset_type = confidence = medium explanation = The search looks for a batch file (.bat) written to the Windows system directory tree. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. providing_technologies = none @@ -1096,7 +1096,7 @@ asset_type = confidence = medium explanation = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. -annotations = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. providing_technologies = none @@ -1108,7 +1108,7 @@ explanation = This search allows you to identify the endpoints that have connect how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"], "security_domain": "network"} +annotations = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} known_false_positives = It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate. providing_technologies = none @@ -1118,7 +1118,7 @@ asset_type = confidence = medium explanation = This search looks for cloud compute instances created by users who have not created them before. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. -annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. providing_technologies = none @@ -1128,7 +1128,7 @@ asset_type = confidence = medium explanation = This search looks for cloud compute instances being created with previously unseen image IDs. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. -annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. providing_technologies = none @@ -1138,7 +1138,7 @@ asset_type = confidence = medium explanation = Find EC2 instances being created with previously unseen instance types. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. -annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. providing_technologies = none @@ -1148,7 +1148,7 @@ asset_type = confidence = medium explanation = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. -annotations = {"analytics_story": ["Cloud Cryptomining"], "asset_type": "Cloud Compute Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. providing_technologies = none @@ -1162,7 +1162,7 @@ This search produces fields (`query`,`query_length`,`count`) that are not yet su 1. \ 1. **Label:** File Extension, **Field:** file_extension\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = It is possible for a legitimate file with these extensions to be created. If this is a true ransomware attack, there will be a large number of files created with these extensions. providing_technologies = none @@ -1172,7 +1172,7 @@ asset_type = confidence = medium explanation = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. providing_technologies = none @@ -1182,7 +1182,7 @@ asset_type = confidence = medium explanation = Detect remote thread creation into LSASS consistent with credential dumping. how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. providing_technologies = none @@ -1192,7 +1192,7 @@ asset_type = confidence = medium explanation = This search looks for the creation of local administrator accounts using net.exe. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Administrators often leverage net.exe to create admin accounts. providing_technologies = none @@ -1202,7 +1202,7 @@ asset_type = confidence = medium explanation = This search looks for the creation or deletion of hidden shares using net.exe. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. providing_technologies = none @@ -1212,7 +1212,7 @@ asset_type = confidence = medium explanation = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. providing_technologies = none @@ -1222,7 +1222,7 @@ asset_type = confidence = medium explanation = This search detects the use of wmic and Powershell to create a shadow copy. how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = Legtimate administrator usage of wmic to create a shadow copy. providing_technologies = none @@ -1232,7 +1232,7 @@ asset_type = confidence = medium explanation = This search detects credential dumping using copy command from a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = unknown providing_technologies = none @@ -1242,7 +1242,7 @@ asset_type = confidence = medium explanation = This search detects the creation of a symlink to a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = unknown providing_technologies = none @@ -1258,7 +1258,7 @@ This search produces fields (`query`,`query_length`,`count`) that are not yet su 1. \ 1. **Label:** Number of events, **Field:** count\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} known_false_positives = If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. providing_technologies = none @@ -1268,7 +1268,7 @@ asset_type = confidence = medium explanation = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. -annotations = {"analytics_story": ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} known_false_positives = It's possible there can be long domain names that are legitimate. providing_technologies = none @@ -1278,7 +1278,7 @@ asset_type = confidence = medium explanation = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. -annotations = {"analytics_story": ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. providing_technologies = none @@ -1292,7 +1292,7 @@ how_to_implement = To successfully implement this search you will need to ensure If Splunk>Phantom is also configured in your environment, a Playbook called "DNS Hijack Enrichment" can be configured to run when any results are found by this detection search. The playbook takes in the DNS record changed and uses Geoip, whois, Censys and PassiveTotal to detect if DNS issuers changed. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook Link:`https://my.phantom.us/4.2/playbook/dns-hijack-enrichment/`).\ -annotations = {"analytics_story": ["DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} known_false_positives = Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate. providing_technologies = none @@ -1302,7 +1302,7 @@ asset_type = confidence = medium explanation = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. providing_technologies = none @@ -1318,7 +1318,7 @@ This search produces fields (`eventName`,`userIdentity.type`,`userIdentity.arn`) 1. \ 1. **Label:** AWS User Type, **Field:** userIdentity.type\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "nist": ["DE.DP", "PR.AC"]} known_false_positives = Many service accounts configured within an AWS infrastructure do not have multi factor authentication enabled. Please ignore the service accounts, if triggered and instead add them to the aws_service_accounts.csv file to fine tune the detection. It is also possible that the search detects users in your environment using Single Sign-On systems, since the MFA is not handled by AWS. providing_technologies = none @@ -1334,7 +1334,7 @@ This search produces fields (`eventName`,`firstTime`,`lastTime`) that are not ye 1. \ 1. **Label:** Last Time, **Field:** lastTime\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC", "ID.AM"]} known_false_positives = It's likely that you'll find activity detected by users/service accounts that are not listed in the `identity_lookup_expanded` or ` aws_service_accounts.csv` file. If the user is a legitimate service account, update the `aws_service_accounts.csv` table with that entry. providing_technologies = none @@ -1344,7 +1344,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. providing_technologies = none @@ -1354,7 +1354,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. providing_technologies = none @@ -1364,7 +1364,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. providing_technologies = none @@ -1374,7 +1374,7 @@ asset_type = confidence = medium explanation = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. -annotations = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "access"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1075"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = Legitimate logon activity by authorized NTLM systems may be detected by this search. Please investigate as appropriate. providing_technologies = none @@ -1384,7 +1384,7 @@ asset_type = confidence = medium explanation = This search looks for reading lsass memory consistent with credential dumping. how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} known_false_positives = The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. providing_technologies = none @@ -1398,7 +1398,7 @@ how_to_implement = You need to ingest data from your DNS logs in the Network_Res If Splunk>Phantom is also configured in your environment, a Playbook called `Lets Encrypt Domain Investigate` can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook link:`https://my.phantom.us/4.2/playbook/lets-encrypt-domain-investigate/`).\ -annotations = {"analytics_story": ["Common Phishing Frameworks"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} known_false_positives = If a known good domain is not listed in the legit_domains.csv file, then the search could give you false postives. Please update that lookup file to filter out DNS requests to legitimate domains. providing_technologies = none @@ -1412,7 +1412,7 @@ how_to_implement = You must ingest your Windows security event logs in the `Chan If Splunk>Phantom is also configured in your environment, a Playbook called "Excessive Account Lockouts Enrichment and Response" can be configured to run when any results are found by this detection search. The Playbook executes the Contextual and Investigative searches in this Story, conducts additional information gathering on Windows endpoints, and takes a response action to shut down the affected endpoint. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search, and set the corresponding Playbook to active. \ (Playbook Link:`https://my.phantom.us/4.1/playbook/excessive-account-lockouts-enrichment-and-response/`).\ -annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} known_false_positives = It's possible that a widely used system, such as a kiosk, could cause a large number of account lockouts. providing_technologies = none @@ -1422,7 +1422,7 @@ asset_type = confidence = medium explanation = This search detects user accounts that have been locked out a relatively high number of times in a short period. how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. -annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["PR.IP"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. providing_technologies = none @@ -1432,7 +1432,7 @@ asset_type = confidence = medium explanation = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -annotations = {"analytics_story": ["Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1095"], "nist": ["DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. providing_technologies = none @@ -1442,7 +1442,7 @@ asset_type = confidence = medium explanation = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. -annotations = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. providing_technologies = none @@ -1452,7 +1452,7 @@ asset_type = confidence = medium explanation = This search looks for reading loaded Images unique to credential dumping with Mimikatz. how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.AE", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.AE", "DE.CM"]} known_false_positives = Other tools can import the same DLLs. These tools should be part of a whtelist. providing_technologies = none @@ -1462,7 +1462,7 @@ asset_type = confidence = medium explanation = This search looks for PowerShell requesting privileges consistent with credential dumping. how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. -annotations = {"asset_type": "Windows", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"], "security_domain": "access"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["PR.IP", "PR.AC", "DE.CM"]} known_false_positives = The activity may be legitimate. PowerShell is often used by administrators to perform various tasks, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need to tweak the search to eliminate noise. providing_technologies = none @@ -1478,7 +1478,7 @@ This search produces fields (`Security_ID`,`Group_Name`,`Message`) that are not 1. \ 1. **Label:** Message, **Field:** Message\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Windows", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1078"], "nist": ["PR.AC", "DE.CM"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1078"], "nist": ["PR.AC", "DE.CM"]} known_false_positives = The activity may be legitimate. For this reason, it's best to verify the account with an administrator and ask whether there was a valid service request for the account creation. If your local administrator group name is not "Administrators", this search may generate an excessive number of false positives providing_technologies = none @@ -1488,7 +1488,7 @@ asset_type = confidence = medium explanation = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. -annotations = {"analytics_story": ["Router and Infrastructure Security"], "asset_type": "Endpoint", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} known_false_positives = Legitimate router connections may appear as new connections providing_technologies = none @@ -1498,7 +1498,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events where a user has created an open/public S3 bucket. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. -annotations = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} known_false_positives = While this search has no known false positives, it is possible that an AWS admin has legitimately created a public bucket for a specific purpose. That said, AWS strongly advises against granting full control to the "All Users" group. providing_technologies = none @@ -1508,7 +1508,7 @@ asset_type = confidence = medium explanation = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -annotations = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} known_false_positives = It is not uncommon for outlook to write legitimate zip files to the disk. providing_technologies = none @@ -1518,7 +1518,7 @@ asset_type = confidence = medium explanation = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model -annotations = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. providing_technologies = none @@ -1528,7 +1528,7 @@ asset_type = confidence = medium explanation = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. -annotations = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. providing_technologies = none @@ -1538,7 +1538,7 @@ asset_type = confidence = medium explanation = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. -annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. providing_technologies = none @@ -1548,7 +1548,7 @@ asset_type = confidence = medium explanation = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["DHS Report TA18-074A", "SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine providing_technologies = none @@ -1558,7 +1558,7 @@ asset_type = confidence = medium explanation = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. -annotations = {"analytics_story": ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. providing_technologies = none @@ -1568,7 +1568,7 @@ asset_type = confidence = medium explanation = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access logs' inputs. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. -annotations = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS", "PR.AC", "DE.CM"]} known_false_positives = S3 buckets can be accessed from any IP, as long as it can make a successful connection. This will be a false postive, since the search is looking for a new IP within the past hour providing_technologies = none @@ -1584,7 +1584,7 @@ This search produces fields (`eventName`,`numberOfApiCalls`,`uniqueApisCalled`) 1. \ 1. **Label:** Unique API Calls, **Field:** uniqueApisCalled\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} known_false_positives = providing_technologies = none @@ -1594,7 +1594,7 @@ asset_type = confidence = medium explanation = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. -annotations = {"analytics_story": ["AWS Network ACL Activity"], "asset_type": "AWS Instance", "cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 12", "CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Please modify this according the your environment. providing_technologies = none @@ -1604,7 +1604,7 @@ asset_type = confidence = medium explanation = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. -annotations = {"analytics_story": ["Suspicious AWS S3 Activities"], "asset_type": "S3 Bucket", "cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. providing_technologies = none @@ -1614,7 +1614,7 @@ asset_type = confidence = medium explanation = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. -annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.CM", "PR.AC"]} known_false_positives = Based on the values of`dataPointThreshold` and `deviationThreshold`, the false positive rate may vary. Please modify this according the your environment. providing_technologies = none @@ -1624,7 +1624,7 @@ asset_type = confidence = medium explanation = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. -annotations = {"analytics_story": ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"], "asset_type": "AWS Instance", "cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} known_false_positives = The false-positive rate may vary based on the values of`dataPointThreshold` and `deviationThreshold`. Additionally, false positives may result when AWS administrators roll out policies enforcing network blocks, causing sudden increases in the number of blocked outbound connections. providing_technologies = none @@ -1634,7 +1634,7 @@ asset_type = confidence = medium explanation = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. -annotations = {"analytics_story": ["Data Protection"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. providing_technologies = none @@ -1644,7 +1644,7 @@ asset_type = confidence = medium explanation = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. -annotations = {"analytics_story": ["Asset Tracking"], "asset_type": "Infrastructure", "cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +annotations = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. providing_technologies = none @@ -1654,7 +1654,7 @@ asset_type = confidence = medium explanation = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Some legitimate applications may exhibit this behavior. providing_technologies = none @@ -1664,7 +1664,7 @@ asset_type = confidence = medium explanation = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. -annotations = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "kill_chain_phases": ["Reconnaissance"], "mitre_attack_id": ["T1082"], "security_domain": "network"} +annotations = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. providing_technologies = none @@ -1680,7 +1680,7 @@ This search produces fields (query, answer, isDynDNS) that are not yet supported 1. \ 1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} known_false_positives = Some users and applications may leverage Dynamic DNS to reach out to some domains on the Internet since dynamic DNS by itself is not malicious, however this activity must be verified. providing_technologies = none @@ -1690,7 +1690,7 @@ asset_type = confidence = medium explanation = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model -annotations = {"analytics_story": ["JBoss Vulnerability", "SamSam Ransomware"], "asset_type": "Web Server", "cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} known_false_positives = No known false positives for this detection. providing_technologies = none @@ -1700,7 +1700,7 @@ asset_type = confidence = medium explanation = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"analytics_story": ["Suspicious MSHTA Activity"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. providing_technologies = none @@ -1710,7 +1710,7 @@ asset_type = confidence = medium explanation = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. -annotations = {"analytics_story": ["AWS User Monitoring"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = It is possible that there are legitimate user roles making new or infrequently used API calls in your infrastructure, causing the search to trigger. providing_technologies = none @@ -1720,7 +1720,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. -annotations = {"analytics_story": ["Suspicious AWS Login Activities"], "asset_type": "AWS Instance", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = When a legitimate new user logins for the first time, this activity will be detected. Check how old the account is and verify that the user activity is legitimate. providing_technologies = none @@ -1730,7 +1730,7 @@ asset_type = confidence = medium explanation = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. -annotations = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. providing_technologies = none @@ -1742,7 +1742,7 @@ explanation = This search looks for web connections to dynamic DNS providers. how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ Detailed documentation on how to create a new field within Incident Review may be found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["Dynamic DNS"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"]} known_false_positives = It is possible that list of dynamic DNS providers is outdated and/or that the URL being requested is legitimate. providing_technologies = none @@ -1752,7 +1752,7 @@ asset_type = confidence = medium explanation = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. -annotations = {"analytics_story": ["Data Protection", "Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "PR.DS"], "security_domain": "network"} +annotations = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "PR.DS"]} known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. providing_technologies = none @@ -1762,7 +1762,7 @@ asset_type = confidence = medium explanation = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1072", "T1087"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072", "T1087"], "nist": ["PR.IP"]} known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. providing_technologies = none @@ -1772,7 +1772,7 @@ asset_type = confidence = medium explanation = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = This registry key may be modified via administrators to implement a change in system policy. This type of change should be a very rare occurrence. providing_technologies = none @@ -1782,7 +1782,7 @@ asset_type = confidence = medium explanation = Detect the usage of comsvcs.dll for dumping the lsass process. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = None identified. providing_technologies = none @@ -1792,7 +1792,7 @@ asset_type = confidence = medium explanation = This search looks for EC2 instances being modified by users who have not previously modified them. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. -annotations = {"analytics_story": ["Unusual AWS EC2 Modifications"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = It's possible that a new user will start to modify EC2 instances when they haven't before for any number of reasons. Verify with the user that is modifying instances that this is the intended behavior. providing_technologies = none @@ -1802,7 +1802,7 @@ asset_type = confidence = medium explanation = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. -annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. providing_technologies = none @@ -1812,7 +1812,7 @@ asset_type = confidence = medium explanation = This search looks for EC2 instances being created with previously unseen AMIs. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. -annotations = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = After a new AMI is created, the first systems created with that AMI will cause this alert to fire. Verify that the AMI being used was created by a legitimate user. providing_technologies = none @@ -1822,7 +1822,7 @@ asset_type = confidence = medium explanation = This search looks for EC2 instances being created with previously unseen instance types. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. -annotations = {"analytics_story": ["AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = It is possible that an admin will create a new system using a new instance type never used before. Verify with the creator that they intended to create the system with the new instance type. providing_technologies = none @@ -1832,7 +1832,7 @@ asset_type = confidence = medium explanation = This search looks for EC2 instances being created by users who have not created them before. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. -annotations = {"analytics_story": ["Suspicious AWS EC2 Activities", "AWS Cryptomining"], "asset_type": "AWS Instance", "cis20": ["CIS 1"], "nist": ["ID.AM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} known_false_positives = It's possible that a user will start to create EC2 instances when they haven't before for any number of reasons. Verify with the user that is launching instances that this is the intended behavior. providing_technologies = none @@ -1844,7 +1844,7 @@ explanation = Attackers often use spaces as a means to obfuscate an attachment's how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ **Splunk Phantom Playbook Integration**\ If Splunk Phantom is also configured in your environment, a playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/` and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -annotations = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} known_false_positives = None at this time providing_technologies = none @@ -1854,7 +1854,7 @@ asset_type = confidence = medium explanation = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114"]} known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. providing_technologies = none @@ -1864,7 +1864,7 @@ asset_type = confidence = medium explanation = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. providing_technologies = none @@ -1874,7 +1874,7 @@ asset_type = confidence = medium explanation = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -annotations = {"analytics_story": ["Suspicious DNS Traffic", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. providing_technologies = none @@ -1884,7 +1884,7 @@ asset_type = confidence = medium explanation = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} known_false_positives = None identified. providing_technologies = none @@ -1894,7 +1894,7 @@ asset_type = confidence = medium explanation = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. -annotations = {"analytics_story": ["Windows File Extension and Association Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} known_false_positives = None identified. providing_technologies = none @@ -1904,7 +1904,7 @@ asset_type = confidence = medium explanation = This search returns a list of hosts that have not successfully completed a backup in over a week. how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. -annotations = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} known_false_positives = None identified providing_technologies = none @@ -1914,7 +1914,7 @@ asset_type = confidence = medium explanation = The search looks for file writes with extensions consistent with a SamSam ransomware attack. how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. providing_technologies = none @@ -1924,7 +1924,7 @@ asset_type = confidence = medium explanation = This search looks for the first time a Windows service is seen running in your environment. how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. -annotations = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group"], "asset_type": "Endpoint", "cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 2", "CIS 9"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1050"], "nist": ["ID.AM", "PR.DS", "PR.AC", "DE.AE"]} known_false_positives = A previously unseen service is not necessarily malicious. Verify that the service is legitimate and that was installed by a legitimate process. providing_technologies = none @@ -1934,7 +1934,7 @@ asset_type = confidence = medium explanation = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. -annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name providing_technologies = none @@ -1944,7 +1944,7 @@ asset_type = confidence = medium explanation = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. -annotations = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "GCP GCR Container", "security_domain": "threat"} +annotations = {} known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload creation which automatically generates a bucket entry for destination path. providing_technologies = none @@ -1954,7 +1954,7 @@ asset_type = confidence = medium explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. -annotations = {"analytics_story": ["Kubernetes Scanning Activity"], "asset_type": "GCP Kubernetes cluster", "kill_chain_phases": ["Reconnaissance"], "security_domain": "threat"} +annotations = {"kill_chain_phases": ["Reconnaissance"]} known_false_positives = Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. providing_technologies = none @@ -1964,7 +1964,7 @@ asset_type = confidence = medium explanation = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. providing_technologies = none @@ -1974,7 +1974,7 @@ asset_type = confidence = medium explanation = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. -annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. providing_technologies = none @@ -1984,7 +1984,7 @@ asset_type = confidence = medium explanation = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. -annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Domain Server", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} known_false_positives = If the Identity_Management data model is not updated regularly, this search could give you false positive alerts. Please consider this and investigate appropriately. providing_technologies = none @@ -1994,7 +1994,7 @@ asset_type = confidence = medium explanation = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. -annotations = {"analytics_story": ["DNS Amplification Attacks"], "asset_type": "DNS Servers", "cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. providing_technologies = none @@ -2004,7 +2004,7 @@ asset_type = confidence = medium explanation = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. -annotations = {"asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. providing_technologies = none @@ -2014,7 +2014,7 @@ asset_type = confidence = medium explanation = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. providing_technologies = none @@ -2024,7 +2024,7 @@ asset_type = confidence = medium explanation = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = System administrators may use this option, but it's not common. providing_technologies = none @@ -2034,7 +2034,7 @@ asset_type = confidence = medium explanation = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. providing_technologies = none @@ -2044,7 +2044,7 @@ asset_type = confidence = medium explanation = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. providing_technologies = none @@ -2054,7 +2054,7 @@ asset_type = confidence = medium explanation = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Malicious PowerShell"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack_id": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} known_false_positives = These characters might be legitimately on the command-line, but it is not common. providing_technologies = none @@ -2064,7 +2064,7 @@ asset_type = confidence = medium explanation = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "kill_chain_phases": ["Delivery", "Actions on Objectives"], "security_domain": "network"} +annotations = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} known_false_positives = None at this time providing_technologies = none @@ -2074,7 +2074,7 @@ asset_type = confidence = medium explanation = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"analytics_story": ["Suspicious Emails", "Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} known_false_positives = None at this time providing_technologies = none @@ -2084,7 +2084,7 @@ asset_type = confidence = medium explanation = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. -annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.AC"]} known_false_positives = You will encounter noise from legitimate print-monitor registry entries. providing_technologies = none @@ -2094,7 +2094,7 @@ asset_type = confidence = medium explanation = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. -annotations = {"analytics_story": ["Brand Monitoring"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} known_false_positives = None at this time providing_technologies = none @@ -2104,7 +2104,7 @@ asset_type = confidence = medium explanation = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} known_false_positives = A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise the threshold or except specific IP adresses from triggering this search. providing_technologies = none @@ -2114,7 +2114,7 @@ asset_type = confidence = medium explanation = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. -annotations = {"analytics_story": ["Container Implantation Monitoring and Investigation"], "asset_type": "AWS ECR container", "security_domain": "threat"} +annotations = {} known_false_positives = Uploading container is a normal behavior from developers or users with access to container registry. providing_technologies = none @@ -2124,7 +2124,7 @@ asset_type = confidence = medium explanation = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. -annotations = {"analytics_story": ["Monitor for Updates"], "asset_type": "Endpoint", "cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} known_false_positives = None identified providing_technologies = none @@ -2134,7 +2134,7 @@ asset_type = confidence = medium explanation = Detect Okta user lockout events how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} known_false_positives = None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. providing_technologies = none @@ -2144,7 +2144,7 @@ asset_type = confidence = medium explanation = Detect failed Okta SSO events how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} known_false_positives = There may be a faulty config preventing legitmate users from accessing apps they should have access to. providing_technologies = none @@ -2154,7 +2154,7 @@ asset_type = confidence = medium explanation = This search detects logins from the same user from different states in a 24 hour period. how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. -annotations = {"analytics_story": ["Suspicious Okta Activity"], "asset_type": "Infrastructure", "cis20": ["CIS 16"], "mitre_attack_id": ["T1078"], "nist": ["DE.CM"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} known_false_positives = Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also relies on the geographical information being populated in the Okta logs. It is also possible that a connection from another region may be attributed to a login from a remote VPN endpoint. providing_technologies = none @@ -2164,7 +2164,7 @@ asset_type = confidence = medium explanation = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. how_to_implement = No extra steps needed to implement this search. -annotations = {"analytics_story": ["Splunk Enterprise Vulnerability"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} known_false_positives = None identified providing_technologies = none @@ -2174,7 +2174,7 @@ asset_type = confidence = medium explanation = This search looks for ColdRoot events from the osx-attacks osquery pack. how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model -annotations = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM", "PR.PT"]} known_false_positives = There are no known false positives. providing_technologies = none @@ -2184,7 +2184,7 @@ asset_type = confidence = medium explanation = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"analytics_story": ["Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. providing_technologies = none @@ -2194,7 +2194,7 @@ asset_type = confidence = medium explanation = This search looks for processes launched via WMI. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = Although unlikely, administrators may use wmi to execute commands for legitimate purposes. providing_technologies = none @@ -2204,7 +2204,7 @@ asset_type = confidence = medium explanation = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. -annotations = {"analytics_story": ["ColdRoot MacOS RAT"], "asset_type": "Endpoint", "cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP"]} known_false_positives = There might be some false positives as keyboard event taps are used by processes like Siri and Zoom video chat, for some good examples of processes to exclude please see [this](https://github.com/facebook/osquery/pull/5345#issuecomment-454639161) comment. providing_technologies = none @@ -2214,7 +2214,7 @@ asset_type = confidence = medium explanation = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"analytics_story": ["Netsh Abuse"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. providing_technologies = none @@ -2224,7 +2224,7 @@ asset_type = confidence = medium explanation = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model -annotations = {"analytics_story": ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. providing_technologies = none @@ -2234,7 +2234,7 @@ asset_type = confidence = medium explanation = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack_id": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"]} known_false_positives = None identified providing_technologies = none @@ -2244,7 +2244,7 @@ asset_type = confidence = medium explanation = This search looks for applications on the endpoint that you have marked as prohibited. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. -annotations = {"analytics_story": ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} known_false_positives = None identified providing_technologies = none @@ -2254,7 +2254,7 @@ asset_type = confidence = medium explanation = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. -annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE", "PR.AC"], "security_domain": "network"} +annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "PR.AC"]} known_false_positives = None identified providing_technologies = none @@ -2264,7 +2264,7 @@ asset_type = confidence = medium explanation = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. -annotations = {"analytics_story": ["Use of Cleartext Protocols"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"], "security_domain": "network"} +annotations = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. providing_technologies = none @@ -2274,7 +2274,7 @@ asset_type = confidence = medium explanation = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. -annotations = {"analytics_story": ["Windows Service Abuse", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} known_false_positives = It is unusual for a service to be created or modified by directly manipulating the registry. However, there may be legitimate instances of this behavior. It is important to validate and investigate, as appropriate. providing_technologies = none @@ -2284,7 +2284,7 @@ asset_type = confidence = medium explanation = The search looks for command-line arguments used to hide a file or directory using the reg add command. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} known_false_positives = None at the moment providing_technologies = none @@ -2294,7 +2294,7 @@ asset_type = confidence = medium explanation = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1103", "T1131"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} known_false_positives = There are many legitimate applications that must execute on system startup and will use these registry keys to accomplish that task. providing_technologies = none @@ -2304,7 +2304,7 @@ asset_type = confidence = medium explanation = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = There are many legitimate applications that must execute upon system startup and will use these registry keys to accomplish that task. providing_technologies = none @@ -2314,7 +2314,7 @@ asset_type = confidence = medium explanation = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = There are many legitimate applications that leverage shim databases for compatibility purposes for legacy applications providing_technologies = none @@ -2324,7 +2324,7 @@ asset_type = confidence = medium explanation = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. -annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. providing_technologies = none @@ -2334,7 +2334,7 @@ asset_type = confidence = medium explanation = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. -annotations = {"analytics_story": ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} known_false_positives = Remote Desktop may be used legitimately by users on the network. providing_technologies = none @@ -2344,7 +2344,7 @@ asset_type = confidence = medium explanation = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. -annotations = {"analytics_story": ["Hidden Cobra Malware", "Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} known_false_positives = Remote Desktop may be used legitimately by users on the network. providing_technologies = none @@ -2354,7 +2354,7 @@ asset_type = confidence = medium explanation = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Suspicious WMI Use", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. providing_technologies = none @@ -2364,7 +2364,7 @@ asset_type = confidence = medium explanation = This search monitors for remote modifications to registry keys. how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. -annotations = {"analytics_story": ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = This technique may be legitimately used by administrators to modify remote registries, so it's important to filter these events out. providing_technologies = none @@ -2374,7 +2374,7 @@ asset_type = confidence = medium explanation = This search looks for wmic.exe being launched with parameters to operate on remote systems. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = Administrators may use this legitimately to gather info from remote systems. providing_technologies = none @@ -2384,7 +2384,7 @@ asset_type = confidence = medium explanation = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1085"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1085"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process providing_technologies = none @@ -2394,7 +2394,7 @@ asset_type = confidence = medium explanation = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. -annotations = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. providing_technologies = none @@ -2407,7 +2407,7 @@ how_to_implement = To successfully implement this search, you will need to ensur This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ 1. **Label:** Number of events, **Field:** count\ Detailed documentation on how to create a new field within Incident Review is found here: `https://docs.splunk.com/Documentation/ES/5.3.0/Admin/Customizenotables#Add_a_field_to_the_notable_event_details` -annotations = {"analytics_story": ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1043"], "nist": ["DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} known_false_positives = If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. Please update the `smb_traffic_spike_mltk_filter` macro to filter out false positive results providing_technologies = none @@ -2417,7 +2417,7 @@ asset_type = confidence = medium explanation = This search looks for long URLs that have several SQL commands visible within them. how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. -annotations = {"analytics_story": ["SQL Injection"], "asset_type": "Database Server", "cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack_id": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. providing_technologies = none @@ -2427,7 +2427,7 @@ asset_type = confidence = medium explanation = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"analytics_story": ["SamSam Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = No false positives have been identified. providing_technologies = none @@ -2437,7 +2437,7 @@ asset_type = confidence = medium explanation = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack_id": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. providing_technologies = none @@ -2447,7 +2447,7 @@ asset_type = confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} known_false_positives = No known false positives providing_technologies = none @@ -2457,7 +2457,7 @@ asset_type = confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} known_false_positives = No known false positives providing_technologies = none @@ -2467,7 +2467,7 @@ asset_type = confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Lateral Movement"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. providing_technologies = none @@ -2477,7 +2477,7 @@ asset_type = confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"analytics_story": ["Windows Persistence Techniques", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1053"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. providing_technologies = none @@ -2487,7 +2487,7 @@ asset_type = confidence = medium explanation = This search looks for scripts launched via WMI. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. providing_technologies = none @@ -2497,7 +2497,7 @@ asset_type = confidence = medium explanation = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. -annotations = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} known_false_positives = Because legitimate shim files are created and used all the time, this event, in itself, is not suspicious. However, if there are other correlating events, it may warrant further investigation. providing_technologies = none @@ -2507,7 +2507,7 @@ asset_type = confidence = medium explanation = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Windows Persistence Techniques"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1138"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} known_false_positives = None identified providing_technologies = none @@ -2517,7 +2517,7 @@ asset_type = confidence = medium explanation = This search detects accounts that were created and deleted in a short time period. how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ -annotations = {"analytics_story": ["Account Monitoring and Controls"], "asset_type": "Windows", "cis20": ["CIS 16"], "mitre_attack_id": ["T1136"], "nist": ["PR.IP"], "security_domain": "access"} +annotations = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. providing_technologies = none @@ -2527,7 +2527,7 @@ asset_type = confidence = medium explanation = This search looks for process names that consist only of a single letter. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["DHS Report TA18-074A"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. providing_technologies = none @@ -2537,7 +2537,7 @@ asset_type = confidence = medium explanation = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. -annotations = {"analytics_story": ["Spectre And Meltdown Vulnerabilities"], "asset_type": "Endpoint", "cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. providing_technologies = none @@ -2547,7 +2547,7 @@ asset_type = confidence = medium explanation = The search looks for a sharp increase in the number of files written to a particular host how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, such as Carbon Black or endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the file system. -annotations = {"analytics_story": ["SamSam Ransomware", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} known_false_positives = It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. providing_technologies = none @@ -2557,7 +2557,7 @@ asset_type = confidence = medium explanation = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. -annotations = {"analytics_story": ["Splunk Enterprise Vulnerability CVE-2018-11409"], "asset_type": "Splunk Server", "cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.AC", "PR.IP", "DE.CM"]} known_false_positives = Retrieving server information may be a legitimate API request. Verify that the attempt is a valid request for information. providing_technologies = none @@ -2567,7 +2567,7 @@ asset_type = confidence = medium explanation = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. -annotations = {"analytics_story": ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} known_false_positives = There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. providing_technologies = none @@ -2577,7 +2577,7 @@ asset_type = confidence = medium explanation = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. -annotations = {"analytics_story": ["Suspicious Emails"], "asset_type": "Endpoint", "cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. providing_technologies = none @@ -2589,7 +2589,7 @@ explanation = This search looks for emails that have attachments with suspicious how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ **Splunk Phantom Playbook Integration**\ If Splunk Phantom is also configured in your environment, a Playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk `https://splunkbase.splunk.com/app/3411/`, and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox. -annotations = {"analytics_story": ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"], "security_domain": "network"} +annotations = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} known_false_positives = None identified providing_technologies = none @@ -2599,7 +2599,7 @@ asset_type = confidence = medium explanation = The search looks for files created with names that have been linked to malicious activity. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. -annotations = {"analytics_story": ["Hidden Cobra Malware"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = It's possible for a legitimate file to be created with the same name as one noted in the lookup file. Filenames listed in the lookup file should be unique enough that collisions are rare. Looking at the location of the file and the process responsible for the activity can help determine whether or not the activity is legitimate. providing_technologies = none @@ -2609,7 +2609,7 @@ asset_type = confidence = medium explanation = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. -annotations = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 7", "CIS 12"], "kill_chain_phases": ["Exploitation"], "nist": ["DE.AE"]} known_false_positives = There are no known false positives. providing_technologies = none @@ -2619,7 +2619,7 @@ asset_type = confidence = medium explanation = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. -annotations = {"analytics_story": ["Phishing Payloads"], "asset_type": "Endpoint", "cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack_id": ["T1193"], "nist": ["ID.AM", "PR.DS"], "security_domain": "network"} +annotations = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1193"], "nist": ["ID.AM", "PR.DS"]} known_false_positives = This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. providing_technologies = none @@ -2629,7 +2629,7 @@ asset_type = confidence = medium explanation = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1112", "T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1112", "T1089"], "nist": ["DE.CM"]} known_false_positives = It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. providing_technologies = none @@ -2639,7 +2639,7 @@ asset_type = confidence = medium explanation = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. providing_technologies = none @@ -2649,7 +2649,7 @@ asset_type = confidence = medium explanation = This search detects writes to the 'System Volume Information' folder by something other than the System process. how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. -annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} known_false_positives = It is possible that other utilities or system processes may legitimately write to this folder. Investigate and modify the search to include exceptions as appropriate. providing_technologies = none @@ -2659,7 +2659,7 @@ asset_type = confidence = medium explanation = This search detects writes to the recycle bin by a process other than explorer.exe. how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. -annotations = {"analytics_story": ["Collection and Staging"], "asset_type": "Windows", "cis20": ["CIS 8"], "mitre_attack_id": ["T1074"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "mitre_attack": ["T1074"], "nist": ["DE.CM"]} known_false_positives = Because the Recycle Bin is a hidden folder in modern versions of Windows, it would be unusual for a process other than explorer.exe to write to it. Incidents should be investigated as appropriate. providing_technologies = none @@ -2669,7 +2669,7 @@ asset_type = confidence = medium explanation = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. -annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1036"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1036"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = None identified providing_technologies = none @@ -2679,7 +2679,7 @@ asset_type = confidence = medium explanation = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. -annotations = {"analytics_story": ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack_id": ["T1043"], "nist": ["DE.AE"], "security_domain": "network"} +annotations = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE"]} known_false_positives = None at this time providing_technologies = none @@ -2689,7 +2689,7 @@ asset_type = confidence = medium explanation = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} known_false_positives = None identified providing_technologies = none @@ -2699,7 +2699,7 @@ asset_type = confidence = medium explanation = This search looks for applications on the endpoint that you have marked as uncommon. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. -annotations = {"analytics_story": ["Windows Privilege Escalation", "Unusual Processes"], "asset_type": "Endpoint", "cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1015"], "nist": ["ID.AM", "PR.DS"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["ID.AM", "PR.DS"]} known_false_positives = None identified providing_technologies = none @@ -2709,7 +2709,7 @@ asset_type = confidence = medium explanation = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. -annotations = {"analytics_story": ["Disabling Security Tools"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1089"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["DE.CM"]} known_false_positives = providing_technologies = none @@ -2719,7 +2719,7 @@ asset_type = confidence = medium explanation = This search detects loading of unsigned images by LSASS. how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. -annotations = {"analytics_story": ["Credential Dumping"], "asset_type": "Windows", "cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1003"], "nist": ["DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} known_false_positives = Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. providing_technologies = none @@ -2729,7 +2729,7 @@ asset_type = confidence = medium explanation = This search gives you the hosts where a backup was attempted and then failed. how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. -annotations = {"analytics_story": ["Monitor Backup Solution"], "asset_type": "Endpoint", "cis20": ["CIS 10"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} known_false_positives = None identified providing_technologies = none @@ -2739,7 +2739,7 @@ asset_type = confidence = medium explanation = Command lines that are extremely long may be indicative of malicious activity on your hosts. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships, from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. -annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Some legitimate applications start with long command lines. providing_technologies = none @@ -2749,7 +2749,7 @@ asset_type = confidence = medium explanation = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. how_to_implement = You must be ingesting endpoint data that monitors command lines and populates the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, MLTK version >= 4.2 must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of Command Line Length - MLTK" must be executed before this detection search, as it builds an ML model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment. -annotations = {"analytics_story": ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"], "asset_type": "", "cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} known_false_positives = Some legitimate applications use long command lines for installs or updates. You should review identified command lines for legitimacy. You may modify the first part of the search to omit legitimate command lines from consideration. If you are seeing more results than desired, you may consider changing the value of threshold in the search to a smaller value. You should also periodically re-run the support search to re-build the ML model on the latest data. You may get unexpected results if the user identified in the results is not present in the data used to build the associated model. providing_technologies = none @@ -2759,7 +2759,7 @@ asset_type = confidence = medium explanation = This search looks for unusually long strings in the Content-Type http header that the client sends the server. how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. -annotations = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"], "security_domain": "network"} +annotations = {"cis20": ["CIS 3", "CIS 4", "CIS 18", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "RS.MI", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} known_false_positives = Very few legitimate Content-Type fields will have a length greater than 100 characters. providing_technologies = none @@ -2769,7 +2769,7 @@ asset_type = confidence = medium explanation = This search looks for the creation of WMI permanent event subscriptions. how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. providing_technologies = none @@ -2779,7 +2779,7 @@ asset_type = confidence = medium explanation = This search looks for the creation of WMI permanent event subscriptions. how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. -annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = Although unlikely, administrators may use event subscriptions for legitimate purposes. providing_technologies = none @@ -2789,7 +2789,7 @@ asset_type = confidence = medium explanation = This search looks for the creation of WMI temporary event subscriptions. how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. -annotations = {"analytics_story": ["Suspicious WMI Use"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} known_false_positives = Some software may create WMI temporary event subscriptions for various purposes. The included search contains an exception for two of these that occur by default on Windows 10 systems. You may need to modify the search to create exceptions for other legitimate events. providing_technologies = none @@ -2799,7 +2799,7 @@ asset_type = confidence = medium explanation = This search is used to identify the creation of multiple user accounts using the same email domain name. how_to_implement = We start with a dataset that provides visibility into the email address used for the account creation. In this example, we are narrowing our search down to the single web page that hosts the Magento2 e-commerce platform (via URI) used for account creation, the single http content-type to grab only the user's clicks, and the http field that provides the username (form_data), for performance reasons. After we have the username and email domain, we look for numerous account creations per email domain. Common data sources used for this detection are customized Apache logs or Splunk Stream. -annotations = {"analytics_story": ["Web Fraud Detection"], "asset_type": "Account", "cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1136"], "nist": ["DE.CM", "DE.DP"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1136"], "nist": ["DE.CM", "DE.DP"]} known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamolous behavior. This search will need to be customized to fit your environment—improving its fidelity by counting based on something much more specific, such as a device ID that may be present in your dataset. Consideration for whether the large number of registrations are occuring from a first-time seen domain may also be important. Extending the search window to look further back in time, or even calculating the average per hour/day for each email domain to look for an anomalous spikes, will improve this search. You can also use Shannon entropy or Levenshtein Distance (both courtesy of URL Toolbox) to consider the randomness or similarity of the email name or email domain, as the names are often machine-generated. providing_technologies = none @@ -2809,7 +2809,7 @@ asset_type = confidence = medium explanation = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. how_to_implement = Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -annotations = {"analytics_story": ["Web Fraud Detection"], "asset_type": "account", "cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1078"], "nist": ["DE.AE", "DE.CM"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078"], "nist": ["DE.AE", "DE.CM"]} known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior. providing_technologies = none @@ -2819,7 +2819,7 @@ asset_type = confidence = medium explanation = This search is used to identify user accounts that share a common password. how_to_implement = We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. -annotations = {"analytics_story": ["Web Fraud Detection"], "asset_type": "account", "cis20": ["CIS 16"], "nist": ["DE.DP"], "security_domain": "threat"} +annotations = {"cis20": ["CIS 16"], "nist": ["DE.DP"]} known_false_positives = As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections that simply detect anamoluous behavior. providing_technologies = none @@ -2829,7 +2829,7 @@ asset_type = confidence = medium explanation = This search looks for suspicious processes on all systems labeled as web servers. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. -annotations = {"analytics_story": ["Apache Struts Vulnerability"], "asset_type": "Web Server", "cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1082"], "nist": ["PR.IP"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["PR.IP"]} known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. providing_technologies = none @@ -2839,7 +2839,7 @@ asset_type = confidence = medium explanation = This search looks for Windows events that indicate one of the Windows event logs has been purged. how_to_implement = To successfully implement this search, you need to be ingesting Windows event logs from your hosts. -annotations = {"analytics_story": ["Windows Log Manipulation", "Ransomware"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack_id": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.AC", "PR.AT", "DE.AE"]} known_false_positives = It is possible that these logs may be legitimately cleared by Administrators. providing_technologies = none @@ -2849,7 +2849,7 @@ asset_type = confidence = medium explanation = The search looks for modifications to the hosts file on all Windows endpoints across your environment. how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. -annotations = {"analytics_story": ["Host Redirection"], "asset_type": "Endpoint", "cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"], "security_domain": "endpoint"} +annotations = {"cis20": ["CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.IP", "PR.PT", "PR.AC", "DE.AE", "DE.CM"]} known_false_positives = There may be legitimate reasons for system administrators to add entries to this file. providing_technologies = none From 4ceb0e14cda2e154caf60647fbe116ce3dc8d5c8 Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 11 May 2020 14:57:16 -0700 Subject: [PATCH 39/93] minor bug and flake8 --- bin/generate.py | 13 ++++++------- bin/jinja2_templates/savedsearches.j2 | 6 +++--- 2 files changed, 9 insertions(+), 10 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index 66868a86cc..3fadc26ee0 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -79,11 +79,8 @@ def generate_savedsearches_conf(detections, response_tasks, baselines, deploymen else: if key in detection['tags']: mappings[key] = detection['tags'][key] - - detection['mappings'] = mappings - for baseline in baselines: data_model = parse_data_models_from_search(baseline['search']) if data_model: @@ -167,8 +164,6 @@ def generate_use_case_library_conf(stories, detections, response_tasks, baseline else: if key in detection['tags']: mappings[key] = detection['tags'][key] - - detection['mappings'] = mappings utc_time = datetime.datetime.utcnow().replace(microsecond=0).isoformat() @@ -192,7 +187,8 @@ def generate_macros_conf(macros, detections): new_dict = {} new_dict['definition'] = 'search *' new_dict['description'] = 'Update this macro to limit the output results to filter out false positives. ' - new_dict['name'] = detection['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + '_filter' + new_dict['name'] = detection['name']. \ + replace(' ', '_').replace('-', '_').replace('.', '_').replace('/', '_').lower() + '_filter' filter_macros.append(new_dict) all_macros = macros + filter_macros @@ -211,7 +207,7 @@ def generate_macros_conf(macros, detections): def parse_data_models_from_search(search): - match = re.search('from\sdatamodel\s?=\s?([^\s.]*)',search) + match = re.search(r'from\sdatamodel\s?=\s?([^\s.]*)', search) if match is not None: return match.group(1) return False @@ -273,6 +269,7 @@ def map_detection_to_stories(detections): sto_det[story].add(str('ESCU - ' + detection['name'] + ' - Rule')) return sto_det + def map_response_tasks_to_stories(response_tasks): sto_res = {} for response_task in response_tasks: @@ -391,6 +388,8 @@ if __name__ == "__main__": REPO_PATH = args.path OUTPUT_PATH = args.output VERBOSE = args.verbose + reload(sys) + sys.setdefaultencoding('utf8') stories = load_objects("stories/*.yml") macros = load_objects("macros/*.yml") diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index cd41ad438d..71adfcde25 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -14,7 +14,7 @@ action.escu.enabled = 1 description = {{ detection.description }} action.escu.mappings = {{ detection.mappings | tojson }} {% if detection.data_model is defined %} -action.escu.data_models = [{{ detection.data_model }}] +action.escu.data_models = [{{ detection.data_model | tojson }}] {% else %} action.escu.data_models = [] {% endif %} @@ -108,7 +108,7 @@ action.escu.analytic_story = {{ baseline.tags.analytics_story | tojson }} action.escu.analytic_story = [] {% endif %} {% if baseline.data_model is defined %} -action.escu.data_models = [{{ baseline.data_model }}] +action.escu.data_models = [{{ baseline.data_model | tojson }}] {% else %} action.escu.data_models = [] {% endif %} @@ -156,7 +156,7 @@ action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] {% if response_task.data_model is defined %} -action.escu.data_models = [{{ response_task.data_model }}] +action.escu.data_models = [{{ response_task.data_model | tojson}}] {% else %} action.escu.data_models = [] {% endif %} From 792792c5b59925c74bc43cc886be248df82cb5b0 Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 11 May 2020 15:12:00 -0700 Subject: [PATCH 40/93] minor bug and flake8 --- bin/generate.py | 1 + 1 file changed, 1 insertion(+) diff --git a/bin/generate.py b/bin/generate.py index 3fadc26ee0..e00e58b0a4 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -13,6 +13,7 @@ import datetime from jinja2 import Environment, FileSystemLoader import re + # global variables REPO_PATH = '' VERBOSE = False From 74175639a59f43761e19a9765c154b1c21bcef19 Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 11 May 2020 15:16:55 -0700 Subject: [PATCH 41/93] minor bug and flake8 --- bin/generate.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/bin/generate.py b/bin/generate.py index e00e58b0a4..06241b770f 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -389,9 +389,6 @@ if __name__ == "__main__": REPO_PATH = args.path OUTPUT_PATH = args.output VERBOSE = args.verbose - reload(sys) - sys.setdefaultencoding('utf8') - stories = load_objects("stories/*.yml") macros = load_objects("macros/*.yml") lookups = load_objects("lookups/*.yml") From 151bbbaa5a35cad92c502729a7c8ed8f4bb29470 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 12 May 2020 13:53:48 +0200 Subject: [PATCH 42/93] bug in generate --- ...baseline_of_command_line_length___mltk.yml | 2 +- baselines/dnstwist_domain_names.yml | 2 +- ...seen_aws_provisioning_activity_sources.yml | 4 +- ...previously_seen_command_line_arguments.yml | 2 +- .../previously_seen_users_in_cloudtrail.yml | 4 +- ...te_previously_seen_users_in_cloudtrail.yml | 4 +- bin/converter_v2_v3.py | 9 + bin/generate.py | 27 + bin/jinja2_templates/es_investigations.j2 | 30 + bin/jinja2_templates/panel.j2 | 9 + bin/jinja2_templates/savedsearches.bak.j2 | 292 --- ...ly_high_aws_instances_launched_by_user.yml | 2 +- ...ution_policy_to_unrestricted_or_bypass.yml | 2 +- ...nts_connecting_to_multiple_dns_servers.yml | 4 +- ...connecting_to_dynamic_domain_providers.yml | 6 +- detections/detect_outbound_smb_traffic.yml | 2 +- ...ohibited_applications_spawning_cmd_exe.yml | 2 +- detections/detect_rare_executables.yml | 2 +- ..._cmd_exe_to_launch_script_interpreters.yml | 2 +- detections/detection_of_dns_tunnels.yml | 2 +- .../disabling_remote_user_account_control.yml | 2 +- .../dns_query_length_outliers___mltk.yml | 2 +- ...ry_length_with_high_standard_deviation.yml | 2 +- ...s_resolved_by_unauthorized_dns_servers.yml | 4 +- ...ce_started_in_previously_unseen_region.yml | 2 +- ...ce_started_with_previously_unseen_user.yml | 2 +- .../first_time_seen_command_line_argument.yml | 6 +- ..._files_and_directories_with_attrib_exe.yml | 2 +- detections/monitor_email_for_brand_abuse.yml | 2 +- ...nitor_registry_keys_for_print_monitors.yml | 2 +- detections/processes_launching_netsh.yml | 4 +- .../prohibited_software_on_endpoint.yml | 2 +- ...ulating_windows_services_registry_keys.yml | 2 +- ...de_files_directories_via_registry_keys.yml | 4 +- ...istry_keys_for_creating_shim_databases.yml | 2 +- .../registry_keys_used_for_persistence.yml | 8 +- ...try_keys_used_for_privilege_escalation.yml | 2 +- detections/remote_desktop_network_traffic.yml | 2 +- ...mote_desktop_process_running_on_system.yml | 2 +- .../remote_registry_key_modifications.yml | 4 +- .../sc_exe_manipulating_windows_services.yml | 4 +- detections/smb_traffic_spike.yml | 4 +- detections/smb_traffic_spike___mltk.yml | 4 +- ...uspicious_changes_to_file_associations.yml | 2 +- detections/suspicious_reg_exe_process.yml | 2 +- ...rocesses_run_from_unexpected_locations.yml | 4 +- detections/uncommon_processes_on_endpoint.yml | 2 +- detections/unusually_long_command_line.yml | 4 +- .../unusually_long_command_line___mltk.yml | 4 +- package/default/analytic_stories.conf | 112 +- .../ui/panels/all_backup_logs_for_host.xml | 9 + ...azon_eks_kubernetes_activity_by_src_ip.xml | 9 + ...stigate_user_activities_by_accesskeyid.xml | 9 + ...aws_investigate_user_activities_by_arn.xml | 9 + ...stigate_user_activities_by_source_user.xml | 9 + .../aws_network_acl_details_from_id.xml | 9 + ...twork_interface_details_via_resourceid.xml | 9 + .../aws_s3_bucket_details_via_bucketname.xml | 9 + .../gcp_kubernetes_activity_by_src_ip.xml | 9 + .../panels/get_all_aws_activity_from_city.xml | 9 + .../get_all_aws_activity_from_country.xml | 9 + .../get_all_aws_activity_from_ip_address.xml | 9 + .../get_all_aws_activity_from_region.xml | 9 + .../get_authentication_logs_for_endpoint.xml | 9 + .../panels/get_backup_logs_for_endpoint.xml | 9 + .../get_certificate_logs_for_a_domain.xml | 9 + .../get_dns_server_history_for_a_host.xml | 9 + .../data/ui/panels/get_dns_traffic_ratio.xml | 9 + ...get_ec2_instance_details_by_instanceid.xml | 9 + .../data/ui/panels/get_ec2_launch_details.xml | 9 + .../default/data/ui/panels/get_email_info.xml | 9 + .../get_emails_from_specific_sender.xml | 9 + ...e_and_last_occurrence_of_a_mac_address.xml | 9 + .../panels/get_history_of_email_sources.xml | 9 + ...ogon_rights_modifications_for_endpoint.xml | 9 + ...et_logon_rights_modifications_for_user.xml | 9 + .../data/ui/panels/get_notable_history.xml | 9 + .../data/ui/panels/get_notable_info.xml | 9 + ...d_emails_to_hidden_cobra_threat_actors.xml | 9 + .../ui/panels/get_parent_process_info.xml | 9 + .../ui/panels/get_process_file_activity.xml | 9 + .../data/ui/panels/get_process_info.xml | 9 + ..._process_information_for_port_activity.xml | 9 + .../panels/get_process_registry_activity.xml | 9 + ...rocess_responsible_for_the_dns_traffic.xml | 9 + .../ui/panels/get_registry_activities.xml | 9 + .../get_risk_modifiers_for_endpoint.xml | 9 + .../ui/panels/get_risk_modifiers_for_user.xml | 9 + .../get_sysmon_wmi_activity_for_host.xml | 9 + .../panels/get_update_logs_for_endpoint.xml | 9 + ...t_user_information_from_identity_table.xml | 9 + .../get_vulnerability_logs_for_endpoint.xml | 9 + ...web_session_information_via_session_id.xml | 9 + ...stigate_aws_activities_via_region_name.xml | 9 + ...ate_aws_ecr_container_listing_activity.xml | 9 + ...gate_aws_user_activities_by_user_field.xml | 9 + ...gate_cloud_compute_instance_activities.xml | 9 + ...ailed_logins_for_multiple_destinations.xml | 9 + ...nvestigate_network_traffic_from_src_ip.xml | 9 + .../investigate_okta_activity_by_app.xml | 9 + ...nvestigate_okta_activity_by_ip_address.xml | 9 + .../investigate_pass_the_hash_attempts.xml | 9 + .../investigate_pass_the_ticket_attempts.xml | 9 + .../investigate_previous_unseen_user.xml | 9 + ...cessful_remote_desktop_authentications.xml | 9 + ...gate_suspicious_strings_in_http_header.xml | 9 + ...e_user_activities_in_all_cloud_regions.xml | 9 + .../investigate_user_activities_in_okta.xml | 9 + ...user_activities_in_single_cloud_region.xml | 9 + .../investigate_web_activity_from_host.xml | 9 + .../investigate_web_activity_from_src_ip.xml | 9 + .../panels/investigate_web_posts_from_src.xml | 9 + .../data/ui/panels/process_chain_analysis.xml | 9 + ...rkbench_panel_all_backup_logs_for_host.xml | 9 + ...azon_eks_kubernetes_activity_by_src_ip.xml | 9 + ...stigate_user_activities_by_accesskeyid.xml | 9 + ...aws_investigate_user_activities_by_arn.xml | 9 + ...stigate_user_activities_by_source_user.xml | 9 + ..._panel_aws_network_acl_details_from_id.xml | 9 + ...twork_interface_details_via_resourceid.xml | 9 + ...l_aws_s3_bucket_details_via_bucketname.xml | 9 + ...anel_gcp_kubernetes_activity_by_src_ip.xml | 9 + ...h_panel_get_all_aws_activity_from_city.xml | 9 + ...anel_get_all_aws_activity_from_country.xml | 9 + ...l_get_all_aws_activity_from_ip_address.xml | 9 + ...panel_get_all_aws_activity_from_region.xml | 9 + ...l_get_authentication_logs_for_endpoint.xml | 9 + ...nch_panel_get_backup_logs_for_endpoint.xml | 9 + ...anel_get_certificate_logs_for_a_domain.xml | 9 + ...anel_get_dns_server_history_for_a_host.xml | 9 + .../workbench_panel_get_dns_traffic_ratio.xml | 9 + ...get_ec2_instance_details_by_instanceid.xml | 9 + ...workbench_panel_get_ec2_launch_details.xml | 9 + .../panels/workbench_panel_get_email_info.xml | 9 + ..._panel_get_emails_from_specific_sender.xml | 9 + ...e_and_last_occurrence_of_a_mac_address.xml | 9 + ...nch_panel_get_history_of_email_sources.xml | 9 + ...ogon_rights_modifications_for_endpoint.xml | 9 + ...et_logon_rights_modifications_for_user.xml | 9 + .../workbench_panel_get_notable_history.xml | 9 + .../workbench_panel_get_notable_info.xml | 9 + ...d_emails_to_hidden_cobra_threat_actors.xml | 9 + ...orkbench_panel_get_parent_process_info.xml | 9 + ...kbench_panel_get_process_file_activity.xml | 9 + .../workbench_panel_get_process_info.xml | 9 + ..._process_information_for_port_activity.xml | 9 + ...ch_panel_get_process_registry_activity.xml | 9 + ...rocess_responsible_for_the_dns_traffic.xml | 9 + ...orkbench_panel_get_registry_activities.xml | 9 + ..._panel_get_risk_modifiers_for_endpoint.xml | 9 + ...ench_panel_get_risk_modifiers_for_user.xml | 9 + ...panel_get_sysmon_wmi_activity_for_host.xml | 9 + ...nch_panel_get_update_logs_for_endpoint.xml | 9 + ...t_user_information_from_identity_table.xml | 9 + ...el_get_vulnerability_logs_for_endpoint.xml | 9 + ...web_session_information_via_session_id.xml | 9 + ...stigate_aws_activities_via_region_name.xml | 9 + ...ate_aws_ecr_container_listing_activity.xml | 9 + ...gate_aws_user_activities_by_user_field.xml | 9 + ...gate_cloud_compute_instance_activities.xml | 9 + ...ailed_logins_for_multiple_destinations.xml | 9 + ...nvestigate_network_traffic_from_src_ip.xml | 9 + ...panel_investigate_okta_activity_by_app.xml | 9 + ...nvestigate_okta_activity_by_ip_address.xml | 9 + ...nel_investigate_pass_the_hash_attempts.xml | 9 + ...l_investigate_pass_the_ticket_attempts.xml | 9 + ...panel_investigate_previous_unseen_user.xml | 9 + ...cessful_remote_desktop_authentications.xml | 9 + ...gate_suspicious_strings_in_http_header.xml | 9 + ...e_user_activities_in_all_cloud_regions.xml | 9 + ...el_investigate_user_activities_in_okta.xml | 9 + ...user_activities_in_single_cloud_region.xml | 9 + ...nel_investigate_web_activity_from_host.xml | 9 + ...l_investigate_web_activity_from_src_ip.xml | 9 + ...h_panel_investigate_web_posts_from_src.xml | 9 + ...workbench_panel_process_chain_analysis.xml | 9 + package/default/es_investigations.conf | 1101 ++++++++ package/default/macros.conf | 2 +- package/default/savedsearches.conf | 182 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 122 +- response_tasks/all_backup_logs_for_host.yml | 2 +- ...azon_eks_kubernetes_activity_by_src_ip.yml | 2 +- ...stigate_user_activities_by_accesskeyid.yml | 2 +- ...aws_investigate_user_activities_by_arn.yml | 2 +- ...stigate_user_activities_by_source_user.yml | 2 +- .../aws_network_acl_details_from_id.yml | 2 +- ...twork_interface_details_via_resourceid.yml | 2 +- .../aws_s3_bucket_details_via_bucketname.yml | 2 +- .../get_all_aws_activity_from_city.yml | 2 +- .../get_all_aws_activity_from_country.yml | 2 +- .../get_all_aws_activity_from_ip_address.yml | 2 +- .../get_all_aws_activity_from_region.yml | 2 +- .../get_authentication_logs_for_endpoint.yml | 2 +- .../get_backup_logs_for_endpoint.yml | 2 +- .../get_certificate_logs_for_a_domain.yml | 2 +- .../get_dns_server_history_for_a_host.yml | 2 +- response_tasks/get_dns_traffic_ratio.yml | 2 +- ...get_ec2_instance_details_by_instanceid.yml | 2 +- response_tasks/get_ec2_launch_details.yml | 2 +- response_tasks/get_email_info.yml | 2 +- .../get_emails_from_specific_sender.yml | 2 +- ...e_and_last_occurrence_of_a_mac_address.yml | 2 +- ...ogon_rights_modifications_for_endpoint.yml | 2 +- ...et_logon_rights_modifications_for_user.yml | 2 +- response_tasks/get_notable_history.yml | 2 +- response_tasks/get_notable_info.yml | 2 +- response_tasks/get_parent_process_info.yml | 2 +- response_tasks/get_process_file_activity.yml | 2 +- response_tasks/get_process_info.yml | 2 +- ..._process_information_for_port_activity.yml | 4 +- .../get_process_registry_activity.yml | 4 +- ...rocess_responsible_for_the_dns_traffic.yml | 2 +- response_tasks/get_registry_activities.yml | 2 +- .../get_risk_modifiers_for_endpoint.yml | 2 +- .../get_risk_modifiers_for_user.yml | 2 +- .../get_sysmon_wmi_activity_for_host.yml | 2 +- .../get_update_logs_for_endpoint.yml | 2 +- ...t_user_information_from_identity_table.yml | 2 +- .../get_vulnerability_logs_for_endpoint.yml | 2 +- ...web_session_information_via_session_id.yml | 2 +- ...stigate_aws_activities_via_region_name.yml | 2 +- ...gate_aws_user_activities_by_user_field.yml | 2 +- ...gate_cloud_compute_instance_activities.yml | 2 +- ...nvestigate_network_traffic_from_src_ip.yml | 2 +- .../investigate_okta_activity_by_app.yml | 2 +- ...gate_suspicious_strings_in_http_header.yml | 2 +- ...e_user_activities_in_all_cloud_regions.yml | 2 +- .../investigate_user_activities_in_okta.yml | 2 +- ...user_activities_in_single_cloud_region.yml | 2 +- .../investigate_web_activity_from_host.yml | 2 +- .../investigate_web_activity_from_src_ip.yml | 2 +- .../investigate_web_posts_from_src.yml | 2 +- stories/lateral_movement.yml | 1 + tmp.js | 2232 ----------------- 235 files changed, 2640 insertions(+), 2853 deletions(-) create mode 100644 bin/jinja2_templates/es_investigations.j2 create mode 100644 bin/jinja2_templates/panel.j2 delete mode 100644 bin/jinja2_templates/savedsearches.bak.j2 create mode 100644 package/default/data/ui/panels/all_backup_logs_for_host.xml create mode 100644 package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml create mode 100644 package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml create mode 100644 package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml create mode 100644 package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml create mode 100644 package/default/data/ui/panels/aws_network_acl_details_from_id.xml create mode 100644 package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml create mode 100644 package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml create mode 100644 package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml create mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_city.xml create mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_country.xml create mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml create mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_region.xml create mode 100644 package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/get_backup_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml create mode 100644 package/default/data/ui/panels/get_dns_server_history_for_a_host.xml create mode 100644 package/default/data/ui/panels/get_dns_traffic_ratio.xml create mode 100644 package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml create mode 100644 package/default/data/ui/panels/get_ec2_launch_details.xml create mode 100644 package/default/data/ui/panels/get_email_info.xml create mode 100644 package/default/data/ui/panels/get_emails_from_specific_sender.xml create mode 100644 package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml create mode 100644 package/default/data/ui/panels/get_history_of_email_sources.xml create mode 100644 package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml create mode 100644 package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml create mode 100644 package/default/data/ui/panels/get_notable_history.xml create mode 100644 package/default/data/ui/panels/get_notable_info.xml create mode 100644 package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml create mode 100644 package/default/data/ui/panels/get_parent_process_info.xml create mode 100644 package/default/data/ui/panels/get_process_file_activity.xml create mode 100644 package/default/data/ui/panels/get_process_info.xml create mode 100644 package/default/data/ui/panels/get_process_information_for_port_activity.xml create mode 100644 package/default/data/ui/panels/get_process_registry_activity.xml create mode 100644 package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml create mode 100644 package/default/data/ui/panels/get_registry_activities.xml create mode 100644 package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml create mode 100644 package/default/data/ui/panels/get_risk_modifiers_for_user.xml create mode 100644 package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml create mode 100644 package/default/data/ui/panels/get_update_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/get_user_information_from_identity_table.xml create mode 100644 package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/get_web_session_information_via_session_id.xml create mode 100644 package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml create mode 100644 package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml create mode 100644 package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml create mode 100644 package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml create mode 100644 package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml create mode 100644 package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml create mode 100644 package/default/data/ui/panels/investigate_okta_activity_by_app.xml create mode 100644 package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml create mode 100644 package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml create mode 100644 package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml create mode 100644 package/default/data/ui/panels/investigate_previous_unseen_user.xml create mode 100644 package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml create mode 100644 package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml create mode 100644 package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml create mode 100644 package/default/data/ui/panels/investigate_user_activities_in_okta.xml create mode 100644 package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml create mode 100644 package/default/data/ui/panels/investigate_web_activity_from_host.xml create mode 100644 package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml create mode 100644 package/default/data/ui/panels/investigate_web_posts_from_src.xml create mode 100644 package/default/data/ui/panels/process_chain_analysis.xml create mode 100644 package/default/data/ui/panels/workbench_panel_all_backup_logs_for_host.xml create mode 100644 package/default/data/ui/panels/workbench_panel_amazon_eks_kubernetes_activity_by_src_ip.xml create mode 100644 package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_accesskeyid.xml create mode 100644 package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_arn.xml create mode 100644 package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_source_user.xml create mode 100644 package/default/data/ui/panels/workbench_panel_aws_network_acl_details_from_id.xml create mode 100644 package/default/data/ui/panels/workbench_panel_aws_network_interface_details_via_resourceid.xml create mode 100644 package/default/data/ui/panels/workbench_panel_aws_s3_bucket_details_via_bucketname.xml create mode 100644 package/default/data/ui/panels/workbench_panel_gcp_kubernetes_activity_by_src_ip.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_city.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_country.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_ip_address.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_region.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_authentication_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_backup_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_certificate_logs_for_a_domain.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_dns_server_history_for_a_host.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_dns_traffic_ratio.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_ec2_instance_details_by_instanceid.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_ec2_launch_details.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_email_info.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_emails_from_specific_sender.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_history_of_email_sources.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_endpoint.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_user.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_notable_history.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_notable_info.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_parent_process_info.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_process_file_activity.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_process_info.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_process_information_for_port_activity.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_process_registry_activity.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_process_responsible_for_the_dns_traffic.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_registry_activities.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_endpoint.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_user.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_sysmon_wmi_activity_for_host.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_update_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_user_information_from_identity_table.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_vulnerability_logs_for_endpoint.xml create mode 100644 package/default/data/ui/panels/workbench_panel_get_web_session_information_via_session_id.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_aws_activities_via_region_name.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_aws_ecr_container_listing_activity.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_aws_user_activities_by_user_field.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_cloud_compute_instance_activities.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_network_traffic_from_src_ip.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_app.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_ip_address.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_pass_the_hash_attempts.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_previous_unseen_user.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_successful_remote_desktop_authentications.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_suspicious_strings_in_http_header.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_all_cloud_regions.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_okta.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_single_cloud_region.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_host.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_src_ip.xml create mode 100644 package/default/data/ui/panels/workbench_panel_investigate_web_posts_from_src.xml create mode 100644 package/default/data/ui/panels/workbench_panel_process_chain_analysis.xml create mode 100644 package/default/es_investigations.conf delete mode 100644 tmp.js diff --git a/baselines/baseline_of_command_line_length___mltk.yml b/baselines/baseline_of_command_line_length___mltk.yml index f5068fa341..28205e56d9 100644 --- a/baselines/baseline_of_command_line_length___mltk.yml +++ b/baselines/baseline_of_command_line_length___mltk.yml @@ -31,5 +31,5 @@ tags: - Suspicious MSHTA Activity - Unusual Processes detections: - - Unusually Long Command Line - MLTK - Detect Prohibited Applications Spawning cmd.exe + - Unusually Long Command Line - MLTK diff --git a/baselines/dnstwist_domain_names.yml b/baselines/dnstwist_domain_names.yml index cd2ebd0aad..9375d75ac2 100644 --- a/baselines/dnstwist_domain_names.yml +++ b/baselines/dnstwist_domain_names.yml @@ -17,5 +17,5 @@ tags: - Suspicious Emails detections: - Monitor DNS For Brand Abuse - - Monitor Web Traffic For Brand Abuse - Monitor Email For Brand Abuse + - Monitor Web Traffic For Brand Abuse diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml index 7d68c6f389..f03a3a3b70 100644 --- a/baselines/previously_seen_aws_provisioning_activity_sources.yml +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -17,7 +17,7 @@ tags: analytics_story: - AWS Suspicious Provisioning Activities detections: - - AWS Cloud Provisioning From Previously Unseen Country + - AWS Cloud Provisioning From Previously Unseen City - AWS Cloud Provisioning From Previously Unseen Region - AWS Cloud Provisioning From Previously Unseen IP Address - - AWS Cloud Provisioning From Previously Unseen City + - AWS Cloud Provisioning From Previously Unseen Country diff --git a/baselines/previously_seen_command_line_arguments.yml b/baselines/previously_seen_command_line_arguments.yml index 32d364cc1e..7ac6d4ed10 100644 --- a/baselines/previously_seen_command_line_arguments.yml +++ b/baselines/previously_seen_command_line_arguments.yml @@ -25,6 +25,6 @@ tags: - Suspicious Command-Line Executions - Suspicious MSHTA Activity detections: - - Processes launching netsh - First time seen command line argument - Detect Prohibited Applications Spawning cmd.exe + - Processes launching netsh diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml index 6a85afd36f..6c2e04ba6b 100644 --- a/baselines/previously_seen_users_in_cloudtrail.yml +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -19,7 +19,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect new user AWS Console Login - Detect AWS Console Login by User from New City - - Detect AWS Console Login by User from New Region - Detect AWS Console Login by User from New Country + - Detect new user AWS Console Login + - Detect AWS Console Login by User from New Region diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml index b50325c51f..fb40d6386d 100644 --- a/baselines/update_previously_seen_users_in_cloudtrail.yml +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -20,7 +20,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect new user AWS Console Login - Detect AWS Console Login by User from New City - - Detect AWS Console Login by User from New Region - Detect AWS Console Login by User from New Country + - Detect new user AWS Console Login + - Detect AWS Console Login by User from New Region diff --git a/bin/converter_v2_v3.py b/bin/converter_v2_v3.py index 33b9b571f1..b4ff19f64b 100644 --- a/bin/converter_v2_v3.py +++ b/bin/converter_v2_v3.py @@ -213,6 +213,7 @@ def generate_content(): if 'splunk' in orig_dict['investigate']: new_dict['inputs'] = orig_dict['investigate']['splunk']['fields_required'] new_dict['search'] = orig_dict['investigate']['splunk']['search'] + new_dict = change_response_task_variable(new_dict) # elif 'phantom' in orig_dict['investigate']: # phantom_dict = {} # phantom_dict['name'] = orig_dict['investigate']['phantom']['playbook_name'] @@ -355,6 +356,14 @@ def check_source_macro(search): return new_search +def change_response_task_variable(object): + if 'inputs' in object: + for input in object['inputs']: + if 'search' in object: + new_search = object['search'].replace("{" + input + "}", "$" + input + "$") + object['search'] = new_search + return object + if __name__ == "__main__": generate_content() diff --git a/bin/generate.py b/bin/generate.py index 06241b770f..723096e462 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -207,6 +207,31 @@ def generate_macros_conf(macros, detections): return output_path +def generate_workbench_panels(response_tasks): + workbench_panel_objects = [] + for response_task in response_tasks: + if 'search' in response_task: + if 'inputs' in response_task: + response_file_name = response_task['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + response_task['lowercase_name'] = response_file_name + workbench_panel_objects.append(response_task) + j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), + trim_blocks=True) + template = j2_env.get_template('panel.j2') + output_path = OUTPUT_PATH + "/default/data/ui/panels/workbench_panel_" + response_file_name + ".xml" + output = template.render(search=response_task['search']) + with open(output_path, 'w') as f: + f.write(output) + + j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), + trim_blocks=True) + template = j2_env.get_template('es_investigations.j2') + output_path = OUTPUT_PATH + "/default/es_investigations.conf" + output = template.render(response_tasks=workbench_panel_objects) + with open(output_path, 'w') as f: + f.write(output) + + def parse_data_models_from_search(search): match = re.search(r'from\sdatamodel\s?=\s?([^\s.]*)', search) if match is not None: @@ -413,6 +438,8 @@ if __name__ == "__main__": macros = sorted(macros, key=lambda m: m['name']) macros_path = generate_macros_conf(macros, detections) + generate_workbench_panels(response_tasks) + if VERBOSE: print("{0} stories have been successfully written to {1}".format(len(stories), story_path)) print("{0} detections have been successfully written to {1}".format(len(detections), detection_path)) diff --git a/bin/jinja2_templates/es_investigations.j2 b/bin/jinja2_templates/es_investigations.j2 new file mode 100644 index 0000000000..3610743094 --- /dev/null +++ b/bin/jinja2_templates/es_investigations.j2 @@ -0,0 +1,30 @@ +{% for response_task in response_tasks %} +[panel://workbench_panel_{{ response_task.lowercase_name }}] +label = {{ response_task.name }} +description = {{ response_task.description }} +disabled = 0 +tokens = {\ +{% for token in response_task.inputs %} +{% if token == 'user' %} + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ +{% else %} + "inventory_asset_{{ token }}_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\{% endif %}{{ "," if not loop.last }} +{% endfor %} +}\ + + +{% endfor %} diff --git a/bin/jinja2_templates/panel.j2 b/bin/jinja2_templates/panel.j2 new file mode 100644 index 0000000000..45be63462f --- /dev/null +++ b/bin/jinja2_templates/panel.j2 @@ -0,0 +1,9 @@ + + + + {{ search }} + + + +
+ diff --git a/bin/jinja2_templates/savedsearches.bak.j2 b/bin/jinja2_templates/savedsearches.bak.j2 deleted file mode 100644 index 8e50fabe6a..0000000000 --- a/bin/jinja2_templates/savedsearches.bak.j2 +++ /dev/null @@ -1,292 +0,0 @@ -############# -# Automatically generated by generator.py in splunk/security-content -# On Date: {{ time }} UTC -# Author: Splunk Security Research -# Contact: research@splunk.com -############# - -### ESCU DETECTIONS ### - - -{% for detection in detections %} -[ESCU - {{ detection.name }} - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = {{ detection.description }} -action.escu.mappings = {{ detection.mappings | tojson }} -{% if detection.data_metadata.data_models is defined %} -action.escu.data_models = {{ detection.data_metadata.data_models | tojson }} -{% endif %} -{% if detection.eli5 is defined %} -action.escu.eli5 = {{ detection.eli5 }} -{% else %} -action.escu.eli5 = none -{% endif %} -{% if detection.how_to_implement is defined %} -action.escu.how_to_implement = {{ detection.how_to_implement }} -{% else %} -action.escu.how_to_implement = none -{% endif %} -{% if detection.known_false_positives is defined %} -action.escu.known_false_positives = {{ detection.known_false_positives }} -{% else %} -action.escu.known_false_positives = None -{% endif %} -action.escu.creation_date = {{ detection.creation_date }} -action.escu.modification_date = {{ detection.modification_date }} -action.escu.confidence = {{ detection.confidence }} -action.escu.full_search_name = ESCU - {{ detection.name }} - Rule -action.escu.search_type = detection -{% if detection.asset_type is defined %} -action.escu.asset_at_risk = {{ detection.asset_type }} -{% endif %} -{% if detection.entities is defined %} -action.escu.fields_required = {{ detection.entities | tojson }} -action.escu.entities = {{ detection.entities | tojson }} -{% endif %} -{% if detection.data_metadata.providing_technologies is defined %} -action.escu.providing_technologies = {{ detection.data_metadata.providing_technologies | tojson }} -{% endif %} -action.escu.analytic_story = {{ detection.stories | tojson | replace("\\u0026","&") }} -{% if detection.detect.splunk is defined %} -{% set correlation_rule = detection.detect.splunk.correlation_rule %} -{% elif detection.detect.uba is defined %} -{% set correlation_rule = detection.detect.uba.correlation_rule %} -{% endif %} -{% if correlation_rule.schedule.cron_schedule is defined %} -cron_schedule = {{ correlation_rule.schedule.cron_schedule }} -{% endif %} -{% if correlation_rule.schedule.earliest_time is defined %} -dispatch.earliest_time = {{ correlation_rule.schedule.earliest_time }} -{% endif %} -{% if correlation_rule.schedule.latest_time is defined %} -dispatch.latest_time = {{ correlation_rule.schedule.latest_time }} -{% endif %} -{% if correlation_rule is defined %} -action.correlationsearch.enabled = 1 -action.correlationsearch.label = {{ detection.name }} -{% if correlation_rule.notable is defined %} -action.notable = 1 -{% endif %} -{% if correlation_rule.notable.nes_fields is defined %} -action.notable.param.nes_fields = {{ correlation_rule.notable.nes_fields }} -action.notable.param.rule_description = {{ correlation_rule.notable.rule_description }} -action.notable.param.rule_title = {{ correlation_rule.notable.rule_title }} -action.notable.param.security_domain = {{ detection.security_domain }} -action.notable.param.severity = {{ detection.confidence }} -{% endif %} -{% if (correlation_rule.notable.drilldown_name is defined) and (correlation_rule.notable.drilldown_search is defined) %} -action.notable.param.drilldown_name = {{ correlation_rule.notable.drilldown_name }} -action.notable.param.drilldown_search = {{ correlation_rule.notable.drilldown_search }} -{% endif %} -{% if correlation_rule.risk is defined %} -action.risk = 1 -action.risk.param._risk_object = {{ correlation_rule.risk.risk_object }} -action.risk.param._risk_object_type = {{ correlation_rule.risk.risk_object_type[0] }} -action.risk.param._risk_score = {{ correlation_rule.risk.risk_score }} -action.risk.param.verbose = 0 -{% endif %} -{% if correlation_rule.suppress is defined %} -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = {{ correlation_rule.suppress.suppress_fields }} -alert.suppress.period = {{ correlation_rule.suppress.suppress_period }} -{% endif %} -{% endif %} -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled = true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -schedule_window = auto -is_visible = false -{% if detection.detect.splunk is defined %} -search = {{ detection.detect.splunk.correlation_rule.search }} -{% elif detection.detect.uba is defined %} -search = {{ detection.detect.uba.correlation_rule.search }} -{% endif %} - -{% endfor %} -### END ESCU DETECTIONS ### - -### ESCU INVESTIGATIONS ### - -{% for investigation in investigations %} -{% if investigation.type != 'phantom' %} -[ESCU - {{ investigation.name }}] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - {{ investigation.name }} -description = {{ investigation.description }} -action.escu.creation_date = {{ investigation.creation_date }} -action.escu.modification_date = {{ investigation.modification_date }} -action.escu.analytic_story = {{ investigation.stories | tojson | replace("\\u0026","&") }} -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -{% if investigation.data_metadata.data_models is defined %} -action.escu.data_models = {{ investigation.data_metadata.data_models | tojson }} -{% endif %} -{% if investigation.data_metadata.providing_technologies is defined %} -action.escu.providing_technologies = {{ investigation.data_metadata.providing_technologies | tojson }} -{% endif %} -{% if investigation.eli5 is defined %} -action.escu.eli5 = {{ investigation.eli5 }} -{% else %} -action.escu.eli5 = none -{% endif %} -{% if investigation.how_to_implement is defined %} -action.escu.how_to_implement = {{ investigation.how_to_implement }} -{% else %} -action.escu.how_to_implement = none -{% endif %} -{% if investigation.known_false_positives is defined %} -action.escu.known_false_positives = {{ investigation.known_false_positives }} -{% else %} -action.escu.known_false_positives = None at this time -{% endif %} -{% if investigation.entities is defined %} -action.escu.fields_required = {{ investigation.entities | tojson }} -action.escu.entities = {{ investigation.entities | tojson }} -{% endif %} -disabled = true -schedule_window = auto -is_visible = false -search = {{ investigation.investigate.splunk.search }} - -{% endif %} -{% endfor %} - -### END ESCU INVESTIGATIONS ### - - -### ESCU BASELINES ### - -{% for baseline in baselines %} -[ESCU - {{ baseline.name }}] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - {{ baseline.name }} -description = {{ baseline.description }} -action.escu.creation_date = {{ baseline.creation_date }} -action.escu.modification_date = {{ baseline.modification_date }} -action.escu.analytic_story = {{ baseline.stories | tojson | replace("\\u0026","&") }} -{% if baseline.data_metadata.data_models is defined %} -action.escu.data_models = {{ baseline.data_metadata.data_models | tojson }} -{% endif %} -{% if baseline.baseline.splunk.schedule.earliest_time is defined %} -dispatch.earliest_time = {{ baseline.baseline.splunk.schedule.earliest_time }} -{% endif %} -{% if baseline.baseline.splunk.schedule.latest_time is defined %} -dispatch.latest_time = {{ baseline.baseline.splunk.schedule.latest_time }} -{% endif %} -{% if baseline.data_metadata.providing_technologies is defined %} -action.escu.providing_technologies = {{ baseline.data_metadata.providing_technologies | tojson }} -{% endif %} -{% if baseline.eli5 is defined %} -action.escu.eli5 = {{ baseline.eli5 }} -{% else %} -action.escu.eli5 = none -{% endif %} -{% if baseline.how_to_implement is defined %} -action.escu.how_to_implement = {{ baseline.how_to_implement }} -{% else %} -action.escu.how_to_implement = none -{% endif %} -{% if baseline.known_false_positives is defined %} -action.escu.known_false_positives = {{ baseline.known_false_positives }} -{% else %} -action.escu.known_false_positives = None at this time -{% endif %} -{% if baseline.entities is defined %} -action.escu.fields_required = {{ baseline.entities | tojson }} -action.escu.entities = {{ baseline.entities | tojson }} -{% endif %} -disabled = true -schedule_window = auto -is_visible = false -search = {{ baseline.baseline.splunk.search }} - -{% endfor %} - -### USAGE DASHBOARD CONFIGURATIONS ### - -[escu-metrics-usage] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -dispatchAs = user -search = index=_audit sourcetype="audittrail" \ -"ESCU - "\ -`comment("Find all the search names in the audittrail.")`\ -| stats count(search) by search savedsearch_name user\ -| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ -`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ -| rex field=search "\"(?.*)\""\ -`comment("Extract the name of the search from the search string")`\ -| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* - -[escu-metrics-search] -action.email.useNSSubject = 1 -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -enableSched = 1 -cron_schedule = 0 0 * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = index=_audit action=search | transaction search_id maxspan=3m | search ESCU | stats sum(total_run_time) avg(total_run_time) max(total_run_time) sum(result_count) - -[escu-metrics-search-events] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -cron_schedule = 0 0 * * * -enableSched = 1 -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = [search index=_audit sourcetype="audittrail" \"ESCU NOT "index=_audit" | where search !="" | dedup search_id | rex field=search "\"(?.*)\"" | rex field=_raw "user=(?[a-zA-Z0-9_\-]+)" | eval usage=if(savedsearch_name!="", "scheduled", "adhoc") | eval savedsearch_name=if(savedsearch_name != "", savedsearch_name, search_name) | table savedsearch_name search_id user _time usage | outputlookup escu_search_id.csv | table search_id] index=_audit total_run_time event_count result_count NOT "index=_audit" | lookup escu_search_id.csv search_id | stats count(savedsearch_name) AS search_count avg(total_run_time) AS search_avg_run_time sum(total_run_time) AS search_total_run_time sum(result_count) AS search_total_results earliest(_time) AS firsts latest(_time) AS lasts by savedsearch_name user usage| eval first_run=strftime(firsts, "%B %d %Y") | eval last_run=strftime(lasts, "%B %d %Y") - -[escu-metrics-search-longest-runtime] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -enableSched = 1 -cron_schedule = 0 0 * * * -disabled = 1 -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -search = index=_* ESCU [search index=_* action=search latest=-2h earliest=-1d| transaction search_id maxspan=3m | search ESCU | stats values(total_run_time) AS run by search_id | sort -run | head 1| table search_id] | table search search_id - -[escu-metrics-usage-search] -action.email.useNSSubject = 1 -alert.digest_mode = True -alert.suppress = 0 -alert.track = 0 -auto_summarize.dispatch.earliest_time = -1d@h -cron_schedule = 0 0 * * * -dispatch.earliest_time = -4h@h -dispatch.latest_time = -1h@h -enableSched = 1 -dispatchAs = user -search = index=_audit sourcetype="audittrail" \ -"ESCU - "\ -`comment("Find all the search names in the audittrail. Ignore the last few minutes so we can exclude this search's text from the result.")`\ -| stats count(search) by search savedsearch_name user\ -| eval usage=(if(savedsearch_name=="","Adhoc","Scheduled")) \ -`comment("If the savedsearch_name field in the audittrail is empty, the search was run adhoc. Otherwise it was run as a scheduled search")`\ -| rex field=search "\"(?.*)\""\ -`comment("Extract the name of the search from the search string")`\ -| table savedsearch_name count(search) usage user | join savedsearch_name max=0 type=left [search sourcetype="manifests" | spath searches{} | mvexpand searches{} | spath input=searches{} | table category search_name | rename search_name as savedsearch_name | dedup savedsearch_name] | search category=* - -### END OF USAGE DASHBOARD CONFIGURATIONS ### diff --git a/detections/abnormally_high_aws_instances_launched_by_user.yml b/detections/abnormally_high_aws_instances_launched_by_user.yml index f05085196d..c53af3d951 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user.yml @@ -24,8 +24,8 @@ known_false_positives: Many service accounts configured within an AWS infrastruc human user. tags: analytics_story: - - Suspicious AWS EC2 Activities - AWS Cryptomining + - Suspicious AWS EC2 Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml index fd95841b2b..96e9e04f15 100644 --- a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml +++ b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml @@ -24,8 +24,8 @@ known_false_positives: Administrators may attempt to change the default executio be reviewed and investigated as appropriate. tags: analytics_story: - - Credential Dumping - Malicious PowerShell + - Credential Dumping mitre_attack_id: - T1086 - T1064 diff --git a/detections/clients_connecting_to_multiple_dns_servers.yml b/detections/clients_connecting_to_multiple_dns_servers.yml index 31ec5b76f6..1a235eee7a 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.yml +++ b/detections/clients_connecting_to_multiple_dns_servers.yml @@ -27,10 +27,10 @@ known_false_positives: It's possible that an enterprise has more than five DNS s that are configured in a round-robin rotation. Please customize the search, as appropriate. tags: analytics_story: - - DNS Hijacking - - Command and Control - Suspicious DNS Traffic - Host Redirection + - Command and Control + - DNS Hijacking mitre_attack_id: - T1048 kill_chain_phases: diff --git a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index 6482e1c848..8c019c3996 100644 --- a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -44,11 +44,11 @@ known_false_positives: Some users and applications may leverage Dynamic DNS to r however this activity must be verified. tags: analytics_story: - - Prohibited Traffic Allowed or Protocol Mismatch - - Command and Control - Data Protection - - Dynamic DNS + - Command and Control - Suspicious DNS Traffic + - Prohibited Traffic Allowed or Protocol Mismatch + - Dynamic DNS - DNS Hijacking kill_chain_phases: - Command and Control diff --git a/detections/detect_outbound_smb_traffic.yml b/detections/detect_outbound_smb_traffic.yml index 598402bc4e..9ba0edee7f 100644 --- a/detections/detect_outbound_smb_traffic.yml +++ b/detections/detect_outbound_smb_traffic.yml @@ -35,8 +35,8 @@ known_false_positives: It is likely that the outbound Server Message Block (SMB) of all SMB versions and related protocols at the network boundary. tags: analytics_story: - - DHS Report TA18-074A - Hidden Cobra Malware + - DHS Report TA18-074A mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/detect_prohibited_applications_spawning_cmd_exe.yml b/detections/detect_prohibited_applications_spawning_cmd_exe.yml index 94a4c9cb39..81ed57b5b4 100644 --- a/detections/detect_prohibited_applications_spawning_cmd_exe.yml +++ b/detections/detect_prohibited_applications_spawning_cmd_exe.yml @@ -22,8 +22,8 @@ known_false_positives: There are circumstances where an application may legitima the lookup file, as appropriate. tags: analytics_story: - - Suspicious Command-Line Executions - Suspicious MSHTA Activity + - Suspicious Command-Line Executions mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detect_rare_executables.yml b/detections/detect_rare_executables.yml index a33667b6b5..f0aa957cab 100644 --- a/detections/detect_rare_executables.yml +++ b/detections/detect_rare_executables.yml @@ -28,8 +28,8 @@ known_false_positives: Some legitimate processes may be only rarely executed in to filter them out of your search results. tags: analytics_story: - - 'Emotet Malware DHS Report TA18-201A ' - Unusual Processes + - 'Emotet Malware DHS Report TA18-201A ' kill_chain_phases: - Installation - Command and Control diff --git a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml index 37fac4086e..d261e24136 100644 --- a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml @@ -22,8 +22,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: Some legitimate applications may exhibit this behavior. tags: analytics_story: - - Suspicious Command-Line Executions - 'Emotet Malware DHS Report TA18-201A ' + - Suspicious Command-Line Executions mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml index 2027a04314..df198f832a 100644 --- a/detections/detection_of_dns_tunnels.yml +++ b/detections/detection_of_dns_tunnels.yml @@ -39,9 +39,9 @@ known_false_positives: It's possible that normal DNS traffic will exhibit this b can also be modified to better suit your environment. tags: analytics_story: - - Data Protection - Suspicious DNS Traffic - Command and Control + - Data Protection mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml index 878a50c013..ecb9b0b969 100644 --- a/detections/disabling_remote_user_account_control.yml +++ b/detections/disabling_remote_user_account_control.yml @@ -21,8 +21,8 @@ known_false_positives: This registry key may be modified via administrators to i a change in system policy. This type of change should be a very rare occurrence. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Defense Evasion Tactics + - Suspicious Windows Registry Activities mitre_attack_id: - T1112 kill_chain_phases: diff --git a/detections/dns_query_length_outliers___mltk.yml b/detections/dns_query_length_outliers___mltk.yml index c06f64e7fe..f002a02944 100644 --- a/detections/dns_query_length_outliers___mltk.yml +++ b/detections/dns_query_length_outliers___mltk.yml @@ -47,8 +47,8 @@ known_false_positives: If you are seeing more results than desired, you may cons the support search to re-build the ML model on the latest data. tags: analytics_story: - - Hidden Cobra Malware - Suspicious DNS Traffic + - Hidden Cobra Malware - Command and Control mitre_attack_id: - T1043 diff --git a/detections/dns_query_length_with_high_standard_deviation.yml b/detections/dns_query_length_with_high_standard_deviation.yml index 1d658defc6..8054a26d51 100644 --- a/detections/dns_query_length_with_high_standard_deviation.yml +++ b/detections/dns_query_length_with_high_standard_deviation.yml @@ -18,8 +18,8 @@ search: '| tstats `security_content_summariesonly` count from datamodel=Network_ known_false_positives: It's possible there can be long domain names that are legitimate. tags: analytics_story: - - Hidden Cobra Malware - Suspicious DNS Traffic + - Hidden Cobra Malware - Command and Control mitre_attack_id: - T1043 diff --git a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml index 5f6597a45d..1e0e8c9f1e 100644 --- a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml +++ b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml @@ -18,10 +18,10 @@ known_false_positives: Legitimate DNS activity can be detected in this search. I verify and update the list of authorized DNS servers as appropriate. tags: analytics_story: - - DNS Hijacking - - Command and Control - Suspicious DNS Traffic - Host Redirection + - Command and Control + - DNS Hijacking kill_chain_phases: - Command and Control cis20: diff --git a/detections/ec2_instance_started_in_previously_unseen_region.yml b/detections/ec2_instance_started_in_previously_unseen_region.yml index eef9f3f3aa..ab52ff8feb 100644 --- a/detections/ec2_instance_started_in_previously_unseen_region.yml +++ b/detections/ec2_instance_started_in_previously_unseen_region.yml @@ -23,8 +23,8 @@ known_false_positives: It's possible that a user has unknowingly started an inst in a new region. Please verify that this activity is legitimate. tags: analytics_story: - - Suspicious AWS EC2 Activities - AWS Cryptomining + - Suspicious AWS EC2 Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/ec2_instance_started_with_previously_unseen_user.yml b/detections/ec2_instance_started_with_previously_unseen_user.yml index 9b4d4bb4a8..2eb9eec2d6 100644 --- a/detections/ec2_instance_started_with_previously_unseen_user.yml +++ b/detections/ec2_instance_started_with_previously_unseen_user.yml @@ -25,8 +25,8 @@ known_false_positives: It's possible that a user will start to create EC2 instan launching instances that this is the intended behavior. tags: analytics_story: - - Suspicious AWS EC2 Activities - AWS Cryptomining + - Suspicious AWS EC2 Activities cis20: - CIS 1 nist: diff --git a/detections/first_time_seen_command_line_argument.yml b/detections/first_time_seen_command_line_argument.yml index 2d852d46bc..c6e8de58d3 100644 --- a/detections/first_time_seen_command_line_argument.yml +++ b/detections/first_time_seen_command_line_argument.yml @@ -34,10 +34,10 @@ known_false_positives: Legitimate programs can also use command-line arguments t macro to exclude legitimate parent_process_name tags: analytics_story: - - Suspicious Command-Line Executions - - Hidden Cobra Malware - - Orangeworm Attack Group - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Orangeworm Attack Group + - Hidden Cobra Malware + - Suspicious Command-Line Executions - DHS Report TA18-074A mitre_attack_id: - T1064 diff --git a/detections/hiding_files_and_directories_with_attrib_exe.yml b/detections/hiding_files_and_directories_with_attrib_exe.yml index 355b7e2e7b..e09f0689af 100644 --- a/detections/hiding_files_and_directories_with_attrib_exe.yml +++ b/detections/hiding_files_and_directories_with_attrib_exe.yml @@ -23,8 +23,8 @@ known_false_positives: 'Some applications and users may legitimately use attrib. to interact with the files. ' tags: analytics_story: - - Windows Defense Evasion Tactics - Windows Persistence Techniques + - Windows Defense Evasion Tactics kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml index 7889964dfc..aa409d05fa 100644 --- a/detections/monitor_email_for_brand_abuse.yml +++ b/detections/monitor_email_for_brand_abuse.yml @@ -21,8 +21,8 @@ search: '| tstats `security_content_summariesonly` values(All_Email.recipient) a known_false_positives: None at this time tags: analytics_story: - - Suspicious Emails - Brand Monitoring + - Suspicious Emails kill_chain_phases: - Delivery cis20: diff --git a/detections/monitor_registry_keys_for_print_monitors.yml b/detections/monitor_registry_keys_for_print_monitors.yml index dad8911dab..50d7ec4353 100644 --- a/detections/monitor_registry_keys_for_print_monitors.yml +++ b/detections/monitor_registry_keys_for_print_monitors.yml @@ -25,8 +25,8 @@ known_false_positives: You will encounter noise from legitimate print-monitor re entries. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Persistence Techniques + - Suspicious Windows Registry Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/processes_launching_netsh.yml b/detections/processes_launching_netsh.yml index 2389e2b249..be9a4d8d2d 100644 --- a/detections/processes_launching_netsh.yml +++ b/detections/processes_launching_netsh.yml @@ -23,9 +23,9 @@ known_false_positives: Some VPN applications are known to launch netsh.exe. Outs commands. tags: analytics_story: - - DHS Report TA18-074A - - Netsh Abuse - Disabling Security Tools + - Netsh Abuse + - DHS Report TA18-074A mitre_attack_id: - T1059 - T1089 diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index 3ad55dfe4e..b402bc90bb 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -24,9 +24,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - SamSam Ransomware - Monitor for Unauthorized Software - 'Emotet Malware DHS Report TA18-201A ' + - SamSam Ransomware kill_chain_phases: - Installation - Command and Control diff --git a/detections/reg_exe_manipulating_windows_services_registry_keys.yml b/detections/reg_exe_manipulating_windows_services_registry_keys.yml index 7c0e571f7e..23ce39e78b 100644 --- a/detections/reg_exe_manipulating_windows_services_registry_keys.yml +++ b/detections/reg_exe_manipulating_windows_services_registry_keys.yml @@ -25,8 +25,8 @@ known_false_positives: It is unusual for a service to be created or modified by It is important to validate and investigate, as appropriate. tags: analytics_story: - - Windows Service Abuse - Windows Persistence Techniques + - Windows Service Abuse mitre_attack_id: - T1050 - T1031 diff --git a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml index ffe1f5b930..0b1586e167 100644 --- a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml +++ b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as known_false_positives: None at the moment tags: analytics_story: - - Suspicious Windows Registry Activities - - Windows Defense Evasion Tactics - Windows Persistence Techniques + - Windows Defense Evasion Tactics + - Suspicious Windows Registry Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/registry_keys_for_creating_shim_databases.yml b/detections/registry_keys_for_creating_shim_databases.yml index 62cf67b895..7c31448d8f 100644 --- a/detections/registry_keys_for_creating_shim_databases.yml +++ b/detections/registry_keys_for_creating_shim_databases.yml @@ -21,8 +21,8 @@ known_false_positives: There are many legitimate applications that leverage shim for compatibility purposes for legacy applications tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Persistence Techniques + - Suspicious Windows Registry Activities mitre_attack_id: - T1138 kill_chain_phases: diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml index 151f418418..331eed4523 100644 --- a/detections/registry_keys_used_for_persistence.yml +++ b/detections/registry_keys_used_for_persistence.yml @@ -27,12 +27,12 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Suspicious Windows Registry Activities - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - DHS Report TA18-074A - - Suspicious MSHTA Activity - Windows Persistence Techniques + - Suspicious Windows Registry Activities + - Suspicious MSHTA Activity + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - 'Emotet Malware DHS Report TA18-201A ' + - DHS Report TA18-074A - Ransomware mitre_attack_id: - T1103 diff --git a/detections/registry_keys_used_for_privilege_escalation.yml b/detections/registry_keys_used_for_privilege_escalation.yml index 9b942e63ca..c7f4ce6e95 100644 --- a/detections/registry_keys_used_for_privilege_escalation.yml +++ b/detections/registry_keys_used_for_privilege_escalation.yml @@ -26,8 +26,8 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Privilege Escalation + - Suspicious Windows Registry Activities mitre_attack_id: - T1015 kill_chain_phases: diff --git a/detections/remote_desktop_network_traffic.yml b/detections/remote_desktop_network_traffic.yml index 5e51ba07fc..af04aa5317 100644 --- a/detections/remote_desktop_network_traffic.yml +++ b/detections/remote_desktop_network_traffic.yml @@ -27,9 +27,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Remote Desktop may be used legitimately by users on the network. tags: analytics_story: + - Lateral Movement - Hidden Cobra Malware - SamSam Ransomware - - Lateral Movement mitre_attack_id: - T1076 kill_chain_phases: diff --git a/detections/remote_desktop_process_running_on_system.yml b/detections/remote_desktop_process_running_on_system.yml index 180761501a..87c7ede512 100644 --- a/detections/remote_desktop_process_running_on_system.yml +++ b/detections/remote_desktop_process_running_on_system.yml @@ -25,8 +25,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Remote Desktop may be used legitimately by users on the network. tags: analytics_story: - - Hidden Cobra Malware - Lateral Movement + - Hidden Cobra Malware mitre_attack_id: - T1076 kill_chain_phases: diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml index 5617b11ce0..024ca7adcc 100644 --- a/detections/remote_registry_key_modifications.yml +++ b/detections/remote_registry_key_modifications.yml @@ -20,9 +20,9 @@ known_false_positives: This technique may be legitimately used by administrators modify remote registries, so it's important to filter these events out. tags: analytics_story: - - Suspicious Windows Registry Activities - - Windows Defense Evasion Tactics - Windows Persistence Techniques + - Windows Defense Evasion Tactics + - Suspicious Windows Registry Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/sc_exe_manipulating_windows_services.yml b/detections/sc_exe_manipulating_windows_services.yml index 907ed5dce3..09d3459007 100644 --- a/detections/sc_exe_manipulating_windows_services.yml +++ b/detections/sc_exe_manipulating_windows_services.yml @@ -23,11 +23,11 @@ known_false_positives: Using sc.exe to manipulate Windows services is uncommon. and investigate as appropriate. tags: analytics_story: + - Windows Persistence Techniques + - Disabling Security Tools - Windows Service Abuse - Orangeworm Attack Group - DHS Report TA18-074A - - Windows Persistence Techniques - - Disabling Security Tools mitre_attack_id: - T1050 - T1031 diff --git a/detections/smb_traffic_spike.yml b/detections/smb_traffic_spike.yml index eca96d7fa9..74c9f2ea94 100644 --- a/detections/smb_traffic_spike.yml +++ b/detections/smb_traffic_spike.yml @@ -21,10 +21,10 @@ known_false_positives: A file server may experience high-demand loads that could this analytic to trigger. tags: analytics_story: - - DHS Report TA18-074A - Hidden Cobra Malware - - Ransomware + - DHS Report TA18-074A - 'Emotet Malware DHS Report TA18-201A ' + - Ransomware mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/smb_traffic_spike___mltk.yml b/detections/smb_traffic_spike___mltk.yml index ab30cefe0d..16263f5d44 100644 --- a/detections/smb_traffic_spike___mltk.yml +++ b/detections/smb_traffic_spike___mltk.yml @@ -42,10 +42,10 @@ known_false_positives: If you are seeing more results than desired, you may cons the `smb_traffic_spike_mltk_filter` macro to filter out false positive results tags: analytics_story: - - DHS Report TA18-074A - Hidden Cobra Malware - - Ransomware + - DHS Report TA18-074A - 'Emotet Malware DHS Report TA18-201A ' + - Ransomware mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/suspicious_changes_to_file_associations.yml b/detections/suspicious_changes_to_file_associations.yml index 83b40ca76d..767b9f7337 100644 --- a/detections/suspicious_changes_to_file_associations.yml +++ b/detections/suspicious_changes_to_file_associations.yml @@ -26,8 +26,8 @@ known_false_positives: There may be other processes in your environment that use finding false positives, you can modify the search to add those processes as exceptions. tags: analytics_story: - - Windows File Extension and Association Abuse - Suspicious Windows Registry Activities + - Windows File Extension and Association Abuse mitre_attack_id: - T1042 kill_chain_phases: diff --git a/detections/suspicious_reg_exe_process.yml b/detections/suspicious_reg_exe_process.yml index f5eb5eba62..612efe3513 100644 --- a/detections/suspicious_reg_exe_process.yml +++ b/detections/suspicious_reg_exe_process.yml @@ -29,9 +29,9 @@ known_false_positives: It's possible for system administrators to write scripts to filter them out. tags: analytics_story: + - Disabling Security Tools - DHS Report TA18-074A - Windows Defense Evasion Tactics - - Disabling Security Tools mitre_attack_id: - T1112 - T1089 diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index 4e7d43fa11..5c789b8407 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -20,9 +20,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Suspicious Command-Line Executions - - Ransomware - Unusual Processes + - Ransomware + - Suspicious Command-Line Executions mitre_attack_id: - T1036 kill_chain_phases: diff --git a/detections/uncommon_processes_on_endpoint.yml b/detections/uncommon_processes_on_endpoint.yml index 39cba734a0..226ddf7b25 100644 --- a/detections/uncommon_processes_on_endpoint.yml +++ b/detections/uncommon_processes_on_endpoint.yml @@ -22,8 +22,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Windows Privilege Escalation - Unusual Processes + - Windows Privilege Escalation mitre_attack_id: - T1015 kill_chain_phases: diff --git a/detections/unusually_long_command_line.yml b/detections/unusually_long_command_line.yml index ff41daf222..69c4ccc933 100644 --- a/detections/unusually_long_command_line.yml +++ b/detections/unusually_long_command_line.yml @@ -22,10 +22,10 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Some legitimate applications start with long command lines. tags: analytics_story: - - Suspicious Command-Line Executions + - Unusual Processes - Ransomware - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Unusual Processes + - Suspicious Command-Line Executions kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml index 2dee1c2e0d..4cfd8e5467 100644 --- a/detections/unusually_long_command_line___mltk.yml +++ b/detections/unusually_long_command_line___mltk.yml @@ -35,10 +35,10 @@ known_false_positives: Some legitimate applications use long command lines for i build the associated model. tags: analytics_story: - - Suspicious Command-Line Executions + - Unusual Processes - Ransomware - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Unusual Processes + - Suspicious Command-Line Executions kill_chain_phases: - Actions on Objectives cis20: diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 539460661d..84707a82c8 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T15:39:38 UTC +# On Date: 2020-05-12T11:51:02 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] +investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] +investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] +investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -511,10 +511,10 @@ creation_date = 2020-02-04 modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 -reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] +investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/data/ui/panels/all_backup_logs_for_host.xml b/package/default/data/ui/panels/all_backup_logs_for_host.xml new file mode 100644 index 0000000000..1ff29ae929 --- /dev/null +++ b/package/default/data/ui/panels/all_backup_logs_for_host.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype="netbackup_logs" dest=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml b/package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml new file mode 100644 index 0000000000..e09827e48a --- /dev/null +++ b/package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml @@ -0,0 +1,9 @@ + + + + sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}=$src_ip$|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml b/package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml new file mode 100644 index 0000000000..10bb4cee2d --- /dev/null +++ b/package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail userIdentity.accessKeyId=$accessKeyId$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml b/package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml new file mode 100644 index 0000000000..fec847550b --- /dev/null +++ b/package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail userIdentity.arn=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml b/package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml new file mode 100644 index 0000000000..ff7ad317cd --- /dev/null +++ b/package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail userIdentity.arn=$src_user$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_network_acl_details_from_id.xml b/package/default/data/ui/panels/aws_network_acl_details_from_id.xml new file mode 100644 index 0000000000..e637d48978 --- /dev/null +++ b/package/default/data/ui/panels/aws_network_acl_details_from_id.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:description id=$networkAclId$ | table id account_id vpc_id network_acl_entries{}.* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml b/package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml new file mode 100644 index 0000000000..804d19a1d0 --- /dev/null +++ b/package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:config resourceId=$resourceId$ | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml b/package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml new file mode 100644 index 0000000000..22732ef048 --- /dev/null +++ b/package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:config resourceId=$bucketName$ | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml b/package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml new file mode 100644 index 0000000000..568cd26380 --- /dev/null +++ b/package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml @@ -0,0 +1,9 @@ + + + + sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_city.xml b/package/default/data/ui/panels/get_all_aws_activity_from_city.xml new file mode 100644 index 0000000000..000cfe9942 --- /dev/null +++ b/package/default/data/ui/panels/get_all_aws_activity_from_city.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City=$City$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_country.xml b/package/default/data/ui/panels/get_all_aws_activity_from_country.xml new file mode 100644 index 0000000000..9830b3459d --- /dev/null +++ b/package/default/data/ui/panels/get_all_aws_activity_from_country.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country=$Country$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml b/package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml new file mode 100644 index 0000000000..008d268420 --- /dev/null +++ b/package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress=$src_ip$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_region.xml b/package/default/data/ui/panels/get_all_aws_activity_from_region.xml new file mode 100644 index 0000000000..4a7a1cdb76 --- /dev/null +++ b/package/default/data/ui/panels/get_all_aws_activity_from_region.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region=$Region$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml b/package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml new file mode 100644 index 0000000000..46d2d923ff --- /dev/null +++ b/package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | tstats count from datamodel=Authentication where Authentication.dest=$dest$ by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_backup_logs_for_endpoint.xml b/package/default/data/ui/panels/get_backup_logs_for_endpoint.xml new file mode 100644 index 0000000000..afdbeba57d --- /dev/null +++ b/package/default/data/ui/panels/get_backup_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype="netbackup_logs" COMPUTERNAME=$dest$ | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml b/package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml new file mode 100644 index 0000000000..2b6d49308a --- /dev/null +++ b/package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml @@ -0,0 +1,9 @@ + + + + | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*$domain$ by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_dns_server_history_for_a_host.xml b/package/default/data/ui/panels/get_dns_server_history_for_a_host.xml new file mode 100644 index 0000000000..1039a71369 --- /dev/null +++ b/package/default/data/ui/panels/get_dns_server_history_for_a_host.xml @@ -0,0 +1,9 @@ + + + + | search tag=dns src_ip=$src_ip$ dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_dns_traffic_ratio.xml b/package/default/data/ui/panels/get_dns_traffic_ratio.xml new file mode 100644 index 0000000000..dc42dd8e39 --- /dev/null +++ b/package/default/data/ui/panels/get_dns_traffic_ratio.xml @@ -0,0 +1,9 @@ + + + + | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src=$src_ip$ All_Traffic.dest=$dest_ip$ | eval ratio = (bytes_out/bytes_in) | table ratio + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml b/package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml new file mode 100644 index 0000000000..7dbc21d376 --- /dev/null +++ b/package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id=$instanceId$ | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_ec2_launch_details.xml b/package/default/data/ui/panels/get_ec2_launch_details.xml new file mode 100644 index 0000000000..e7f2a45294 --- /dev/null +++ b/package/default/data/ui/panels/get_ec2_launch_details.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId=$dest$ |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_email_info.xml b/package/default/data/ui/panels/get_email_info.xml new file mode 100644 index 0000000000..6afb5067bf --- /dev/null +++ b/package/default/data/ui/panels/get_email_info.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Email.All_Email | search message_id=$message_id$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_emails_from_specific_sender.xml b/package/default/data/ui/panels/get_emails_from_specific_sender.xml new file mode 100644 index 0000000000..21a977f746 --- /dev/null +++ b/package/default/data/ui/panels/get_emails_from_specific_sender.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Email.All_Email | search src_user=$src_user$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml b/package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml new file mode 100644 index 0000000000..e92d6d3f65 --- /dev/null +++ b/package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= $src_mac$ by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_history_of_email_sources.xml b/package/default/data/ui/panels/get_history_of_email_sources.xml new file mode 100644 index 0000000000..8d26ae3247 --- /dev/null +++ b/package/default/data/ui/panels/get_history_of_email_sources.xml @@ -0,0 +1,9 @@ + + + + |tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml b/package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml new file mode 100644 index 0000000000..a3068ae9c1 --- /dev/null +++ b/package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest=$dest$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml b/package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml new file mode 100644 index 0000000000..3c8c81230b --- /dev/null +++ b/package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml @@ -0,0 +1,9 @@ + + + + | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user=$user$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_notable_history.xml b/package/default/data/ui/panels/get_notable_history.xml new file mode 100644 index 0000000000..f4e93f2338 --- /dev/null +++ b/package/default/data/ui/panels/get_notable_history.xml @@ -0,0 +1,9 @@ + + + + | search `notable` | search dest=$dest$ | table _time, rule_name, owner, priority, severity, status_description + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_notable_info.xml b/package/default/data/ui/panels/get_notable_info.xml new file mode 100644 index 0000000000..141520df51 --- /dev/null +++ b/package/default/data/ui/panels/get_notable_info.xml @@ -0,0 +1,9 @@ + + + + | search `notable_by_id($event_id$)` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml b/package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml new file mode 100644 index 0000000000..d67b828a9b --- /dev/null +++ b/package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_parent_process_info.xml b/package/default/data/ui/panels/get_parent_process_info.xml new file mode 100644 index 0000000000..09eba16eb6 --- /dev/null +++ b/package/default/data/ui/panels/get_parent_process_info.xml @@ -0,0 +1,9 @@ + + + + | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = $process_name$ Processes.dest = $dest$ by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_file_activity.xml b/package/default/data/ui/panels/get_process_file_activity.xml new file mode 100644 index 0000000000..28f5412de6 --- /dev/null +++ b/package/default/data/ui/panels/get_process_file_activity.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest=$dest$ Filesystem.process_id=$process_id$ by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_info.xml b/package/default/data/ui/panels/get_process_info.xml new file mode 100644 index 0000000000..20d3333796 --- /dev/null +++ b/package/default/data/ui/panels/get_process_info.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest=$dest$ Proceses.process_name=$process_name$ by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_information_for_port_activity.xml b/package/default/data/ui/panels/get_process_information_for_port_activity.xml new file mode 100644 index 0000000000..9898b46006 --- /dev/null +++ b/package/default/data/ui/panels/get_process_information_for_port_activity.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=$dest_port$ by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_registry_activity.xml b/package/default/data/ui/panels/get_process_registry_activity.xml new file mode 100644 index 0000000000..e33c11f498 --- /dev/null +++ b/package/default/data/ui/panels/get_process_registry_activity.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id=$process_id$ AND Registry.dest=$dest$ by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml b/package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml new file mode 100644 index 0000000000..318ae20b38 --- /dev/null +++ b/package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_registry_activities.xml b/package/default/data/ui/panels/get_registry_activities.xml new file mode 100644 index 0000000000..73bb5bee45 --- /dev/null +++ b/package/default/data/ui/panels/get_registry_activities.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "$dest$" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml b/package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml new file mode 100644 index 0000000000..f9e4e70b8a --- /dev/null +++ b/package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object=$dest$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_risk_modifiers_for_user.xml b/package/default/data/ui/panels/get_risk_modifiers_for_user.xml new file mode 100644 index 0000000000..4dcf2fd577 --- /dev/null +++ b/package/default/data/ui/panels/get_risk_modifiers_for_user.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object=$user$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml b/package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml new file mode 100644 index 0000000000..b4642ac7a7 --- /dev/null +++ b/package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml @@ -0,0 +1,9 @@ + + + + sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host=$dest$ | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_update_logs_for_endpoint.xml b/package/default/data/ui/panels/get_update_logs_for_endpoint.xml new file mode 100644 index 0000000000..eb3ee6c657 --- /dev/null +++ b/package/default/data/ui/panels/get_update_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_user_information_from_identity_table.xml b/package/default/data/ui/panels/get_user_information_from_identity_table.xml new file mode 100644 index 0000000000..9269961083 --- /dev/null +++ b/package/default/data/ui/panels/get_user_information_from_identity_table.xml @@ -0,0 +1,9 @@ + + + + | `identities` | search identity=$user$ | table _time, identity, first, last, email, category, watchlist + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml b/package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml new file mode 100644 index 0000000000..30b224262c --- /dev/null +++ b/package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Vulnerabilities.Vulnerabilities | search dest=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/get_web_session_information_via_session_id.xml b/package/default/data/ui/panels/get_web_session_information_via_session_id.xml new file mode 100644 index 0000000000..1be6d5c2c1 --- /dev/null +++ b/package/default/data/ui/panels/get_web_session_information_via_session_id.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=stream:http $session_id$ | stats values(url) values(http_user_agent) by src_ip status + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml b/package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml new file mode 100644 index 0000000000..669b2a7e63 --- /dev/null +++ b/package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail awsRegion=$awsRegion$| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml b/package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml new file mode 100644 index 0000000000..30e3630ed5 --- /dev/null +++ b/package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml @@ -0,0 +1,9 @@ + + + + |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1 + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml b/package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml new file mode 100644 index 0000000000..a4b65f0856 --- /dev/null +++ b/package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail user=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml b/package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml new file mode 100644 index 0000000000..5a042540fc --- /dev/null +++ b/package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Cloud_Infrastructure.Compute | search dest=$dest$ | fields - _* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml b/package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml new file mode 100644 index 0000000000..eaacf46c7b --- /dev/null +++ b/package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml @@ -0,0 +1,9 @@ + + + + | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml b/package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml new file mode 100644 index 0000000000..448e215f7d --- /dev/null +++ b/package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Network_Traffic.All_Traffic | search src_ip=$src_ip$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_okta_activity_by_app.xml b/package/default/data/ui/panels/investigate_okta_activity_by_app.xml new file mode 100644 index 0000000000..b7e6637221 --- /dev/null +++ b/package/default/data/ui/panels/investigate_okta_activity_by_app.xml @@ -0,0 +1,9 @@ + + + + eventtype=okta_log app=$app$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml b/package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml new file mode 100644 index 0000000000..f702ab0a9b --- /dev/null +++ b/package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml @@ -0,0 +1,9 @@ + + + + eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml b/package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml new file mode 100644 index 0000000000..b06e6c71c1 --- /dev/null +++ b/package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml @@ -0,0 +1,9 @@ + + + + `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml new file mode 100644 index 0000000000..02d2dff20d --- /dev/null +++ b/package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml @@ -0,0 +1,9 @@ + + + + `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_previous_unseen_user.xml b/package/default/data/ui/panels/investigate_previous_unseen_user.xml new file mode 100644 index 0000000000..ab5940c8fe --- /dev/null +++ b/package/default/data/ui/panels/investigate_previous_unseen_user.xml @@ -0,0 +1,9 @@ + + + + | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml b/package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml new file mode 100644 index 0000000000..fc1ff90dda --- /dev/null +++ b/package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| table firstTime lastTime src src_nt_domain dest user app count | sort count + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml b/package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml new file mode 100644 index 0000000000..bb306f81a8 --- /dev/null +++ b/package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=stream:http src_ip="$src_ip$" dest_ip="$dest_ip$" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml b/package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml new file mode 100644 index 0000000000..78154b2139 --- /dev/null +++ b/package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Cloud_Infrastructure.Compute | search user=$src_user$ | fields - _* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_user_activities_in_okta.xml b/package/default/data/ui/panels/investigate_user_activities_in_okta.xml new file mode 100644 index 0000000000..0adc7b4f9c --- /dev/null +++ b/package/default/data/ui/panels/investigate_user_activities_in_okta.xml @@ -0,0 +1,9 @@ + + + + eventtype=okta_log user=$user$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml b/package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml new file mode 100644 index 0000000000..1aa8d0f2a3 --- /dev/null +++ b/package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Cloud_Infrastructure.Compute | search region=$region$ user=$src_user$ | fields - _* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_web_activity_from_host.xml b/package/default/data/ui/panels/investigate_web_activity_from_host.xml new file mode 100644 index 0000000000..0c8c4e596d --- /dev/null +++ b/package/default/data/ui/panels/investigate_web_activity_from_host.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Web.Web | search src=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml b/package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml new file mode 100644 index 0000000000..612d227d1b --- /dev/null +++ b/package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Web.Web | search src=$src_ip$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_web_posts_from_src.xml b/package/default/data/ui/panels/investigate_web_posts_from_src.xml new file mode 100644 index 0000000000..43d10b1103 --- /dev/null +++ b/package/default/data/ui/panels/investigate_web_posts_from_src.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "$src$") and like(http_method, "POST") + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/process_chain_analysis.xml b/package/default/data/ui/panels/process_chain_analysis.xml new file mode 100644 index 0000000000..582373453a --- /dev/null +++ b/package/default/data/ui/panels/process_chain_analysis.xml @@ -0,0 +1,9 @@ + + + + `sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_all_backup_logs_for_host.xml b/package/default/data/ui/panels/workbench_panel_all_backup_logs_for_host.xml new file mode 100644 index 0000000000..1ff29ae929 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_all_backup_logs_for_host.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype="netbackup_logs" dest=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_amazon_eks_kubernetes_activity_by_src_ip.xml b/package/default/data/ui/panels/workbench_panel_amazon_eks_kubernetes_activity_by_src_ip.xml new file mode 100644 index 0000000000..e09827e48a --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_amazon_eks_kubernetes_activity_by_src_ip.xml @@ -0,0 +1,9 @@ + + + + sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}=$src_ip$|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_accesskeyid.xml b/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_accesskeyid.xml new file mode 100644 index 0000000000..10bb4cee2d --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_accesskeyid.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail userIdentity.accessKeyId=$accessKeyId$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_arn.xml b/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_arn.xml new file mode 100644 index 0000000000..fec847550b --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_arn.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail userIdentity.arn=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_source_user.xml b/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_source_user.xml new file mode 100644 index 0000000000..ff7ad317cd --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_aws_investigate_user_activities_by_source_user.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail userIdentity.arn=$src_user$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_aws_network_acl_details_from_id.xml b/package/default/data/ui/panels/workbench_panel_aws_network_acl_details_from_id.xml new file mode 100644 index 0000000000..e637d48978 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_aws_network_acl_details_from_id.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:description id=$networkAclId$ | table id account_id vpc_id network_acl_entries{}.* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_aws_network_interface_details_via_resourceid.xml b/package/default/data/ui/panels/workbench_panel_aws_network_interface_details_via_resourceid.xml new file mode 100644 index 0000000000..804d19a1d0 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_aws_network_interface_details_via_resourceid.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:config resourceId=$resourceId$ | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_aws_s3_bucket_details_via_bucketname.xml b/package/default/data/ui/panels/workbench_panel_aws_s3_bucket_details_via_bucketname.xml new file mode 100644 index 0000000000..22732ef048 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_aws_s3_bucket_details_via_bucketname.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:config resourceId=$bucketName$ | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_gcp_kubernetes_activity_by_src_ip.xml b/package/default/data/ui/panels/workbench_panel_gcp_kubernetes_activity_by_src_ip.xml new file mode 100644 index 0000000000..568cd26380 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_gcp_kubernetes_activity_by_src_ip.xml @@ -0,0 +1,9 @@ + + + + sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_city.xml b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_city.xml new file mode 100644 index 0000000000..000cfe9942 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_city.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City=$City$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_country.xml b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_country.xml new file mode 100644 index 0000000000..9830b3459d --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_country.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country=$Country$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_ip_address.xml b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_ip_address.xml new file mode 100644 index 0000000000..008d268420 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_ip_address.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress=$src_ip$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_region.xml b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_region.xml new file mode 100644 index 0000000000..4a7a1cdb76 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_all_aws_activity_from_region.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region=$Region$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_authentication_logs_for_endpoint.xml b/package/default/data/ui/panels/workbench_panel_get_authentication_logs_for_endpoint.xml new file mode 100644 index 0000000000..46d2d923ff --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_authentication_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | tstats count from datamodel=Authentication where Authentication.dest=$dest$ by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_backup_logs_for_endpoint.xml b/package/default/data/ui/panels/workbench_panel_get_backup_logs_for_endpoint.xml new file mode 100644 index 0000000000..afdbeba57d --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_backup_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype="netbackup_logs" COMPUTERNAME=$dest$ | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_certificate_logs_for_a_domain.xml b/package/default/data/ui/panels/workbench_panel_get_certificate_logs_for_a_domain.xml new file mode 100644 index 0000000000..2b6d49308a --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_certificate_logs_for_a_domain.xml @@ -0,0 +1,9 @@ + + + + | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*$domain$ by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_dns_server_history_for_a_host.xml b/package/default/data/ui/panels/workbench_panel_get_dns_server_history_for_a_host.xml new file mode 100644 index 0000000000..1039a71369 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_dns_server_history_for_a_host.xml @@ -0,0 +1,9 @@ + + + + | search tag=dns src_ip=$src_ip$ dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_dns_traffic_ratio.xml b/package/default/data/ui/panels/workbench_panel_get_dns_traffic_ratio.xml new file mode 100644 index 0000000000..dc42dd8e39 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_dns_traffic_ratio.xml @@ -0,0 +1,9 @@ + + + + | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src=$src_ip$ All_Traffic.dest=$dest_ip$ | eval ratio = (bytes_out/bytes_in) | table ratio + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_ec2_instance_details_by_instanceid.xml b/package/default/data/ui/panels/workbench_panel_get_ec2_instance_details_by_instanceid.xml new file mode 100644 index 0000000000..7dbc21d376 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_ec2_instance_details_by_instanceid.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id=$instanceId$ | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_ec2_launch_details.xml b/package/default/data/ui/panels/workbench_panel_get_ec2_launch_details.xml new file mode 100644 index 0000000000..e7f2a45294 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_ec2_launch_details.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId=$dest$ |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_email_info.xml b/package/default/data/ui/panels/workbench_panel_get_email_info.xml new file mode 100644 index 0000000000..6afb5067bf --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_email_info.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Email.All_Email | search message_id=$message_id$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_emails_from_specific_sender.xml b/package/default/data/ui/panels/workbench_panel_get_emails_from_specific_sender.xml new file mode 100644 index 0000000000..21a977f746 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_emails_from_specific_sender.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Email.All_Email | search src_user=$src_user$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address.xml b/package/default/data/ui/panels/workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address.xml new file mode 100644 index 0000000000..e92d6d3f65 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= $src_mac$ by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_history_of_email_sources.xml b/package/default/data/ui/panels/workbench_panel_get_history_of_email_sources.xml new file mode 100644 index 0000000000..8d26ae3247 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_history_of_email_sources.xml @@ -0,0 +1,9 @@ + + + + |tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_endpoint.xml b/package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_endpoint.xml new file mode 100644 index 0000000000..a3068ae9c1 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest=$dest$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_user.xml b/package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_user.xml new file mode 100644 index 0000000000..3c8c81230b --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_logon_rights_modifications_for_user.xml @@ -0,0 +1,9 @@ + + + + | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user=$user$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_notable_history.xml b/package/default/data/ui/panels/workbench_panel_get_notable_history.xml new file mode 100644 index 0000000000..f4e93f2338 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_notable_history.xml @@ -0,0 +1,9 @@ + + + + | search `notable` | search dest=$dest$ | table _time, rule_name, owner, priority, severity, status_description + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_notable_info.xml b/package/default/data/ui/panels/workbench_panel_get_notable_info.xml new file mode 100644 index 0000000000..141520df51 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_notable_info.xml @@ -0,0 +1,9 @@ + + + + | search `notable_by_id($event_id$)` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors.xml b/package/default/data/ui/panels/workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors.xml new file mode 100644 index 0000000000..d67b828a9b --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_parent_process_info.xml b/package/default/data/ui/panels/workbench_panel_get_parent_process_info.xml new file mode 100644 index 0000000000..09eba16eb6 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_parent_process_info.xml @@ -0,0 +1,9 @@ + + + + | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = $process_name$ Processes.dest = $dest$ by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_process_file_activity.xml b/package/default/data/ui/panels/workbench_panel_get_process_file_activity.xml new file mode 100644 index 0000000000..28f5412de6 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_process_file_activity.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest=$dest$ Filesystem.process_id=$process_id$ by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_process_info.xml b/package/default/data/ui/panels/workbench_panel_get_process_info.xml new file mode 100644 index 0000000000..20d3333796 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_process_info.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest=$dest$ Proceses.process_name=$process_name$ by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_process_information_for_port_activity.xml b/package/default/data/ui/panels/workbench_panel_get_process_information_for_port_activity.xml new file mode 100644 index 0000000000..9898b46006 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_process_information_for_port_activity.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=$dest_port$ by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_process_registry_activity.xml b/package/default/data/ui/panels/workbench_panel_get_process_registry_activity.xml new file mode 100644 index 0000000000..e33c11f498 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_process_registry_activity.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id=$process_id$ AND Registry.dest=$dest$ by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_process_responsible_for_the_dns_traffic.xml b/package/default/data/ui/panels/workbench_panel_get_process_responsible_for_the_dns_traffic.xml new file mode 100644 index 0000000000..318ae20b38 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_process_responsible_for_the_dns_traffic.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_registry_activities.xml b/package/default/data/ui/panels/workbench_panel_get_registry_activities.xml new file mode 100644 index 0000000000..73bb5bee45 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_registry_activities.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "$dest$" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_endpoint.xml b/package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_endpoint.xml new file mode 100644 index 0000000000..f9e4e70b8a --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object=$dest$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_user.xml b/package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_user.xml new file mode 100644 index 0000000000..4dcf2fd577 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_risk_modifiers_for_user.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object=$user$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_sysmon_wmi_activity_for_host.xml b/package/default/data/ui/panels/workbench_panel_get_sysmon_wmi_activity_for_host.xml new file mode 100644 index 0000000000..b4642ac7a7 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_sysmon_wmi_activity_for_host.xml @@ -0,0 +1,9 @@ + + + + sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host=$dest$ | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_update_logs_for_endpoint.xml b/package/default/data/ui/panels/workbench_panel_get_update_logs_for_endpoint.xml new file mode 100644 index 0000000000..eb3ee6c657 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_update_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_user_information_from_identity_table.xml b/package/default/data/ui/panels/workbench_panel_get_user_information_from_identity_table.xml new file mode 100644 index 0000000000..9269961083 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_user_information_from_identity_table.xml @@ -0,0 +1,9 @@ + + + + | `identities` | search identity=$user$ | table _time, identity, first, last, email, category, watchlist + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_vulnerability_logs_for_endpoint.xml b/package/default/data/ui/panels/workbench_panel_get_vulnerability_logs_for_endpoint.xml new file mode 100644 index 0000000000..30b224262c --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_vulnerability_logs_for_endpoint.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Vulnerabilities.Vulnerabilities | search dest=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_get_web_session_information_via_session_id.xml b/package/default/data/ui/panels/workbench_panel_get_web_session_information_via_session_id.xml new file mode 100644 index 0000000000..1be6d5c2c1 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_get_web_session_information_via_session_id.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=stream:http $session_id$ | stats values(url) values(http_user_agent) by src_ip status + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_aws_activities_via_region_name.xml b/package/default/data/ui/panels/workbench_panel_investigate_aws_activities_via_region_name.xml new file mode 100644 index 0000000000..669b2a7e63 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_aws_activities_via_region_name.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail awsRegion=$awsRegion$| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_aws_ecr_container_listing_activity.xml b/package/default/data/ui/panels/workbench_panel_investigate_aws_ecr_container_listing_activity.xml new file mode 100644 index 0000000000..30e3630ed5 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_aws_ecr_container_listing_activity.xml @@ -0,0 +1,9 @@ + + + + |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1 + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_aws_user_activities_by_user_field.xml b/package/default/data/ui/panels/workbench_panel_investigate_aws_user_activities_by_user_field.xml new file mode 100644 index 0000000000..a4b65f0856 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_aws_user_activities_by_user_field.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=aws:cloudtrail user=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_cloud_compute_instance_activities.xml b/package/default/data/ui/panels/workbench_panel_investigate_cloud_compute_instance_activities.xml new file mode 100644 index 0000000000..5a042540fc --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_cloud_compute_instance_activities.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Cloud_Infrastructure.Compute | search dest=$dest$ | fields - _* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml b/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml new file mode 100644 index 0000000000..eaacf46c7b --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml @@ -0,0 +1,9 @@ + + + + | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_network_traffic_from_src_ip.xml b/package/default/data/ui/panels/workbench_panel_investigate_network_traffic_from_src_ip.xml new file mode 100644 index 0000000000..448e215f7d --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_network_traffic_from_src_ip.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Network_Traffic.All_Traffic | search src_ip=$src_ip$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_app.xml b/package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_app.xml new file mode 100644 index 0000000000..b7e6637221 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_app.xml @@ -0,0 +1,9 @@ + + + + eventtype=okta_log app=$app$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_ip_address.xml b/package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_ip_address.xml new file mode 100644 index 0000000000..f702ab0a9b --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_okta_activity_by_ip_address.xml @@ -0,0 +1,9 @@ + + + + eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_hash_attempts.xml b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_hash_attempts.xml new file mode 100644 index 0000000000..b06e6c71c1 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_hash_attempts.xml @@ -0,0 +1,9 @@ + + + + `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml new file mode 100644 index 0000000000..02d2dff20d --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml @@ -0,0 +1,9 @@ + + + + `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_previous_unseen_user.xml b/package/default/data/ui/panels/workbench_panel_investigate_previous_unseen_user.xml new file mode 100644 index 0000000000..ab5940c8fe --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_previous_unseen_user.xml @@ -0,0 +1,9 @@ + + + + | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_successful_remote_desktop_authentications.xml b/package/default/data/ui/panels/workbench_panel_investigate_successful_remote_desktop_authentications.xml new file mode 100644 index 0000000000..fc1ff90dda --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_successful_remote_desktop_authentications.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| table firstTime lastTime src src_nt_domain dest user app count | sort count + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_suspicious_strings_in_http_header.xml b/package/default/data/ui/panels/workbench_panel_investigate_suspicious_strings_in_http_header.xml new file mode 100644 index 0000000000..bb306f81a8 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_suspicious_strings_in_http_header.xml @@ -0,0 +1,9 @@ + + + + | search sourcetype=stream:http src_ip="$src_ip$" dest_ip="$dest_ip$" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_all_cloud_regions.xml b/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_all_cloud_regions.xml new file mode 100644 index 0000000000..78154b2139 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_all_cloud_regions.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Cloud_Infrastructure.Compute | search user=$src_user$ | fields - _* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_okta.xml b/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_okta.xml new file mode 100644 index 0000000000..0adc7b4f9c --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_okta.xml @@ -0,0 +1,9 @@ + + + + eventtype=okta_log user=$user$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_single_cloud_region.xml b/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_single_cloud_region.xml new file mode 100644 index 0000000000..1aa8d0f2a3 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_user_activities_in_single_cloud_region.xml @@ -0,0 +1,9 @@ + + + + | from datamodel:Cloud_Infrastructure.Compute | search region=$region$ user=$src_user$ | fields - _* + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_host.xml b/package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_host.xml new file mode 100644 index 0000000000..0c8c4e596d --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_host.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Web.Web | search src=$dest$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_src_ip.xml b/package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_src_ip.xml new file mode 100644 index 0000000000..612d227d1b --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_web_activity_from_src_ip.xml @@ -0,0 +1,9 @@ + + + + | from datamodel Web.Web | search src=$src_ip$ + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_investigate_web_posts_from_src.xml b/package/default/data/ui/panels/workbench_panel_investigate_web_posts_from_src.xml new file mode 100644 index 0000000000..43d10b1103 --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_investigate_web_posts_from_src.xml @@ -0,0 +1,9 @@ + + + + | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "$src$") and like(http_method, "POST") + + + +
+ \ No newline at end of file diff --git a/package/default/data/ui/panels/workbench_panel_process_chain_analysis.xml b/package/default/data/ui/panels/workbench_panel_process_chain_analysis.xml new file mode 100644 index 0000000000..582373453a --- /dev/null +++ b/package/default/data/ui/panels/workbench_panel_process_chain_analysis.xml @@ -0,0 +1,9 @@ + + + + `sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count + + + +
+ \ No newline at end of file diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf new file mode 100644 index 0000000000..76de39f31d --- /dev/null +++ b/package/default/es_investigations.conf @@ -0,0 +1,1101 @@ +[panel://workbench_panel_aws_investigate_user_activities_by_arn] +label = AWS Investigate User Activities By ARN +description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. +disabled = 0 +tokens = {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ + +}\ + + +[panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid] +label = AWS Investigate User Activities By AccessKeyId +description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. +disabled = 0 +tokens = {\ + "inventory_asset_accessKeyId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_aws_investigate_user_activities_by_source_user] +label = AWS Investigate User Activities By Source User +description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. +disabled = 0 +tokens = {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_aws_network_acl_details_from_id] +label = AWS Network ACL Details from ID +description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID +disabled = 0 +tokens = {\ + "inventory_asset_networkAclId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_aws_network_interface_details_via_resourceid] +label = AWS Network Interface details via resourceId +description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. +disabled = 0 +tokens = {\ + "inventory_asset_resourceId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_aws_s3_bucket_details_via_bucketname] +label = AWS S3 Bucket details via bucketName +description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. +disabled = 0 +tokens = {\ + "inventory_asset_bucketName_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_all_backup_logs_for_host] +label = All backup logs for host +description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip] +label = Amazon EKS Kubernetes activity by src ip +description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address +disabled = 0 +tokens = {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_gcp_kubernetes_activity_by_src_ip] +label = GCP Kubernetes activity by src ip +description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address +disabled = 0 +tokens = {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_all_aws_activity_from_city] +label = Get All AWS Activity From City +description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +disabled = 0 +tokens = {\ + "inventory_asset_City_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_all_aws_activity_from_country] +label = Get All AWS Activity From Country +description = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +disabled = 0 +tokens = {\ + "inventory_asset_Country_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_all_aws_activity_from_ip_address] +label = Get All AWS Activity From IP Address +description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +disabled = 0 +tokens = {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_all_aws_activity_from_region] +label = Get All AWS Activity From Region +description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. +disabled = 0 +tokens = {\ + "inventory_asset_Region_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_authentication_logs_for_endpoint] +label = Get Authentication Logs For Endpoint +description = This search returns all users that have attempted to access a particular endpoint. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_backup_logs_for_endpoint] +label = Get Backup Logs For Endpoint +description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_certificate_logs_for_a_domain] +label = Get Certificate logs for a domain +description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. +disabled = 0 +tokens = {\ + "inventory_asset_domain_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_dns_server_history_for_a_host] +label = Get DNS Server History for a host +description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. +disabled = 0 +tokens = {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_dns_traffic_ratio] +label = Get DNS traffic ratio +description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. +disabled = 0 +tokens = {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_ec2_instance_details_by_instanceid] +label = Get EC2 Instance Details by instanceId +description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field +disabled = 0 +tokens = {\ + "inventory_asset_instanceId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_ec2_launch_details] +label = Get EC2 Launch Details +description = This search returns some of the launch details for a EC2 instance. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_email_info] +label = Get Email Info +description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. +disabled = 0 +tokens = {\ + "inventory_asset_message_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_emails_from_specific_sender] +label = Get Emails From Specific Sender +description = This search returns all the emails from a specific sender over the last 24 and next hours. +disabled = 0 +tokens = {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address] +label = Get First Occurrence and Last Occurrence of a MAC Address +description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. +disabled = 0 +tokens = {\ + "inventory_asset_src_mac_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_history_of_email_sources] +label = Get History Of Email Sources +description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. +disabled = 0 +tokens = {\ + "inventory_asset_src_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_logon_rights_modifications_for_endpoint] +label = Get Logon Rights Modifications For Endpoint +description = This search allows you to retrieve any modifications to logon rights associated with a specific host. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_logon_rights_modifications_for_user] +label = Get Logon Rights Modifications For User +description = This search allows you to retrieve any modifications to logon rights for a specific user account. +disabled = 0 +tokens = {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ + +}\ + + +[panel://workbench_panel_get_notable_history] +label = Get Notable History +description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_notable_info] +label = Get Notable Info +description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. +disabled = 0 +tokens = {\ + "inventory_asset_event_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_outbound_emails_to_hidden_cobra_threat_actors] +label = Get Outbound Emails to Hidden Cobra Threat Actors +description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. +disabled = 0 +tokens = {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_recipient_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_parent_process_info] +label = Get Parent Process Info +description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest +disabled = 0 +tokens = {\ + "inventory_asset_process_name_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_process_file_activity] +label = Get Process File Activity +description = This search returns the file activity for a specific process on a specific endpoint +disabled = 0 +tokens = {\ + "inventory_asset_process_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_process_info] +label = Get Process Info +description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. +disabled = 0 +tokens = {\ + "inventory_asset_process_name_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_process_information_for_port_activity] +label = Get Process Information For Port Activity +description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. +disabled = 0 +tokens = {\ + "inventory_asset_dest_port_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_process_registry_activity] +label = Get Process Registry Activity +description = This search returns the registry activity for a specific process on a specific endpoint +disabled = 0 +tokens = {\ + "inventory_asset_process_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_process_responsible_for_the_dns_traffic] +label = Get Process Responsible For The DNS Traffic +description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_registry_activities] +label = Get Registry Activities +description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_risk_modifiers_for_endpoint] +label = Get Risk Modifiers For Endpoint +description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_risk_modifiers_for_user] +label = Get Risk Modifiers For User +description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user +disabled = 0 +tokens = {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ + +}\ + + +[panel://workbench_panel_get_sysmon_wmi_activity_for_host] +label = Get Sysmon WMI Activity for Host +description = This search queries Sysmon WMI events for the host of interest. +disabled = 0 +tokens = {\ + "inventory_asset_process_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_update_logs_for_endpoint] +label = Get Update Logs For Endpoint +description = This search will tell you give you the update logs for a specific endpoint for the last week. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_user_information_from_identity_table] +label = Get User Information from Identity Table +description = Gather more information about the user identified in the Notable Event. +disabled = 0 +tokens = {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ + +}\ + + +[panel://workbench_panel_get_vulnerability_logs_for_endpoint] +label = Get Vulnerability Logs For Endpoint +description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_get_web_session_information_via_session_id] +label = Get Web Session Information via session id +description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. +disabled = 0 +tokens = {\ + "inventory_asset_session_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_aws_ecr_container_listing_activity] +label = Investigate AWS ECR container listing activity +description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. +disabled = 0 +tokens = {\ + "inventory_asset_Compute.event_name_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_aws_user_activities_by_user_field] +label = Investigate AWS User Activities by user field +description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. +disabled = 0 +tokens = {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ + +}\ + + +[panel://workbench_panel_investigate_aws_activities_via_region_name] +label = Investigate AWS activities via region name +description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user +disabled = 0 +tokens = {\ + "inventory_asset_awsRegion_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_cloud_compute_instance_activities] +label = Investigate Cloud Compute Instance Activities +description = This search returns a logs of events that operated on the compute instance. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_failed_logins_for_multiple_destinations] +label = Investigate Failed Logins for Multiple Destinations +description = This search returns failed logins to multiple destinations by user. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_network_traffic_from_src_ip] +label = Investigate Network Traffic From src ip +description = This search allows you to find all the network traffic from a specific IP address. +disabled = 0 +tokens = {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_okta_activity_by_ip_address] +label = Investigate Okta Activity by IP Address +description = This search returns all okta events from a specific IP address. +disabled = 0 +tokens = {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ + +}\ + + +[panel://workbench_panel_investigate_okta_activity_by_app] +label = Investigate Okta Activity by app +description = This search returns all okta events associated with a specific app +disabled = 0 +tokens = {\ + "inventory_asset_app_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_pass_the_hash_attempts] +label = Investigate Pass the Hash Attempts +description = This search hunts for dumped NTLM hashes used for pass the hash. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_pass_the_ticket_attempts] +label = Investigate Pass the Ticket Attempts +description = This search hunts for dumped kerberos ticket from LSASS memory. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_previous_unseen_user] +label = Investigate Previous Unseen User +description = This search returns previous unseen user, which didn't log in for 30 days. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_successful_remote_desktop_authentications] +label = Investigate Successful Remote Desktop Authentications +description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_suspicious_strings_in_http_header] +label = Investigate Suspicious Strings in HTTP Header +description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. +disabled = 0 +tokens = {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_dest_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_user_activities_in_all_cloud_regions] +label = Investigate User Activities In All Cloud Regions +description = This search lists all the logged cloud infrastructure activities by a specific cloud user +disabled = 0 +tokens = {\ + "inventory_asset_region_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_user_activities_in_okta] +label = Investigate User Activities In Okta +description = This search returns all okta events by a specific user +disabled = 0 +tokens = {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "identity",\ + "default": "_1!=1"\ + }\ + +}\ + + +[panel://workbench_panel_investigate_user_activities_in_single_cloud_region] +label = Investigate User Activities In Single Cloud Region +description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region +disabled = 0 +tokens = {\ + "inventory_asset_region_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\, + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_web_activity_from_host] +label = Investigate Web Activity From Host +description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +disabled = 0 +tokens = {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_web_activity_from_src_ip] +label = Investigate Web Activity From src ip +description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. +disabled = 0 +tokens = {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_investigate_web_posts_from_src] +label = Investigate Web POSTs From src +description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. +disabled = 0 +tokens = {\ + "inventory_asset_src_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ + + +[panel://workbench_panel_process_chain_analysis] +label = Process Chain Analysis +description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. +disabled = 0 +tokens = {\ + "inventory_asset_process_guid_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ + "valueType": "primitive",\ + "value": "asset",\ + "default": "_1!=1"\ + }\ +}\ diff --git a/package/default/macros.conf b/package/default/macros.conf index c93e15c0a1..da84dbce0d 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T15:39:38 UTC +# On Date: 2020-05-12T11:51:02 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index c53098f2e9..0a1502c8c4 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T15:39:38 UTC +# On Date: 2020-05-12T11:51:02 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -306,7 +306,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] +action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -622,7 +622,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Credential Dumping", "Malicious PowerShell"] +action.escu.analytic_story = ["Malicious PowerShell", "Credential Dumping"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -824,7 +824,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Clients Connecting to Multiple DNS Servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] +action.escu.analytic_story = ["Suspicious DNS Traffic", "Host Redirection", "Command and Control", "DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1394,7 +1394,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length Outliers - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] +action.escu.analytic_story = ["Suspicious DNS Traffic", "Hidden Cobra Malware", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1434,7 +1434,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length With High Standard Deviation - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] +action.escu.analytic_story = ["Suspicious DNS Traffic", "Hidden Cobra Malware", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1473,7 +1473,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] +action.escu.analytic_story = ["Suspicious DNS Traffic", "Host Redirection", "Command and Control", "DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2341,7 +2341,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Outbound SMB Traffic - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware"] +action.escu.analytic_story = ["Hidden Cobra Malware", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2420,7 +2420,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] +action.escu.analytic_story = ["Suspicious MSHTA Activity", "Suspicious Command-Line Executions"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2500,7 +2500,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Rare Executables - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"] +action.escu.analytic_story = ["Unusual Processes", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2863,7 +2863,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Suspicious Command-Line Executions"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2949,7 +2949,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect hosts connecting to dynamic domain providers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Data Protection", "Dynamic DNS", "Suspicious DNS Traffic", "DNS Hijacking"] +action.escu.analytic_story = ["Data Protection", "Command and Control", "Suspicious DNS Traffic", "Prohibited Traffic Allowed or Protocol Mismatch", "Dynamic DNS", "DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3230,7 +3230,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of DNS Tunnels - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Data Protection", "Suspicious DNS Traffic", "Command and Control"] +action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control", "Data Protection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3310,7 +3310,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Disabling Remote User Account Control - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"] +action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3430,7 +3430,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started In Previously Unseen Region - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] +action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3548,7 +3548,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - EC2 Instance Started With Previously Unseen User - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "AWS Cryptomining"] +action.escu.analytic_story = ["AWS Cryptomining", "Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3947,7 +3947,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - First time seen command line argument - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A"] +action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Orangeworm Attack Group", "Hidden Cobra Malware", "Suspicious Command-Line Executions", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4065,7 +4065,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Hiding Files And Directories With Attrib exe - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Defense Evasion Tactics"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4501,7 +4501,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Email For Brand Abuse - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails", "Brand Monitoring"] +action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4540,7 +4540,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Registry Keys for Print Monitors - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5094,7 +5094,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Processes launching netsh - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A", "Netsh Abuse", "Disabling Security Tools"] +action.escu.analytic_story = ["Disabling Security Tools", "Netsh Abuse", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5173,7 +5173,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Software On Endpoint - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A ", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5292,7 +5292,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Service Abuse", "Windows Persistence Techniques"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Service Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5332,7 +5332,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe used to hide files directories via registry keys - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5372,7 +5372,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Persistence - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "DHS Report TA18-074A", "Suspicious MSHTA Activity", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Suspicious Windows Registry Activities", "Suspicious MSHTA Activity", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Emotet Malware DHS Report TA18-201A ", "DHS Report TA18-074A", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5412,7 +5412,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Privilege Escalation - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Privilege Escalation"] +action.escu.analytic_story = ["Windows Privilege Escalation", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5452,7 +5452,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys for Creating SHIM Databases - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5531,7 +5531,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Traffic - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "SamSam Ransomware", "Lateral Movement"] +action.escu.analytic_story = ["Lateral Movement", "Hidden Cobra Malware", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5571,7 +5571,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Process Running On System - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement"] +action.escu.analytic_story = ["Lateral Movement", "Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5651,7 +5651,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Registry Key modifications - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics", "Windows Persistence Techniques"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5771,7 +5771,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Hidden Cobra Malware", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5814,7 +5814,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A", "Hidden Cobra Malware", "Ransomware", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Hidden Cobra Malware", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5934,7 +5934,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Sc exe Manipulating Windows Services - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A", "Windows Persistence Techniques", "Disabling Security Tools"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Disabling Security Tools", "Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6452,7 +6452,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Changes to File Associations - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows File Extension and Association Abuse", "Suspicious Windows Registry Activities"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows File Extension and Association Abuse"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6693,7 +6693,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Reg exe Process - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A", "Windows Defense Evasion Tactics", "Disabling Security Tools"] +action.escu.analytic_story = ["Disabling Security Tools", "DHS Report TA18-074A", "Windows Defense Evasion Tactics"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6852,7 +6852,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - System Processes Run From Unexpected Locations - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"] +action.escu.analytic_story = ["Unusual Processes", "Ransomware", "Suspicious Command-Line Executions"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6971,7 +6971,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Uncommon Processes On Endpoint - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Privilege Escalation", "Unusual Processes"] +action.escu.analytic_story = ["Unusual Processes", "Windows Privilege Escalation"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -7130,7 +7130,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] +action.escu.analytic_story = ["Unusual Processes", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -7170,7 +7170,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] +action.escu.analytic_story = ["Unusual Processes", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -8444,7 +8444,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType +search = | search sourcetype=aws:cloudtrail userIdentity.arn=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType [ESCU - AWS Investigate User Activities By AccessKeyId - Response Task] action.escu = 0 @@ -8465,7 +8465,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage +search = | search sourcetype=aws:cloudtrail userIdentity.accessKeyId=$accessKeyId$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage [ESCU - AWS Investigate User Activities By Source User - Response Task] action.escu = 0 @@ -8486,7 +8486,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage +search = | search sourcetype=aws:cloudtrail userIdentity.arn=$src_user$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage [ESCU - AWS Network ACL Details from ID - Response Task] action.escu = 0 @@ -8507,7 +8507,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:description id={networkAclId} | table id account_id vpc_id network_acl_entries{}.* +search = | search sourcetype=aws:description id=$networkAclId$ | table id account_id vpc_id network_acl_entries{}.* [ESCU - AWS Network Interface details via resourceId - Response Task] action.escu = 0 @@ -8528,7 +8528,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:config resourceId={resourceId} | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp +search = | search sourcetype=aws:config resourceId=$resourceId$ | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp [ESCU - AWS S3 Bucket details via bucketName - Response Task] action.escu = 0 @@ -8549,7 +8549,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList +search = | search sourcetype=aws:config resourceId=$bucketName$ | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList [ESCU - All backup logs for host - Response Task] action.escu = 0 @@ -8570,7 +8570,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype="netbackup_logs" dest={dest} +search = | search sourcetype="netbackup_logs" dest=$dest$ [ESCU - Amazon EKS Kubernetes activity by src ip - Response Task] action.escu = 0 @@ -8591,7 +8591,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip +search = sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}=$src_ip$|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip [ESCU - GCP Kubernetes activity by src ip - Response Task] action.escu = 0 @@ -8633,7 +8633,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City=$City$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode [ESCU - Get All AWS Activity From Country - Response Task] action.escu = 0 @@ -8654,7 +8654,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country=$Country$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode [ESCU - Get All AWS Activity From IP Address - Response Task] action.escu = 0 @@ -8675,7 +8675,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress=$src_ip$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode [ESCU - Get All AWS Activity From Region - Response Task] action.escu = 0 @@ -8696,7 +8696,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode +search = | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region=$Region$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode [ESCU - Get Authentication Logs For Endpoint - Response Task] action.escu = 0 @@ -8717,7 +8717,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats count from datamodel=Authentication where Authentication.dest={dest} by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` +search = | tstats count from datamodel=Authentication where Authentication.dest=$dest$ by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` [ESCU - Get Backup Logs For Endpoint - Response Task] action.escu = 0 @@ -8738,7 +8738,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature +search = | search sourcetype="netbackup_logs" COMPUTERNAME=$dest$ | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature [ESCU - Get Certificate logs for a domain - Response Task] action.escu = 0 @@ -8759,7 +8759,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*$domain$ by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` [ESCU - Get DNS Server History for a host - Response Task] action.escu = 0 @@ -8780,7 +8780,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count +search = | search tag=dns src_ip=$src_ip$ dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count [ESCU - Get DNS traffic ratio - Response Task] action.escu = 0 @@ -8801,7 +8801,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval ratio = (bytes_out/bytes_in) | table ratio +search = | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src=$src_ip$ All_Traffic.dest=$dest_ip$ | eval ratio = (bytes_out/bytes_in) | table ratio [ESCU - Get EC2 Instance Details by instanceId - Response Task] action.escu = 0 @@ -8822,7 +8822,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC +search = | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id=$instanceId$ | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC [ESCU - Get EC2 Launch Details - Response Task] action.escu = 0 @@ -8843,7 +8843,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName +search = | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId=$dest$ |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName [ESCU - Get Email Info - Response Task] action.escu = 0 @@ -8864,7 +8864,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel Email.All_Email | search message_id={message_id} +search = | from datamodel Email.All_Email | search message_id=$message_id$ [ESCU - Get Emails From Specific Sender - Response Task] action.escu = 0 @@ -8885,7 +8885,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel Email.All_Email | search src_user={src_user} +search = | from datamodel Email.All_Email | search src_user=$src_user$ [ESCU - Get First Occurrence and Last Occurrence of a MAC Address - Response Task] action.escu = 0 @@ -8906,7 +8906,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= $src_mac$ by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` [ESCU - Get History Of Email Sources - Response Task] action.escu = 0 @@ -8948,7 +8948,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest={dest} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature +search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest=$dest$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature [ESCU - Get Logon Rights Modifications For User - Response Task] action.escu = 0 @@ -8969,7 +8969,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user={user} | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature +search = | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user=$user$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature [ESCU - Get Notable History - Response Task] action.escu = 0 @@ -8990,7 +8990,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search `notable` | search dest={dest} | table _time, rule_name, owner, priority, severity, status_description +search = | search `notable` | search dest=$dest$ | table _time, rule_name, owner, priority, severity, status_description [ESCU - Get Notable Info - Response Task] action.escu = 0 @@ -9011,7 +9011,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description +search = | search `notable_by_id($event_id$)` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description [ESCU - Get Outbound Emails to Hidden Cobra Threat Actors - Response Task] action.escu = 0 @@ -9053,7 +9053,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` +search = | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = $process_name$ Processes.dest = $dest$ by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` [ESCU - Get Process File Activity - Response Task] action.escu = 0 @@ -9074,7 +9074,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path +search = | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest=$dest$ Filesystem.process_id=$process_id$ by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path [ESCU - Get Process Info - Response Task] action.escu = 0 @@ -9095,7 +9095,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` +search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest=$dest$ Proceses.process_name=$process_name$ by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` [ESCU - Get Process Information For Port Activity - Response Task] action.escu = 0 @@ -9116,7 +9116,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] +search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=$dest_port$ by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] [ESCU - Get Process Registry Activity - Response Task] action.escu = 0 @@ -9137,7 +9137,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id={process_id} AND Registry.dest={dest} by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path +search = | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id=$process_id$ AND Registry.dest=$dest$ by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path [ESCU - Get Process Responsible For The DNS Traffic - Response Task] action.escu = 0 @@ -9158,7 +9158,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] +search = | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] [ESCU - Get Registry Activities - Response Task] action.escu = 0 @@ -9179,7 +9179,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "{dest}" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] +search = | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "$dest$" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] [ESCU - Get Risk Modifiers For Endpoint - Response Task] action.escu = 0 @@ -9200,7 +9200,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` +search = | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object=$dest$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` [ESCU - Get Risk Modifiers For User - Response Task] action.escu = 0 @@ -9221,7 +9221,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` +search = | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object=$user$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` [ESCU - Get Sysmon WMI Activity for Host - Response Task] action.escu = 0 @@ -9242,7 +9242,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter +search = sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host=$dest$ | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter [ESCU - Get Update Logs For Endpoint - Response Task] action.escu = 0 @@ -9263,7 +9263,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest} +search = | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest=$dest$ [ESCU - Get User Information from Identity Table - Response Task] action.escu = 0 @@ -9284,7 +9284,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | `identities` | search identity={user} | table _time, identity, first, last, email, category, watchlist +search = | `identities` | search identity=$user$ | table _time, identity, first, last, email, category, watchlist [ESCU - Get Vulnerability Logs For Endpoint - Response Task] action.escu = 0 @@ -9305,7 +9305,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel Vulnerabilities.Vulnerabilities | search dest={dest} +search = | from datamodel Vulnerabilities.Vulnerabilities | search dest=$dest$ [ESCU - Get Web Session Information via session id - Response Task] action.escu = 0 @@ -9326,7 +9326,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) by src_ip status +search = | search sourcetype=stream:http $session_id$ | stats values(url) values(http_user_agent) by src_ip status [ESCU - Investigate AWS ECR container listing activity - Response Task] action.escu = 0 @@ -9368,7 +9368,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType +search = | search sourcetype=aws:cloudtrail user=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType [ESCU - Investigate AWS activities via region name - Response Task] action.escu = 0 @@ -9389,7 +9389,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId +search = | search sourcetype=aws:cloudtrail awsRegion=$awsRegion$| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId [ESCU - Investigate Cloud Compute Instance Activities - Response Task] action.escu = 0 @@ -9410,7 +9410,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields - _* +search = | from datamodel:Cloud_Infrastructure.Compute | search dest=$dest$ | fields - _* [ESCU - Investigate Failed Logins for Multiple Destinations - Response Task] action.escu = 0 @@ -9452,7 +9452,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip} +search = | from datamodel Network_Traffic.All_Traffic | search src_ip=$src_ip$ [ESCU - Investigate Okta Activity by IP Address - Response Task] action.escu = 0 @@ -9494,7 +9494,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = eventtype=okta_log app={app} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason +search = eventtype=okta_log app=$app$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason [ESCU - Investigate Pass the Hash Attempts - Response Task] action.escu = 0 @@ -9599,7 +9599,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url +search = | search sourcetype=stream:http src_ip="$src_ip$" dest_ip="$dest_ip$" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url [ESCU - Investigate User Activities In All Cloud Regions - Response Task] action.escu = 0 @@ -9620,7 +9620,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | fields - _* +search = | from datamodel:Cloud_Infrastructure.Compute | search user=$src_user$ | fields - _* [ESCU - Investigate User Activities In Okta - Response Task] action.escu = 0 @@ -9641,7 +9641,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = eventtype=okta_log user={user} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason +search = eventtype=okta_log user=$user$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason [ESCU - Investigate User Activities In Single Cloud Region - Response Task] action.escu = 0 @@ -9662,7 +9662,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} | fields - _* +search = | from datamodel:Cloud_Infrastructure.Compute | search region=$region$ user=$src_user$ | fields - _* [ESCU - Investigate Web Activity From Host - Response Task] action.escu = 0 @@ -9683,7 +9683,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel Web.Web | search src={dest} +search = | from datamodel Web.Web | search src=$dest$ [ESCU - Investigate Web Activity From src ip - Response Task] action.escu = 0 @@ -9704,7 +9704,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | from datamodel Web.Web | search src={src_ip} +search = | from datamodel Web.Web | search src=$src_ip$ [ESCU - Investigate Web POSTs From src - Response Task] action.escu = 0 @@ -9725,7 +9725,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "{src}") and like(http_method, "POST") +search = | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "$src$") and like(http_method, "POST") [ESCU - Process Chain Analysis - Response Task] action.escu = 0 diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 95e5cd8368..8ca321fa58 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T15:39:38 UTC +# On Date: 2020-05-12T11:51:02 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index f74724152d..2756054261 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-11T15:39:38 UTC +# On Date: 2020-05-12T11:51:02 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] +searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] +searches = ["ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts"] +searches = ["ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Stop Security Service - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] +searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -374,10 +374,10 @@ narrative = Kubernetes is the most used container orchestration platform, this o category = Adversary Tactics last_updated = 2020-02-04 version = 2 -references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network ACL Details from ID"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. diff --git a/response_tasks/all_backup_logs_for_host.yml b/response_tasks/all_backup_logs_for_host.yml index 6008ac5583..412f36e5fa 100644 --- a/response_tasks/all_backup_logs_for_host.yml +++ b/response_tasks/all_backup_logs_for_host.yml @@ -9,7 +9,7 @@ how_to_implement: The successfully implement this search you must first send you author: Rico Valdez, Splunk inputs: - dest -search: '| search sourcetype="netbackup_logs" dest={dest}' +search: '| search sourcetype="netbackup_logs" dest=$dest$' tags: analytics_story: - Monitor Backup Solution diff --git a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml index 77692a4e2e..9c86ab624a 100644 --- a/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml +++ b/response_tasks/amazon_eks_kubernetes_activity_by_src_ip.yml @@ -11,7 +11,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Rod Soto, Splunk inputs: - src_ip -search: sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}={src_ip}|rename sourceIPs{} +search: sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}=$src_ip$|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip diff --git a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml index a6222a2fcc..716351370d 100644 --- a/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml +++ b/response_tasks/aws_investigate_user_activities_by_accesskeyid.yml @@ -10,7 +10,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: David Dorsey, Splunk inputs: - accessKeyId -search: '| search sourcetype=aws:cloudtrail userIdentity.accessKeyId={accessKeyId} +search: '| search sourcetype=aws:cloudtrail userIdentity.accessKeyId=$accessKeyId$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' tags: diff --git a/response_tasks/aws_investigate_user_activities_by_arn.yml b/response_tasks/aws_investigate_user_activities_by_arn.yml index a08a1f6743..a6550aedde 100644 --- a/response_tasks/aws_investigate_user_activities_by_arn.yml +++ b/response_tasks/aws_investigate_user_activities_by_arn.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - user -search: '| search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time +search: '| search sourcetype=aws:cloudtrail userIdentity.arn=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType' tags: diff --git a/response_tasks/aws_investigate_user_activities_by_source_user.yml b/response_tasks/aws_investigate_user_activities_by_source_user.yml index c2dbbe06f8..cd1083288b 100644 --- a/response_tasks/aws_investigate_user_activities_by_source_user.yml +++ b/response_tasks/aws_investigate_user_activities_by_source_user.yml @@ -10,7 +10,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - src_user -search: '| search sourcetype=aws:cloudtrail userIdentity.arn={src_user} | spath output=user +search: '| search sourcetype=aws:cloudtrail userIdentity.arn=$src_user$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage' tags: diff --git a/response_tasks/aws_network_acl_details_from_id.yml b/response_tasks/aws_network_acl_details_from_id.yml index 821a486c94..a6e73d4846 100644 --- a/response_tasks/aws_network_acl_details_from_id.yml +++ b/response_tasks/aws_network_acl_details_from_id.yml @@ -10,7 +10,7 @@ how_to_implement: In order to implement this search, you must install the AWS Ap author: Bhavin Patel, Splunk inputs: - networkAclId -search: '| search sourcetype=aws:description id={networkAclId} | table id account_id +search: '| search sourcetype=aws:description id=$networkAclId$ | table id account_id vpc_id network_acl_entries{}.*' tags: analytics_story: diff --git a/response_tasks/aws_network_interface_details_via_resourceid.yml b/response_tasks/aws_network_interface_details_via_resourceid.yml index ac876efd64..d7b216c3ff 100644 --- a/response_tasks/aws_network_interface_details_via_resourceid.yml +++ b/response_tasks/aws_network_interface_details_via_resourceid.yml @@ -12,7 +12,7 @@ how_to_implement: In order to implement this search, you must install the AWS Ap author: Bhavin Patel, Splunk inputs: - resourceId -search: '| search sourcetype=aws:config resourceId={resourceId} | table _time ARN +search: '| search sourcetype=aws:config resourceId=$resourceId$ | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp' tags: diff --git a/response_tasks/aws_s3_bucket_details_via_bucketname.yml b/response_tasks/aws_s3_bucket_details_via_bucketname.yml index cef02b7d78..984bc003d1 100644 --- a/response_tasks/aws_s3_bucket_details_via_bucketname.yml +++ b/response_tasks/aws_s3_bucket_details_via_bucketname.yml @@ -13,7 +13,7 @@ how_to_implement: To implement this search, you must install the AWS App for Spl author: Bhavin Patel, Splunk inputs: - bucketName -search: '| search sourcetype=aws:config resourceId={bucketName} | table resourceCreationTime +search: '| search sourcetype=aws:config resourceId=$bucketName$ | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList' tags: analytics_story: diff --git a/response_tasks/get_all_aws_activity_from_city.yml b/response_tasks/get_all_aws_activity_from_city.yml index 5e79c1cc66..5724dcaf9d 100644 --- a/response_tasks/get_all_aws_activity_from_city.yml +++ b/response_tasks/get_all_aws_activity_from_city.yml @@ -13,7 +13,7 @@ author: David Dorsey, Splunk inputs: - City search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - City={City} | spath output=user path=userIdentity.arn | spath output=awsUserName + City=$City$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode' diff --git a/response_tasks/get_all_aws_activity_from_country.yml b/response_tasks/get_all_aws_activity_from_country.yml index 883f6ccb66..beb035556c 100644 --- a/response_tasks/get_all_aws_activity_from_country.yml +++ b/response_tasks/get_all_aws_activity_from_country.yml @@ -13,7 +13,7 @@ author: David Dorsey, Splunk inputs: - Country search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - Country={Country} | spath output=user path=userIdentity.arn | spath output=awsUserName + Country=$Country$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode' diff --git a/response_tasks/get_all_aws_activity_from_ip_address.yml b/response_tasks/get_all_aws_activity_from_ip_address.yml index 8c7f10a917..270ec77de0 100644 --- a/response_tasks/get_all_aws_activity_from_ip_address.yml +++ b/response_tasks/get_all_aws_activity_from_ip_address.yml @@ -13,7 +13,7 @@ author: David Dorsey, Splunk inputs: - src_ip search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - sourceIPAddress={src_ip} | spath output=user path=userIdentity.arn | spath output=awsUserName + sourceIPAddress=$src_ip$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode' diff --git a/response_tasks/get_all_aws_activity_from_region.yml b/response_tasks/get_all_aws_activity_from_region.yml index 3a85824785..8a0a73b1a3 100644 --- a/response_tasks/get_all_aws_activity_from_region.yml +++ b/response_tasks/get_all_aws_activity_from_region.yml @@ -13,7 +13,7 @@ author: David Dorsey, Splunk inputs: - Region search: '| search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search - Region={Region} | spath output=user path=userIdentity.arn | spath output=awsUserName + Region=$Region$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode' diff --git a/response_tasks/get_authentication_logs_for_endpoint.yml b/response_tasks/get_authentication_logs_for_endpoint.yml index f1c27cb433..7c8c273710 100644 --- a/response_tasks/get_authentication_logs_for_endpoint.yml +++ b/response_tasks/get_authentication_logs_for_endpoint.yml @@ -9,7 +9,7 @@ how_to_implement: To successfully implement this search you need to be ingesting author: Bhavin Patel, Splunk inputs: - dest -search: '| tstats count from datamodel=Authentication where Authentication.dest={dest} +search: '| tstats count from datamodel=Authentication where Authentication.dest=$dest$ by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")`' tags: diff --git a/response_tasks/get_backup_logs_for_endpoint.yml b/response_tasks/get_backup_logs_for_endpoint.yml index eb2042594e..30d16c96e0 100644 --- a/response_tasks/get_backup_logs_for_endpoint.yml +++ b/response_tasks/get_backup_logs_for_endpoint.yml @@ -8,7 +8,7 @@ how_to_implement: You must be ingesting your backup logs. author: David Dorsey, Splunk inputs: - dest -search: '| search sourcetype="netbackup_logs" COMPUTERNAME={dest} | rename COMPUTERNAME +search: '| search sourcetype="netbackup_logs" COMPUTERNAME=$dest$ | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature' tags: analytics_story: diff --git a/response_tasks/get_certificate_logs_for_a_domain.yml b/response_tasks/get_certificate_logs_for_a_domain.yml index 0b47390142..a0838f51f4 100644 --- a/response_tasks/get_certificate_logs_for_a_domain.yml +++ b/response_tasks/get_certificate_logs_for_a_domain.yml @@ -12,7 +12,7 @@ author: Bhavin Patel, Splunk inputs: - domain search: '| tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime - FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*{domain} by + FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*$domain$ by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` diff --git a/response_tasks/get_dns_server_history_for_a_host.yml b/response_tasks/get_dns_server_history_for_a_host.yml index d948a5a6d1..c392604282 100644 --- a/response_tasks/get_dns_server_history_for_a_host.yml +++ b/response_tasks/get_dns_server_history_for_a_host.yml @@ -11,7 +11,7 @@ how_to_implement: To successfully implement this search, you must be ingesting y author: Bhavin Patel, Splunk inputs: - src_ip -search: '| search tag=dns src_ip={src_ip} dest_port=53 | streamstats time_window=1d +search: '| search tag=dns src_ip=$src_ip$ dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count' tags: diff --git a/response_tasks/get_dns_traffic_ratio.yml b/response_tasks/get_dns_traffic_ratio.yml index bbd2f55cd5..2846f5b464 100644 --- a/response_tasks/get_dns_traffic_ratio.yml +++ b/response_tasks/get_dns_traffic_ratio.yml @@ -14,7 +14,7 @@ inputs: - dest_ip search: '| tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic - All_Traffic.dest_port=53 All_Traffic.src={src_ip} All_Traffic.dest={dest_ip} | eval + All_Traffic.dest_port=53 All_Traffic.src=$src_ip$ All_Traffic.dest=$dest_ip$ | eval ratio = (bytes_out/bytes_in) | table ratio' tags: analytics_story: diff --git a/response_tasks/get_ec2_instance_details_by_instanceid.yml b/response_tasks/get_ec2_instance_details_by_instanceid.yml index 28cbab449e..b28bdcedbe 100644 --- a/response_tasks/get_ec2_instance_details_by_instanceid.yml +++ b/response_tasks/get_ec2_instance_details_by_instanceid.yml @@ -11,7 +11,7 @@ author: Bhavin Patel, Splunk inputs: - instanceId search: '| search sourcetype="aws:description" source="*:ec2_instances"| dedup id - sortby -_time | search id={instanceId} | spath output=tags path=tags | eval tags=mvzip(key,value," + sortby -_time | search id=$instanceId$ | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, diff --git a/response_tasks/get_ec2_launch_details.yml b/response_tasks/get_ec2_launch_details.yml index a43d352f23..3736eabbdc 100644 --- a/response_tasks/get_ec2_launch_details.yml +++ b/response_tasks/get_ec2_launch_details.yml @@ -9,7 +9,7 @@ how_to_implement: In order to implement this search, you must install the AWS Ap author: Bhavin Patel, Splunk inputs: - dest -search: '| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId={dest} +search: '| search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId=$dest$ |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture diff --git a/response_tasks/get_email_info.yml b/response_tasks/get_email_info.yml index 09ef1ec4b5..48e051569b 100644 --- a/response_tasks/get_email_info.yml +++ b/response_tasks/get_email_info.yml @@ -9,7 +9,7 @@ how_to_implement: To successfully implement this search you must be ingesting yo author: Bhavin Patel, Splunk inputs: - message_id -search: '| from datamodel Email.All_Email | search message_id={message_id}' +search: '| from datamodel Email.All_Email | search message_id=$message_id$' tags: analytics_story: - Brand Monitoring diff --git a/response_tasks/get_emails_from_specific_sender.yml b/response_tasks/get_emails_from_specific_sender.yml index 57630e5ee2..59d4592c35 100644 --- a/response_tasks/get_emails_from_specific_sender.yml +++ b/response_tasks/get_emails_from_specific_sender.yml @@ -10,7 +10,7 @@ how_to_implement: To successfully implement this search you must ingest your ema author: David Dorsey, Splunk inputs: - src_user -search: '| from datamodel Email.All_Email | search src_user={src_user}' +search: '| from datamodel Email.All_Email | search src_user=$src_user$' tags: analytics_story: - Brand Monitoring diff --git a/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml index 1960efe6fd..351dc4c90b 100644 --- a/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml +++ b/response_tasks/get_first_occurrence_and_last_occurrence_of_a_mac_address.yml @@ -13,7 +13,7 @@ inputs: - src_mac search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST - All_Sessions.All_Sessions.src_mac= {src_mac} by All_Sessions.src_ip All_Sessions.user + All_Sessions.All_Sessions.src_mac= $src_mac$ by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`' tags: analytics_story: diff --git a/response_tasks/get_logon_rights_modifications_for_endpoint.yml b/response_tasks/get_logon_rights_modifications_for_endpoint.yml index 5df2fbf971..8bf608d76d 100644 --- a/response_tasks/get_logon_rights_modifications_for_endpoint.yml +++ b/response_tasks/get_logon_rights_modifications_for_endpoint.yml @@ -10,7 +10,7 @@ author: David Dorsey, Splunk inputs: - dest search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) - dest={dest} | rename user as "Account Modified" | table _time, dest, "Account Modified", + dest=$dest$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature' tags: analytics_story: diff --git a/response_tasks/get_logon_rights_modifications_for_user.yml b/response_tasks/get_logon_rights_modifications_for_user.yml index d31659ada4..9118a6df0f 100644 --- a/response_tasks/get_logon_rights_modifications_for_user.yml +++ b/response_tasks/get_logon_rights_modifications_for_user.yml @@ -10,7 +10,7 @@ author: David Dorsey, Splunk inputs: - user search: '| search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) - user={user} | rename user as "Account Modified" | table _time, dest, "Account Modified", + user=$user$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature' tags: analytics_story: diff --git a/response_tasks/get_notable_history.yml b/response_tasks/get_notable_history.yml index e08af91d68..6a7a5bb371 100644 --- a/response_tasks/get_notable_history.yml +++ b/response_tasks/get_notable_history.yml @@ -10,7 +10,7 @@ how_to_implement: If you are using Enterprise Security you are likely already cr author: Bhavin Patel, Splunk inputs: - dest -search: '| search `notable` | search dest={dest} | table _time, rule_name, owner, +search: '| search `notable` | search dest=$dest$ | table _time, rule_name, owner, priority, severity, status_description' tags: analytics_story: diff --git a/response_tasks/get_notable_info.yml b/response_tasks/get_notable_info.yml index 9f392da726..b51d7d48b7 100644 --- a/response_tasks/get_notable_info.yml +++ b/response_tasks/get_notable_info.yml @@ -10,7 +10,7 @@ how_to_implement: If you are using Enterprise Security you are likely already cr author: Bhavin Patel, Splunk inputs: - event_id -search: '| search `notable_by_id({event_id})` | table time, rule_name, dest, dest_asset_id, +search: '| search `notable_by_id($event_id$)` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description' tags: analytics_story: diff --git a/response_tasks/get_parent_process_info.yml b/response_tasks/get_parent_process_info.yml index 1eb8425219..6260214e89 100644 --- a/response_tasks/get_parent_process_info.yml +++ b/response_tasks/get_parent_process_info.yml @@ -15,7 +15,7 @@ inputs: - dest search: '| tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name - = {process_name} Processes.dest = {dest} by Processes.user Processes.parent_process_name Processes.process_name | + = $process_name$ Processes.dest = $dest$ by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`' tags: analytics_story: diff --git a/response_tasks/get_process_file_activity.yml b/response_tasks/get_process_file_activity.yml index 306d2293ad..541db0c677 100644 --- a/response_tasks/get_process_file_activity.yml +++ b/response_tasks/get_process_file_activity.yml @@ -12,7 +12,7 @@ inputs: - dest search: '| tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id - from datamodel=Endpoint.Filesystem where Filesystem.dest={dest} Filesystem.process_id={process_id} + from datamodel=Endpoint.Filesystem where Filesystem.dest=$dest$ Filesystem.process_id=$process_id$ by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path' tags: diff --git a/response_tasks/get_process_info.yml b/response_tasks/get_process_info.yml index fcccc68d69..ae5ec4c163 100644 --- a/response_tasks/get_process_info.yml +++ b/response_tasks/get_process_info.yml @@ -12,7 +12,7 @@ inputs: - process_name - dest search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as - lastTime from datamodel=Endpoint.Processes where Proceses.dest={dest} Proceses.process_name={process_name} + lastTime from datamodel=Endpoint.Processes where Proceses.dest=$dest$ Proceses.process_name=$process_name$ by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` ' tags: diff --git a/response_tasks/get_process_information_for_port_activity.yml b/response_tasks/get_process_information_for_port_activity.yml index 01f48a736b..f4973b5717 100644 --- a/response_tasks/get_process_information_for_port_activity.yml +++ b/response_tasks/get_process_information_for_port_activity.yml @@ -11,11 +11,11 @@ inputs: - dest_port - dest search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as - lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.process_name + lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where - Ports.dest_port={dest_port} by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` + Ports.dest_port=$dest_port$ by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest]' tags: analytics_story: diff --git a/response_tasks/get_process_registry_activity.yml b/response_tasks/get_process_registry_activity.yml index d67d0a3ffb..71b74cb8ad 100644 --- a/response_tasks/get_process_registry_activity.yml +++ b/response_tasks/get_process_registry_activity.yml @@ -12,8 +12,8 @@ inputs: - dest search: '| tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) - as process_id from datamodel=Endpoint.Registry where Registry.process_id={process_id} - AND Registry.dest={dest} by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` + as process_id from datamodel=Endpoint.Registry where Registry.process_id=$process_id$ + AND Registry.dest=$dest$ by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path' tags: analytics_story: diff --git a/response_tasks/get_process_responsible_for_the_dns_traffic.yml b/response_tasks/get_process_responsible_for_the_dns_traffic.yml index 0607c901c5..2599737070 100644 --- a/response_tasks/get_process_responsible_for_the_dns_traffic.yml +++ b/response_tasks/get_process_responsible_for_the_dns_traffic.yml @@ -13,7 +13,7 @@ author: Bhavin Patel, Splunk inputs: - dest search: '| tstats `security_content_summariesonly` count min(_time) max(_time) as - lastTime from datamodel=Endpoint.Processes where Processes.dest = {dest} by Processes.parent_process + lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where diff --git a/response_tasks/get_registry_activities.yml b/response_tasks/get_registry_activities.yml index 91c46f85cb..5ee2c4385f 100644 --- a/response_tasks/get_registry_activities.yml +++ b/response_tasks/get_registry_activities.yml @@ -13,7 +13,7 @@ inputs: - dest search: '| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM - datamodel=Endpoint.Registry where Registry.dest = "{dest}" by Registry.process_id + datamodel=Endpoint.Registry where Registry.dest = "$dest$" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes diff --git a/response_tasks/get_risk_modifiers_for_endpoint.yml b/response_tasks/get_risk_modifiers_for_endpoint.yml index 26b5bea1e5..665c2dd28a 100644 --- a/response_tasks/get_risk_modifiers_for_endpoint.yml +++ b/response_tasks/get_risk_modifiers_for_endpoint.yml @@ -10,7 +10,7 @@ how_to_implement: Enable the correlation searches included in Splunk Enterprise author: Bhavin Patel, Splunk inputs: - dest -search: '| from datamodel:Risk.All_Risk | search risk_object_type=system risk_object={dest} +search: '| from datamodel:Risk.All_Risk | search risk_object_type=system risk_object=$dest$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' tags: diff --git a/response_tasks/get_risk_modifiers_for_user.yml b/response_tasks/get_risk_modifiers_for_user.yml index ab376cb744..37d53e5e5c 100644 --- a/response_tasks/get_risk_modifiers_for_user.yml +++ b/response_tasks/get_risk_modifiers_for_user.yml @@ -10,7 +10,7 @@ how_to_implement: Enable the correlation searches included in Splunk Enterprise author: Bhavin Patel, Splunk inputs: - user -search: '| from datamodel:Risk.All_Risk | search risk_object_type=user risk_object={user} +search: '| from datamodel:Risk.All_Risk | search risk_object_type=user risk_object=$user$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` ' tags: diff --git a/response_tasks/get_sysmon_wmi_activity_for_host.yml b/response_tasks/get_sysmon_wmi_activity_for_host.yml index ec20c01540..eb6ba7909c 100644 --- a/response_tasks/get_sysmon_wmi_activity_for_host.yml +++ b/response_tasks/get_sysmon_wmi_activity_for_host.yml @@ -12,7 +12,7 @@ inputs: - process - dest search: sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 - EventCode<22 host={dest} | rename host as dest | table _time, dest, user, Name, + EventCode<22 host=$dest$ | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter tags: analytics_story: diff --git a/response_tasks/get_update_logs_for_endpoint.yml b/response_tasks/get_update_logs_for_endpoint.yml index 2011cd4e71..0c26920660 100644 --- a/response_tasks/get_update_logs_for_endpoint.yml +++ b/response_tasks/get_update_logs_for_endpoint.yml @@ -9,7 +9,7 @@ author: David Dorsey, Splunk inputs: - dest search: '| from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" - OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest={dest}' + OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest=$dest$' tags: analytics_story: - 'Emotet Malware DHS Report TA18-201A ' diff --git a/response_tasks/get_user_information_from_identity_table.yml b/response_tasks/get_user_information_from_identity_table.yml index 6f9435f45a..60df58e6d6 100644 --- a/response_tasks/get_user_information_from_identity_table.yml +++ b/response_tasks/get_user_information_from_identity_table.yml @@ -8,7 +8,7 @@ how_to_implement: To successfully implement this search you must have populated author: Bhavin Patel, Splunk inputs: - user -search: '| `identities` | search identity={user} | table _time, identity, first, last, +search: '| `identities` | search identity=$user$ | table _time, identity, first, last, email, category, watchlist' tags: analytics_story: diff --git a/response_tasks/get_vulnerability_logs_for_endpoint.yml b/response_tasks/get_vulnerability_logs_for_endpoint.yml index 0d86c377fc..9daed1be94 100644 --- a/response_tasks/get_vulnerability_logs_for_endpoint.yml +++ b/response_tasks/get_vulnerability_logs_for_endpoint.yml @@ -8,7 +8,7 @@ how_to_implement: You need to be ingesting the logs from your vulnerability scan author: David Dorsey, Splunk inputs: - dest -search: '| from datamodel Vulnerabilities.Vulnerabilities | search dest={dest}' +search: '| from datamodel Vulnerabilities.Vulnerabilities | search dest=$dest$' tags: analytics_story: - ColdRoot MacOS RAT diff --git a/response_tasks/get_web_session_information_via_session_id.yml b/response_tasks/get_web_session_information_via_session_id.yml index a196ae731f..d519ed6e79 100644 --- a/response_tasks/get_web_session_information_via_session_id.yml +++ b/response_tasks/get_web_session_information_via_session_id.yml @@ -12,7 +12,7 @@ how_to_implement: This search leverages data extracted from Stream:HTTP. You mus author: Bhavin Patel, Splunk inputs: - session_id -search: '| search sourcetype=stream:http {session_id} | stats values(url) values(http_user_agent) +search: '| search sourcetype=stream:http $session_id$ | stats values(url) values(http_user_agent) by src_ip status' tags: analytics_story: diff --git a/response_tasks/investigate_aws_activities_via_region_name.yml b/response_tasks/investigate_aws_activities_via_region_name.yml index 2c7b4d9a04..ef214d8ea1 100644 --- a/response_tasks/investigate_aws_activities_via_region_name.yml +++ b/response_tasks/investigate_aws_activities_via_region_name.yml @@ -11,7 +11,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - awsRegion -search: '| search sourcetype=aws:cloudtrail awsRegion={awsRegion}| rename requestParameters.instancesSet.items{}.instanceId +search: '| search sourcetype=aws:cloudtrail awsRegion=$awsRegion$| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId' tags: analytics_story: diff --git a/response_tasks/investigate_aws_user_activities_by_user_field.yml b/response_tasks/investigate_aws_user_activities_by_user_field.yml index eaf8bfd9bc..b2fcc388ae 100644 --- a/response_tasks/investigate_aws_user_activities_by_user_field.yml +++ b/response_tasks/investigate_aws_user_activities_by_user_field.yml @@ -12,7 +12,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late author: Bhavin Patel, Splunk inputs: - user -search: '| search sourcetype=aws:cloudtrail user={user} | table _time userIdentity.type +search: '| search sourcetype=aws:cloudtrail user=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType ' tags: analytics_story: diff --git a/response_tasks/investigate_cloud_compute_instance_activities.yml b/response_tasks/investigate_cloud_compute_instance_activities.yml index 7f397bad95..417a96ff09 100644 --- a/response_tasks/investigate_cloud_compute_instance_activities.yml +++ b/response_tasks/investigate_cloud_compute_instance_activities.yml @@ -8,7 +8,7 @@ how_to_implement: You must be ingesting the approrpiate cloud infrastructure log author: David Dorsey, Splunk inputs: - dest -search: '| from datamodel:Cloud_Infrastructure.Compute | search dest={dest} | fields +search: '| from datamodel:Cloud_Infrastructure.Compute | search dest=$dest$ | fields - _*' tags: analytics_story: diff --git a/response_tasks/investigate_network_traffic_from_src_ip.yml b/response_tasks/investigate_network_traffic_from_src_ip.yml index 47f5a8a820..af381cae68 100644 --- a/response_tasks/investigate_network_traffic_from_src_ip.yml +++ b/response_tasks/investigate_network_traffic_from_src_ip.yml @@ -9,7 +9,7 @@ how_to_implement: To successfully implement this search, you must be ingesting y author: David Dorsey, Splunk inputs: - src_ip -search: '| from datamodel Network_Traffic.All_Traffic | search src_ip={src_ip}' +search: '| from datamodel Network_Traffic.All_Traffic | search src_ip=$src_ip$' tags: analytics_story: - ColdRoot MacOS RAT diff --git a/response_tasks/investigate_okta_activity_by_app.yml b/response_tasks/investigate_okta_activity_by_app.yml index 83554e6648..b281e92d21 100644 --- a/response_tasks/investigate_okta_activity_by_app.yml +++ b/response_tasks/investigate_okta_activity_by_app.yml @@ -7,7 +7,7 @@ how_to_implement: You must be ingesting Okta logs author: Rico Valdez, Splunk inputs: - app -search: eventtype=okta_log app={app} | rename client.geographicalContext.country as +search: eventtype=okta_log app=$app$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason tags: diff --git a/response_tasks/investigate_suspicious_strings_in_http_header.yml b/response_tasks/investigate_suspicious_strings_in_http_header.yml index e4d29c4bd2..9bc50b2b36 100644 --- a/response_tasks/investigate_suspicious_strings_in_http_header.yml +++ b/response_tasks/investigate_suspicious_strings_in_http_header.yml @@ -15,7 +15,7 @@ author: Bhavin Patel, Splunk inputs: - src_ip - dest_ip -search: '| search sourcetype=stream:http src_ip="{src_ip}" dest_ip="{dest_ip}" | eval +search: '| search sourcetype=stream:http src_ip="$src_ip$" dest_ip="$dest_ip$" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious diff --git a/response_tasks/investigate_user_activities_in_all_cloud_regions.yml b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml index e9b0624029..e162510d2a 100644 --- a/response_tasks/investigate_user_activities_in_all_cloud_regions.yml +++ b/response_tasks/investigate_user_activities_in_all_cloud_regions.yml @@ -10,7 +10,7 @@ author: David Dorsey, Splunk inputs: - region - src_user -search: '| from datamodel:Cloud_Infrastructure.Compute | search user={src_user} | +search: '| from datamodel:Cloud_Infrastructure.Compute | search user=$src_user$ | fields - _*' tags: analytics_story: diff --git a/response_tasks/investigate_user_activities_in_okta.yml b/response_tasks/investigate_user_activities_in_okta.yml index 97132725af..942d9d7e76 100644 --- a/response_tasks/investigate_user_activities_in_okta.yml +++ b/response_tasks/investigate_user_activities_in_okta.yml @@ -7,7 +7,7 @@ how_to_implement: You must be ingesting Okta logs author: Rico Valdez, Splunk inputs: - user -search: eventtype=okta_log user={user} | rename client.geographicalContext.country +search: eventtype=okta_log user=$user$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason tags: diff --git a/response_tasks/investigate_user_activities_in_single_cloud_region.yml b/response_tasks/investigate_user_activities_in_single_cloud_region.yml index e3c3491f19..be63a4df81 100644 --- a/response_tasks/investigate_user_activities_in_single_cloud_region.yml +++ b/response_tasks/investigate_user_activities_in_single_cloud_region.yml @@ -10,7 +10,7 @@ author: David Dorsey, Splunk inputs: - region - src_user -search: '| from datamodel:Cloud_Infrastructure.Compute | search region={region} user={src_user} +search: '| from datamodel:Cloud_Infrastructure.Compute | search region=$region$ user=$src_user$ | fields - _*' tags: analytics_story: diff --git a/response_tasks/investigate_web_activity_from_host.yml b/response_tasks/investigate_web_activity_from_host.yml index 18667da5df..e8b14e65f3 100644 --- a/response_tasks/investigate_web_activity_from_host.yml +++ b/response_tasks/investigate_web_activity_from_host.yml @@ -10,7 +10,7 @@ how_to_implement: To successfully implement this search you must be ingesting yo author: Bhavin Patel, Splunk inputs: - dest -search: '| from datamodel Web.Web | search src={dest}' +search: '| from datamodel Web.Web | search src=$dest$' tags: analytics_story: - Brand Monitoring diff --git a/response_tasks/investigate_web_activity_from_src_ip.yml b/response_tasks/investigate_web_activity_from_src_ip.yml index 0aac0b5eff..f23344f44a 100644 --- a/response_tasks/investigate_web_activity_from_src_ip.yml +++ b/response_tasks/investigate_web_activity_from_src_ip.yml @@ -10,7 +10,7 @@ how_to_implement: To successfully implement this search, you must be ingesting y author: David Dorsey, Splunk inputs: - src_ip -search: '| from datamodel Web.Web | search src={src_ip}' +search: '| from datamodel Web.Web | search src=$src_ip$' tags: analytics_story: - ColdRoot MacOS RAT diff --git a/response_tasks/investigate_web_posts_from_src.yml b/response_tasks/investigate_web_posts_from_src.yml index d16985c53a..820de7a950 100644 --- a/response_tasks/investigate_web_posts_from_src.yml +++ b/response_tasks/investigate_web_posts_from_src.yml @@ -12,7 +12,7 @@ inputs: - src search: '| tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where - like(src, "{src}") and like(http_method, "POST")' + like(src, "$src$") and like(http_method, "POST")' tags: analytics_story: - Apache Struts Vulnerability diff --git a/stories/lateral_movement.yml b/stories/lateral_movement.yml index 9d7d1efff9..ac9b5e0ebc 100644 --- a/stories/lateral_movement.yml +++ b/stories/lateral_movement.yml @@ -32,6 +32,7 @@ narrative: "Once attackers gain a foothold within an enterprise, they will seek author: David Dorsey, Splunk type: ESCU references: +- https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis - 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t.content.label : e.app; - return Object.assign(e, { - appLabel: a - }) - }); - e.setState((0, u.default)({ - apps: l.map(function(e) { - return { - name: e.name, - label: e.content.label - } - }) - }, o && { - modal: "escu" - }, { - analyticStories: i - })) - }), this.fetchAndSetDataModelsDataSources() - } - }, { - key: "setSavedSearchPropertiesAndInUse", - value: function(e) { - var t = this; - return new Promise(function(a) { - (0, C.fetchRESTURL)("saved/searches", { - app: oe.app, - owner: "nobody" - }, { - output_mode: "json", - count: 0 - }).then(function(t) { - var n = e.slice().map(function(e) { - return e.searches = e.searches.map(function(e) { - var a = t.entry.find(function(t) { - return e.name === t.name - }); - return Object.assign(e, { - label: void 0 !== a ? a.content["action.correlationsearch.label"] : "", - active: void 0 !== a && a.content.is_scheduled && a.content.disabled === !1, - app: void 0 !== a ? a.acl.app : "", - uri: void 0 !== a ? a.links.edit : "", - isCorrelationSearch: void 0 !== a && (0, b.normalizeBoolean)(a.content["action.correlationsearch.enabled"]) === !0 - }) - }), e.in_use = e.searches.some(function(e) { - return "detection" === e.type && e.active - }), e - }); - a(n) - }).catch(function(n) { - t.setState({ - errorMsg: (0, H._)("Error detecting if analytic stories are in use.") + " " + n - }), a(e) - }) - }) - } - }, { - key: "setBookmarkedStories", - value: function(e) { - var t = this.getCurrentBookmarks(); - if (t.length > 0) { - var a = e.slice().map(function(e) { - return e.bookmarked = Boolean(t.indexOf(e.name) !== -1), e - }); - return a - } - return e.map(function(e) { - return e.bookmarked = !1, e - }) - } - }, { - key: "getFilteredStories", - value: function(e, t, a) { - var n = arguments.length > 3 && void 0 !== arguments[3] ? 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(0, H._)("category") + ": " + a : (0, H._)("categories") + ": " + a, - l = 1 === e.length ? 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Promise.resolve(ue[e]) : new Promise(function(t) { - (0, ie.fetchContentInfo)("savedsearch", e, "nobody", oe.app, de).then(function(a) { - if (a && a.entry && a.entry.length > 0 && a.entry[0].content && a.entry[0].content.datasets) { - var n = (0, ie.parseDatasets)(a.entry[0].content.datasets); - ue[e] = n, t(n) - } - t({}) - }).catch(function() { - t({}) - }) - }) - } - }, { - key: "fetchStoryContentInfo", - value: function(e) { - var t = this; - return new Promise(function(a) { - var n = e.searches.filter(function(e) { - return "detection" === e.type - }).map(function(e) { - return t.fetchSearchContentInfo(e.name) - }); - Promise.all(n).then(function(n) { - var l = (0, z.getMetadataInfo)([e]), - r = l.technologies.map(function(e) { - return { - label: e, - id: e - } - }), - o = n.filter(function(e) { - return e.size > 0 - }), - s = o.map(function(e) { - return e.get("sourcetype") - }), - u = o.map(function(e) { - return e.get("datamodel") - }), - d = o.map(function(e) { - return e.get("lookup") - }); - a({ - providingTechnologies: r, - sourcetypes: t.addReadinessToItems("sourcetype", K.unionBy.apply(void 0, (0, i.default)(s).concat(["id"]))), - dataModels: t.addReadinessToItems("datamodel", K.unionBy.apply(void 0, (0, i.default)(u).concat(["id"]))), - lookups: t.addReadinessToItems("lookup", K.unionBy.apply(void 0, (0, i.default)(d).concat(["id"]))) - }) - }) - }) - } - }, { - key: "addReadinessToItems", - value: function(e, t) { - return t.map(function(t) { - return t.reason = (0, ie.getReasonForReadiness)(e, t.readiness), t - }) - } - }, { - key: "fetchAndSetDataModelsDataSources", - value: function() { - var e = this; - (0, ie.fetchContentInfo)("datamodel", void 0, "nobody", oe.app).then(function(t) { - e.setState({ - dataModels: t.entry.map(function(e) { - return e.name - }) - }) - }).catch(function() { - e.setState({ - errorMsg: (0, H._)("Error fetching the data models.") - }) - }); - var t = { - output_mode: "json", - count: -1 - }; - (0, C.fetchRESTURL)("storage/collections/data/dataset_cache", { - app: "SA-Utils", - owner: "nobody" - }, t).then(function(t) { - var a = t.filter(function(e) { - return "datamodel" === e.type && e.usedby && e.usedby.savedsearch - }).map(function(e) { - return [e.name, e.usedby.savedsearch] - }), - n = new Map(a); - e.setState({ - dataModelsSearchesMap: n - }) - }).catch(function() {}) - } - }, { - key: "handleBookmarkClick", - value: function(e, t) { - var a = t.value, - n = this.state.analyticStories, - l = this.getCurrentBookmarks(); - l.indexOf(a) === -1 ? l.push(a) : l = l.filter(function(e) { - return e !== a - }), this.userPrefModel.entry.content.set({ - analyticStoryBookmarks: JSON.stringify(l) - }), this.userPrefModel.save(); - var r = n.slice().map(function(e) { - return e.name === a && (e.bookmarked = !e.bookmarked), e - }); - this.setState({ - analyticStories: r - }) - } - }, { - key: "handleMetadataFilterChange", - value: function(e, t) { - var a = t.values; - this.updateMetadataState(a) - } - }, { - key: "handleFiltersChange", - value: function(e, t) { - var a = t.name, - n = t.value; - this.setState((0, r.default)({}, a, n)) - } - }, { - key: "handleCategoryClick", - value: function(e, t) { - var a = t.value, - n = this.state.selectedCategories, - l = n; - (0, K.includes)(l, a) ? this.setState({ - selectedCategories: (0, K.without)(l, a) - }): this.setState({ - selectedCategories: l.concat(a) - }) - } - }, { - key: "handleSearchChange", - value: function(e, t) { - var a = t.value; - this.setState({ - searchValue: a - }), this.setSearchTerm(a) - } - }, { - key: "render", - value: function() { - var e = this, - t = this.state, - a = t.errorMsg, - n = t.isLoading, - l = t.analyticStories, - r = t.searchTerm, - o = t.selectedCategories, - i = t.filterMetadata, - s = t.filterApp, - u = t.filterDataSource, - d = t.filterDataModel, - f = t.filterInUse, - c = t.filterBookmarked, - p = t.useCases, - m = t.modal, - h = t.optOut, - g = t.apps, - y = t.annotations, - v = t.dataModels, - k = t.dataSources, - S = t.searchValue, - C = t.openDiscoverRecStoriesModal, - b = { - searchTerm: r, - metadata: i, - app: s, - dataSource: u, - dataModel: d, - inUse: f, - bookmarked: c - }, - E = a.length > 0; - if (n) return _.default.createElement(Y.default, { - size: "medium", - style: se.spinnerStyle - }); - var M = this.getFilteredStories(l, r, o, { - filterMetadata: i, - filterApp: s, - filterDataSource: u, - filterDataModel: d, - filterInUse: f, - filterBookmarked: c - }), - q = (0, K.uniq)(M.map(function(e) { - return e.category - })), - O = this.getAnalyticStoriesLabel(M, q), - A = (0, ne.makeURLfromArgs)("manager", oe.app, "appsremote", { - count: 1, - query: "Splunk ES Content Update" - }); 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"desc" : "asc"; - this.setState({ - sortKey: a, - sortDir: o - }) - } - }, { - key: "renderAnalyticStoryRow", - value: function(e) { - var t = this.props.handleBookmarkClick, - a = e.name, - n = (0, h.makeURLfromArgs)("app", g.app, "ess_analytic_story_details", { - analytic_story: a - }); - return p.default.createElement(C.default.Row, { - key: e.id, - expansionRow: this.getExpansionRow(e) - }, p.default.createElement(C.default.Cell, { - align: "center", - "data-test": "in-use-section", - "data-test-value": e.in_use - }, this.getStoryInUseComponent(e)), p.default.createElement(C.default.Cell, { - data: e, - "data-test": "analytic-story-section", - "data-test-value": a - }, p.default.createElement(S.default, { - to: n - }, a)), p.default.createElement(C.default.Cell, { - data: e, - "data-test": "use-case-section", - "data-test-value": e.category - }, e.category), p.default.createElement(C.default.Cell, { - "data-test": "description-section" - }, e.description), p.default.createElement(C.default.Cell, { - "data-test": "app-section" - }, e.appLabel), p.default.createElement(C.default.Cell, { - "data-test": "last-updated-section" - }, B.default.newSplunkTime({ - time: e.last_updated - }).format("ll")), p.default.createElement(C.default.Cell, { - "data-test": "bookmarked-section", - "data-test-value": e.bookmarked - }, void 0 !== e.bookmarked && p.default.createElement(U.default, { - key: e.id, - value: e.name, - onClick: t, - selected: e.bookmarked, - selectedLabel: (0, m._)("Bookmark enabled"), - unselectedLabel: (0, m._)("Bookmark disabled"), - appearance: "toggle", - size: "small" - }))) - } - }, { - key: "render", - value: function() { - var e = this, - t = this.state, - a = t.sortKey, - n = t.sortDir, - l = this.props, - r = l.analyticStories, - o = l.filters, - i = o.searchTerm, - s = o.metadata, - u = o.app, - d = o.dataSource, - f = o.dataModel, - c = o.inUse, - h = o.bookmarked, - g = this.sortAnalyticStoriesWithKey(r, a, n); - return p.default.createElement(C.default, { - stripeRows: !0, - rowExpansion: "single", - innerStyle: x.tableStyle, - "data-test-filter-metadata": s.join(","), - "data-test-filter-app": u, - "data-test-filter-datasource": d, - "data-test-filter-datamodel": f, - "data-test-filter-inuse": c, - "data-test-filter-bookmarked": h, - "data-test-search-term": i - }, p.default.createElement(C.default.Head, null, p.default.createElement(C.default.HeadCell, { - width: 30 - }, (0, m._)("In use")), p.default.createElement(C.default.HeadCell, { - width: 180, - onSort: this.handleSort, - sortKey: "name", - sortDir: "name" === a ? 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function t() { - return (0, r.default)(this, t), (0, u.default)(this, (t.__proto__ || Object.getPrototypeOf(t)).apply(this, arguments)) - } - return (0, f.default)(t, e), (0, i.default)(t, [{ - key: "render", - value: function() { - var e = this.props, - t = e.data, - a = e.onItemClick; - return t.map(function(e) { - return p.default.createElement(h.default, { - key: e.name, - name: e.name, - label: e.label || e.name, - color: e.color, - items: e.items, - onItemClick: a, - clickable: !0 - }) - }) - } - }]), t - }(c.Component); - v.propTypes = { - data: y.default.arrayOf(y.default.shape({ - color: y.default.string, - name: y.default.string.isRequired, - label: y.default.string.isRequired, - items: y.default.arrayOf(y.default.string).isRequired - })).isRequired, - onItemClick: y.default.func.isRequired - }, t.default = v, e.exports = t.default - }, - 2934: function(e, t, a) { - "use strict"; - - function n(e) { - return e && e.__esModule ? e : { - default: e - } - } - Object.defineProperty(t, "__esModule", { - 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span: 2.4 - }, this.getInUseFilterSelect()), p.default.createElement(C.default.Column, { - span: 2.4 - }, this.getBookmarkedFilterSelect()))) - } - }]), t - }(c.Component); - E.propTypes = { - apps: h.default.arrayOf(h.default.shape({ - name: h.default.string.isRequired, - label: h.default.string.isRequired - })).isRequired, - annotations: h.default.arrayOf(h.default.shape({ - name: h.default.string.isRequired, - label: h.default.string.isRequired, - items: h.default.arrayOf(h.default.string).isRequired - })).isRequired, - dataModels: h.default.arrayOf(h.default.string).isRequired, - dataSources: h.default.arrayOf(h.default.string).isRequired, - onFilterChanged: h.default.func.isRequired, - onMetadataChanged: h.default.func.isRequired, - filterMetadata: h.default.arrayOf(h.default.string).isRequired, - filterInUse: h.default.string.isRequired, - filterDataModel: h.default.string.isRequired, - filterDataSource: h.default.string.isRequired, - filterApp: h.default.string.isRequired, - filterBookmarked: h.default.string.isRequired - }, t.default = E, e.exports = t.default - } -}); From a8866e6788d69fbee4316b6a499570cee12a93bb Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 12 May 2020 13:57:36 +0200 Subject: [PATCH 43/93] bug in generate --- stories/lateral_movement.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/stories/lateral_movement.yml b/stories/lateral_movement.yml index ac9b5e0ebc..9d7d1efff9 100644 --- a/stories/lateral_movement.yml +++ b/stories/lateral_movement.yml @@ -32,7 +32,6 @@ narrative: "Once attackers gain a foothold within an enterprise, they will seek author: David Dorsey, Splunk type: ESCU references: -- https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis - https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html tags: analytics_story: Lateral Movement From e645c7586f171373e189ad415e8c087393c1a56f Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 12 May 2020 14:02:11 +0200 Subject: [PATCH 44/93] bug in generate --- bin/jinja2_templates/es_investigations.j2 | 3 +- package/default/analytic_stories.conf | 122 +++++------ package/default/es_investigations.conf | 19 +- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 256 +++++++++++----------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 130 +++++------ 7 files changed, 264 insertions(+), 270 deletions(-) diff --git a/bin/jinja2_templates/es_investigations.j2 b/bin/jinja2_templates/es_investigations.j2 index 3610743094..1c00c17c6c 100644 --- a/bin/jinja2_templates/es_investigations.j2 +++ b/bin/jinja2_templates/es_investigations.j2 @@ -13,8 +13,7 @@ tokens = {\ "valueType": "primitive",\ "value": "identity",\ "default": "_1!=1"\ - }\ -{% else %} + }\{% else %} "inventory_asset_{{ token }}_filter": {\ "valuePrefix": "",\ "valueSuffix": "",\ diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 84707a82c8..15c865bfc5 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T11:51:02 UTC +# On Date: 2020-05-12T12:01:50 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -511,10 +511,10 @@ creation_date = 2020-02-04 modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 -reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 76de39f31d..7c30896680 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -11,7 +11,6 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }\ - }\ @@ -273,7 +272,7 @@ tokens = {\ [panel://workbench_panel_get_dns_traffic_ratio] label = Get DNS traffic ratio -description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. +description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ @@ -420,7 +419,6 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }\ - }\ @@ -634,7 +632,7 @@ tokens = {\ [panel://workbench_panel_get_risk_modifiers_for_endpoint] label = Get Risk Modifiers For Endpoint -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) +description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ @@ -650,7 +648,7 @@ tokens = {\ [panel://workbench_panel_get_risk_modifiers_for_user] label = Get Risk Modifiers For User -description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user +description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ @@ -661,7 +659,6 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }\ - }\ @@ -718,7 +715,6 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }\ - }\ @@ -783,7 +779,6 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }\ - }\ @@ -864,7 +859,6 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }\ - }\ @@ -934,7 +928,7 @@ tokens = {\ [panel://workbench_panel_investigate_successful_remote_desktop_authentications] label = Investigate Successful Remote Desktop Authentications -description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. +description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ @@ -1009,7 +1003,6 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }\ - }\ @@ -1071,7 +1064,7 @@ tokens = {\ [panel://workbench_panel_investigate_web_posts_from_src] label = Investigate Web POSTs From src -description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. +description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. disabled = 0 tokens = {\ "inventory_asset_src_filter": {\ @@ -1099,3 +1092,5 @@ tokens = {\ "default": "_1!=1"\ }\ }\ + + diff --git a/package/default/macros.conf b/package/default/macros.conf index da84dbce0d..01c094f303 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T11:51:02 UTC +# On Date: 2020-05-12T12:01:50 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 0a1502c8c4..b464293fe5 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T11:51:02 UTC +# On Date: 2020-05-12T12:01:50 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -572,7 +572,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attempt to add a certificate to the untrusted certificate store action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Attempt to add a certificate to the untrusted certificate store action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically be done on a large number of systems. @@ -612,7 +612,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. action.escu.known_false_positives = Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should be reviewed and investigated as appropriate. @@ -652,7 +652,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for attempts to stop security-related services on the endpoint. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for attempts to stop security-related services on the endpoint. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., action.escu.known_false_positives = None identified. Attempts to disable security-related services should be identified and understood. @@ -692,7 +692,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -732,7 +732,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search looks for a batch file (.bat) written to the Windows system directory tree. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = It is possible for this search to generate a notable event for a batch file write to a path that includes the string "system32", but is not the actual Windows system directory. As such, you should confirm the path of the batch file identified by the search. In addition, a false positive may be generated by an administrator copying a legitimate batch file in this directory tree. You should confirm that the activity is legitimate and modify the search to add exclusions, as necessary. @@ -772,7 +772,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.mappings = {"cis20": ["CIS 5", "CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1068"], "nist": ["PR.AC", "PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. action.escu.known_false_positives = Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. @@ -812,7 +812,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["PR.PT", "DE.AE", "PR.DS"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.escu.how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ This search produces fields (`dest_count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Distinct DNS Connections, **Field:** dest_count\ @@ -854,7 +854,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances created by users who have not created them before. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] action.escu.eli5 = This search looks for cloud compute instances created by users who have not created them before. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. action.escu.known_false_positives = It's possible that a user will start to create compute instances for the first time, for any number of reasons. Verify with the user launching instances that this is the intended behavior. @@ -894,7 +894,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] action.escu.eli5 = This search looks for cloud compute instances being created with previously unseen image IDs. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. action.escu.known_false_positives = After a new image is created, the first systems created with that image will cause this alert to fire. Verify that the image being used was created by a legitimate user. @@ -934,7 +934,7 @@ action.escu = 0 action.escu.enabled = 1 description = Find EC2 instances being created with previously unseen instance types. action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] action.escu.eli5 = Find EC2 instances being created with previously unseen instance types. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It is possible that an admin will create a new system using a new instance type that has never been used before. Verify with the creator that they intended to create the system with the new instance type. @@ -974,7 +974,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.DP", "DE.AE"]} -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] action.escu.eli5 = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.escu.how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. action.escu.known_false_positives = It's possible that a user has unknowingly started an instance in a new region. Please verify that this activity is legitimate. @@ -1014,7 +1014,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file modifications with extensions commonly used by Ransomware action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search looks for file modifications with extensions commonly used by Ransomware action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** Name, **Field:** Name\ @@ -1058,7 +1058,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = It's possible that a legitimate file could be created with the same name used by ransomware note files. @@ -1138,7 +1138,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation of local administrator accounts using net.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for the creation of local administrator accounts using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create admin accounts. @@ -1178,7 +1178,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for the creation or deletion of hidden shares using net.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. @@ -1218,7 +1218,7 @@ action.escu = 0 action.escu.enabled = 1 description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legtimate administrator usage of Ntdsutil, Vssadmin, or Wmic will create false positives. @@ -1298,7 +1298,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects credential dumping using copy command from a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search detects credential dumping using copy command from a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1338,7 +1338,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the creation of a symlink to a shadow copy. action.escu.mappings = {"cis20": ["CIS 8", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search detects the creation of a symlink to a shadow copy. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = unknown @@ -1378,7 +1378,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces fields (`query`,`query_length`,`count`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -1424,7 +1424,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It's possible there can be long domain names that are legitimate. @@ -1463,7 +1463,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. action.escu.known_false_positives = Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. @@ -1503,7 +1503,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.mappings = {"cis20": ["CIS 1", "CIS 3", "CIS 8", "CIS 12"], "kill_chain_phases": ["Command and Control"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.escu.how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ **Splunk>Phantom Playbook Integration**\ @@ -1547,7 +1547,7 @@ action.escu = 0 action.escu.enabled = 1 description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.mappings = {"cis20": ["CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = vssadmin.exe and wmic.exe are standard applications shipped with modern versions of windows. They may be used by administrators to legitimately delete old backup copies, although this is typically rare. @@ -1879,7 +1879,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.mappings = {"cis20": ["CIS 8", "CIS 7"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1192"], "nist": ["ID.AM", "PR.DS", "PR.IP", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.escu.how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ **Splunk>Phantom Playbook Integration**\ @@ -1923,7 +1923,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = [Change] +action.escu.data_models = ["Change"] action.escu.eli5 = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.escu.how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ **Splunk>Phantom Playbook Integration**\ @@ -1967,7 +1967,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["PR.IP"]} -action.escu.data_models = [Change] +action.escu.data_models = ["Change"] action.escu.eli5 = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.escu.how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. action.escu.known_false_positives = It is possible that a legitimate user is experiencing an issue causing multiple account login failures leading to lockouts. @@ -2007,7 +2007,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1095"], "nist": ["DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = ICMP packets are used in a variety of ways to help troubleshoot networking issues and ensure the proper flow of traffic. As such, it is possible that a large ICMP packet could be perfectly legitimate. If large ICMP packets are associated with command and control traffic, there will typically be a large number of these packets observed over time. If the search is providing a large number of false positives, you can modify the search to adjust the byte threshold or whitelist specific IP addresses, as necessary. @@ -2046,7 +2046,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.escu.how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. action.escu.known_false_positives = It's possible that legitimate TXT record responses can be long enough to trigger this search. You can modify the packet threshold for this search to help mitigate false positives. @@ -2211,7 +2211,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "PR.AC", "PR.IP"]} -action.escu.data_models = [Authentication] +action.escu.data_models = ["Authentication"] action.escu.eli5 = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.escu.how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. action.escu.known_false_positives = Legitimate router connections may appear as new connections @@ -2331,7 +2331,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.escu.how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model action.escu.known_false_positives = It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the lookup file to avoid creating notable events for traffic destined to those CIDR blocks. Any other network connection that is going out to the Internet should be investigated and blocked. Best practices suggest preventing external communications of all SMB versions and related protocols at the network boundary. @@ -2370,7 +2370,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. action.escu.known_false_positives = It is unlikely that a normal user may create and place this file in the C: drive. Confirm with the user. @@ -2410,7 +2410,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. action.escu.known_false_positives = There are circumstances where an application may legitimately execute and interact with the Windows command-line interface. Investigate and modify the lookup file, as appropriate. @@ -2450,7 +2450,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators can leverage PsExec for accessing remote systems and might pass `accepteula` as an argument if they are running this tool for the first time. However, it is not likely that you'd see multiple occurrences of this event on a machine @@ -2490,7 +2490,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.PT", "PR.DS", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. action.escu.known_false_positives = Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. @@ -2774,7 +2774,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = [Change_Analysis] +action.escu.data_models = ["Change_Analysis"] action.escu.eli5 = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.escu.how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. action.escu.known_false_positives = Legitimate USB activity will also be detected. Please verify and investigate as appropriate. @@ -2814,7 +2814,7 @@ action.escu = 0 action.escu.enabled = 1 description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Reconnaissance", "Delivery", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Network_Sessions] +action.escu.data_models = ["Network_Sessions"] action.escu.eli5 = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.escu.how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. action.escu.known_false_positives = This search might be prone to high false positives. Please consider this when conducting analysis or investigations. Authorized devices may be detected as unauthorized. If this is the case, verify the MAC address of the system responsible for the false positive and add it to the Assets and Identity framework with the proper information. @@ -2853,7 +2853,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Some legitimate applications may exhibit this behavior. @@ -2893,7 +2893,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.mappings = {"kill_chain_phases": ["Reconnaissance"], "mitre_attack": ["T1082"]} -action.escu.data_models = [Web] +action.escu.data_models = ["Web"] action.escu.eli5 = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.escu.how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. action.escu.known_false_positives = It's possible for legitimate HTTP requests to be made to URLs containing the suspicious paths. @@ -2933,7 +2933,7 @@ action.escu = 0 action.escu.enabled = 1 description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.mappings = {"cis20": ["CIS 8", "CIS 12", "CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "nist": ["PR.DS", "PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.escu.how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ This search produces fields (query, answer, isDynDNS) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable event. To see the additional metadata, add the following fields, if not already present, to Incident Review. Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** DNS Query, **Field:** query\ @@ -2978,7 +2978,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.mappings = {"cis20": ["CIS 12", "CIS 4", "CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["ID.RA", "PR.PT", "PR.IP", "DE.AE", "PR.MA", "DE.CM"]} -action.escu.data_models = [Web] +action.escu.data_models = ["Web"] action.escu.eli5 = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.escu.how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model action.escu.known_false_positives = No known false positives for this detection. @@ -3018,7 +3018,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Exploitation"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.escu.how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Although unlikely, some legitimate applications may exhibit this behavior, triggering a false positive. @@ -3138,7 +3138,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.escu.how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. action.escu.known_false_positives = It is uncommon for normal users to execute a series of commands used for network discovery. System administrators often use scripts to execute these commands. These can generate false positives. @@ -3178,7 +3178,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for web connections to dynamic DNS providers. action.escu.mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1102", "T1041"], "nist": ["PR.IP", "DE.DP"]} -action.escu.data_models = [Web] +action.escu.data_models = ["Web"] action.escu.eli5 = This search looks for web connections to dynamic DNS providers. action.escu.how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ This search produces fields (`isDynDNS`) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\\n1. **Label:** IsDynamicDNS, **Field:** isDynDNS\ @@ -3220,7 +3220,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.mappings = {"cis20": ["CIS 13"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "PR.DS"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.escu.how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. action.escu.known_false_positives = It's possible that normal DNS traffic will exhibit this behavior. If an alert is generated, please investigate and validate as appropriate. The threshold can also be modified to better suit your environment. @@ -3260,7 +3260,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Installation", "Actions on Objectives"], "mitre_attack": ["T1072", "T1087"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While legitimate, these NirSoft tools are prone to abuse. You should verfiy that the tool was used for a legitimate purpose. @@ -3340,7 +3340,7 @@ action.escu = 0 action.escu.enabled = 1 description = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1003"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Detect the usage of comsvcs.dll for dumping the lsass process. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified. @@ -3578,7 +3578,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [Email] +action.escu.data_models = ["Email"] action.escu.eli5 = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ **Splunk Phantom Playbook Integration**\ @@ -3619,7 +3619,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. action.escu.known_false_positives = Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. @@ -3659,7 +3659,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1114", "T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -3698,7 +3698,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.mappings = {"cis20": ["CIS 8", "CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048", "T1043"], "nist": ["PR.PT", "DE.AE", "DE.CM"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment. @@ -3737,7 +3737,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = None identified. @@ -3777,7 +3777,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.PT", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. action.escu.known_false_positives = None identified. @@ -3857,7 +3857,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.escu.how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Because these extensions are not typically used in normal operations, you should investigate all results. @@ -3937,7 +3937,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1064", "T1059"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. action.escu.known_false_positives = Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name @@ -4055,7 +4055,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Some applications and users may legitimately use attrib.exe to interact with the files. @@ -4095,7 +4095,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["PR.PT", "DE.CM", "DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.escu.how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. action.escu.known_false_positives = The false-positive rate will vary based on how you set the deviation_threshold and data_samples values. Our recommendation is to adjust these values based on your network traffic to and from your email servers. @@ -4173,7 +4173,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.IP"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.escu.how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. action.escu.known_false_positives = Legitimate ANY requests may trigger this search, however it is unusual to see a large volume of them under typical circumstances. You may modify the threshold in the search to better suit your environment. @@ -4212,7 +4212,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation", "Command and Control"], "nist": ["DE.DP", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. action.escu.known_false_positives = At this stage, there are no known false positives. During testing, no process events refering the com.apple.loginwindow.plist files were observed during normal operation of re-opening applications on reboot. Therefore, it can be asumed that any occurences of this in the process events would be worth investigating. In the event that the legitimate modification by the system of these files is in fact logged to the process log, then the process_name of that process can be whitelisted. @@ -4252,7 +4252,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -4292,7 +4292,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = System administrators may use this option, but it's not common. @@ -4332,7 +4332,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = There may be legitimate reasons to bypass the PowerShell execution policy. The PowerShell script being run with this parameter should be validated to ensure that it is legitimate. @@ -4372,7 +4372,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Legitimate process can have this combination of command-line options, but it's not common. @@ -4412,7 +4412,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Command and Control", "Actions on Objectives"], "mitre_attack": ["T1086", "T1064"], "nist": ["PR.PT", "DE.CM", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = These characters might be legitimately on the command-line, but it is not common. @@ -4452,7 +4452,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.mappings = {"kill_chain_phases": ["Delivery", "Actions on Objectives"]} -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] action.escu.eli5 = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4491,7 +4491,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [Email] +action.escu.data_models = ["Email"] action.escu.eli5 = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4570,7 +4570,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [Web] +action.escu.data_models = ["Web"] action.escu.eli5 = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.escu.how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. action.escu.known_false_positives = None at this time @@ -4689,7 +4689,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.mappings = {"cis20": ["CIS 18"], "nist": ["PR.PT", "PR.MA"]} -action.escu.data_models = [Updates] +action.escu.data_models = ["Updates"] action.escu.eli5 = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.escu.how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. action.escu.known_false_positives = None identified @@ -4925,7 +4925,7 @@ action.escu = 0 action.escu.enabled = 1 description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.escu.how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = Microsoft may provide updates to these binaries. Verify that these changes do not correspond with your normal software update cycle. @@ -5044,7 +5044,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = It is unusual for netsh.exe to have any child processes in most environments. It makes sense to investigate the child process and verify whether the process spawned is legitimate. @@ -5084,7 +5084,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model action.escu.known_false_positives = Some VPN applications are known to launch netsh.exe. Outside of these instances, it is unusual for an executable to launch netsh.exe and run commands. @@ -5124,7 +5124,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Delivery", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None identified @@ -5163,7 +5163,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Installation", "Command and Control", "Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as prohibited. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. action.escu.known_false_positives = None identified @@ -5203,7 +5203,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "PR.AC"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.escu.how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. action.escu.known_false_positives = None identified @@ -5242,7 +5242,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.mappings = {"cis20": ["CIS 9", "CIS 14"], "kill_chain_phases": ["Reconnaissance", "Actions on Objectives"], "nist": ["PR.PT", "DE.AE", "PR.AC", "PR.DS"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.escu.how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. action.escu.known_false_positives = Some networks may use kerberized FTP or telnet servers, however, this is rare. @@ -5322,7 +5322,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None at the moment @@ -5481,7 +5481,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.mappings = {"cis20": ["CIS 12", "CIS 9", "CIS 16"], "kill_chain_phases": ["Reconnaissance", "Delivery"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.escu.how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. action.escu.known_false_positives = RDP gateways may have unusually high amounts of traffic from all other hosts' RDP applications in the network. @@ -5521,7 +5521,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.escu.how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -5561,7 +5561,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.mappings = {"cis20": ["CIS 3", "CIS 9", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.escu.how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. action.escu.known_false_positives = Remote Desktop may be used legitimately by users on the network. @@ -5601,7 +5601,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wmic.exe utility is a benign Windows application. It may be used legitimately by Administrators with these parameters for remote system administration, but it's relatively uncommon. @@ -5681,7 +5681,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047"], "nist": ["PR.PT", "PR.AT", "PR.AC", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may use this legitimately to gather info from remote systems. @@ -5721,7 +5721,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1085"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = While not common, loading a DLL under %AppData% and calling a function by ordinal is possible by a legitimate process @@ -5761,7 +5761,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.escu.how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. action.escu.known_false_positives = A file server may experience high-demand loads that could cause this analytic to trigger. @@ -5801,7 +5801,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.escu.how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ This search produces a field (Number of events,count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. This field contributes additional context to the notable. To see the additional metadata, add the following field, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry): \ @@ -5844,7 +5844,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for long URLs that have several SQL commands visible within them. action.escu.mappings = {"cis20": ["CIS 4", "CIS 13", "CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["PR.DS", "ID.RA", "PR.PT", "PR.IP", "DE.CM"]} -action.escu.data_models = [Web] +action.escu.data_models = ["Web"] action.escu.eli5 = This search looks for long URLs that have several SQL commands visible within them. action.escu.how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. action.escu.known_false_positives = It's possible that legitimate traffic will have long URLs or long user agent strings and that common SQL commands may be found within the URL. Please investigate as appropriate. @@ -5884,7 +5884,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Delivery"], "nist": ["PR.PT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.escu.how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. action.escu.known_false_positives = No false positives have been identified. @@ -5924,7 +5924,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Installation"], "mitre_attack": ["T1050", "T1031", "T1089"], "nist": ["PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Using sc.exe to manipulate Windows services is uncommon. However, there may be legitimate instances of this behavior. It is important to validate and investigate as appropriate. @@ -5964,7 +5964,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.escu.how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -6004,7 +6004,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = No known false positives @@ -6044,7 +6044,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Administrators may create jobs on remote systems, but this activity is usually limited to a small set of hosts or users. It is important to validate and investigate as appropriate. @@ -6084,7 +6084,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.escu.how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. action.escu.known_false_positives = Administrators may create jobs on systems forcing reboots to perform updates, maintenance, etc. @@ -6204,7 +6204,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1138"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -6244,7 +6244,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search detects accounts that were created and deleted in a short time period. action.escu.mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1136"], "nist": ["PR.IP"]} -action.escu.data_models = [Change] +action.escu.data_models = ["Change"] action.escu.eli5 = This search detects accounts that were created and deleted in a short time period. action.escu.how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ action.escu.known_false_positives = It is possible that an administrator created and deleted an account in a short time period. Verifying activity with an administrator is advised. @@ -6284,7 +6284,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for process names that consist only of a single letter. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for process names that consist only of a single letter. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = Single-letter executables are not always malicious. Investigate this activity with your normal incident-response process. @@ -6323,7 +6323,7 @@ action.escu = 0 action.escu.enabled = 1 description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.mappings = {"cis20": ["CIS 4"], "nist": ["ID.RA", "RS.MI", "PR.IP", "DE.CM"]} -action.escu.data_models = [Vulnerabilities] +action.escu.data_models = ["Vulnerabilities"] action.escu.eli5 = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.escu.how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. action.escu.known_false_positives = It is possible that your vulnerability scanner is not detecting that the patches have been applied. @@ -6482,7 +6482,7 @@ action.escu = 0 action.escu.enabled = 1 description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["PR.IP"]} -action.escu.data_models = [UEBA] +action.escu.data_models = ["UEBA"] action.escu.eli5 = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.escu.how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. action.escu.known_false_positives = This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and whitelist the URL if you determine that it is a legitimate sender. @@ -6522,7 +6522,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for emails that have attachments with suspicious file extensions. action.escu.mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 12"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -action.escu.data_models = [Email] +action.escu.data_models = ["Email"] action.escu.eli5 = This search looks for emails that have attachments with suspicious file extensions. action.escu.how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ **Splunk Phantom Playbook Integration**\ @@ -6723,7 +6723,7 @@ action.escu = 0 action.escu.enabled = 1 description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.DP", "PR.IP", "PR.PT", "PR.AC", "PR.AT", "DE.AE"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = The wevtutil.exe application is a legitimate Windows event log utility. Administrators may use it to manage Windows event logs. @@ -6882,7 +6882,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.mappings = {"cis20": ["CIS 9", "CIS 12"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE"]} -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.escu.how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. action.escu.known_false_positives = None at this time @@ -6921,7 +6921,7 @@ action.escu = 0 action.escu.enabled = 1 description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.mappings = {"cis20": ["CIS 6", "CIS 8", "CIS 10"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.CM", "PR.PT", "DE.AE", "DE.DP", "PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. action.escu.known_false_positives = None identified @@ -6961,7 +6961,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015"], "nist": ["ID.AM", "PR.DS"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for applications on the endpoint that you have marked as uncommon. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. action.escu.known_false_positives = None identified @@ -7001,7 +7001,7 @@ action.escu = 0 action.escu.enabled = 1 description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089"], "nist": ["DE.CM"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search is also shipped with `unload_sysmon_filter_driver_filter` macro, update this macro to filter out false positives. action.escu.known_false_positives = @@ -7477,7 +7477,7 @@ action.escu = 0 action.escu.enabled = 1 description = This search looks for suspicious processes on all systems labeled as web servers. action.escu.mappings = {"cis20": ["CIS 3"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1082"], "nist": ["PR.IP"]} -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search looks for suspicious processes on all systems labeled as web servers. action.escu.how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. action.escu.known_false_positives = Some of these processes may be used legitimately on web servers during maintenance or other administrative tasks. @@ -7666,7 +7666,7 @@ description = This search is used to build a Machine Learning Toolkit (MLTK) mod action.escu.creation_date = 2019-05-08 action.escu.modification_date = 2019-05-08 action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -7770,7 +7770,7 @@ description = This search is used to build a Machine Learning Toolkit (MLTK) mod action.escu.creation_date = 2019-05-08 action.escu.modification_date = 2019-05-08 action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Netsh Abuse", "Ransomware"] -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -7830,7 +7830,7 @@ description = The search counts the number of times a connection was observed to action.escu.creation_date = 2017-09-13 action.escu.modification_date = 2017-09-13 action.escu.analytic_story = [] -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -7910,7 +7910,7 @@ description = The search takes corporate and common cloud provider domains confi action.escu.creation_date = 2019-02-14 action.escu.modification_date = 2019-02-14 action.escu.analytic_story = ["DNS Hijacking"] -action.escu.data_models = [Network_Resolution] +action.escu.data_models = ["Network_Resolution"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -7930,7 +7930,7 @@ description = This search counts the numbers of times the system has generated r action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 action.escu.analytic_story = [] -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -7950,7 +7950,7 @@ description = This search counts the numbers of times the system has created rem action.escu.creation_date = 2017-09-15 action.escu.modification_date = 2017-09-15 action.escu.analytic_story = [] -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -7970,7 +7970,7 @@ description = This search counts the numbers of times the remote desktop process action.escu.creation_date = 2019-04-01 action.escu.modification_date = 2019-04-01 action.escu.analytic_story = [] -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -8090,7 +8090,7 @@ description = This search builds a table of previously seen users that have laun action.escu.creation_date = 2018-03-15 action.escu.modification_date = 2018-03-15 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -8110,7 +8110,7 @@ description = This search builds a table of previously seen images used to launc action.escu.creation_date = 2018-03-12 action.escu.modification_date = 2018-03-12 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -8130,7 +8130,7 @@ description = This search builds a table of previously seen cloud compute instan action.escu.creation_date = 2019-10-03 action.escu.modification_date = 2019-10-03 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -8150,7 +8150,7 @@ description = This search looks for cloud compute events where a compute instanc action.escu.creation_date = 2019-10-02 action.escu.modification_date = 2019-10-02 action.escu.analytic_story = ["Cloud Cryptomining"] -action.escu.data_models = [Cloud_Infrastructure] +action.escu.data_models = ["Cloud_Infrastructure"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -8310,7 +8310,7 @@ description = This search looks for command-line arguments where `cmd.exe /c` is action.escu.creation_date = 2019-03-01 action.escu.modification_date = 2019-03-01 action.escu.analytic_story = ["DHS Report TA18-074A", "Disabling Security Tools", "Hidden Cobra Malware", "Netsh Abuse", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] dispatch.earliest_time = -30m dispatch.latest_time = now schedule_window = auto @@ -8710,7 +8710,7 @@ action.escu.analytic_story = ["AWS Network ACL Activity", "Account Monitoring an action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] +action.escu.data_models = ["Authentication"] action.escu.eli5 = This search returns all users that have attempted to access a particular endpoint. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -8794,7 +8794,7 @@ action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Network_Traffic] +action.escu.data_models = ["Network_Traffic"] action.escu.eli5 = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -8899,7 +8899,7 @@ action.escu.analytic_story = ["Asset Tracking"] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Network_Sessions] +action.escu.data_models = ["Network_Sessions"] action.escu.eli5 = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -8920,7 +8920,7 @@ action.escu.analytic_story = [] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Email] +action.escu.data_models = ["Email"] action.escu.eli5 = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9067,7 +9067,7 @@ action.escu.analytic_story = ["DHS Report TA18-074A"] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search returns the file activity for a specific process on a specific endpoint action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9088,7 +9088,7 @@ action.escu.analytic_story = ["AWS Network ACL Activity", "Collection and Stagin action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9109,7 +9109,7 @@ action.escu.analytic_story = ["AWS Network ACL Activity", "Command and Control", action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9130,7 +9130,7 @@ action.escu.analytic_story = ["DHS Report TA18-074A"] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = This search returns the registry activity for a specific process on a specific endpoint action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9151,7 +9151,7 @@ action.escu.analytic_story = ["AWS Network ACL Activity", "Brand Monitoring", "C action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Endpoint] +action.escu.data_models = ["Endpoint"] action.escu.eli5 = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9424,7 +9424,7 @@ action.escu.analytic_story = ["Credential Dumping"] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] +action.escu.data_models = ["Authentication"] action.escu.eli5 = This search returns failed logins to multiple destinations by user. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9550,7 +9550,7 @@ action.escu.analytic_story = ["Credential Dumping"] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] +action.escu.data_models = ["Authentication"] action.escu.eli5 = This search returns previous unseen user, which didn't log in for 30 days. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9571,7 +9571,7 @@ action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement", "SamSa action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Authentication] +action.escu.data_models = ["Authentication"] action.escu.eli5 = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time @@ -9718,7 +9718,7 @@ action.escu.analytic_story = ["Apache Struts Vulnerability"] action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 action.escu.providing_technologies = [] -action.escu.data_models = [Web] +action.escu.data_models = ["Web"] action.escu.eli5 = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. action.escu.how_to_implement = none action.escu.known_false_positives = None at this time diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 8ca321fa58..26d89fee92 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T11:51:02 UTC +# On Date: 2020-05-12T12:01:50 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 2756054261..fe8aa5d369 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T11:51:02 UTC +# On Date: 2020-05-12T12:01:50 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Registry Activity", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -374,10 +374,10 @@ narrative = Kubernetes is the most used container orchestration platform, this o category = Adversary Tactics last_updated = 2020-02-04 version = 2 -references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host", "ESCU - Get Notable History"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Sysmon WMI Activity for Host"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 707e21278fb59db961e9dcf17f98a9cce9381ff5 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 12 May 2020 14:19:23 +0200 Subject: [PATCH 45/93] bug in generate --- bin/jinja2_templates/es_investigations.j2 | 20 +- package/default/analytic_stories.conf | 122 ++-- package/default/es_investigations.conf | 740 +++++++--------------- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 128 ++-- 7 files changed, 356 insertions(+), 660 deletions(-) diff --git a/bin/jinja2_templates/es_investigations.j2 b/bin/jinja2_templates/es_investigations.j2 index 1c00c17c6c..57fcf4abb0 100644 --- a/bin/jinja2_templates/es_investigations.j2 +++ b/bin/jinja2_templates/es_investigations.j2 @@ -7,21 +7,13 @@ tokens = {\ {% for token in response_task.inputs %} {% if token == 'user' %} "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\{% else %} + "valueType": "primitive",\ + "value": "identity"\ + }\{% else %} "inventory_asset_{{ token }}_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\{% endif %}{{ "," if not loop.last }} + "valueType": "primitive",\ + "value": "asset"\ + }\{% endif %}{{ "," if not loop.last }} {% endfor %} }\ diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 15c865bfc5..1e3ae48dac 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:01:50 UTC +# On Date: 2020-05-12T12:19:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country"] +investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] +investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip"] +investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] +investigative_searches = ["ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 7c30896680..f1ec0662eb 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -4,13 +4,9 @@ description = This search lists all the logged CloudTrail activities by a specif disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -20,13 +16,9 @@ description = This search retrieves the times, ARN, source IPs, AWS regions, eve disabled = 0 tokens = {\ "inventory_asset_accessKeyId_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -36,13 +28,9 @@ description = This search retrieves the times, ARN, source IPs, AWS regions, eve disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -52,13 +40,9 @@ description = This search queries AWS description logs and returns all the infor disabled = 0 tokens = {\ "inventory_asset_networkAclId_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -68,13 +52,9 @@ description = This search queries AWS configuration logs and returns the informa disabled = 0 tokens = {\ "inventory_asset_resourceId_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -84,13 +64,9 @@ description = This search queries AWS configuration logs and returns the informa disabled = 0 tokens = {\ "inventory_asset_bucketName_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -100,13 +76,9 @@ description = Retrieve the backup logs for the last 2 weeks for a specific host disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -116,13 +88,9 @@ description = This search provides investigation data about requests via user ag disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -132,13 +100,9 @@ description = This search provides investigation data about requests via user ag disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -148,13 +112,9 @@ description = This search retrieves all the activity from a specific city and wi disabled = 0 tokens = {\ "inventory_asset_City_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -164,13 +124,9 @@ description = This search retrieves all the activity from a specific country and disabled = 0 tokens = {\ "inventory_asset_Country_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -180,13 +136,9 @@ description = This search retrieves all the activity from a specific IP address disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -196,13 +148,9 @@ description = This search retrieves all the activity from a specific geographic disabled = 0 tokens = {\ "inventory_asset_Region_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -212,13 +160,9 @@ description = This search returns all users that have attempted to access a part disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -228,13 +172,9 @@ description = This search will tell you the backup status from your netbackup_lo disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -244,13 +184,9 @@ description = This search queries the Certificates datamodel and give you all th disabled = 0 tokens = {\ "inventory_asset_domain_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -260,13 +196,9 @@ description = While investigating any detections it is important to understand w disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -276,21 +208,13 @@ description = This search calculates the ratio of DNS traffic originating and co disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -300,13 +224,9 @@ description = This search queries AWS description logs and returns all the infor disabled = 0 tokens = {\ "inventory_asset_instanceId_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -316,13 +236,9 @@ description = This search returns some of the launch details for a EC2 instance. disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -332,13 +248,9 @@ description = This search returns all the information Splunk might have collecte disabled = 0 tokens = {\ "inventory_asset_message_id_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -348,13 +260,9 @@ description = This search returns all the emails from a specific sender over the disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -364,13 +272,9 @@ description = This search allows you to gather more context around a notable whi disabled = 0 tokens = {\ "inventory_asset_src_mac_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -380,13 +284,9 @@ description = This search returns a list of all email sources seen in the 48 hou disabled = 0 tokens = {\ "inventory_asset_src_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -396,13 +296,9 @@ description = This search allows you to retrieve any modifications to logon righ disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -412,13 +308,9 @@ description = This search allows you to retrieve any modifications to logon righ disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -428,13 +320,9 @@ description = This search queries the notable index and returns all the Notable disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -444,13 +332,9 @@ description = This search queries the notable index to retrieve detailed informa disabled = 0 tokens = {\ "inventory_asset_event_id_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -460,21 +344,13 @@ description = This search returns the information of the users that sent emails disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_recipient_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -484,21 +360,13 @@ description = This search queries the Endpoint data model to give you details ab disabled = 0 tokens = {\ "inventory_asset_process_name_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -508,21 +376,13 @@ description = This search returns the file activity for a specific process on a disabled = 0 tokens = {\ "inventory_asset_process_id_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -532,21 +392,13 @@ description = This search queries the Endpoint data model to give you details ab disabled = 0 tokens = {\ "inventory_asset_process_name_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -556,21 +408,13 @@ description = This search will return information about the process associated w disabled = 0 tokens = {\ "inventory_asset_dest_port_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -580,21 +424,13 @@ description = This search returns the registry activity for a specific process o disabled = 0 tokens = {\ "inventory_asset_process_id_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -604,13 +440,9 @@ description = While investigating, an analyst will want to know what process and disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -620,13 +452,9 @@ description = This search queries the Endpoint Datamodel to give you details of disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -636,13 +464,9 @@ description = For the last 7 days, the search will query the Risk data model in disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -652,13 +476,9 @@ description = For the last 7 days, the search will query the Risk data model in disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -668,21 +488,13 @@ description = This search queries Sysmon WMI events for the host of interest. disabled = 0 tokens = {\ "inventory_asset_process_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -692,13 +504,9 @@ description = This search will tell you give you the update logs for a specific disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -708,13 +516,9 @@ description = Gather more information about the user identified in the Notable E disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -724,13 +528,9 @@ description = This search will show you any vulnerabilities noted for a specific disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -740,13 +540,9 @@ description = This search helps an analyst investigate a notable event to find o disabled = 0 tokens = {\ "inventory_asset_session_id_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -756,13 +552,9 @@ description = This search lists all the users performing a list image operation disabled = 0 tokens = {\ "inventory_asset_Compute.event_name_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -772,13 +564,9 @@ description = This search lists all the logged CloudTrail activities by a specif disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -788,13 +576,9 @@ description = This search lists all the user activities logged by CloudTrail for disabled = 0 tokens = {\ "inventory_asset_awsRegion_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -804,13 +588,9 @@ description = This search returns a logs of events that operated on the compute disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -820,13 +600,9 @@ description = This search returns failed logins to multiple destinations by user disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -836,13 +612,9 @@ description = This search allows you to find all the network traffic from a spec disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -852,13 +624,9 @@ description = This search returns all okta events from a specific IP address. disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -868,13 +636,9 @@ description = This search returns all okta events associated with a specific app disabled = 0 tokens = {\ "inventory_asset_app_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -884,13 +648,9 @@ description = This search hunts for dumped NTLM hashes used for pass the hash. disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -900,13 +660,9 @@ description = This search hunts for dumped kerberos ticket from LSASS memory. disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -916,13 +672,9 @@ description = This search returns previous unseen user, which didn't log in for disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -932,13 +684,9 @@ description = This search returns the source, destination, and user for all succ disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -948,21 +696,13 @@ description = This search helps an analyst investigate a notable event related t disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -972,21 +712,13 @@ description = This search lists all the logged cloud infrastructure activities b disabled = 0 tokens = {\ "inventory_asset_region_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_src_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -996,13 +728,9 @@ description = This search returns all okta events by a specific user disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "identity",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -1012,21 +740,13 @@ description = This search lists all the logged cloud infrastructure activities b disabled = 0 tokens = {\ "inventory_asset_region_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_src_user_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -1036,13 +756,9 @@ description = This search allows you to find all the web activity from a specifi disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -1052,13 +768,9 @@ description = This search searches for all web activity from a specific host. Du disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -1068,13 +780,9 @@ description = This investigative search retrieves POST requests from a specified disabled = 0 tokens = {\ "inventory_asset_src_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -1084,13 +792,9 @@ description = Analyze the Process Chain and identify the malicious file. By anal disabled = 0 tokens = {\ "inventory_asset_process_guid_filter": {\ - "valuePrefix": "",\ - "valueSuffix": "",\ - "delimiter": " OR ",\ - "valueType": "primitive",\ - "value": "asset",\ - "default": "_1!=1"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ diff --git a/package/default/macros.conf b/package/default/macros.conf index 01c094f303..80b4883423 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:01:50 UTC +# On Date: 2020-05-12T12:19:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index b464293fe5..8956d6fd12 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:01:50 UTC +# On Date: 2020-05-12T12:19:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 26d89fee92..c8db18a5a5 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:01:50 UTC +# On Date: 2020-05-12T12:19:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index fe8aa5d369..12b0c266db 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:01:50 UTC +# On Date: 2020-05-12T12:19:19 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User", "ESCU - AWS Investigate User Activities By AccessKeyId"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] +searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User"] +searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] +searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications"] +searches = ["ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Notable History"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 18722520e9e5859596d35d520afab55e16fa1c46 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 12 May 2020 14:31:56 +0200 Subject: [PATCH 46/93] bug in generate --- bin/jinja2_templates/es_investigations.j2 | 12 +- package/default/analytic_stories.conf | 118 +++--- package/default/es_investigations.conf | 444 +++++++++++----------- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 124 +++--- 7 files changed, 352 insertions(+), 352 deletions(-) diff --git a/bin/jinja2_templates/es_investigations.j2 b/bin/jinja2_templates/es_investigations.j2 index 57fcf4abb0..bfe484889d 100644 --- a/bin/jinja2_templates/es_investigations.j2 +++ b/bin/jinja2_templates/es_investigations.j2 @@ -7,13 +7,13 @@ tokens = {\ {% for token in response_task.inputs %} {% if token == 'user' %} "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\{% else %} + "valueType": "primitive",\ + "value": "identity"\ + }\{% else %} "inventory_asset_{{ token }}_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\{% endif %}{{ "," if not loop.last }} + "valueType": "primitive",\ + "value": "asset"\ + }\{% endif %}{{ "," if not loop.last }} {% endfor %} }\ diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 1e3ae48dac..fe60f3efec 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:19:19 UTC +# On Date: 2020-05-12T12:31:52 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] +investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index f1ec0662eb..096d19aac5 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -4,9 +4,9 @@ description = This search lists all the logged CloudTrail activities by a specif disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -16,9 +16,9 @@ description = This search retrieves the times, ARN, source IPs, AWS regions, eve disabled = 0 tokens = {\ "inventory_asset_accessKeyId_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -28,9 +28,9 @@ description = This search retrieves the times, ARN, source IPs, AWS regions, eve disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -40,9 +40,9 @@ description = This search queries AWS description logs and returns all the infor disabled = 0 tokens = {\ "inventory_asset_networkAclId_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -52,9 +52,9 @@ description = This search queries AWS configuration logs and returns the informa disabled = 0 tokens = {\ "inventory_asset_resourceId_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -64,9 +64,9 @@ description = This search queries AWS configuration logs and returns the informa disabled = 0 tokens = {\ "inventory_asset_bucketName_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -76,9 +76,9 @@ description = Retrieve the backup logs for the last 2 weeks for a specific host disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -88,9 +88,9 @@ description = This search provides investigation data about requests via user ag disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -100,9 +100,9 @@ description = This search provides investigation data about requests via user ag disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -112,9 +112,9 @@ description = This search retrieves all the activity from a specific city and wi disabled = 0 tokens = {\ "inventory_asset_City_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -124,9 +124,9 @@ description = This search retrieves all the activity from a specific country and disabled = 0 tokens = {\ "inventory_asset_Country_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -136,9 +136,9 @@ description = This search retrieves all the activity from a specific IP address disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -148,9 +148,9 @@ description = This search retrieves all the activity from a specific geographic disabled = 0 tokens = {\ "inventory_asset_Region_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -160,9 +160,9 @@ description = This search returns all users that have attempted to access a part disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -172,9 +172,9 @@ description = This search will tell you the backup status from your netbackup_lo disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -184,9 +184,9 @@ description = This search queries the Certificates datamodel and give you all th disabled = 0 tokens = {\ "inventory_asset_domain_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -196,9 +196,9 @@ description = While investigating any detections it is important to understand w disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -208,13 +208,13 @@ description = This search calculates the ratio of DNS traffic originating and co disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -224,9 +224,9 @@ description = This search queries AWS description logs and returns all the infor disabled = 0 tokens = {\ "inventory_asset_instanceId_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -236,9 +236,9 @@ description = This search returns some of the launch details for a EC2 instance. disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -248,9 +248,9 @@ description = This search returns all the information Splunk might have collecte disabled = 0 tokens = {\ "inventory_asset_message_id_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -260,9 +260,9 @@ description = This search returns all the emails from a specific sender over the disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -272,9 +272,9 @@ description = This search allows you to gather more context around a notable whi disabled = 0 tokens = {\ "inventory_asset_src_mac_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -284,9 +284,9 @@ description = This search returns a list of all email sources seen in the 48 hou disabled = 0 tokens = {\ "inventory_asset_src_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -296,9 +296,9 @@ description = This search allows you to retrieve any modifications to logon righ disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -308,9 +308,9 @@ description = This search allows you to retrieve any modifications to logon righ disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -320,9 +320,9 @@ description = This search queries the notable index and returns all the Notable disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -332,9 +332,9 @@ description = This search queries the notable index to retrieve detailed informa disabled = 0 tokens = {\ "inventory_asset_event_id_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -344,13 +344,13 @@ description = This search returns the information of the users that sent emails disabled = 0 tokens = {\ "inventory_asset_src_user_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_recipient_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -360,13 +360,13 @@ description = This search queries the Endpoint data model to give you details ab disabled = 0 tokens = {\ "inventory_asset_process_name_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -376,13 +376,13 @@ description = This search returns the file activity for a specific process on a disabled = 0 tokens = {\ "inventory_asset_process_id_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -392,13 +392,13 @@ description = This search queries the Endpoint data model to give you details ab disabled = 0 tokens = {\ "inventory_asset_process_name_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -408,13 +408,13 @@ description = This search will return information about the process associated w disabled = 0 tokens = {\ "inventory_asset_dest_port_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -424,13 +424,13 @@ description = This search returns the registry activity for a specific process o disabled = 0 tokens = {\ "inventory_asset_process_id_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -440,9 +440,9 @@ description = While investigating, an analyst will want to know what process and disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -452,9 +452,9 @@ description = This search queries the Endpoint Datamodel to give you details of disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -464,9 +464,9 @@ description = For the last 7 days, the search will query the Risk data model in disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -476,9 +476,9 @@ description = For the last 7 days, the search will query the Risk data model in disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -488,13 +488,13 @@ description = This search queries Sysmon WMI events for the host of interest. disabled = 0 tokens = {\ "inventory_asset_process_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -504,9 +504,9 @@ description = This search will tell you give you the update logs for a specific disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -516,9 +516,9 @@ description = Gather more information about the user identified in the Notable E disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -528,9 +528,9 @@ description = This search will show you any vulnerabilities noted for a specific disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -540,9 +540,9 @@ description = This search helps an analyst investigate a notable event to find o disabled = 0 tokens = {\ "inventory_asset_session_id_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -552,9 +552,9 @@ description = This search lists all the users performing a list image operation disabled = 0 tokens = {\ "inventory_asset_Compute.event_name_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -564,9 +564,9 @@ description = This search lists all the logged CloudTrail activities by a specif disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -576,9 +576,9 @@ description = This search lists all the user activities logged by CloudTrail for disabled = 0 tokens = {\ "inventory_asset_awsRegion_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -588,9 +588,9 @@ description = This search returns a logs of events that operated on the compute disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -600,9 +600,9 @@ description = This search returns failed logins to multiple destinations by user disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -612,9 +612,9 @@ description = This search allows you to find all the network traffic from a spec disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -624,9 +624,9 @@ description = This search returns all okta events from a specific IP address. disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -636,9 +636,9 @@ description = This search returns all okta events associated with a specific app disabled = 0 tokens = {\ "inventory_asset_app_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -648,9 +648,9 @@ description = This search hunts for dumped NTLM hashes used for pass the hash. disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -660,9 +660,9 @@ description = This search hunts for dumped kerberos ticket from LSASS memory. disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -672,9 +672,9 @@ description = This search returns previous unseen user, which didn't log in for disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -684,9 +684,9 @@ description = This search returns the source, destination, and user for all succ disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -696,13 +696,13 @@ description = This search helps an analyst investigate a notable event related t disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_dest_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -712,13 +712,13 @@ description = This search lists all the logged cloud infrastructure activities b disabled = 0 tokens = {\ "inventory_asset_region_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_src_user_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -728,9 +728,9 @@ description = This search returns all okta events by a specific user disabled = 0 tokens = {\ "inventory_identity_user_filter": {\ - "valueType": "primitive",\ - "value": "identity"\ - }\ + "valueType": "primitive",\ + "value": "identity"\ + }\ }\ @@ -740,13 +740,13 @@ description = This search lists all the logged cloud infrastructure activities b disabled = 0 tokens = {\ "inventory_asset_region_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\, + "valueType": "primitive",\ + "value": "asset"\ + }\, "inventory_asset_src_user_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -756,9 +756,9 @@ description = This search allows you to find all the web activity from a specifi disabled = 0 tokens = {\ "inventory_asset_dest_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -768,9 +768,9 @@ description = This search searches for all web activity from a specific host. Du disabled = 0 tokens = {\ "inventory_asset_src_ip_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -780,9 +780,9 @@ description = This investigative search retrieves POST requests from a specified disabled = 0 tokens = {\ "inventory_asset_src_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ @@ -792,9 +792,9 @@ description = Analyze the Process Chain and identify the malicious file. By anal disabled = 0 tokens = {\ "inventory_asset_process_guid_filter": {\ - "valueType": "primitive",\ - "value": "asset"\ - }\ + "valueType": "primitive",\ + "value": "asset"\ + }\ }\ diff --git a/package/default/macros.conf b/package/default/macros.conf index 80b4883423..f277a69a4e 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:19:19 UTC +# On Date: 2020-05-12T12:31:52 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 8956d6fd12..d32a7a01dc 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:19:19 UTC +# On Date: 2020-05-12T12:31:52 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index c8db18a5a5..d81d621e85 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:19:19 UTC +# On Date: 2020-05-12T12:31:52 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 12b0c266db..fbb7aab440 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:19:19 UTC +# On Date: 2020-05-12T12:31:52 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] +searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From City"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Web POSTs From src", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info"] +searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Process Info"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host"] +searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +searches = ["ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Notable History"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info"] +searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Info"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From b332406c91f6fd33bfade27f0f4a3e50a5eb2935 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 12 May 2020 14:43:24 +0200 Subject: [PATCH 47/93] bug in generate --- bin/jinja2_templates/es_investigations.j2 | 20 +- package/default/analytic_stories.conf | 122 ++--- package/default/es_investigations.conf | 614 ++++++++++++++++------ package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 128 ++--- 7 files changed, 597 insertions(+), 293 deletions(-) diff --git a/bin/jinja2_templates/es_investigations.j2 b/bin/jinja2_templates/es_investigations.j2 index bfe484889d..6c685678d6 100644 --- a/bin/jinja2_templates/es_investigations.j2 +++ b/bin/jinja2_templates/es_investigations.j2 @@ -6,14 +6,22 @@ disabled = 0 tokens = {\ {% for token in response_task.inputs %} {% if token == 'user' %} - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ - }\{% else %} - "inventory_asset_{{ token }}_filter": {\ + "value": "identity",\ + "default": "_1!=1"\ + }{% else %} + "inventory_asset_{{ token }}_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\{% endif %}{{ "," if not loop.last }} + "value": "asset",\ + "default": "_1!=1"\ + }{% endif %}{{ "," if not loop.last }}\ {% endfor %} }\ diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index fe60f3efec..184f8e25ce 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:31:52 UTC +# On Date: 2020-05-12T12:42:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] +investigative_searches = ["ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] +investigative_searches = ["ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 096d19aac5..81e00f0c0a 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -3,9 +3,13 @@ label = AWS Investigate User Activities By ARN description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ + "value": "identity",\ + "default": "_1!=1"\ }\ }\ @@ -15,9 +19,13 @@ label = AWS Investigate User Activities By AccessKeyId description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. disabled = 0 tokens = {\ - "inventory_asset_accessKeyId_filter": {\ + "inventory_asset_accessKeyId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -27,9 +35,13 @@ label = AWS Investigate User Activities By Source User description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -39,9 +51,13 @@ label = AWS Network ACL Details from ID description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID disabled = 0 tokens = {\ - "inventory_asset_networkAclId_filter": {\ + "inventory_asset_networkAclId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -51,9 +67,13 @@ label = AWS Network Interface details via resourceId description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. disabled = 0 tokens = {\ - "inventory_asset_resourceId_filter": {\ + "inventory_asset_resourceId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -63,9 +83,13 @@ label = AWS S3 Bucket details via bucketName description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. disabled = 0 tokens = {\ - "inventory_asset_bucketName_filter": {\ + "inventory_asset_bucketName_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -75,9 +99,13 @@ label = All backup logs for host description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -87,9 +115,13 @@ label = Amazon EKS Kubernetes activity by src ip description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -99,9 +131,13 @@ label = GCP Kubernetes activity by src ip description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -111,9 +147,13 @@ label = Get All AWS Activity From City description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_City_filter": {\ + "inventory_asset_City_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -123,9 +163,13 @@ label = Get All AWS Activity From Country description = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_Country_filter": {\ + "inventory_asset_Country_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -135,9 +179,13 @@ label = Get All AWS Activity From IP Address description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -147,9 +195,13 @@ label = Get All AWS Activity From Region description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_Region_filter": {\ + "inventory_asset_Region_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -159,9 +211,13 @@ label = Get Authentication Logs For Endpoint description = This search returns all users that have attempted to access a particular endpoint. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -171,9 +227,13 @@ label = Get Backup Logs For Endpoint description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -183,9 +243,13 @@ label = Get Certificate logs for a domain description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. disabled = 0 tokens = {\ - "inventory_asset_domain_filter": {\ + "inventory_asset_domain_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -195,9 +259,13 @@ label = Get DNS Server History for a host description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -207,13 +275,21 @@ label = Get DNS traffic ratio description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_ip_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -223,9 +299,13 @@ label = Get EC2 Instance Details by instanceId description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field disabled = 0 tokens = {\ - "inventory_asset_instanceId_filter": {\ + "inventory_asset_instanceId_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -235,9 +315,13 @@ label = Get EC2 Launch Details description = This search returns some of the launch details for a EC2 instance. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -247,9 +331,13 @@ label = Get Email Info description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. disabled = 0 tokens = {\ - "inventory_asset_message_id_filter": {\ + "inventory_asset_message_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -259,9 +347,13 @@ label = Get Emails From Specific Sender description = This search returns all the emails from a specific sender over the last 24 and next hours. disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -271,9 +363,13 @@ label = Get First Occurrence and Last Occurrence of a MAC Address description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. disabled = 0 tokens = {\ - "inventory_asset_src_mac_filter": {\ + "inventory_asset_src_mac_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -283,9 +379,13 @@ label = Get History Of Email Sources description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. disabled = 0 tokens = {\ - "inventory_asset_src_filter": {\ + "inventory_asset_src_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -295,9 +395,13 @@ label = Get Logon Rights Modifications For Endpoint description = This search allows you to retrieve any modifications to logon rights associated with a specific host. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -307,9 +411,13 @@ label = Get Logon Rights Modifications For User description = This search allows you to retrieve any modifications to logon rights for a specific user account. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ + "value": "identity",\ + "default": "_1!=1"\ }\ }\ @@ -319,9 +427,13 @@ label = Get Notable History description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -331,9 +443,13 @@ label = Get Notable Info description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. disabled = 0 tokens = {\ - "inventory_asset_event_id_filter": {\ + "inventory_asset_event_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -343,13 +459,21 @@ label = Get Outbound Emails to Hidden Cobra Threat Actors description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_recipient_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_recipient_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -359,13 +483,21 @@ label = Get Parent Process Info description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest disabled = 0 tokens = {\ - "inventory_asset_process_name_filter": {\ + "inventory_asset_process_name_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -375,13 +507,21 @@ label = Get Process File Activity description = This search returns the file activity for a specific process on a specific endpoint disabled = 0 tokens = {\ - "inventory_asset_process_id_filter": {\ + "inventory_asset_process_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -391,13 +531,21 @@ label = Get Process Info description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. disabled = 0 tokens = {\ - "inventory_asset_process_name_filter": {\ + "inventory_asset_process_name_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -407,13 +555,21 @@ label = Get Process Information For Port Activity description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. disabled = 0 tokens = {\ - "inventory_asset_dest_port_filter": {\ + "inventory_asset_dest_port_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -423,13 +579,21 @@ label = Get Process Registry Activity description = This search returns the registry activity for a specific process on a specific endpoint disabled = 0 tokens = {\ - "inventory_asset_process_id_filter": {\ + "inventory_asset_process_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -439,9 +603,13 @@ label = Get Process Responsible For The DNS Traffic description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -451,9 +619,13 @@ label = Get Registry Activities description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -463,9 +635,13 @@ label = Get Risk Modifiers For Endpoint description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -475,9 +651,13 @@ label = Get Risk Modifiers For User description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ + "value": "identity",\ + "default": "_1!=1"\ }\ }\ @@ -487,13 +667,21 @@ label = Get Sysmon WMI Activity for Host description = This search queries Sysmon WMI events for the host of interest. disabled = 0 tokens = {\ - "inventory_asset_process_filter": {\ + "inventory_asset_process_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -503,9 +691,13 @@ label = Get Update Logs For Endpoint description = This search will tell you give you the update logs for a specific endpoint for the last week. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -515,9 +707,13 @@ label = Get User Information from Identity Table description = Gather more information about the user identified in the Notable Event. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ + "value": "identity",\ + "default": "_1!=1"\ }\ }\ @@ -527,9 +723,13 @@ label = Get Vulnerability Logs For Endpoint description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -539,9 +739,13 @@ label = Get Web Session Information via session id description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. disabled = 0 tokens = {\ - "inventory_asset_session_id_filter": {\ + "inventory_asset_session_id_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -551,9 +755,13 @@ label = Investigate AWS ECR container listing activity description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. disabled = 0 tokens = {\ - "inventory_asset_Compute.event_name_filter": {\ + "inventory_asset_Compute.event_name_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -563,9 +771,13 @@ label = Investigate AWS User Activities by user field description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ + "value": "identity",\ + "default": "_1!=1"\ }\ }\ @@ -575,9 +787,13 @@ label = Investigate AWS activities via region name description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user disabled = 0 tokens = {\ - "inventory_asset_awsRegion_filter": {\ + "inventory_asset_awsRegion_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -587,9 +803,13 @@ label = Investigate Cloud Compute Instance Activities description = This search returns a logs of events that operated on the compute instance. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -599,9 +819,13 @@ label = Investigate Failed Logins for Multiple Destinations description = This search returns failed logins to multiple destinations by user. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -611,9 +835,13 @@ label = Investigate Network Traffic From src ip description = This search allows you to find all the network traffic from a specific IP address. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -623,9 +851,13 @@ label = Investigate Okta Activity by IP Address description = This search returns all okta events from a specific IP address. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ + "value": "identity",\ + "default": "_1!=1"\ }\ }\ @@ -635,9 +867,13 @@ label = Investigate Okta Activity by app description = This search returns all okta events associated with a specific app disabled = 0 tokens = {\ - "inventory_asset_app_filter": {\ + "inventory_asset_app_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -647,9 +883,13 @@ label = Investigate Pass the Hash Attempts description = This search hunts for dumped NTLM hashes used for pass the hash. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -659,9 +899,13 @@ label = Investigate Pass the Ticket Attempts description = This search hunts for dumped kerberos ticket from LSASS memory. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -671,9 +915,13 @@ label = Investigate Previous Unseen User description = This search returns previous unseen user, which didn't log in for 30 days. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -683,9 +931,13 @@ label = Investigate Successful Remote Desktop Authentications description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -695,13 +947,21 @@ label = Investigate Suspicious Strings in HTTP Header description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_dest_ip_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_dest_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -711,13 +971,21 @@ label = Investigate User Activities In All Cloud Regions description = This search lists all the logged cloud infrastructure activities by a specific cloud user disabled = 0 tokens = {\ - "inventory_asset_region_filter": {\ + "inventory_asset_region_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_src_user_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -727,9 +995,13 @@ label = Investigate User Activities In Okta description = This search returns all okta events by a specific user disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "inventory_identity_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "identity"\ + "value": "identity",\ + "default": "_1!=1"\ }\ }\ @@ -739,13 +1011,21 @@ label = Investigate User Activities In Single Cloud Region description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region disabled = 0 tokens = {\ - "inventory_asset_region_filter": {\ + "inventory_asset_region_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ - }\, - "inventory_asset_src_user_filter": {\ + "value": "asset",\ + "default": "_1!=1"\ + },\ + "inventory_asset_src_user_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -755,9 +1035,13 @@ label = Investigate Web Activity From Host description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "inventory_asset_dest_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -767,9 +1051,13 @@ label = Investigate Web Activity From src ip description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "inventory_asset_src_ip_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -779,9 +1067,13 @@ label = Investigate Web POSTs From src description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. disabled = 0 tokens = {\ - "inventory_asset_src_filter": {\ + "inventory_asset_src_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ @@ -791,9 +1083,13 @@ label = Process Chain Analysis description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. disabled = 0 tokens = {\ - "inventory_asset_process_guid_filter": {\ + "inventory_asset_process_guid_filter": {\ + "valuePrefix": "",\ + "valueSuffix": "",\ + "delimiter": " OR ",\ "valueType": "primitive",\ - "value": "asset"\ + "value": "asset",\ + "default": "_1!=1"\ }\ }\ diff --git a/package/default/macros.conf b/package/default/macros.conf index f277a69a4e..722eeba32c 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:31:52 UTC +# On Date: 2020-05-12T12:42:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index d32a7a01dc..925e95d977 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:31:52 UTC +# On Date: 2020-05-12T12:42:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index d81d621e85..65a6875798 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:31:52 UTC +# On Date: 2020-05-12T12:42:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index fbb7aab440..c64bfab184 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:31:52 UTC +# On Date: 2020-05-12T12:42:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] +searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions"] +searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Creation of Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Notable Info", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] +searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - TOR Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Investigate Successful Remote Desktop Authentications"] +searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Emails From Specific Sender", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 4836bad27e7cc23ae3e0540d8c249695c04d4f5b Mon Sep 17 00:00:00 2001 From: bpatel Date: Tue, 12 May 2020 12:28:04 -0700 Subject: [PATCH 48/93] removing deprecated html files --- package/default/data/ui/alerts/escu_contextualize.html | 2 -- package/default/data/ui/alerts/escu_investigate.html | 2 -- 2 files changed, 4 deletions(-) delete mode 100644 package/default/data/ui/alerts/escu_contextualize.html delete mode 100644 package/default/data/ui/alerts/escu_investigate.html diff --git a/package/default/data/ui/alerts/escu_contextualize.html b/package/default/data/ui/alerts/escu_contextualize.html deleted file mode 100644 index c46913dea7..0000000000 --- a/package/default/data/ui/alerts/escu_contextualize.html +++ /dev/null @@ -1,2 +0,0 @@ -
-
diff --git a/package/default/data/ui/alerts/escu_investigate.html b/package/default/data/ui/alerts/escu_investigate.html deleted file mode 100644 index c46913dea7..0000000000 --- a/package/default/data/ui/alerts/escu_investigate.html +++ /dev/null @@ -1,2 +0,0 @@ -
-
From f37525692504006e081938cbfd5978786adff77c Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 13 May 2020 10:10:42 +0200 Subject: [PATCH 49/93] bug in generate --- bin/generate.py | 18 +- bin/jinja2_templates/es_investigations.j2 | 15 +- package/default/analytic_stories.conf | 118 ++-- .../ui/panels/all_backup_logs_for_host.xml | 9 - ...azon_eks_kubernetes_activity_by_src_ip.xml | 9 - ...stigate_user_activities_by_accesskeyid.xml | 9 - ...aws_investigate_user_activities_by_arn.xml | 9 - ...stigate_user_activities_by_source_user.xml | 9 - .../aws_network_acl_details_from_id.xml | 9 - ...twork_interface_details_via_resourceid.xml | 9 - .../aws_s3_bucket_details_via_bucketname.xml | 9 - .../gcp_kubernetes_activity_by_src_ip.xml | 9 - .../panels/get_all_aws_activity_from_city.xml | 9 - .../get_all_aws_activity_from_country.xml | 9 - .../get_all_aws_activity_from_ip_address.xml | 9 - .../get_all_aws_activity_from_region.xml | 9 - .../get_authentication_logs_for_endpoint.xml | 9 - .../panels/get_backup_logs_for_endpoint.xml | 9 - .../get_certificate_logs_for_a_domain.xml | 9 - .../get_dns_server_history_for_a_host.xml | 9 - .../data/ui/panels/get_dns_traffic_ratio.xml | 9 - ...get_ec2_instance_details_by_instanceid.xml | 9 - .../data/ui/panels/get_ec2_launch_details.xml | 9 - .../default/data/ui/panels/get_email_info.xml | 9 - .../get_emails_from_specific_sender.xml | 9 - ...e_and_last_occurrence_of_a_mac_address.xml | 9 - .../panels/get_history_of_email_sources.xml | 9 - ...ogon_rights_modifications_for_endpoint.xml | 9 - ...et_logon_rights_modifications_for_user.xml | 9 - .../data/ui/panels/get_notable_history.xml | 9 - .../data/ui/panels/get_notable_info.xml | 9 - ...d_emails_to_hidden_cobra_threat_actors.xml | 9 - .../ui/panels/get_parent_process_info.xml | 9 - .../ui/panels/get_process_file_activity.xml | 9 - .../data/ui/panels/get_process_info.xml | 9 - ..._process_information_for_port_activity.xml | 9 - .../panels/get_process_registry_activity.xml | 9 - ...rocess_responsible_for_the_dns_traffic.xml | 9 - .../ui/panels/get_registry_activities.xml | 9 - .../get_risk_modifiers_for_endpoint.xml | 9 - .../ui/panels/get_risk_modifiers_for_user.xml | 9 - .../get_sysmon_wmi_activity_for_host.xml | 9 - .../panels/get_update_logs_for_endpoint.xml | 9 - ...t_user_information_from_identity_table.xml | 9 - .../get_vulnerability_logs_for_endpoint.xml | 9 - ...web_session_information_via_session_id.xml | 9 - ...stigate_aws_activities_via_region_name.xml | 9 - ...ate_aws_ecr_container_listing_activity.xml | 9 - ...gate_aws_user_activities_by_user_field.xml | 9 - ...gate_cloud_compute_instance_activities.xml | 9 - ...ailed_logins_for_multiple_destinations.xml | 9 - ...nvestigate_network_traffic_from_src_ip.xml | 9 - .../investigate_okta_activity_by_app.xml | 9 - ...nvestigate_okta_activity_by_ip_address.xml | 9 - .../investigate_pass_the_hash_attempts.xml | 9 - .../investigate_pass_the_ticket_attempts.xml | 9 - .../investigate_previous_unseen_user.xml | 9 - ...cessful_remote_desktop_authentications.xml | 9 - ...gate_suspicious_strings_in_http_header.xml | 9 - ...e_user_activities_in_all_cloud_regions.xml | 9 - .../investigate_user_activities_in_okta.xml | 9 - ...user_activities_in_single_cloud_region.xml | 9 - .../investigate_web_activity_from_host.xml | 9 - .../investigate_web_activity_from_src_ip.xml | 9 - .../panels/investigate_web_posts_from_src.xml | 9 - .../data/ui/panels/process_chain_analysis.xml | 9 - package/default/es_investigations.conf | 541 +++++++++++++++--- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 124 ++-- 71 files changed, 619 insertions(+), 770 deletions(-) delete mode 100644 package/default/data/ui/panels/all_backup_logs_for_host.xml delete mode 100644 package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml delete mode 100644 package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml delete mode 100644 package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml delete mode 100644 package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml delete mode 100644 package/default/data/ui/panels/aws_network_acl_details_from_id.xml delete mode 100644 package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml delete mode 100644 package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml delete mode 100644 package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml delete mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_city.xml delete mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_country.xml delete mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml delete mode 100644 package/default/data/ui/panels/get_all_aws_activity_from_region.xml delete mode 100644 package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml delete mode 100644 package/default/data/ui/panels/get_backup_logs_for_endpoint.xml delete mode 100644 package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml delete mode 100644 package/default/data/ui/panels/get_dns_server_history_for_a_host.xml delete mode 100644 package/default/data/ui/panels/get_dns_traffic_ratio.xml delete mode 100644 package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml delete mode 100644 package/default/data/ui/panels/get_ec2_launch_details.xml delete mode 100644 package/default/data/ui/panels/get_email_info.xml delete mode 100644 package/default/data/ui/panels/get_emails_from_specific_sender.xml delete mode 100644 package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml delete mode 100644 package/default/data/ui/panels/get_history_of_email_sources.xml delete mode 100644 package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml delete mode 100644 package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml delete mode 100644 package/default/data/ui/panels/get_notable_history.xml delete mode 100644 package/default/data/ui/panels/get_notable_info.xml delete mode 100644 package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml delete mode 100644 package/default/data/ui/panels/get_parent_process_info.xml delete mode 100644 package/default/data/ui/panels/get_process_file_activity.xml delete mode 100644 package/default/data/ui/panels/get_process_info.xml delete mode 100644 package/default/data/ui/panels/get_process_information_for_port_activity.xml delete mode 100644 package/default/data/ui/panels/get_process_registry_activity.xml delete mode 100644 package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml delete mode 100644 package/default/data/ui/panels/get_registry_activities.xml delete mode 100644 package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml delete mode 100644 package/default/data/ui/panels/get_risk_modifiers_for_user.xml delete mode 100644 package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml delete mode 100644 package/default/data/ui/panels/get_update_logs_for_endpoint.xml delete mode 100644 package/default/data/ui/panels/get_user_information_from_identity_table.xml delete mode 100644 package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml delete mode 100644 package/default/data/ui/panels/get_web_session_information_via_session_id.xml delete mode 100644 package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml delete mode 100644 package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml delete mode 100644 package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml delete mode 100644 package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml delete mode 100644 package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml delete mode 100644 package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml delete mode 100644 package/default/data/ui/panels/investigate_okta_activity_by_app.xml delete mode 100644 package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml delete mode 100644 package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml delete mode 100644 package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml delete mode 100644 package/default/data/ui/panels/investigate_previous_unseen_user.xml delete mode 100644 package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml delete mode 100644 package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml delete mode 100644 package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml delete mode 100644 package/default/data/ui/panels/investigate_user_activities_in_okta.xml delete mode 100644 package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml delete mode 100644 package/default/data/ui/panels/investigate_web_activity_from_host.xml delete mode 100644 package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml delete mode 100644 package/default/data/ui/panels/investigate_web_posts_from_src.xml delete mode 100644 package/default/data/ui/panels/process_chain_analysis.xml diff --git a/bin/generate.py b/bin/generate.py index 723096e462..709cba02dc 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -207,7 +207,19 @@ def generate_macros_conf(macros, detections): return output_path -def generate_workbench_panels(response_tasks): +def generate_workbench_panels(response_tasks, stories): + + sto_res = map_response_tasks_to_stories(response_tasks) + + for story in stories: + if story['name'] in sto_res: + response_task_names = list(sto_res[story['name']]) + story['workbench_panels'] = [] + for response_task_name in response_task_names: + str = 'panel://workbench_panel_' + response_task_name[7:].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + story['workbench_panels'].append(str) + story['lowercase_name'] = story['name'].replace(' ', '_').replace('-','_').replace('.','_').replace('/','_').lower() + workbench_panel_objects = [] for response_task in response_tasks: if 'search' in response_task: @@ -227,7 +239,7 @@ def generate_workbench_panels(response_tasks): trim_blocks=True) template = j2_env.get_template('es_investigations.j2') output_path = OUTPUT_PATH + "/default/es_investigations.conf" - output = template.render(response_tasks=workbench_panel_objects) + output = template.render(response_tasks=workbench_panel_objects, stories=stories) with open(output_path, 'w') as f: f.write(output) @@ -438,7 +450,7 @@ if __name__ == "__main__": macros = sorted(macros, key=lambda m: m['name']) macros_path = generate_macros_conf(macros, detections) - generate_workbench_panels(response_tasks) + generate_workbench_panels(response_tasks, stories) if VERBOSE: print("{0} stories have been successfully written to {1}".format(len(stories), story_path)) diff --git a/bin/jinja2_templates/es_investigations.j2 b/bin/jinja2_templates/es_investigations.j2 index 6c685678d6..865efd48ec 100644 --- a/bin/jinja2_templates/es_investigations.j2 +++ b/bin/jinja2_templates/es_investigations.j2 @@ -1,3 +1,14 @@ + +{% for story in stories %} +[panel_group://workbench_panel_group_{{ story.lowercase_name}}] +label = {{ story.name }} +description = {{ story.description }} +disabled = 0 +panels = {{ story.workbench_panels | tojson }} + +{% endfor %} + + {% for response_task in response_tasks %} [panel://workbench_panel_{{ response_task.lowercase_name }}] label = {{ response_task.name }} @@ -6,7 +17,7 @@ disabled = 0 tokens = {\ {% for token in response_task.inputs %} {% if token == 'user' %} - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -14,7 +25,7 @@ tokens = {\ "value": "identity",\ "default": "_1!=1"\ }{% else %} - "inventory_asset_{{ token }}_filter": {\ + "{{ token }}": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 184f8e25ce..c06c360904 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:42:45 UTC +# On Date: 2020-05-13T08:09:53 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] +investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -86,7 +86,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Process Registry Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/data/ui/panels/all_backup_logs_for_host.xml b/package/default/data/ui/panels/all_backup_logs_for_host.xml deleted file mode 100644 index 1ff29ae929..0000000000 --- a/package/default/data/ui/panels/all_backup_logs_for_host.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype="netbackup_logs" dest=$dest$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml b/package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml deleted file mode 100644 index e09827e48a..0000000000 --- a/package/default/data/ui/panels/amazon_eks_kubernetes_activity_by_src_ip.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - sourcetype="aws:cloudwatchlogs:eks" sourceIPs{}=$src_ip$|rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(user.username) values(requestURI) values(verb) values(userAgent) by source annotations.authorization.k8s.io/decision src_ip - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml b/package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml deleted file mode 100644 index 10bb4cee2d..0000000000 --- a/package/default/data/ui/panels/aws_investigate_user_activities_by_accesskeyid.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail userIdentity.accessKeyId=$accessKeyId$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml b/package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml deleted file mode 100644 index fec847550b..0000000000 --- a/package/default/data/ui/panels/aws_investigate_user_activities_by_arn.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail userIdentity.arn=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml b/package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml deleted file mode 100644 index ff7ad317cd..0000000000 --- a/package/default/data/ui/panels/aws_investigate_user_activities_by_source_user.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail userIdentity.arn=$src_user$ | spath output=user path=userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, awsRegion, eventName, errorCode, errorMessage - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_network_acl_details_from_id.xml b/package/default/data/ui/panels/aws_network_acl_details_from_id.xml deleted file mode 100644 index e637d48978..0000000000 --- a/package/default/data/ui/panels/aws_network_acl_details_from_id.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:description id=$networkAclId$ | table id account_id vpc_id network_acl_entries{}.* - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml b/package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml deleted file mode 100644 index 804d19a1d0..0000000000 --- a/package/default/data/ui/panels/aws_network_interface_details_via_resourceid.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:config resourceId=$resourceId$ | table _time ARN relationships{}.resourceType relationships{}.name relationships{}.resourceId configuration.privateIpAddresses{}.privateIpAddress configuration.privateIpAddresses{}.association.publicIp - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml b/package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml deleted file mode 100644 index 22732ef048..0000000000 --- a/package/default/data/ui/panels/aws_s3_bucket_details_via_bucketname.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:config resourceId=$bucketName$ | table resourceCreationTime resourceId awsRegion action aws_account_id supplementaryConfiguration.AccessControlList - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml b/package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml deleted file mode 100644 index 568cd26380..0000000000 --- a/package/default/data/ui/panels/gcp_kubernetes_activity_by_src_ip.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - sourcetype="google:gcp:pubsub:message" data.protoPayload.requestMetadata.callerIp={src_ip} | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_names values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent values(data.protoPayload.authenticationInfo.principalEmail) as user values(data.protoPayload.status.message) by src_ip data.resource.labels.cluster_name data.resource.type - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_city.xml b/package/default/data/ui/panels/get_all_aws_activity_from_city.xml deleted file mode 100644 index 000cfe9942..0000000000 --- a/package/default/data/ui/panels/get_all_aws_activity_from_city.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search City=$City$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, City, user, userName, userType, src_ip, awsRegion, eventName, errorCode - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_country.xml b/package/default/data/ui/panels/get_all_aws_activity_from_country.xml deleted file mode 100644 index 9830b3459d..0000000000 --- a/package/default/data/ui/panels/get_all_aws_activity_from_country.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Country=$Country$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Country, user, userName, userType, src_ip, awsRegion, eventName, errorCode - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml b/package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml deleted file mode 100644 index 008d268420..0000000000 --- a/package/default/data/ui/panels/get_all_aws_activity_from_ip_address.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search sourceIPAddress=$src_ip$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, user, userName, userType, src_ip, awsRegion, eventName, errorCode - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_all_aws_activity_from_region.xml b/package/default/data/ui/panels/get_all_aws_activity_from_region.xml deleted file mode 100644 index 4a7a1cdb76..0000000000 --- a/package/default/data/ui/panels/get_all_aws_activity_from_region.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail | iplocation sourceIPAddress | search Region=$Region$ | spath output=user path=userIdentity.arn | spath output=awsUserName path=userIdentity.userName | spath output=userType path=userIdentity.type | rename sourceIPAddress as src_ip | table _time, Region, user, userName, userType, src_ip, awsRegion, eventName, errorCode - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml b/package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml deleted file mode 100644 index 46d2d923ff..0000000000 --- a/package/default/data/ui/panels/get_authentication_logs_for_endpoint.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats count from datamodel=Authentication where Authentication.dest=$dest$ by _time, Authentication.dest, Authentication.user, Authentication.app, Authentication.action | `drop_dm_object_name("Authentication")` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_backup_logs_for_endpoint.xml b/package/default/data/ui/panels/get_backup_logs_for_endpoint.xml deleted file mode 100644 index afdbeba57d..0000000000 --- a/package/default/data/ui/panels/get_backup_logs_for_endpoint.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype="netbackup_logs" COMPUTERNAME=$dest$ | rename COMPUTERNAME as dest, MESSAGE as signature | table _time, dest, signature - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml b/package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml deleted file mode 100644 index 2b6d49308a..0000000000 --- a/package/default/data/ui/panels/get_certificate_logs_for_a_domain.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Certificates.All_Certificates where All_Certificates.SSL.ssl_subject_common_name=*$domain$ by All_Certificates.dest All_Certificates.src All_Certificates.SSL.ssl_issuer_common_name All_Certificates.SSL.ssl_subject_common_name All_Certificates.SSL.ssl_hash | `drop_dm_object_name(All_Certificates)` | `drop_dm_object_name(SSL)` | rename ssl_subject_common_name as domain | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_dns_server_history_for_a_host.xml b/package/default/data/ui/panels/get_dns_server_history_for_a_host.xml deleted file mode 100644 index 1039a71369..0000000000 --- a/package/default/data/ui/panels/get_dns_server_history_for_a_host.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search tag=dns src_ip=$src_ip$ dest_port=53 | streamstats time_window=1d count values(dest_ip) as dcip by src_ip | table date_mday src_ip dcip count | sort -count - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_dns_traffic_ratio.xml b/package/default/data/ui/panels/get_dns_traffic_ratio.xml deleted file mode 100644 index dc42dd8e39..0000000000 --- a/package/default/data/ui/panels/get_dns_traffic_ratio.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats allow_old_summaries=true sum(All_Traffic.bytes_out) as "bytes_out" sum(All_Traffic.bytes_in) as "bytes_in" from datamodel=Network_Traffic where nodename=All_Traffic All_Traffic.dest_port=53 All_Traffic.src=$src_ip$ All_Traffic.dest=$dest_ip$ | eval ratio = (bytes_out/bytes_in) | table ratio - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml b/package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml deleted file mode 100644 index 7dbc21d376..0000000000 --- a/package/default/data/ui/panels/get_ec2_instance_details_by_instanceid.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype="aws:description" source="*:ec2_instances"| dedup id sortby -_time | search id=$instanceId$ | spath output=tags path=tags | eval tags=mvzip(key,value," = "), ip_address=if((ip_address == "null"),private_ip_address,ip_address) | table id, tags.Name, aws_account_id, placement, instance_type, key_name, ip_address, launch_time, state, vpc_id, subnet_id, tags | rename aws_account_id as "Account ID", id as ID, instance_type as Type, ip_address as "IP Address", key_name as "Key Pair", launch_time as "Launch Time", placement as "Availability Zone", state as State, subnet_id as Subnet, "tags.Name" as Name, vpc_id as VPC - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_ec2_launch_details.xml b/package/default/data/ui/panels/get_ec2_launch_details.xml deleted file mode 100644 index e7f2a45294..0000000000 --- a/package/default/data/ui/panels/get_ec2_launch_details.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail responseElements.instancesSet.items{}.instanceId=$dest$ |rename userIdentity.arn as arn, responseElements.instancesSet.items{}.instanceId as instanceId, responseElements.instancesSet.items{}.privateIpAddress as privateIpAddress, responseElements.instancesSet.items{}.imageId as amiID, responseElements.instancesSet.items{}.architecture as architecture, responseElements.instancesSet.items{}.keyName as keyName | table arn, awsRegion, instanceId, architecture, privateIpAddress, amiID, keyName - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_email_info.xml b/package/default/data/ui/panels/get_email_info.xml deleted file mode 100644 index 6afb5067bf..0000000000 --- a/package/default/data/ui/panels/get_email_info.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Email.All_Email | search message_id=$message_id$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_emails_from_specific_sender.xml b/package/default/data/ui/panels/get_emails_from_specific_sender.xml deleted file mode 100644 index 21a977f746..0000000000 --- a/package/default/data/ui/panels/get_emails_from_specific_sender.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Email.All_Email | search src_user=$src_user$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml b/package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml deleted file mode 100644 index e92d6d3f65..0000000000 --- a/package/default/data/ui/panels/get_first_occurrence_and_last_occurrence_of_a_mac_address.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Network_Sessions where nodename=All_Sessions.DHCP All_Sessions.signature=DHCPREQUEST All_Sessions.All_Sessions.src_mac= $src_mac$ by All_Sessions.src_ip All_Sessions.user | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_history_of_email_sources.xml b/package/default/data/ui/panels/get_history_of_email_sources.xml deleted file mode 100644 index 8d26ae3247..0000000000 --- a/package/default/data/ui/panels/get_history_of_email_sources.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - |tstats `security_content_summariesonly` values(All_Email.dest) as dest values(All_Email.recipient) as recepient min(_time) as firstTime max(_time) as lastTime count from datamodel=Email.All_Email by All_Email.src |`drop_dm_object_name(All_Email)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml b/package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml deleted file mode 100644 index a3068ae9c1..0000000000 --- a/package/default/data/ui/panels/get_logon_rights_modifications_for_endpoint.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) dest=$dest$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml b/package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml deleted file mode 100644 index 3c8c81230b..0000000000 --- a/package/default/data/ui/panels/get_logon_rights_modifications_for_user.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search eventtype=wineventlog_security (signature_id=4718 OR signature_id=4717) user=$user$ | rename user as "Account Modified" | table _time, dest, "Account Modified", Access_Right, signature - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_notable_history.xml b/package/default/data/ui/panels/get_notable_history.xml deleted file mode 100644 index f4e93f2338..0000000000 --- a/package/default/data/ui/panels/get_notable_history.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search `notable` | search dest=$dest$ | table _time, rule_name, owner, priority, severity, status_description - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_notable_info.xml b/package/default/data/ui/panels/get_notable_info.xml deleted file mode 100644 index 141520df51..0000000000 --- a/package/default/data/ui/panels/get_notable_info.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search `notable_by_id($event_id$)` | table time, rule_name, dest, dest_asset_id, dest_owner, priority, severity, owner, status_description - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml b/package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml deleted file mode 100644 index d67b828a9b..0000000000 --- a/package/default/data/ui/panels/get_outbound_emails_to_hidden_cobra_threat_actors.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Email.All_Email | search recipient=misswang8107@gmail.com OR src_user=redhat@gmail.com | stats count earliest(_time) as firstTime, latest(_time) as lastTime values(dest) values(src) by src_user recipient | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_parent_process_info.xml b/package/default/data/ui/panels/get_parent_process_info.xml deleted file mode 100644 index 09eba16eb6..0000000000 --- a/package/default/data/ui/panels/get_parent_process_info.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = $process_name$ Processes.dest = $dest$ by Processes.user Processes.parent_process_name Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_file_activity.xml b/package/default/data/ui/panels/get_process_file_activity.xml deleted file mode 100644 index 28f5412de6..0000000000 --- a/package/default/data/ui/panels/get_process_file_activity.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` values(Filesystem.file_name) as file_name values(Filesystem.dest) as dest, values(Filesystem.process_id) as process_id from datamodel=Endpoint.Filesystem where Filesystem.dest=$dest$ Filesystem.process_id=$process_id$ by Filesystem.file_path, Filesystem.action, _time | `drop_dm_object_name(Filesystem)` | sort _time | table _time, process_id, dest, action, file_name, file_path - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_info.xml b/package/default/data/ui/panels/get_process_info.xml deleted file mode 100644 index 20d3333796..0000000000 --- a/package/default/data/ui/panels/get_process_info.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Proceses.dest=$dest$ Proceses.process_name=$process_name$ by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_information_for_port_activity.xml b/package/default/data/ui/panels/get_process_information_for_port_activity.xml deleted file mode 100644 index 9898b46006..0000000000 --- a/package/default/data/ui/panels/get_process_information_for_port_activity.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=$dest_port$ by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_registry_activity.xml b/package/default/data/ui/panels/get_process_registry_activity.xml deleted file mode 100644 index e33c11f498..0000000000 --- a/package/default/data/ui/panels/get_process_registry_activity.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` values(Registry.registry_key_name) as registry_key_name, values(Registry.dest) as dest, values(Registry.process_id) as process_id from datamodel=Endpoint.Registry where Registry.process_id=$process_id$ AND Registry.dest=$dest$ by Registry.registry_path, Registry.action, _time | `drop_dm_object_name(Registry)` | sort _time | table _time, process_id, dest, action, registry_key_name, registry_path - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml b/package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml deleted file mode 100644 index 318ae20b38..0000000000 --- a/package/default/data/ui/panels/get_process_responsible_for_the_dns_traffic.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` count min(_time) max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.dest = $dest$ by Processes.parent_process Processes.process_name Processes.user Processes.dest Processes.process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count from datamodel=Endpoint.Ports where Ports.dest_port=53 by Ports.process_id Ports.src | `drop_dm_object_name(Ports)` | rename src as dest] - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_registry_activities.xml b/package/default/data/ui/panels/get_registry_activities.xml deleted file mode 100644 index 73bb5bee45..0000000000 --- a/package/default/data/ui/panels/get_registry_activities.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path values(Registry.registry_key_name) as registry_key_name count FROM datamodel=Endpoint.Registry where Registry.dest = "$dest$" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | join [| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id | `drop_dm_object_name("Processes")`] - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml b/package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml deleted file mode 100644 index f9e4e70b8a..0000000000 --- a/package/default/data/ui/panels/get_risk_modifiers_for_endpoint.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel:Risk.All_Risk | search risk_object_type=system risk_object=$dest$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_risk_modifiers_for_user.xml b/package/default/data/ui/panels/get_risk_modifiers_for_user.xml deleted file mode 100644 index 4dcf2fd577..0000000000 --- a/package/default/data/ui/panels/get_risk_modifiers_for_user.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel:Risk.All_Risk | search risk_object_type=user risk_object=$user$ | stats count sum(risk_score) as risk_score values(search_name) min(_time) as firstTime max(_time) as lastTime by risk_object |`security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml b/package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml deleted file mode 100644 index b4642ac7a7..0000000000 --- a/package/default/data/ui/panels/get_sysmon_wmi_activity_for_host.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - sourcetype="XmlWinEventLog:Microsoft-Windows-Sysmon/Operational" EventCode>18 EventCode<22 host=$dest$ | rename host as dest | table _time, dest, user, Name, Operation, EventType, Type, Query, Consumer, Filter - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_update_logs_for_endpoint.xml b/package/default/data/ui/panels/get_update_logs_for_endpoint.xml deleted file mode 100644 index eb3ee6c657..0000000000 --- a/package/default/data/ui/panels/get_update_logs_for_endpoint.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Updates.Updates | search (vendor_product="Microsoft Windows" OR vendor_product="OSX:Update" OR vendor_product="Linux:Update") dest=$dest$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_user_information_from_identity_table.xml b/package/default/data/ui/panels/get_user_information_from_identity_table.xml deleted file mode 100644 index 9269961083..0000000000 --- a/package/default/data/ui/panels/get_user_information_from_identity_table.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | `identities` | search identity=$user$ | table _time, identity, first, last, email, category, watchlist - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml b/package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml deleted file mode 100644 index 30b224262c..0000000000 --- a/package/default/data/ui/panels/get_vulnerability_logs_for_endpoint.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Vulnerabilities.Vulnerabilities | search dest=$dest$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/get_web_session_information_via_session_id.xml b/package/default/data/ui/panels/get_web_session_information_via_session_id.xml deleted file mode 100644 index 1be6d5c2c1..0000000000 --- a/package/default/data/ui/panels/get_web_session_information_via_session_id.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=stream:http $session_id$ | stats values(url) values(http_user_agent) by src_ip status - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml b/package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml deleted file mode 100644 index 669b2a7e63..0000000000 --- a/package/default/data/ui/panels/investigate_aws_activities_via_region_name.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail awsRegion=$awsRegion$| rename requestParameters.instancesSet.items{}.instanceId as instanceId| stats values(eventName) by userName instanceId - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml b/package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml deleted file mode 100644 index 30e3630ed5..0000000000 --- a/package/default/data/ui/panels/investigate_aws_ecr_container_listing_activity.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.event_name="ListImages" by Compute.image_id Compute.src_user Compute.src Compute.http_user_agent Compute.user_type | rename "Compute.*" as * |stats values(http_user_agent) as http_user_agent distinct_count(http_user_agent) as unique_ua_count by src_user, image_id, src, user_type | where unique_ua_count > 1 - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml b/package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml deleted file mode 100644 index a4b65f0856..0000000000 --- a/package/default/data/ui/panels/investigate_aws_user_activities_by_user_field.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=aws:cloudtrail user=$user$ | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml b/package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml deleted file mode 100644 index 5a042540fc..0000000000 --- a/package/default/data/ui/panels/investigate_cloud_compute_instance_activities.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel:Cloud_Infrastructure.Compute | search dest=$dest$ | fields - _* - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml b/package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml deleted file mode 100644 index eaacf46c7b..0000000000 --- a/package/default/data/ui/panels/investigate_failed_logins_for_multiple_destinations.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml b/package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml deleted file mode 100644 index 448e215f7d..0000000000 --- a/package/default/data/ui/panels/investigate_network_traffic_from_src_ip.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Network_Traffic.All_Traffic | search src_ip=$src_ip$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_okta_activity_by_app.xml b/package/default/data/ui/panels/investigate_okta_activity_by_app.xml deleted file mode 100644 index b7e6637221..0000000000 --- a/package/default/data/ui/panels/investigate_okta_activity_by_app.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - eventtype=okta_log app=$app$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml b/package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml deleted file mode 100644 index f702ab0a9b..0000000000 --- a/package/default/data/ui/panels/investigate_okta_activity_by_ip_address.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - eventtype=okta_log src_ip={src_ip} | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml b/package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml deleted file mode 100644 index b06e6c71c1..0000000000 --- a/package/default/data/ui/panels/investigate_pass_the_hash_attempts.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - `wineventlog_security` EventCode=4624 Logon_Type=9 AuthenticationPackageName=Negotiate | stats count earliest(_time) as first_login latest(_time) as last_login by src_user dest | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml deleted file mode 100644 index 02d2dff20d..0000000000 --- a/package/default/data/ui/panels/investigate_pass_the_ticket_attempts.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_previous_unseen_user.xml b/package/default/data/ui/panels/investigate_previous_unseen_user.xml deleted file mode 100644 index ab5940c8fe..0000000000 --- a/package/default/data/ui/panels/investigate_previous_unseen_user.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app values(Authentication.action) AS Authentication.action from datamodel=Authentication where Authentication.action=success by _time, Authentication.user | bucket _time span=30d | stats count min(first_login) as first_login max(last_login) as last_login values(Authentication.dest) AS Authentication.dest by Authentication.user | where count=1 | where first_login >= relative_time(now(), "-30d") | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml b/package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml deleted file mode 100644 index fc1ff90dda..0000000000 --- a/package/default/data/ui/panels/investigate_successful_remote_desktop_authentications.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Authentication where Authentication.signature_id=4624 Authentication.app=win:remote by Authentication.src Authentication.dest Authentication.app Authentication.user Authentication.signature Authentication.src_nt_domain | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `drop_dm_object_name("Authentication")`| table firstTime lastTime src src_nt_domain dest user app count | sort count - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml b/package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml deleted file mode 100644 index bb306f81a8..0000000000 --- a/package/default/data/ui/panels/investigate_suspicious_strings_in_http_header.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | search sourcetype=stream:http src_ip="$src_ip$" dest_ip="$dest_ip$" | eval cs_content_type_length = len(cs_content_type) | search cs_content_type_length > 100 | rex field="cs_content_type" (?cmd.exe) | eval suspicious_strings_found=if(match(cs_content_type, "application"), "True", "False") | rename suspicious_strings_found AS "Suspicious Content-Type Found" | fields "Suspicious Content-Type Found", dest_ip, src_ip, suspicious_strings, cs_content_type, cs_content_type_length, url - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml b/package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml deleted file mode 100644 index 78154b2139..0000000000 --- a/package/default/data/ui/panels/investigate_user_activities_in_all_cloud_regions.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel:Cloud_Infrastructure.Compute | search user=$src_user$ | fields - _* - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_user_activities_in_okta.xml b/package/default/data/ui/panels/investigate_user_activities_in_okta.xml deleted file mode 100644 index 0adc7b4f9c..0000000000 --- a/package/default/data/ui/panels/investigate_user_activities_in_okta.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - eventtype=okta_log user=$user$ | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, displayMessage, app, src_ip, state, city, result, outcome.reason - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml b/package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml deleted file mode 100644 index 1aa8d0f2a3..0000000000 --- a/package/default/data/ui/panels/investigate_user_activities_in_single_cloud_region.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel:Cloud_Infrastructure.Compute | search region=$region$ user=$src_user$ | fields - _* - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_web_activity_from_host.xml b/package/default/data/ui/panels/investigate_web_activity_from_host.xml deleted file mode 100644 index 0c8c4e596d..0000000000 --- a/package/default/data/ui/panels/investigate_web_activity_from_host.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Web.Web | search src=$dest$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml b/package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml deleted file mode 100644 index 612d227d1b..0000000000 --- a/package/default/data/ui/panels/investigate_web_activity_from_src_ip.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | from datamodel Web.Web | search src=$src_ip$ - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/investigate_web_posts_from_src.xml b/package/default/data/ui/panels/investigate_web_posts_from_src.xml deleted file mode 100644 index 43d10b1103..0000000000 --- a/package/default/data/ui/panels/investigate_web_posts_from_src.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - | tstats `security_content_summariesonly` values(Web.url) as url from datamodel=Web by Web.src,Web.http_user_agent,Web.http_method | `drop_dm_object_name("Web")`| where like(src, "$src$") and like(http_method, "POST") - - - -
- \ No newline at end of file diff --git a/package/default/data/ui/panels/process_chain_analysis.xml b/package/default/data/ui/panels/process_chain_analysis.xml deleted file mode 100644 index 582373453a..0000000000 --- a/package/default/data/ui/panels/process_chain_analysis.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - `sysmon` EventCode=1 NOT process=*Splunk* | rename process_guid AS out_process_guid process_name AS out_process_name parent_process_guid AS out_parent_process_guid parent_process_name AS out_parent_process_name | stats count by out_process_guid out_process_name out_parent_process_guid out_parent_process_name | eval join_process_guid = out_process_guid | join join_process_guid [ search `sysmon` process_guid={process_guid} EventCode=1 | rename process_name AS sub_process_name process_guid AS sub_process_guid parent_process_name AS sub_parent_process_name parent_process_guid AS sub_parent_process_guid | stats count by sub_process_name sub_process_guid sub_parent_process_name sub_parent_process_guid | eval join_process_guid = sub_parent_process_guid] | rename sub_process_guid AS process_guid sub_process_name AS process_name out_process_guid AS parent_process_guid out_process_name AS parent_process_name out_parent_process_guid AS grandparent_process_guid out_parent_process_name AS grandparent_process_name | stats count by process_guid process_name parent_process_guid parent_process_name grandparent_process_guid grandparent_process_name | head 1 | fields - count - - - -
- \ No newline at end of file diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 81e00f0c0a..b434f33517 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -1,9 +1,402 @@ + +[panel_group://workbench_panel_group_aws_cross_account_activity] +label = AWS Cross Account Activity +description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. +disabled = 0 +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_source_user"] + +[panel_group://workbench_panel_group_aws_cryptomining] +label = AWS Cryptomining +description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. +disabled = 0 +panels = ["panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_aws_network_acl_activity] +label = AWS Network ACL Activity +description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_aws_suspicious_provisioning_activities] +label = AWS Suspicious Provisioning Activities +description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. +disabled = 0 +panels = ["panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_country", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] + +[panel_group://workbench_panel_group_aws_user_monitoring] +label = AWS User Monitoring +description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. +disabled = 0 +panels = ["panel://workbench_panel_investigate_aws_user_activities_by_user_field", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_account_monitoring_and_controls] +label = Account Monitoring and Controls +description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint"] + +[panel_group://workbench_panel_group_apache_struts_vulnerability] +label = Apache Struts Vulnerability +description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_investigate_suspicious_strings_in_http_header"] + +[panel_group://workbench_panel_group_asset_tracking] +label = Asset Tracking +description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. +disabled = 0 +panels = ["panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_brand_monitoring] +label = Brand Monitoring +description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_cloud_cryptomining] +label = Cloud Cryptomining +description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. +disabled = 0 +panels = ["panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_coldroot_macos_rat] +label = ColdRoot MacOS RAT +description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_collection_and_staging] +label = Collection and Staging +description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_command_and_control] +label = Command and Control +description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_common_phishing_frameworks] +label = Common Phishing Frameworks +description = Detect DNS and web requests to fake websites generated by the EvilGinx2 toolkit. These websites are designed to fool unwitting users who have clicked on a malicious link in a phishing email. +disabled = 0 +panels = ["panel://workbench_panel_get_certificate_logs_for_a_domain"] + +[panel_group://workbench_panel_group_container_implantation_monitoring_and_investigation] +label = Container Implantation Monitoring and Investigation +description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. +disabled = 0 +panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activity"] + +[panel_group://workbench_panel_group_credential_dumping] +label = Credential Dumping +description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. +disabled = 0 +panels = ["panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] + +[panel_group://workbench_panel_group_dhs_report_ta18_074a] +label = DHS Report TA18-074A +description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. +disabled = 0 +panels = ["panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_dns_amplification_attacks] +label = DNS Amplification Attacks +description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. +disabled = 0 +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] + +[panel_group://workbench_panel_group_dns_hijacking] +label = DNS Hijacking +description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. +disabled = 0 +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host"] + +[panel_group://workbench_panel_group_data_protection] +label = Data Protection +description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_disabling_security_tools] +label = Disabling Security Tools +description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_dynamic_dns] +label = Dynamic DNS +description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_emotet_malware__dhs_report_ta18_201a_] +label = Emotet Malware DHS Report TA18-201A +description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_hidden_cobra_malware] +label = Hidden Cobra Malware +description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_host_redirection] +label = Host Redirection +description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host"] + +[panel_group://workbench_panel_group_jboss_vulnerability] +label = JBoss Vulnerability +description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_kubernetes_scanning_activity] +label = Kubernetes Scanning Activity +description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. +disabled = 0 +panels = ["panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_lateral_movement] +label = Lateral Movement +description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_malicious_powershell] +label = Malicious PowerShell +description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_monitor_backup_solution] +label = Monitor Backup Solution +description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. +disabled = 0 +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] + +[panel_group://workbench_panel_group_monitor_for_unauthorized_software] +label = Monitor for Unauthorized Software +description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_monitor_for_updates] +label = Monitor for Updates +description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] + +[panel_group://workbench_panel_group_netsh_abuse] +label = Netsh Abuse +description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_orangeworm_attack_group] +label = Orangeworm Attack Group +description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_phishing_payloads] +label = Phishing Payloads +description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. +disabled = 0 +panels = ["panel://workbench_panel_get_parent_process_info"] + +[panel_group://workbench_panel_group_possible_backdoor_activity_associated_with_mudcarp_espionage_campaigns] +label = Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns +description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_prohibited_traffic_allowed_or_protocol_mismatch] +label = Prohibited Traffic Allowed or Protocol Mismatch +description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host"] + +[panel_group://workbench_panel_group_ransomware] +label = Ransomware +description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host"] + +[panel_group://workbench_panel_group_router_and_infrastructure_security] +label = Router and Infrastructure Security +description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_sql_injection] +label = SQL Injection +description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] + +[panel_group://workbench_panel_group_samsam_ransomware] +label = SamSam Ransomware +description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] +label = Spectre And Meltdown Vulnerabilities +description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_splunk_enterprise_vulnerability] +label = Splunk Enterprise Vulnerability +description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] + +[panel_group://workbench_panel_group_splunk_enterprise_vulnerability_cve_2018_11409] +label = Splunk Enterprise Vulnerability CVE-2018-11409 +description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_suspicious_aws_ec2_activities] +label = Suspicious AWS EC2 Activities +description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. +disabled = 0 +panels = ["panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_suspicious_aws_login_activities] +label = Suspicious AWS Login Activities +description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. +disabled = 0 +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] + +[panel_group://workbench_panel_group_suspicious_aws_s3_activities] +label = Suspicious AWS S3 Activities +description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. +disabled = 0 +panels = ["panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_suspicious_aws_traffic] +label = Suspicious AWS Traffic +description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). +disabled = 0 +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_suspicious_command_line_executions] +label = Suspicious Command-Line Executions +description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_suspicious_dns_traffic] +label = Suspicious DNS Traffic +description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] + +[panel_group://workbench_panel_group_suspicious_emails] +label = Suspicious Emails +description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_suspicious_mshta_activity] +label = Suspicious MSHTA Activity +description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_suspicious_okta_activity] +label = Suspicious Okta Activity +description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. +disabled = 0 +panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_user_activities_in_okta"] + +[panel_group://workbench_panel_group_suspicious_wmi_use] +label = Suspicious WMI Use +description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host"] + +[panel_group://workbench_panel_group_suspicious_windows_registry_activities] +label = Suspicious Windows Registry Activities +description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_unusual_aws_ec2_modifications] +label = Unusual AWS EC2 Modifications +description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. +disabled = 0 +panels = ["panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] + +[panel_group://workbench_panel_group_unusual_processes] +label = Unusual Processes +description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_use_of_cleartext_protocols] +label = Use of Cleartext Protocols +description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_notable_info"] + +[panel_group://workbench_panel_group_web_fraud_detection] +label = Web Fraud Detection +description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. +disabled = 0 +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_emails_from_specific_sender"] + +[panel_group://workbench_panel_group_windows_defense_evasion_tactics] +label = Windows Defense Evasion Tactics +description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_windows_file_extension_and_association_abuse] +label = Windows File Extension and Association Abuse +description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_windows_log_manipulation] +label = Windows Log Manipulation +description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_windows_persistence_techniques] +label = Windows Persistence Techniques +description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_windows_privilege_escalation] +label = Windows Privilege Escalation +description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + +[panel_group://workbench_panel_group_windows_service_abuse] +label = Windows Service Abuse +description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. +disabled = 0 +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] + + + [panel://workbench_panel_aws_investigate_user_activities_by_arn] label = AWS Investigate User Activities By ARN description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -19,7 +412,7 @@ label = AWS Investigate User Activities By AccessKeyId description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific credentials. disabled = 0 tokens = {\ - "inventory_asset_accessKeyId_filter": {\ + "accessKeyId": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -35,7 +428,7 @@ label = AWS Investigate User Activities By Source User description = This search retrieves the times, ARN, source IPs, AWS regions, event names, and the result of the event for specific ARNs. disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "src_user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -51,7 +444,7 @@ label = AWS Network ACL Details from ID description = This search queries AWS description logs and returns all the information about a specific network ACL via network ACL ID disabled = 0 tokens = {\ - "inventory_asset_networkAclId_filter": {\ + "networkAclId": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -67,7 +460,7 @@ label = AWS Network Interface details via resourceId description = This search queries AWS configuration logs and returns the information about a specific network interface via network interface ID. The information will include the ARN of the network interface, its relationships with other AWS resources, the public and the private IP associated with the network interface. disabled = 0 tokens = {\ - "inventory_asset_resourceId_filter": {\ + "resourceId": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -83,7 +476,7 @@ label = AWS S3 Bucket details via bucketName description = This search queries AWS configuration logs and returns the information about a specific S3 bucket. The information returned includes the time the S3 bucket was created, the resource ID, the region it belongs to, the value of action performed, AWS account ID, and configuration values of the access-control lists associated with the bucket. disabled = 0 tokens = {\ - "inventory_asset_bucketName_filter": {\ + "bucketName": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -99,7 +492,7 @@ label = All backup logs for host description = Retrieve the backup logs for the last 2 weeks for a specific host in order to investigate why backups are not completing successfully. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -115,7 +508,7 @@ label = Amazon EKS Kubernetes activity by src ip description = This search provides investigation data about requests via user agent, authentication request URI, verb and cluster name data against Kubernetes cluster from a specific IP address disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "src_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -131,7 +524,7 @@ label = GCP Kubernetes activity by src ip description = This search provides investigation data about requests via user agent, authentication request URI, resource path and cluster name data against Kubernetes cluster from a specific IP address disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "src_user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -147,7 +540,7 @@ label = Get All AWS Activity From City description = This search retrieves all the activity from a specific city and will create a table containing the time, city, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_City_filter": {\ + "City": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -163,7 +556,7 @@ label = Get All AWS Activity From Country description = This search retrieves all the activity from a specific country and will create a table containing the time, country, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_Country_filter": {\ + "Country": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -179,7 +572,7 @@ label = Get All AWS Activity From IP Address description = This search retrieves all the activity from a specific IP address and will create a table containing the time, ARN, username, the type of user, the IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "src_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -195,7 +588,7 @@ label = Get All AWS Activity From Region description = This search retrieves all the activity from a specific geographic region and will create a table containing the time, geographic region, ARN, username, the type of user, the source IP address, the AWS region the activity was in, the API called, and whether or not the API call was successful. disabled = 0 tokens = {\ - "inventory_asset_Region_filter": {\ + "Region": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -211,7 +604,7 @@ label = Get Authentication Logs For Endpoint description = This search returns all users that have attempted to access a particular endpoint. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -227,7 +620,7 @@ label = Get Backup Logs For Endpoint description = This search will tell you the backup status from your netbackup_logs of a specific endpoint for the last week. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -243,7 +636,7 @@ label = Get Certificate logs for a domain description = This search queries the Certificates datamodel and give you all the information for a specific domain. Please note that the certificates issued by "Let's Encrypt" are widely used by attackers. disabled = 0 tokens = {\ - "inventory_asset_domain_filter": {\ + "domain": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -259,7 +652,7 @@ label = Get DNS Server History for a host description = While investigating any detections it is important to understand which and how many DNS servers a host has connected to in the past. This search uses data that is tagged as DNS and gives you a count and list of DNS servers that a particular host has connected to the previous 24 hours. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "src_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -275,7 +668,7 @@ label = Get DNS traffic ratio description = This search calculates the ratio of DNS traffic originating and coming from a host to a list of DNS servers over the last 24 hours. A high value of this ratio could be very useful to quickly understand if a src_ip (host) is sending a high volume of data out via port 53, could be an indicator of data exfiltration via DNS. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "src_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -283,7 +676,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_ip_filter": {\ + "dest_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -299,7 +692,7 @@ label = Get EC2 Instance Details by instanceId description = This search queries AWS description logs and returns all the information about a specific instance via the instanceId field disabled = 0 tokens = {\ - "inventory_asset_instanceId_filter": {\ + "instanceId": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -315,7 +708,7 @@ label = Get EC2 Launch Details description = This search returns some of the launch details for a EC2 instance. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -331,7 +724,7 @@ label = Get Email Info description = This search returns all the information Splunk might have collected a specific email message over the last 2 hours. disabled = 0 tokens = {\ - "inventory_asset_message_id_filter": {\ + "message_id": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -347,7 +740,7 @@ label = Get Emails From Specific Sender description = This search returns all the emails from a specific sender over the last 24 and next hours. disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "src_user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -363,7 +756,7 @@ label = Get First Occurrence and Last Occurrence of a MAC Address description = This search allows you to gather more context around a notable which has detected a new device connecting to your network. Use this search to determine the first and last occurrences of the suspicious device attempting to connect with your network. disabled = 0 tokens = {\ - "inventory_asset_src_mac_filter": {\ + "src_mac": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -379,7 +772,7 @@ label = Get History Of Email Sources description = This search returns a list of all email sources seen in the 48 hours prior to the notable event to 24 hours after, and the number of emails from each source. disabled = 0 tokens = {\ - "inventory_asset_src_filter": {\ + "src": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -395,7 +788,7 @@ label = Get Logon Rights Modifications For Endpoint description = This search allows you to retrieve any modifications to logon rights associated with a specific host. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -411,7 +804,7 @@ label = Get Logon Rights Modifications For User description = This search allows you to retrieve any modifications to logon rights for a specific user account. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -427,7 +820,7 @@ label = Get Notable History description = This search queries the notable index and returns all the Notable Events for the particular destination host, giving the analyst an overview of the incidents that may have occurred with the host under investigation. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -443,7 +836,7 @@ label = Get Notable Info description = This search queries the notable index to retrieve detailed information captured within the notable. Every notable has a unique ID associated with it, which is used to point us directly to the notable event under investigation. disabled = 0 tokens = {\ - "inventory_asset_event_id_filter": {\ + "event_id": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -459,7 +852,7 @@ label = Get Outbound Emails to Hidden Cobra Threat Actors description = This search returns the information of the users that sent emails to the accounts controlled by the Hidden Cobra Threat Actors: specifically to `misswang8107@gmail.com`, and from `redhat@gmail.com`. disabled = 0 tokens = {\ - "inventory_asset_src_user_filter": {\ + "src_user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -467,7 +860,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_recipient_filter": {\ + "recipient": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -483,7 +876,7 @@ label = Get Parent Process Info description = This search queries the Endpoint data model to give you details about the parent process of a process running on a host which is under investigation. Enter the values of the process name in question and the dest disabled = 0 tokens = {\ - "inventory_asset_process_name_filter": {\ + "process_name": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -491,7 +884,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -507,7 +900,7 @@ label = Get Process File Activity description = This search returns the file activity for a specific process on a specific endpoint disabled = 0 tokens = {\ - "inventory_asset_process_id_filter": {\ + "process_id": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -515,7 +908,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -531,7 +924,7 @@ label = Get Process Info description = This search queries the Endpoint data model to give you details about the process running on a host which is under investigation. To gather the process info, enter the values for the process name in question and the destination IP address. disabled = 0 tokens = {\ - "inventory_asset_process_name_filter": {\ + "process_name": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -539,7 +932,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -555,7 +948,7 @@ label = Get Process Information For Port Activity description = This search will return information about the process associated with observed network traffic to a specific destination port from a specific host. disabled = 0 tokens = {\ - "inventory_asset_dest_port_filter": {\ + "dest_port": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -563,7 +956,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -579,7 +972,7 @@ label = Get Process Registry Activity description = This search returns the registry activity for a specific process on a specific endpoint disabled = 0 tokens = {\ - "inventory_asset_process_id_filter": {\ + "process_id": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -587,7 +980,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -603,7 +996,7 @@ label = Get Process Responsible For The DNS Traffic description = While investigating, an analyst will want to know what process and parent_process is responsible for generating suspicious DNS traffic. Use the following search and enter the value of `dest` in the search to get specific details on the process responsible for creating the DNS traffic. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -619,7 +1012,7 @@ label = Get Registry Activities description = This search queries the Endpoint Datamodel to give you details of the latest registry values for a specific destination computer. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -635,7 +1028,7 @@ label = Get Risk Modifiers For Endpoint description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk\_scores, names of the correlation searches that contributed to create a risk score for a specific endpoint(machine\_name) disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -651,7 +1044,7 @@ label = Get Risk Modifiers For User description = For the last 7 days, the search will query the Risk data model in Splunk Enterprise Security and calculate the count, sum of the risk_scores, names of the correlation searches that contributed to create a risk score for a specific user disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -667,7 +1060,7 @@ label = Get Sysmon WMI Activity for Host description = This search queries Sysmon WMI events for the host of interest. disabled = 0 tokens = {\ - "inventory_asset_process_filter": {\ + "process": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -675,7 +1068,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -691,7 +1084,7 @@ label = Get Update Logs For Endpoint description = This search will tell you give you the update logs for a specific endpoint for the last week. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -707,7 +1100,7 @@ label = Get User Information from Identity Table description = Gather more information about the user identified in the Notable Event. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -723,7 +1116,7 @@ label = Get Vulnerability Logs For Endpoint description = This search will show you any vulnerabilities noted for a specific endpoint for the last week. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -739,7 +1132,7 @@ label = Get Web Session Information via session id description = This search helps an analyst investigate a notable event to find out more about a specific web session. The search looks for a specific web session ID in the HTTP web traffic and outputs the URL and user agents, grouped by source IP address and HTTP status code. disabled = 0 tokens = {\ - "inventory_asset_session_id_filter": {\ + "session_id": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -755,7 +1148,7 @@ label = Investigate AWS ECR container listing activity description = This search lists all the users performing a list image operation on AWS Elastic Container Registry. Listing source user, image id, source IP, user type, http user agent. This search also gives counts of unique user agents per listing source. disabled = 0 tokens = {\ - "inventory_asset_Compute.event_name_filter": {\ + "Compute.event_name": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -771,7 +1164,7 @@ label = Investigate AWS User Activities by user field description = This search lists all the logged CloudTrail activities by a specific user and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and the user's identity information. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -787,7 +1180,7 @@ label = Investigate AWS activities via region name description = This search lists all the user activities logged by CloudTrail for a specific region in question and will create a table of the values of parameters requested, the type of the event and the response from the AWS API by each user disabled = 0 tokens = {\ - "inventory_asset_awsRegion_filter": {\ + "awsRegion": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -803,7 +1196,7 @@ label = Investigate Cloud Compute Instance Activities description = This search returns a logs of events that operated on the compute instance. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -819,7 +1212,7 @@ label = Investigate Failed Logins for Multiple Destinations description = This search returns failed logins to multiple destinations by user. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -835,7 +1228,7 @@ label = Investigate Network Traffic From src ip description = This search allows you to find all the network traffic from a specific IP address. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "src_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -851,7 +1244,7 @@ label = Investigate Okta Activity by IP Address description = This search returns all okta events from a specific IP address. disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -867,7 +1260,7 @@ label = Investigate Okta Activity by app description = This search returns all okta events associated with a specific app disabled = 0 tokens = {\ - "inventory_asset_app_filter": {\ + "app": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -883,7 +1276,7 @@ label = Investigate Pass the Hash Attempts description = This search hunts for dumped NTLM hashes used for pass the hash. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -899,7 +1292,7 @@ label = Investigate Pass the Ticket Attempts description = This search hunts for dumped kerberos ticket from LSASS memory. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -915,7 +1308,7 @@ label = Investigate Previous Unseen User description = This search returns previous unseen user, which didn't log in for 30 days. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -931,7 +1324,7 @@ label = Investigate Successful Remote Desktop Authentications description = This search returns the source, destination, and user for all successful remote-desktop authentications. A successful authentication after a brute-force attack on a destination machine is suspicious behavior. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -947,7 +1340,7 @@ label = Investigate Suspicious Strings in HTTP Header description = This search helps an analyst investigate a notable event related to a potential Apache Struts exploitation. To investigate, we will want to isolate and analyze the "payload" or the commands that were passed to the vulnerable hosts by creating a few regular expressions to carve out the commands focusing on common keywords from the payload, such as cmd.exe, /bin/bash and whois. The search returns these suspicious strings found in the HTTP logs of the system of interest. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "src_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -955,7 +1348,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_dest_ip_filter": {\ + "dest_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -971,7 +1364,7 @@ label = Investigate User Activities In All Cloud Regions description = This search lists all the logged cloud infrastructure activities by a specific cloud user disabled = 0 tokens = {\ - "inventory_asset_region_filter": {\ + "region": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -979,7 +1372,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_src_user_filter": {\ + "src_user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -995,7 +1388,7 @@ label = Investigate User Activities In Okta description = This search returns all okta events by a specific user disabled = 0 tokens = {\ - "inventory_identity_user_filter": {\ + "user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -1011,7 +1404,7 @@ label = Investigate User Activities In Single Cloud Region description = This search lists all the logged cloud infrastructure activities by a specific cloud user in a specific cloud region disabled = 0 tokens = {\ - "inventory_asset_region_filter": {\ + "region": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -1019,7 +1412,7 @@ tokens = {\ "value": "asset",\ "default": "_1!=1"\ },\ - "inventory_asset_src_user_filter": {\ + "src_user": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -1035,7 +1428,7 @@ label = Investigate Web Activity From Host description = This search allows you to find all the web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. disabled = 0 tokens = {\ - "inventory_asset_dest_filter": {\ + "dest": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -1051,7 +1444,7 @@ label = Investigate Web Activity From src ip description = This search searches for all web activity from a specific host. During an investigation, it is important to profile web activity to characterize user or host activity. disabled = 0 tokens = {\ - "inventory_asset_src_ip_filter": {\ + "src_ip": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -1067,7 +1460,7 @@ label = Investigate Web POSTs From src description = This investigative search retrieves POST requests from a specified source IP or hostname. Identifying the POST requests, as well as their associated destination URLs and user agent(s), may help you scope and characterize the suspicious traffic. disabled = 0 tokens = {\ - "inventory_asset_src_filter": {\ + "src": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ @@ -1083,7 +1476,7 @@ label = Process Chain Analysis description = Analyze the Process Chain and identify the malicious file. By analyzing the parent process guid and searching for the process guid, the spawning process chain can be identified. disabled = 0 tokens = {\ - "inventory_asset_process_guid_filter": {\ + "process_guid": {\ "valuePrefix": "",\ "valueSuffix": "",\ "delimiter": " OR ",\ diff --git a/package/default/macros.conf b/package/default/macros.conf index 722eeba32c..3b66489c41 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:42:45 UTC +# On Date: 2020-05-13T08:09:53 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 925e95d977..ec76772734 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:42:45 UTC +# On Date: 2020-05-13T08:09:53 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 65a6875798..08dd3ad213 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:42:45 UTC +# On Date: 2020-05-13T08:09:53 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index c64bfab184..94d509161e 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-12T12:42:45 UTC +# On Date: 2020-05-13T08:09:53 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Process Registry Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - All backup logs for host"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint"] +searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get DNS traffic ratio", "ESCU - Get DNS Server History for a host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get User Information from Identity Table"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 3ac6c62937f30315ed6c185a0125c6447c759648 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 13 May 2020 10:30:46 +0200 Subject: [PATCH 50/93] bug in generate --- bin/jinja2_templates/savedsearches.j2 | 2 +- .../attempted_credential_dump_from_registry_via_reg_exe.yml | 2 +- .../investigate_failed_logins_for_multiple_destinations.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/bin/jinja2_templates/savedsearches.j2 b/bin/jinja2_templates/savedsearches.j2 index 71adfcde25..68f28ae60f 100644 --- a/bin/jinja2_templates/savedsearches.j2 +++ b/bin/jinja2_templates/savedsearches.j2 @@ -60,7 +60,7 @@ action.notable.param.nes_fields = {{ detection.nes_fields }} action.notable.param.rule_description = {{ detection.deployment.alert_action.notable.rule_description | custom_jinja2_enrichment_filter(detection) }} action.notable.param.rule_title = {{ detection.deployment.alert_action.notable.rule_title | custom_jinja2_enrichment_filter(detection) }} action.notable.param.security_domain = {{ detection.tags.security_domain }} -action.notable.param.severity = medium +action.notable.param.severity = high {% endif %} {% if detection.deployment.alert_action.email is defined %} action.email.subject.alert = {{ detection.deployment.alert_action.email.subject | custom_jinja2_enrichment_filter(detection) }} diff --git a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml index bd0cd57c99..df66cbec11 100644 --- a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml +++ b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_filter`' + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_exe_filter`' known_false_positives: None identified. tags: analytics_story: diff --git a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml index fd0ffd8e6c..cc3e9d7a08 100644 --- a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml +++ b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml @@ -12,7 +12,7 @@ search: '| tstats count `security_content_summariesonly` earliest(_time) as firs latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest - > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` + > 0 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")`' tags: analytics_story: From eedb7c49e2b7c5308f0baa14ce459b81df539168 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 13 May 2020 10:46:58 +0200 Subject: [PATCH 51/93] bug in generate --- response_tasks/investigate_pass_the_ticket_attempts.yml | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/response_tasks/investigate_pass_the_ticket_attempts.yml b/response_tasks/investigate_pass_the_ticket_attempts.yml index 7ca5f470c9..e6de16dd57 100644 --- a/response_tasks/investigate_pass_the_ticket_attempts.yml +++ b/response_tasks/investigate_pass_the_ticket_attempts.yml @@ -12,10 +12,8 @@ how_to_implement: To successfully implement this search you need to be ingesting author: Patrick Bareiss, Splunk inputs: - dest -search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user - "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) - AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 - | rename new_user AS user' +search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) + AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2' tags: analytics_story: - Credential Dumping From 347c94032e21cc2e42f470ac07611fb60cdcc465 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 13 May 2020 11:09:33 +0200 Subject: [PATCH 52/93] bug in generate --- bin/generate.py | 8 + bin/jinja2_templates/workflow_actions.j2 | 18 + package/default/analytic_stories.conf | 120 ++--- ...ailed_logins_for_multiple_destinations.xml | 2 +- ...l_investigate_pass_the_ticket_attempts.xml | 2 +- package/default/es_investigations.conf | 118 ++--- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 386 +++++++------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 128 ++--- package/default/workflow_actions.conf | 480 ++++++++++++++++++ 11 files changed, 886 insertions(+), 380 deletions(-) create mode 100644 bin/jinja2_templates/workflow_actions.j2 create mode 100644 package/default/workflow_actions.conf diff --git a/bin/generate.py b/bin/generate.py index 709cba02dc..ab45aa86d4 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -243,6 +243,14 @@ def generate_workbench_panels(response_tasks, stories): with open(output_path, 'w') as f: f.write(output) + j2_env = Environment(loader=FileSystemLoader('bin/jinja2_templates'), + trim_blocks=True) + template = j2_env.get_template('workflow_actions.j2') + output_path = OUTPUT_PATH + "/default/workflow_actions.conf" + output = template.render(response_tasks=workbench_panel_objects) + with open(output_path, 'w') as f: + f.write(output) + def parse_data_models_from_search(search): match = re.search(r'from\sdatamodel\s?=\s?([^\s.]*)', search) diff --git a/bin/jinja2_templates/workflow_actions.j2 b/bin/jinja2_templates/workflow_actions.j2 new file mode 100644 index 0000000000..82b25cfe54 --- /dev/null +++ b/bin/jinja2_templates/workflow_actions.j2 @@ -0,0 +1,18 @@ + +{% for response_task in response_tasks %} +{% if response_task.inputs|length == 1 %} +[workbench_panel_{{ response_task.lowercase_name }}]] +label = Workbench - {{ response_task.name }} +type = link +fields = *{{ response_task.inputs[0] }}* +display_location = field_menu +{% if response_task.inputs[0] == "user" %} +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_{{ response_task.lowercase_name }}&drilldown_field=$@field_name$&use_drilldown_time=true +{% else %} +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_{{ response_task.lowercase_name }}&drilldown_field=$@field_name$&use_drilldown_time=true +{% endif %} +link.target = blank +link.method = get +{% endif %} + +{% endfor %} diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index c06c360904..a195ea49ce 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T08:09:53 UTC +# On Date: 2020-05-13T09:08:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] support_searches = [] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = [] data_models = [] providing_technologies = none @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] support_searches = [] data_models = [] providing_technologies = none @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,7 +184,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = [] data_models = ["Cloud_Infrastructure"] providing_technologies = none @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Registry Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,7 +433,7 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host"] support_searches = [] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = [] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name"] support_searches = [] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] support_searches = [] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = [] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml b/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml index eaacf46c7b..dba9569081 100644 --- a/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml +++ b/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml @@ -1,7 +1,7 @@ - | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 0 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` diff --git a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml index 02d2dff20d..3f5dff58ab 100644 --- a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml +++ b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml @@ -1,7 +1,7 @@
- `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user + `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index b434f33517..3dd63416e1 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -3,25 +3,25 @@ label = AWS Cross Account Activity description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_source_user"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_source_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid"] [panel_group://workbench_panel_group_aws_cryptomining] label = AWS Cryptomining description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_aws_network_acl_activity] label = AWS Network ACL Activity description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] [panel_group://workbench_panel_group_aws_suspicious_provisioning_activities] label = AWS Suspicious Provisioning Activities description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_country", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] +panels = ["panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_country"] [panel_group://workbench_panel_group_aws_user_monitoring] label = AWS User Monitoring @@ -33,49 +33,49 @@ panels = ["panel://workbench_panel_investigate_aws_user_activities_by_user_field label = Account Monitoring and Controls description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint"] +panels = ["panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_apache_struts_vulnerability] label = Apache Struts Vulnerability description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_investigate_suspicious_strings_in_http_header"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_asset_tracking] label = Asset Tracking description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. disabled = 0 -panels = ["panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_brand_monitoring] label = Brand Monitoring description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_cloud_cryptomining] label = Cloud Cryptomining description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_coldroot_macos_rat] label = ColdRoot MacOS RAT description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] [panel_group://workbench_panel_group_collection_and_staging] label = Collection and Staging description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_command_and_control] label = Command and Control description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_common_phishing_frameworks] label = Common Phishing Frameworks @@ -93,19 +93,19 @@ panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activit label = Credential Dumping description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. disabled = 0 -panels = ["panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] +panels = ["panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_ticket_attempts", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_previous_unseen_user"] [panel_group://workbench_panel_group_dhs_report_ta18_074a] label = DHS Report TA18-074A description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. disabled = 0 -panels = ["panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_dns_amplification_attacks] label = DNS Amplification Attacks description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_dns_hijacking] label = DNS Hijacking @@ -117,91 +117,91 @@ panels = ["panel://workbench_panel_get_dns_server_history_for_a_host"] label = Data Protection description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_disabling_security_tools] label = Disabling Security Tools description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_dynamic_dns] label = Dynamic DNS description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_emotet_malware__dhs_report_ta18_201a_] label = Emotet Malware DHS Report TA18-201A description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_hidden_cobra_malware] label = Hidden Cobra Malware description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_host_redirection] label = Host Redirection description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_jboss_vulnerability] label = JBoss Vulnerability description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] [panel_group://workbench_panel_group_kubernetes_scanning_activity] label = Kubernetes Scanning Activity description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. disabled = 0 -panels = ["panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_lateral_movement] label = Lateral Movement description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_malicious_powershell] label = Malicious PowerShell description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_monitor_backup_solution] label = Monitor Backup Solution description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_all_backup_logs_for_host"] [panel_group://workbench_panel_group_monitor_for_unauthorized_software] label = Monitor for Unauthorized Software description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_monitor_for_updates] label = Monitor for Updates description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_netsh_abuse] label = Netsh Abuse description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_orangeworm_attack_group] label = Orangeworm Attack Group description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_phishing_payloads] label = Phishing Payloads @@ -213,61 +213,61 @@ panels = ["panel://workbench_panel_get_parent_process_info"] label = Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_prohibited_traffic_allowed_or_protocol_mismatch] label = Prohibited Traffic Allowed or Protocol Mismatch description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_ransomware] label = Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_router_and_infrastructure_security] label = Router and Infrastructure Security description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_sql_injection] label = SQL Injection description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_samsam_ransomware] label = SamSam Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] label = Spectre And Meltdown Vulnerabilities description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability] label = Splunk Enterprise Vulnerability description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability_cve_2018_11409] label = Splunk Enterprise Vulnerability CVE-2018-11409 description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_aws_ec2_activities] label = Suspicious AWS EC2 Activities description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. disabled = 0 -panels = ["panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_suspicious_aws_login_activities] label = Suspicious AWS Login Activities @@ -279,115 +279,115 @@ panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] label = Suspicious AWS S3 Activities description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. disabled = 0 -panels = ["panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_aws_activities_via_region_name"] [panel_group://workbench_panel_group_suspicious_aws_traffic] label = Suspicious AWS Traffic description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] [panel_group://workbench_panel_group_suspicious_command_line_executions] label = Suspicious Command-Line Executions description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_dns_traffic] label = Suspicious DNS Traffic description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_emails] label = Suspicious Emails description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_mshta_activity] label = Suspicious MSHTA Activity description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_okta_activity] label = Suspicious Okta Activity description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. disabled = 0 -panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_user_activities_in_okta"] +panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_user_activities_in_okta", "panel://workbench_panel_investigate_okta_activity_by_ip_address"] [panel_group://workbench_panel_group_suspicious_wmi_use] label = Suspicious WMI Use description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_windows_registry_activities] label = Suspicious Windows Registry Activities description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_unusual_aws_ec2_modifications] label = Unusual AWS EC2 Modifications description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. disabled = 0 -panels = ["panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_unusual_processes] label = Unusual Processes description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_use_of_cleartext_protocols] label = Use of Cleartext Protocols description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_web_fraud_detection] label = Web Fraud Detection description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_emails_from_specific_sender"] +panels = ["panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_windows_defense_evasion_tactics] label = Windows Defense Evasion Tactics description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_file_extension_and_association_abuse] label = Windows File Extension and Association Abuse description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_log_manipulation] label = Windows Log Manipulation description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_persistence_techniques] label = Windows Persistence Techniques description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_privilege_escalation] label = Windows Privilege Escalation description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_service_abuse] label = Windows Service Abuse description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] diff --git a/package/default/macros.conf b/package/default/macros.conf index 3b66489c41..f6237d2cb2 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T08:09:53 UTC +# On Date: 2020-05-13T09:08:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index ec76772734..9a83cae4be 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T08:09:53 UTC +# On Date: 2020-05-13T09:08:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -35,7 +35,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen City action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -76,7 +76,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Country action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -117,7 +117,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen IP Address action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -158,7 +158,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." action.notable.param.rule_title = AWS Cloud Provisioning From Previously Unseen Region action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -198,7 +198,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. action.notable.param.rule_title = AWS Cross Account Activity From Previously Unseen Account action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -238,7 +238,7 @@ action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. action.notable.param.rule_title = AWS Network Access Control List Created with All Open Ports action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -278,7 +278,7 @@ action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. action.notable.param.rule_title = AWS Network Access Control List Deleted action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -317,7 +317,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.notable.param.rule_title = Abnormally High AWS Instances Launched by User action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -357,7 +357,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. action.notable.param.rule_title = Abnormally High AWS Instances Launched by User - MLTK action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -396,7 +396,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -436,7 +436,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. action.notable.param.rule_title = Abnormally High AWS Instances Terminated by User - MLTK action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -476,7 +476,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = Detect memory dumping of the LSASS process. action.notable.param.rule_title = Access LSASS Memory for Dump Creation action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -515,7 +515,7 @@ action.notable = 1 action.notable.param.rule_description = This search provides detection information on unauthenticated requests against Kubernetes' Pods API action.notable.param.rule_title = Amazon EKS Kubernetes Pod scan detection action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -554,7 +554,7 @@ action.notable = 1 action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS action.notable.param.rule_title = Amazon EKS Kubernetes cluster scan detection action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -594,7 +594,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = Attempt to add a certificate to the untrusted certificate store action.notable.param.rule_title = Attempt To Add Certificate To Untrusted Store action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -634,7 +634,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. action.notable.param.rule_title = Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -674,7 +674,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for attempts to stop security-related services on the endpoint. action.notable.param.rule_title = Attempt To Stop Security Service action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -714,7 +714,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. action.notable.param.rule_title = Attempted Credential Dump From Registry via Reg exe action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -725,7 +725,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=reg.exe OR Processes.process_name=cmd.exe) Processes.process=*save* (Processes.process=*HKEY_LOCAL_MACHINE\\Security* OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=reg.exe OR Processes.process_name=cmd.exe) Processes.process=*save* (Processes.process=*HKEY_LOCAL_MACHINE\\Security* OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_exe_filter` [ESCU - Batch File Write to System32 - Rule] action.escu = 0 @@ -754,7 +754,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for a batch file (.bat) written to the Windows system directory tree. action.notable.param.rule_title = Batch File Write to System32 action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -794,7 +794,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. action.notable.param.rule_title = Child Processes of Spoolsv exe action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -836,7 +836,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. action.notable.param.rule_title = Clients Connecting to Multiple DNS Servers action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -876,7 +876,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for cloud compute instances created by users who have not created them before. action.notable.param.rule_title = Cloud Compute Instance Created By Previously Unseen User action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -916,7 +916,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for cloud compute instances being created with previously unseen image IDs. action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Image action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -956,7 +956,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Find EC2 instances being created with previously unseen instance types. action.notable.param.rule_title = Cloud Compute Instance Created With Previously Unseen Instance Type action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -996,7 +996,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. action.notable.param.rule_title = Cloud Compute Instance Started In Previously Unused Region action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1040,7 +1040,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for file modifications with extensions commonly used by Ransomware action.notable.param.rule_title = Common Ransomware Extensions action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1080,7 +1080,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. action.notable.param.rule_title = Common Ransomware Notes action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1120,7 +1120,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = Detect remote thread creation into LSASS consistent with credential dumping. action.notable.param.rule_title = Create Remote Thread into LSASS action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1160,7 +1160,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the creation of local administrator accounts using net.exe. action.notable.param.rule_title = Create local admin accounts using net exe action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1200,7 +1200,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the creation or deletion of hidden shares using net.exe. action.notable.param.rule_title = Create or delete windows shares using net exe action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1240,7 +1240,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. action.notable.param.rule_title = Creation of Shadow Copy action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1280,7 +1280,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search detects the use of wmic and Powershell to create a shadow copy. action.notable.param.rule_title = Creation of Shadow Copy with wmic and powershell action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1320,7 +1320,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects credential dumping using copy command from a shadow copy. action.notable.param.rule_title = Credential Dumping via Copy Command from Shadow Copy action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1360,7 +1360,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects the creation of a symlink to a shadow copy. action.notable.param.rule_title = Credential Dumping via Symlink to Shadow Copy action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1406,7 +1406,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. action.notable.param.rule_title = DNS Query Length Outliers - MLTK action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1445,7 +1445,7 @@ action.notable = 1 action.notable.param.rule_description = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. action.notable.param.rule_title = DNS Query Length With High Standard Deviation action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1485,7 +1485,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. action.notable.param.rule_title = DNS Query Requests Resolved by Unauthorized DNS Servers action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1529,7 +1529,7 @@ action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. action.notable.param.rule_title = DNS record changed action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1569,7 +1569,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. action.notable.param.rule_title = Deleting Shadow Copies action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1615,7 +1615,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. action.notable.param.rule_title = Detect API activity from users without MFA action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1661,7 +1661,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. action.notable.param.rule_title = Detect AWS API Activities From Unapproved Accounts action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1701,7 +1701,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect AWS Console Login by User from New City action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1741,7 +1741,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect AWS Console Login by User from New Country action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1781,7 +1781,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect AWS Console Login by User from New Region action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1821,7 +1821,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. action.notable.param.rule_title = Detect Activity Related to Pass the Hash Attacks action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1861,7 +1861,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for reading lsass memory consistent with credential dumping. action.notable.param.rule_title = Detect Credential Dumping through LSASS access action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1905,7 +1905,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. action.notable.param.rule_title = Detect DNS requests to Phishing Sites leveraging EvilGinx2 action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1949,7 +1949,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. action.notable.param.rule_title = Detect Excessive Account Lockouts From Endpoint action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -1989,7 +1989,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects user accounts that have been locked out a relatively high number of times in a short period. action.notable.param.rule_title = Detect Excessive User Account Lockouts action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2028,7 +2028,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. action.notable.param.rule_title = Detect Large Outbound ICMP Packets action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2068,7 +2068,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. action.notable.param.rule_title = Detect Long DNS TXT Record Response action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2108,7 +2108,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for reading loaded Images unique to credential dumping with Mimikatz. action.notable.param.rule_title = Detect Mimikatz Using Loaded Images action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2147,7 +2147,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for PowerShell requesting privileges consistent with credential dumping. action.notable.param.rule_title = Detect Mimikatz Via PowerShell And EventCode 4703 action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2193,7 +2193,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for newly created accounts that have been elevated to local administrators. action.notable.param.rule_title = Detect New Local Admin account action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2233,7 +2233,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. action.notable.param.rule_title = Detect New Login Attempts to Routers action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2273,7 +2273,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events where a user has created an open/public S3 bucket. action.notable.param.rule_title = Detect New Open S3 buckets action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2313,7 +2313,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. action.notable.param.rule_title = Detect Oulook exe writing a zip file action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2352,7 +2352,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. action.notable.param.rule_title = Detect Outbound SMB Traffic action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2392,7 +2392,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search is looking for the creation of program.exe in the C: drive. The creation of this file in that location may be driven by a motive to perform path interception. action.notable.param.rule_title = Detect Path Interception By Creation Of program exe action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2432,7 +2432,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. action.notable.param.rule_title = Detect Prohibited Applications Spawning cmd exe action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2472,7 +2472,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. action.notable.param.rule_title = Detect PsExec With accepteula Flag action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2512,7 +2512,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. action.notable.param.rule_title = Detect Rare Executables action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2551,7 +2551,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. action.notable.param.rule_title = Detect S3 access from a new IP action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2597,7 +2597,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in AWS API Activity action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2637,7 +2637,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. action.notable.param.rule_title = Detect Spike in Network ACL Activity action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2677,7 +2677,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in S3 Bucket deletion action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2717,7 +2717,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in Security Group Activity action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2756,7 +2756,7 @@ action.notable = 1 action.notable.param.rule_description = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. action.notable.param.rule_title = Detect Spike in blocked Outbound Traffic from your AWS action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2796,7 +2796,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. action.notable.param.rule_title = Detect USB device insertion action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2835,7 +2835,7 @@ action.notable = 1 action.notable.param.rule_description = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. action.notable.param.rule_title = Detect Unauthorized Assets by MAC address action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2875,7 +2875,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine action.notable.param.rule_title = Detect Use of cmd exe to Launch Script Interpreters action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2915,7 +2915,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. action.notable.param.rule_title = Detect attackers scanning for vulnerable JBoss servers action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -2960,7 +2960,7 @@ action.notable = 1 action.notable.param.rule_description = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. action.notable.param.rule_title = Detect hosts connecting to dynamic domain providers action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3000,7 +3000,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. action.notable.param.rule_title = Detect malicious requests to exploit JBoss servers action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3040,7 +3040,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. action.notable.param.rule_title = Detect mshta exe running scripts in command-line arguments action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3080,7 +3080,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. action.notable.param.rule_title = Detect new API calls from user roles action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3120,7 +3120,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour action.notable.param.rule_title = Detect new user AWS Console Login action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3160,7 +3160,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. action.notable.param.rule_title = Detect processes used for System Network Configuration Discovery action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3202,7 +3202,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for web connections to dynamic DNS providers. action.notable.param.rule_title = Detect web traffic to dynamic domain providers action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3242,7 +3242,7 @@ action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. action.notable.param.rule_title = Detection of DNS Tunnels action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3282,7 +3282,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. action.notable.param.rule_title = Detection of tools built by NirSoft action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3322,7 +3322,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). action.notable.param.rule_title = Disabling Remote User Account Control action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3362,7 +3362,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Detect the usage of comsvcs.dll for dumping the lsass process. action.notable.param.rule_title = Dump LSASS via comsvcs DLL action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3402,7 +3402,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for EC2 instances being modified by users who have not previously modified them. action.notable.param.rule_title = EC2 Instance Modified With Previously Unseen User action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3441,7 +3441,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started action.notable.param.rule_title = EC2 Instance Started In Previously Unseen Region action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3480,7 +3480,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen AMIs. action.notable.param.rule_title = EC2 Instance Started With Previously Unseen AMI action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3520,7 +3520,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for EC2 instances being created with previously unseen instance types. action.notable.param.rule_title = EC2 Instance Started With Previously Unseen Instance Type action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3560,7 +3560,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for EC2 instances being created by users who have not created them before. action.notable.param.rule_title = EC2 Instance Started With Previously Unseen User action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3601,7 +3601,7 @@ action.notable = 1 action.notable.param.rule_description = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. action.notable.param.rule_title = Email Attachments With Lots Of Spaces action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3641,7 +3641,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. action.notable.param.rule_title = Email files written outside of the Outlook directory action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3680,7 +3680,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.notable.param.rule_title = Email servers sending high volume traffic to hosts action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3719,7 +3719,7 @@ action.notable = 1 action.notable.param.rule_description = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. action.notable.param.rule_title = Excessive DNS Failures action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3759,7 +3759,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. action.notable.param.rule_title = Execution of File With Spaces Before Extension action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3799,7 +3799,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. action.notable.param.rule_title = Execution of File with Multiple Extensions action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3839,7 +3839,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search returns a list of hosts that have not successfully completed a backup in over a week. action.notable.param.rule_title = Extended Period Without Successful Netbackup Backups action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3879,7 +3879,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for file writes with extensions consistent with a SamSam ransomware attack. action.notable.param.rule_title = File with Samsam Extension action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3919,7 +3919,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for the first time a Windows service is seen running in your environment. action.notable.param.rule_title = First Time Seen Running Windows Service action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3958,7 +3958,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. action.notable.param.rule_title = First time seen command line argument action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -3998,7 +3998,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. action.notable.param.rule_title = GCP GCR container uploaded action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4037,7 +4037,7 @@ action.notable = 1 action.notable.param.rule_description = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster action.notable.param.rule_title = GCP Kubernetes cluster scan detection action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4077,7 +4077,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.notable.param.rule_title = Hiding Files And Directories With Attrib exe action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4116,7 +4116,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. action.notable.param.rule_title = Hosts receiving high volume of network traffic from email server action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4155,7 +4155,7 @@ action.notable = 1 action.notable.param.rule_description = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. action.notable.param.rule_title = Identify New User Accounts action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4194,7 +4194,7 @@ action.notable = 1 action.notable.param.rule_description = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. action.notable.param.rule_title = Large Volume of DNS ANY Queries action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4234,7 +4234,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. action.notable.param.rule_title = MacOS - Re-opened Applications action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4274,7 +4274,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. action.notable.param.rule_title = Malicious PowerShell Process - Connect To Internet With Hidden Window action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4314,7 +4314,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. action.notable.param.rule_title = Malicious PowerShell Process - Encoded Command action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4354,7 +4354,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. action.notable.param.rule_title = Malicious PowerShell Process - Execution Policy Bypass action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4394,7 +4394,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. action.notable.param.rule_title = Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4434,7 +4434,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. action.notable.param.rule_title = Malicious PowerShell Process With Obfuscation Techniques action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4473,7 +4473,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. action.notable.param.rule_title = Monitor DNS For Brand Abuse action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4512,7 +4512,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. action.notable.param.rule_title = Monitor Email For Brand Abuse action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4552,7 +4552,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. action.notable.param.rule_title = Monitor Registry Keys for Print Monitors action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4592,7 +4592,7 @@ action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. action.notable.param.rule_title = Monitor Web Traffic For Brand Abuse action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4631,7 +4631,7 @@ action.notable = 1 action.notable.param.rule_description = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. action.notable.param.rule_title = Multiple Okta Users With Invalid Credentails From The Same IP action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4671,7 +4671,7 @@ action.notable.param.nes_fields = ['user', 'src'] action.notable.param.rule_description = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. action.notable.param.rule_title = New container uploaded to AWS ECR action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4711,7 +4711,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. action.notable.param.rule_title = No Windows Updates in a time frame action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4750,7 +4750,7 @@ action.notable = 1 action.notable.param.rule_description = Detect Okta user lockout events action.notable.param.rule_title = Okta Account Lockout Events action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4789,7 +4789,7 @@ action.notable = 1 action.notable.param.rule_description = Detect failed Okta SSO events action.notable.param.rule_title = Okta Failed SSO Attempts action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4829,7 +4829,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search detects logins from the same user from different states in a 24 hour period. action.notable.param.rule_title = Okta User Logins From Multiple Cities action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4868,7 +4868,7 @@ action.notable = 1 action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. action.notable.param.rule_title = Open Redirect in Splunk Web action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4907,7 +4907,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for ColdRoot events from the osx-attacks osquery pack. action.notable.param.rule_title = Osquery pack - ColdRoot detection action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4947,7 +4947,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. action.notable.param.rule_title = Overwriting Accessibility Binaries action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -4987,7 +4987,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launched via WMI. action.notable.param.rule_title = Process Execution via WMI action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5026,7 +5026,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input action.notable.param.rule_title = Processes Tapping Keyboard Events action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5066,7 +5066,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. action.notable.param.rule_title = Processes created by netsh action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5106,7 +5106,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. action.notable.param.rule_title = Processes launching netsh action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5145,7 +5145,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. action.notable.param.rule_title = Prohibited Network Traffic Allowed action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5185,7 +5185,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as prohibited. action.notable.param.rule_title = Prohibited Software On Endpoint action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5224,7 +5224,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. action.notable.param.rule_title = Protocol or Port Mismatch action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5264,7 +5264,7 @@ action.notable.param.nes_fields = ['user', 'dest', 'src'] action.notable.param.rule_description = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. action.notable.param.rule_title = Protocols passing authentication in cleartext action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5304,7 +5304,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.notable.param.rule_title = Reg exe Manipulating Windows Services Registry Keys action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5344,7 +5344,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for command-line arguments used to hide a file or directory using the reg add command. action.notable.param.rule_title = Reg exe used to hide files directories via registry keys action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5384,7 +5384,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. action.notable.param.rule_title = Registry Keys Used For Persistence action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5424,7 +5424,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. action.notable.param.rule_title = Registry Keys Used For Privilege Escalation action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5463,7 +5463,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. action.notable.param.rule_title = Registry Keys for Creating SHIM Databases action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5503,7 +5503,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. action.notable.param.rule_title = Remote Desktop Network Bruteforce action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5543,7 +5543,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. action.notable.param.rule_title = Remote Desktop Network Traffic action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5583,7 +5583,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. action.notable.param.rule_title = Remote Desktop Process Running On System action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5623,7 +5623,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. action.notable.param.rule_title = Remote Process Instantiation via WMI action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5663,7 +5663,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search monitors for remote modifications to registry keys. action.notable.param.rule_title = Remote Registry Key modifications action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5703,7 +5703,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for wmic.exe being launched with parameters to operate on remote systems. action.notable.param.rule_title = Remote WMI Command Attempt action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5743,7 +5743,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. action.notable.param.rule_title = RunDLL Loading DLL By Ordinal action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5783,7 +5783,7 @@ action.notable.param.nes_fields = ['src'] action.notable.param.rule_description = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. action.notable.param.rule_title = SMB Traffic Spike action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5826,7 +5826,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. action.notable.param.rule_title = SMB Traffic Spike - MLTK action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5866,7 +5866,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for long URLs that have several SQL commands visible within them. action.notable.param.rule_title = SQL Injection with Long URLs action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5906,7 +5906,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. action.notable.param.rule_title = Samsam Test File Write action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5946,7 +5946,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. action.notable.param.rule_title = Sc exe Manipulating Windows Services action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -5986,7 +5986,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. action.notable.param.rule_title = Scheduled Task Name Used by Dragonfly Threat Actors action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6026,7 +6026,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. action.notable.param.rule_title = Scheduled tasks used in BadRabbit ransomware action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6066,7 +6066,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. action.notable.param.rule_title = Schtasks scheduling job on remote system action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6106,7 +6106,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. action.notable.param.rule_title = Schtasks used for forcing a reboot action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6146,7 +6146,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for scripts launched via WMI. action.notable.param.rule_title = Script Execution via WMI action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6186,7 +6186,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.notable.param.rule_title = Shim Database File Creation action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6226,7 +6226,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. action.notable.param.rule_title = Shim Database Installation With Suspicious Parameters action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6266,7 +6266,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects accounts that were created and deleted in a short time period. action.notable.param.rule_title = Short Lived Windows Accounts action.notable.param.security_domain = access -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6305,7 +6305,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for process names that consist only of a single letter. action.notable.param.rule_title = Single Letter Process On Endpoint action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6344,7 +6344,7 @@ action.notable = 1 action.notable.param.rule_description = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. action.notable.param.rule_title = Spectre and Meltdown Vulnerable Systems action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6384,7 +6384,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for a sharp increase in the number of files written to a particular host action.notable.param.rule_title = Spike in File Writes action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6424,7 +6424,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. action.notable.param.rule_title = Splunk Enterprise Information Disclosure action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6464,7 +6464,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. action.notable.param.rule_title = Suspicious Changes to File Associations action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6504,7 +6504,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). action.notable.param.rule_title = Suspicious Email - UBA Anomaly action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6545,7 +6545,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for emails that have attachments with suspicious file extensions. action.notable.param.rule_title = Suspicious Email Attachment Extensions action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6585,7 +6585,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for files created with names that have been linked to malicious activity. action.notable.param.rule_title = Suspicious File Write action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6625,7 +6625,7 @@ action.notable.param.nes_fields = ['dest', 'src'] action.notable.param.rule_description = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. action.notable.param.rule_title = Suspicious Java Classes action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6665,7 +6665,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. action.notable.param.rule_title = Suspicious LNK file launching a process action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6705,7 +6705,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. action.notable.param.rule_title = Suspicious Reg exe Process action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6745,7 +6745,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The wevtutil.exe application is the windows event log utility. This searches for wevtutil.exe with parameters for clearing the application, security, setup, or system event logs. action.notable.param.rule_title = Suspicious wevtutil Usage action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6784,7 +6784,7 @@ action.notable = 1 action.notable.param.rule_description = This search detects writes to the 'System Volume Information' folder by something other than the System process. action.notable.param.rule_title = Suspicious writes to System Volume Information action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6824,7 +6824,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search detects writes to the recycle bin by a process other than explorer.exe. action.notable.param.rule_title = Suspicious writes to windows Recycle Bin action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6864,7 +6864,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. action.notable.param.rule_title = System Processes Run From Unexpected Locations action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6903,7 +6903,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. action.notable.param.rule_title = TOR Traffic action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6943,7 +6943,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. action.notable.param.rule_title = USN Journal Deletion action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -6983,7 +6983,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = This search looks for applications on the endpoint that you have marked as uncommon. action.notable.param.rule_title = Uncommon Processes On Endpoint action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7023,7 +7023,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Attackers often disable security tools to avoid detection. This search looks for the usage of process `fltMC.exe` to unload a Sysmon Driver that will stop sysmon from collecting the data. action.notable.param.rule_title = Unload Sysmon Filter Driver action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7063,7 +7063,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search detects loading of unsigned images by LSASS. action.notable.param.rule_title = Unsigned Image Loaded by LSASS action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7102,7 +7102,7 @@ action.notable = 1 action.notable.param.rule_description = This search gives you the hosts where a backup was attempted and then failed. action.notable.param.rule_title = Unsuccessful Netbackup backups action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7142,7 +7142,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. action.notable.param.rule_title = Unusually Long Command Line action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7182,7 +7182,7 @@ action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Command lines that are extremely long may be indicative of malicious activity on your hosts. This search leverages the Machine Learning Toolkit (MLTK) to help identify command lines with lengths that are unusual for a given user. action.notable.param.rule_title = Unusually Long Command Line - MLTK action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7221,7 +7221,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for unusually long strings in the Content-Type http header that the client sends the server. action.notable.param.rule_title = Unusually Long Content-Type Length action.notable.param.security_domain = network -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7261,7 +7261,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. action.notable.param.rule_title = WMI Permanent Event Subscription action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7301,7 +7301,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for the creation of WMI permanent event subscriptions. action.notable.param.rule_title = WMI Permanent Event Subscription - Sysmon action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7340,7 +7340,7 @@ action.notable = 1 action.notable.param.rule_description = This search looks for the creation of WMI temporary event subscriptions. action.notable.param.rule_title = WMI Temporary Event Subscription action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7380,7 +7380,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search is used to identify the creation of multiple user accounts using the same email domain name. action.notable.param.rule_title = Web Fraud - Account Harvesting action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7419,7 +7419,7 @@ action.notable = 1 action.notable.param.rule_description = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. action.notable.param.rule_title = Web Fraud - Anomalous User Clickspeed action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7459,7 +7459,7 @@ action.notable.param.nes_fields = ['user'] action.notable.param.rule_description = This search is used to identify user accounts that share a common password. action.notable.param.rule_title = Web Fraud - Password Sharing Across Accounts action.notable.param.security_domain = threat -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7499,7 +7499,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for suspicious processes on all systems labeled as web servers. action.notable.param.rule_title = Web Servers Executing Suspicious Processes action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7539,7 +7539,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = This search looks for Windows events that indicate one of the Windows event logs has been purged. action.notable.param.rule_title = Windows Event Log Cleared action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -7579,7 +7579,7 @@ action.notable.param.nes_fields = ['dest'] action.notable.param.rule_description = The search looks for modifications to the hosts file on all Windows endpoints across your environment. action.notable.param.rule_title = Windows hosts file modification action.notable.param.security_domain = endpoint -action.notable.param.severity = medium +action.notable.param.severity = high alert.digest_mode = 1 action.escu.earliest_time_offset = 3600 action.escu.latest_time_offset = 86400 @@ -9431,7 +9431,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` +search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 0 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` [ESCU - Investigate Network Traffic From src ip - Response Task] action.escu = 0 @@ -9536,7 +9536,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user +search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 [ESCU - Investigate Previous Unseen User - Response Task] action.escu = 0 diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 08dd3ad213..065592c473 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T08:09:53 UTC +# On Date: 2020-05-13T09:08:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 94d509161e..e07980a915 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T08:09:53 UTC +# On Date: 2020-05-13T09:08:45 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint"] +searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info"] +searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Process Registry Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process File Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS record changed - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] +searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] +searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get EC2 Launch Details", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host"] +searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Notable Info"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. diff --git a/package/default/workflow_actions.conf b/package/default/workflow_actions.conf new file mode 100644 index 0000000000..e18c065b73 --- /dev/null +++ b/package/default/workflow_actions.conf @@ -0,0 +1,480 @@ + +[workbench_panel_aws_investigate_user_activities_by_arn]] +label = Workbench - AWS Investigate User Activities By ARN +type = link +fields = *user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_aws_investigate_user_activities_by_arn&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_aws_investigate_user_activities_by_accesskeyid]] +label = Workbench - AWS Investigate User Activities By AccessKeyId +type = link +fields = *accessKeyId* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_aws_investigate_user_activities_by_accesskeyid&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_aws_investigate_user_activities_by_source_user]] +label = Workbench - AWS Investigate User Activities By Source User +type = link +fields = *src_user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_aws_investigate_user_activities_by_source_user&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_aws_network_acl_details_from_id]] +label = Workbench - AWS Network ACL Details from ID +type = link +fields = *networkAclId* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_aws_network_acl_details_from_id&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_aws_network_interface_details_via_resourceid]] +label = Workbench - AWS Network Interface details via resourceId +type = link +fields = *resourceId* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_aws_network_interface_details_via_resourceid&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_aws_s3_bucket_details_via_bucketname]] +label = Workbench - AWS S3 Bucket details via bucketName +type = link +fields = *bucketName* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_aws_s3_bucket_details_via_bucketname&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_all_backup_logs_for_host]] +label = Workbench - All backup logs for host +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_all_backup_logs_for_host&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_amazon_eks_kubernetes_activity_by_src_ip]] +label = Workbench - Amazon EKS Kubernetes activity by src ip +type = link +fields = *src_ip* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_amazon_eks_kubernetes_activity_by_src_ip&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_gcp_kubernetes_activity_by_src_ip]] +label = Workbench - GCP Kubernetes activity by src ip +type = link +fields = *src_user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_gcp_kubernetes_activity_by_src_ip&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_all_aws_activity_from_city]] +label = Workbench - Get All AWS Activity From City +type = link +fields = *City* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_all_aws_activity_from_city&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_all_aws_activity_from_country]] +label = Workbench - Get All AWS Activity From Country +type = link +fields = *Country* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_all_aws_activity_from_country&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_all_aws_activity_from_ip_address]] +label = Workbench - Get All AWS Activity From IP Address +type = link +fields = *src_ip* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_all_aws_activity_from_ip_address&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_all_aws_activity_from_region]] +label = Workbench - Get All AWS Activity From Region +type = link +fields = *Region* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_all_aws_activity_from_region&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_authentication_logs_for_endpoint]] +label = Workbench - Get Authentication Logs For Endpoint +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_authentication_logs_for_endpoint&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_backup_logs_for_endpoint]] +label = Workbench - Get Backup Logs For Endpoint +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_backup_logs_for_endpoint&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_certificate_logs_for_a_domain]] +label = Workbench - Get Certificate logs for a domain +type = link +fields = *domain* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_certificate_logs_for_a_domain&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_dns_server_history_for_a_host]] +label = Workbench - Get DNS Server History for a host +type = link +fields = *src_ip* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_dns_server_history_for_a_host&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + + +[workbench_panel_get_ec2_instance_details_by_instanceid]] +label = Workbench - Get EC2 Instance Details by instanceId +type = link +fields = *instanceId* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_ec2_instance_details_by_instanceid&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_ec2_launch_details]] +label = Workbench - Get EC2 Launch Details +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_ec2_launch_details&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_email_info]] +label = Workbench - Get Email Info +type = link +fields = *message_id* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_email_info&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_emails_from_specific_sender]] +label = Workbench - Get Emails From Specific Sender +type = link +fields = *src_user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_emails_from_specific_sender&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address]] +label = Workbench - Get First Occurrence and Last Occurrence of a MAC Address +type = link +fields = *src_mac* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_history_of_email_sources]] +label = Workbench - Get History Of Email Sources +type = link +fields = *src* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_history_of_email_sources&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_logon_rights_modifications_for_endpoint]] +label = Workbench - Get Logon Rights Modifications For Endpoint +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_logon_rights_modifications_for_endpoint&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_logon_rights_modifications_for_user]] +label = Workbench - Get Logon Rights Modifications For User +type = link +fields = *user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_get_logon_rights_modifications_for_user&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_notable_history]] +label = Workbench - Get Notable History +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_notable_history&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_notable_info]] +label = Workbench - Get Notable Info +type = link +fields = *event_id* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_notable_info&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + + + + + + + +[workbench_panel_get_process_responsible_for_the_dns_traffic]] +label = Workbench - Get Process Responsible For The DNS Traffic +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_process_responsible_for_the_dns_traffic&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_registry_activities]] +label = Workbench - Get Registry Activities +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_registry_activities&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_risk_modifiers_for_endpoint]] +label = Workbench - Get Risk Modifiers For Endpoint +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_risk_modifiers_for_endpoint&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_risk_modifiers_for_user]] +label = Workbench - Get Risk Modifiers For User +type = link +fields = *user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_get_risk_modifiers_for_user&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + + +[workbench_panel_get_update_logs_for_endpoint]] +label = Workbench - Get Update Logs For Endpoint +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_update_logs_for_endpoint&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_user_information_from_identity_table]] +label = Workbench - Get User Information from Identity Table +type = link +fields = *user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_get_user_information_from_identity_table&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_vulnerability_logs_for_endpoint]] +label = Workbench - Get Vulnerability Logs For Endpoint +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_vulnerability_logs_for_endpoint&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_get_web_session_information_via_session_id]] +label = Workbench - Get Web Session Information via session id +type = link +fields = *session_id* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_get_web_session_information_via_session_id&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_aws_ecr_container_listing_activity]] +label = Workbench - Investigate AWS ECR container listing activity +type = link +fields = *Compute.event_name* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_aws_ecr_container_listing_activity&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_aws_user_activities_by_user_field]] +label = Workbench - Investigate AWS User Activities by user field +type = link +fields = *user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_investigate_aws_user_activities_by_user_field&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_aws_activities_via_region_name]] +label = Workbench - Investigate AWS activities via region name +type = link +fields = *awsRegion* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_aws_activities_via_region_name&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_cloud_compute_instance_activities]] +label = Workbench - Investigate Cloud Compute Instance Activities +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_cloud_compute_instance_activities&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_failed_logins_for_multiple_destinations]] +label = Workbench - Investigate Failed Logins for Multiple Destinations +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_failed_logins_for_multiple_destinations&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_network_traffic_from_src_ip]] +label = Workbench - Investigate Network Traffic From src ip +type = link +fields = *src_ip* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_network_traffic_from_src_ip&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_okta_activity_by_ip_address]] +label = Workbench - Investigate Okta Activity by IP Address +type = link +fields = *user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_investigate_okta_activity_by_ip_address&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_okta_activity_by_app]] +label = Workbench - Investigate Okta Activity by app +type = link +fields = *app* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_okta_activity_by_app&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_pass_the_hash_attempts]] +label = Workbench - Investigate Pass the Hash Attempts +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_pass_the_hash_attempts&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_pass_the_ticket_attempts]] +label = Workbench - Investigate Pass the Ticket Attempts +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_pass_the_ticket_attempts&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_previous_unseen_user]] +label = Workbench - Investigate Previous Unseen User +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_previous_unseen_user&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_successful_remote_desktop_authentications]] +label = Workbench - Investigate Successful Remote Desktop Authentications +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_successful_remote_desktop_authentications&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + + + +[workbench_panel_investigate_user_activities_in_okta]] +label = Workbench - Investigate User Activities In Okta +type = link +fields = *user* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_identity=$@field_value$&panel=workbench_panel_investigate_user_activities_in_okta&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + + +[workbench_panel_investigate_web_activity_from_host]] +label = Workbench - Investigate Web Activity From Host +type = link +fields = *dest* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_web_activity_from_host&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_web_activity_from_src_ip]] +label = Workbench - Investigate Web Activity From src ip +type = link +fields = *src_ip* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_web_activity_from_src_ip&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_investigate_web_posts_from_src]] +label = Workbench - Investigate Web POSTs From src +type = link +fields = *src* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_investigate_web_posts_from_src&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + +[workbench_panel_process_chain_analysis]] +label = Workbench - Process Chain Analysis +type = link +fields = *process_guid* +display_location = field_menu +link.uri = /app/$@namespace$/ess_workbench_panel?type_asset=$@field_value$&panel=workbench_panel_process_chain_analysis&drilldown_field=$@field_name$&use_drilldown_time=true +link.target = blank +link.method = get + From 9a50a74ee772c396397a44ced0d21760efd27b5c Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 14 May 2020 10:00:55 +0200 Subject: [PATCH 53/93] bug in generate --- ...baseline_of_command_line_length___mltk.yml | 2 +- baselines/baseline_of_smb_traffic___mltk.yml | 2 +- baselines/dnstwist_domain_names.yml | 2 +- ...seen_aws_provisioning_activity_sources.yml | 2 +- ...previously_seen_command_line_arguments.yml | 2 +- .../previously_seen_users_in_cloudtrail.yml | 4 +- ...te_previously_seen_users_in_cloudtrail.yml | 4 +- bin/converter_v2_v3.py | 15 +- bin/generate.py | 20 +- bin/jinja2_templates/analytic_stories.j2 | 4 + bin/validate.py | 4 + ..._aws_instances_launched_by_user___mltk.yml | 4 +- ...ws_instances_terminated_by_user___mltk.yml | 2 +- ..._eks_kubernetes_cluster_scan_detection.yml | 2 +- ...azon_eks_kubernetes_pod_scan_detection.yml | 2 +- ...dential_dump_from_registry_via_reg_exe.yml | 2 +- detections/child_processes_of_spoolsv_exe.yml | 2 +- ...nts_connecting_to_multiple_dns_servers.yml | 6 +- ...e_created_with_previously_unseen_image.yml | 2 +- ...d_with_previously_unseen_instance_type.yml | 12 +- ...ce_started_in_previously_unused_region.yml | 4 +- ...ate_local_admin_accounts_using_net_exe.yml | 2 +- ...or_delete_windows_shares_using_net_exe.yml | 2 +- ...ping_via_copy_command_from_shadow_copy.yml | 2 +- ...ial_dumping_via_symlink_to_shadow_copy.yml | 2 +- ..._scanning_for_vulnerable_jboss_servers.yml | 2 +- ...redential_dumping_through_LSASS_access.yml | 2 +- ...connecting_to_dynamic_domain_providers.yml | 8 +- .../detect_long_dns_txt_record_response.yml | 2 +- ...ious_requests_to_exploit_jboss_servers.yml | 2 +- .../detect_oulook_exe_writing_a__zip_file.yml | 2 +- detections/detect_outbound_smb_traffic.yml | 2 +- ...ohibited_applications_spawning_cmd_exe.yml | 2 +- .../detect_psexec_with_accepteula_flag.yml | 2 +- detections/detect_rare_executables.yml | 4 +- ...blocked_outbound_traffic_from_your_aws.yml | 4 +- ..._cmd_exe_to_launch_script_interpreters.yml | 2 +- detections/detection_of_dns_tunnels.yml | 2 +- .../disabling_remote_user_account_control.yml | 2 +- .../dns_query_length_outliers___mltk.yml | 6 +- ...ry_length_with_high_standard_deviation.yml | 4 +- ...s_resolved_by_unauthorized_dns_servers.yml | 6 +- ...itten_outside_of_the_outlook_directory.yml | 2 +- detections/excessive_dns_failures.yml | 2 +- .../first_time_seen_command_line_argument.yml | 8 +- detections/gcp_gcr_container_uploaded.yml | 2 +- .../gcp_kubernetes_cluster_scan_detection.yml | 2 +- ..._files_and_directories_with_attrib_exe.yml | 2 +- ...connect_to_internet_with_hidden_window.yml | 2 +- ...ll_process_with_obfuscation_techniques.yml | 2 +- detections/monitor_email_for_brand_abuse.yml | 2 +- ...nitor_registry_keys_for_print_monitors.yml | 2 +- ...h_invalid_credentails_from_the_same_ip.yml | 2 +- .../new_container_uploaded_to_aws_ecr.yml | 2 +- detections/okta_account_lockout_events.yml | 2 +- detections/okta_failed_sso_attempts.yml | 2 +- detections/process_execution_via_wmi.yml | 2 +- detections/processes_launching_netsh.yml | 2 +- .../prohibited_network_traffic_allowed.yml | 2 +- .../prohibited_software_on_endpoint.yml | 4 +- detections/protocol_or_port_mismatch.yml | 2 +- ...de_files_directories_via_registry_keys.yml | 2 +- ...istry_keys_for_creating_shim_databases.yml | 2 +- .../registry_keys_used_for_persistence.yml | 8 +- detections/remote_desktop_network_traffic.yml | 4 +- ...mote_desktop_process_running_on_system.yml | 2 +- .../remote_process_instantiation_via_wmi.yml | 2 +- .../remote_registry_key_modifications.yml | 2 +- .../sc_exe_manipulating_windows_services.yml | 4 +- ...k_name_used_by_dragonfly_threat_actors.yml | 2 +- detections/script_execution_via_wmi.yml | 2 +- detections/smb_traffic_spike.yml | 4 +- detections/smb_traffic_spike___mltk.yml | 6 +- detections/spike_in_file_writes.yml | 2 +- ...uspicious_changes_to_file_associations.yml | 2 +- ...suspicious_email_attachment_extensions.yml | 2 +- ...uspicious_lnk_file_launching_a_process.yml | 2 +- detections/suspicious_reg_exe_process.yml | 4 +- ...rocesses_run_from_unexpected_locations.yml | 4 +- detections/tor_traffic.yml | 2 +- detections/uncommon_processes_on_endpoint.yml | 4 +- detections/unsigned_image_loaded_by_LSASS.yml | 2 +- detections/unusually_long_command_line.yml | 6 +- .../unusually_long_command_line___mltk.yml | 4 +- package/default/analytic_stories.conf | 188 +++++++++--------- ...ailed_logins_for_multiple_destinations.xml | 2 +- ...l_investigate_pass_the_ticket_attempts.xml | 2 +- package/default/es_investigations.conf | 118 +++++------ package/default/macros.conf | 2 +- package/default/savedsearches.conf | 172 ++++++++-------- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 132 ++++++------ ...ailed_logins_for_multiple_destinations.yml | 2 +- .../investigate_pass_the_ticket_attempts.yml | 6 +- stories/lateral_movement.yml | 1 + 95 files changed, 474 insertions(+), 434 deletions(-) diff --git a/baselines/baseline_of_command_line_length___mltk.yml b/baselines/baseline_of_command_line_length___mltk.yml index 28205e56d9..f5068fa341 100644 --- a/baselines/baseline_of_command_line_length___mltk.yml +++ b/baselines/baseline_of_command_line_length___mltk.yml @@ -31,5 +31,5 @@ tags: - Suspicious MSHTA Activity - Unusual Processes detections: - - Detect Prohibited Applications Spawning cmd.exe - Unusually Long Command Line - MLTK + - Detect Prohibited Applications Spawning cmd.exe diff --git a/baselines/baseline_of_smb_traffic___mltk.yml b/baselines/baseline_of_smb_traffic___mltk.yml index e5b850a63c..f852ea17ce 100644 --- a/baselines/baseline_of_smb_traffic___mltk.yml +++ b/baselines/baseline_of_smb_traffic___mltk.yml @@ -36,5 +36,5 @@ tags: - Netsh Abuse - Ransomware detections: - - Processes launching netsh - SMB Traffic Spike - MLTK + - Processes launching netsh diff --git a/baselines/dnstwist_domain_names.yml b/baselines/dnstwist_domain_names.yml index 9375d75ac2..7955295932 100644 --- a/baselines/dnstwist_domain_names.yml +++ b/baselines/dnstwist_domain_names.yml @@ -16,6 +16,6 @@ tags: - Brand Monitoring - Suspicious Emails detections: - - Monitor DNS For Brand Abuse - Monitor Email For Brand Abuse - Monitor Web Traffic For Brand Abuse + - Monitor DNS For Brand Abuse diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml index f03a3a3b70..24fad13984 100644 --- a/baselines/previously_seen_aws_provisioning_activity_sources.yml +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -18,6 +18,6 @@ tags: - AWS Suspicious Provisioning Activities detections: - AWS Cloud Provisioning From Previously Unseen City - - AWS Cloud Provisioning From Previously Unseen Region - AWS Cloud Provisioning From Previously Unseen IP Address + - AWS Cloud Provisioning From Previously Unseen Region - AWS Cloud Provisioning From Previously Unseen Country diff --git a/baselines/previously_seen_command_line_arguments.yml b/baselines/previously_seen_command_line_arguments.yml index 7ac6d4ed10..32d364cc1e 100644 --- a/baselines/previously_seen_command_line_arguments.yml +++ b/baselines/previously_seen_command_line_arguments.yml @@ -25,6 +25,6 @@ tags: - Suspicious Command-Line Executions - Suspicious MSHTA Activity detections: + - Processes launching netsh - First time seen command line argument - Detect Prohibited Applications Spawning cmd.exe - - Processes launching netsh diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml index 6c2e04ba6b..6f5a11191f 100644 --- a/baselines/previously_seen_users_in_cloudtrail.yml +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -19,7 +19,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Country - - Detect new user AWS Console Login + - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Region + - Detect new user AWS Console Login diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml index fb40d6386d..ca2d520640 100644 --- a/baselines/update_previously_seen_users_in_cloudtrail.yml +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -20,7 +20,7 @@ tags: analytics_story: - Suspicious AWS Login Activities detections: - - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Country - - Detect new user AWS Console Login + - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Region + - Detect new user AWS Console Login diff --git a/bin/converter_v2_v3.py b/bin/converter_v2_v3.py index b4ff19f64b..6c0cba747c 100644 --- a/bin/converter_v2_v3.py +++ b/bin/converter_v2_v3.py @@ -78,7 +78,9 @@ def generate_content(): if not str('_filter') in new_dict['search']: new_dict['search'] = new_dict['search'] + ' | `' + new_dict['name'].replace('-','_').replace(' ','_').lower() + '_filter`' - new_dict['search'] = check_source_macro(new_dict['search']) + if 'search' in new_dict: + new_dict['search'] = check_source_macro(new_dict['search']) + new_dict['search'] = change_filter_macro(new_dict) new_dict['known_false_positives'] = orig_dict['known_false_positives'] tag_dict = {} @@ -356,6 +358,17 @@ def check_source_macro(search): return new_search +def change_filter_macro(object): + new_search = object['search'] + filter_macro = re.search("([a-z0-9_]*_filter)", new_search) + if filter_macro.group(1) != (object['name'].replace(' ', '_').replace('-', '_').replace('.', '_').replace('/', '_').lower() + '_filter'): + for match in re.finditer("([a-z0-9_]*_filter)", new_search): + new_search = new_search[0: match.start() - 1:] + new_search[match.end() + 1::] + new_search = new_search[:match.start() - 1] + '`' + object['name'].replace(' ', '_').replace('-', '_').replace('.', '_').replace('/', '_').lower() + '_filter' + '` ' + new_search[match.start():] + + return new_search + + def change_response_task_variable(object): if 'inputs' in object: for input in object['inputs']: diff --git a/bin/generate.py b/bin/generate.py index ab45aa86d4..cd28d011d1 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -112,17 +112,21 @@ def generate_savedsearches_conf(detections, response_tasks, baselines, deploymen return output_path -def generate_analytics_story_conf(stories, detections, response_tasks): +def generate_analytics_story_conf(stories, detections, response_tasks, baselines): sto_det = map_detection_to_stories(detections) sto_res = map_response_tasks_to_stories(response_tasks) + sto_bas = map_baselines_to_stories(baselines) + for story in stories: if story['name'] in sto_det: story['detections'] = list(sto_det[story['name']]) if story['name'] in sto_res: story['response_tasks'] = list(sto_res[story['name']]) + if story['name'] in sto_bas: + story['baselines'] = list(sto_bas[story['name']]) stories = prepare_stories(stories, detections) @@ -329,6 +333,18 @@ def map_response_tasks_to_stories(response_tasks): return sto_res +def map_baselines_to_stories(baselines): + sto_bas = {} + for baseline in baselines: + if 'tags' in baseline: + if 'analytics_story' in baseline['tags']: + for story in baseline['tags']['analytics_story']: + if not (story in sto_bas): + sto_bas[story] = {str('ESCU - ' + baseline['name'])} + else: + sto_bas[story].add(str('ESCU - ' + baseline['name'])) + return sto_bas + def custom_jinja2_enrichment_filter(string, object): customized_string = string for key in object.keys(): @@ -451,7 +467,7 @@ if __name__ == "__main__": detection_path = generate_savedsearches_conf(detections, response_tasks, baselines, deployments) stories = sorted(stories, key=lambda s: s['name']) - story_path = generate_analytics_story_conf(stories, detections, response_tasks) + story_path = generate_analytics_story_conf(stories, detections, response_tasks, baselines) use_case_lib_path = generate_use_case_library_conf(stories, detections, response_tasks, baselines) diff --git a/bin/jinja2_templates/analytic_stories.j2 b/bin/jinja2_templates/analytic_stories.j2 index 5cef46332e..fd88d98915 100644 --- a/bin/jinja2_templates/analytic_stories.j2 +++ b/bin/jinja2_templates/analytic_stories.j2 @@ -24,7 +24,11 @@ investigative_searches = {{ story.response_tasks | tojson }} {% else %} investigative_searches = [] {% endif %} +{% if story.baselines is defined %} +support_searches = {{ story.baselines | tojson }} +{% else %} support_searches = [] +{% endif %} {% if story.data_models is defined %} data_models = {{ story.data_models | tojson }} {% else %} diff --git a/bin/validate.py b/bin/validate.py index f95debab60..44540b146e 100644 --- a/bin/validate.py +++ b/bin/validate.py @@ -130,6 +130,10 @@ def validate_detection_search(object, macros): if not '_filter' in object['search']: errors.append("ERROR: Missing filter for detection: " + object['name']) + filter_macro = re.search("([a-z0-9_]*_filter)", object['search']) + if filter_macro.group(1) != (object['name'].replace(' ', '_').replace('-', '_').replace('.', '_').replace('/', '_').lower() + '_filter'): + errors.append("ERROR: filter for detection: " + object['name'] + " needs to use the name of the detection in lowercase and the special characters needs to be converted into _ .") + if any(x in object['search'] for x in ['eventtype=', 'sourcetype=', ' source=', 'index=']): if not 'index=_internal' in object['search']: errors.append("ERROR: Use source macro instead of eventtype, sourcetype, source or index in detection: " + object['name']) diff --git a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml index fa51d0eafc..41a777f6b4 100644 --- a/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_launched_by_user___mltk.yml @@ -10,7 +10,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Jason Brewer, Splunk -search: '`cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` +search: '`cloudtrail` eventName=RunInstances errorCode=success `abnormally_high_aws_instances_launched_by_user___mltk_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as isOutlier | where isOutlier=1' @@ -20,8 +20,8 @@ known_false_positives: Many service accounts configured within an AWS infrastruc human user. tags: analytics_story: - - Suspicious AWS EC2 Activities - Cloud Cryptomining + - Suspicious AWS EC2 Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml index a367d6f7f9..94c4b059e3 100644 --- a/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml +++ b/detections/abnormally_high_aws_instances_terminated_by_user___mltk.yml @@ -10,7 +10,7 @@ how_to_implement: You must install the AWS App for Splunk (version 5.1.0 or late type: ESCU references: [] author: Jason Brewer, Splunk -search: '`cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` +search: '`cloudtrail` eventName=TerminateInstances errorCode=success `abnormally_high_aws_instances_terminated_by_user___mltk_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" as isOutlier | where isOutlier=1' diff --git a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml index d2ecb7fc03..c226e5ee2f 100644 --- a/detections/amazon_eks_kubernetes_cluster_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_cluster_scan_detection.yml @@ -15,7 +15,7 @@ search: '`aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!= max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` - |`kubernetes_aws_scan_fingerprint_filter`' + |`amazon_eks_kubernetes_cluster_scan_detection_filter` ' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs will provide context. tags: diff --git a/detections/amazon_eks_kubernetes_pod_scan_detection.yml b/detections/amazon_eks_kubernetes_pod_scan_detection.yml index 0589ed924d..846074fa72 100644 --- a/detections/amazon_eks_kubernetes_pod_scan_detection.yml +++ b/detections/amazon_eks_kubernetes_pod_scan_detection.yml @@ -16,7 +16,7 @@ search: '`aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list o | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` - | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_filter`' + | `security_content_ctime(firstTime)` | `amazon_eks_kubernetes_pod_scan_detection_filter` ' known_false_positives: Not all unauthenticated requests are malicious, but frequency, UA and source IPs and direct request to API provide context. tags: diff --git a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml index df66cbec11..557c69ae1c 100644 --- a/detections/attempted_credential_dump_from_registry_via_reg_exe.yml +++ b/detections/attempted_credential_dump_from_registry_via_reg_exe.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_exe_filter`' + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_exe_filter` ' known_false_positives: None identified. tags: analytics_story: diff --git a/detections/child_processes_of_spoolsv_exe.yml b/detections/child_processes_of_spoolsv_exe.yml index cfcf99aee2..5e1cb995bf 100644 --- a/detections/child_processes_of_spoolsv_exe.yml +++ b/detections/child_processes_of_spoolsv_exe.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | `children_of_spoolsv_filter`' + | `security_content_ctime(lastTime)` | `child_processes_of_spoolsv_exe_filter` ' known_false_positives: Some legitimate printer-related processes may show up as children of spoolsv.exe. You should confirm that any activity as legitimate and may be added as exclusions in the search. diff --git a/detections/clients_connecting_to_multiple_dns_servers.yml b/detections/clients_connecting_to_multiple_dns_servers.yml index 1a235eee7a..3de2319de0 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.yml +++ b/detections/clients_connecting_to_multiple_dns_servers.yml @@ -22,14 +22,14 @@ author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count > 5 | - `clients_connecting_to_multiple_dns_servers_output_filter`' + `clients_connecting_to_multiple_dns_servers_filter` ' known_false_positives: It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate. tags: analytics_story: - - Suspicious DNS Traffic - - Host Redirection - Command and Control + - Host Redirection + - Suspicious DNS Traffic - DNS Hijacking mitre_attack_id: - T1048 diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml index 000613765e..11dfaa1d7d 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_image.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_image.yml @@ -12,7 +12,7 @@ type: ESCU references: [] author: David Dorsey, Splunk search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) - as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` + as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `cloud_compute_instance_created_with_previously_unseen_image_filter` by Compute.image_id, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_images | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by image_id, src_user | multireport diff --git a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml index d9fbd474e5..e81483bfff 100644 --- a/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml +++ b/detections/cloud_compute_instance_created_with_previously_unseen_instance_type.yml @@ -12,12 +12,12 @@ references: [] author: David Dorsey, Splunk search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances - `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type, - Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_instance_types - | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest - by instance_type, src_user | multireport [| table instance_type, firstTime, lastTime - | outputlookup previously_seen_cloud_compute_instance_types | where fact=fiction][| - eval new_type=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), + `cloud_compute_instance_created_with_previously_unseen_instance_type_filter` by + Compute.instance_type, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup + append=t previously_seen_cloud_compute_instance_types | stats min(firstTime) as + firstTime max(lastTime) as lastTime, values(dest) as dest by instance_type, src_user + | multireport [| table instance_type, firstTime, lastTime | outputlookup previously_seen_cloud_compute_instance_types + | where fact=fiction][| eval new_type=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), 1, 0) | where new_type=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table instance_type, dest, src_user, firstTime, lastTime' known_false_positives: It is possible that an admin will create a new system using diff --git a/detections/cloud_compute_instance_started_in_previously_unused_region.yml b/detections/cloud_compute_instance_started_in_previously_unused_region.yml index c17b568fba..f1e972da8a 100644 --- a/detections/cloud_compute_instance_started_in_previously_unused_region.yml +++ b/detections/cloud_compute_instance_started_in_previously_unused_region.yml @@ -14,8 +14,8 @@ references: [] author: David Dorsey, Splunk search: '| tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances - `previously_seen_cloud_regions_input_filter` by Compute.region, Compute.src_user - | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions + `cloud_compute_instance_started_in_previously_unused_region_filter` by Compute.region, + Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by region, src_user | multireport [| table region, firstTime, lastTime | outputlookup previously_seen_cloud_regions | where fact=fiction][| eval new_region=if(firstTime diff --git a/detections/create_local_admin_accounts_using_net_exe.yml b/detections/create_local_admin_accounts_using_net_exe.yml index e588eadeae..236489d1d2 100644 --- a/detections/create_local_admin_accounts_using_net_exe.yml +++ b/detections/create_local_admin_accounts_using_net_exe.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.user) OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* - OR process=*user*) |`create_local_admin_via_net_filter`' + OR process=*user*) |`create_local_admin_accounts_using_net_exe_filter` ' known_false_positives: Administrators often leverage net.exe to create admin accounts. tags: analytics_story: diff --git a/detections/create_or_delete_windows_shares_using_net_exe.yml b/detections/create_or_delete_windows_shares_using_net_exe.yml index ea3c23b4cd..9eb576fe3a 100644 --- a/detections/create_or_delete_windows_shares_using_net_exe.yml +++ b/detections/create_or_delete_windows_shares_using_net_exe.yml @@ -20,7 +20,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.user) OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) - | `create_or_delete_windows_shares_filter`' + | `create_or_delete_windows_shares_using_net_exe_filter` ' known_false_positives: Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. tags: diff --git a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml index 99704797b4..0031a9b18a 100644 --- a/detections/credential_dumping_via_copy_command_from_shadow_copy.yml +++ b/detections/credential_dumping_via_copy_command_from_shadow_copy.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime OR Processes.process=*\\system32\\config\\system* OR Processes.process=*\\windows\\ntds\\ntds.dit*) by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_copy_from_shadowcopy_filter`' + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `credential_dumping_via_copy_command_from_shadow_copy_filter` ' known_false_positives: unknown tags: analytics_story: diff --git a/detections/credential_dumping_via_symlink_to_shadow_copy.yml b/detections/credential_dumping_via_symlink_to_shadow_copy.yml index 2fe8fc2cba..2be920fab2 100644 --- a/detections/credential_dumping_via_symlink_to_shadow_copy.yml +++ b/detections/credential_dumping_via_symlink_to_shadow_copy.yml @@ -16,7 +16,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime Processes.process=*mklink* Processes.process=*HarddiskVolumeShadowCopy* by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` - | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_symlink_shadowcopy_filter` ' + | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `credential_dumping_via_symlink_to_shadow_copy_filter` ' known_false_positives: unknown tags: analytics_story: diff --git a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml index 9cc94a66ce..7b7dfec741 100644 --- a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml +++ b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml @@ -19,8 +19,8 @@ known_false_positives: It's possible for legitimate HTTP requests to be made to containing the suspicious paths. tags: analytics_story: - - JBoss Vulnerability - SamSam Ransomware + - JBoss Vulnerability mitre_attack_id: - T1082 kill_chain_phases: diff --git a/detections/detect_credential_dumping_through_LSASS_access.yml b/detections/detect_credential_dumping_through_LSASS_access.yml index 966c583019..42f7ba29a1 100644 --- a/detections/detect_credential_dumping_through_LSASS_access.yml +++ b/detections/detect_credential_dumping_through_LSASS_access.yml @@ -17,7 +17,7 @@ search: '`sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR G | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `detect_credential_dumping_through_LSASS_access_filter`' + | `detect_credential_dumping_through_LSAS`detect_credential_dumping_through_lsass_access_filter` ' known_false_positives: The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need diff --git a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index 8c019c3996..71f1c02a11 100644 --- a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -44,12 +44,12 @@ known_false_positives: Some users and applications may leverage Dynamic DNS to r however this activity must be verified. tags: analytics_story: - - Data Protection - - Command and Control - - Suspicious DNS Traffic - Prohibited Traffic Allowed or Protocol Mismatch - - Dynamic DNS + - Suspicious DNS Traffic - DNS Hijacking + - Dynamic DNS + - Command and Control + - Data Protection kill_chain_phases: - Command and Control - Actions on Objectives diff --git a/detections/detect_long_dns_txt_record_response.yml b/detections/detect_long_dns_txt_record_response.yml index 12a52379a4..b335fa7f35 100644 --- a/detections/detect_long_dns_txt_record_response.yml +++ b/detections/detect_long_dns_txt_record_response.yml @@ -28,8 +28,8 @@ known_false_positives: It's possible that legitimate TXT record responses can be to help mitigate false positives. tags: analytics_story: - - Suspicious DNS Traffic - Command and Control + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml index ba130244e6..49be7121db 100644 --- a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml +++ b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml @@ -20,8 +20,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: No known false positives for this detection. tags: analytics_story: - - JBoss Vulnerability - SamSam Ransomware + - JBoss Vulnerability kill_chain_phases: - Delivery cis20: diff --git a/detections/detect_oulook_exe_writing_a__zip_file.yml b/detections/detect_oulook_exe_writing_a__zip_file.yml index c7a4375e06..e5d0e39b9f 100644 --- a/detections/detect_oulook_exe_writing_a__zip_file.yml +++ b/detections/detect_oulook_exe_writing_a__zip_file.yml @@ -25,7 +25,7 @@ search: '| tstats `security_content_summariesonly` min(_time) as firstTime max( | rename process_id as malicious_id| fields malicious_id outlook_id dest file_path file_name file_hash count file_id] | table firstTime lastTime user malicious_id outlook_id process_name parent_process_name file_name file_path | where file_name - != "" | `outlook_writing_zip_filter`' + != "" | `detect_oulook_exe_writing_a__zip_file_filter` ' known_false_positives: It is not uncommon for outlook to write legitimate zip files to the disk. tags: diff --git a/detections/detect_outbound_smb_traffic.yml b/detections/detect_outbound_smb_traffic.yml index 9ba0edee7f..6e20f9fd16 100644 --- a/detections/detect_outbound_smb_traffic.yml +++ b/detections/detect_outbound_smb_traffic.yml @@ -25,7 +25,7 @@ search: '| tstats `security_content_summariesonly` count earliest(_time) as earl OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(earliest)`| `security_content_ctime(latest)` - | `outbound_smb_connections_filter` ' + | `detect_outbound_smb_traffic_filter` ' known_false_positives: It is likely that the outbound Server Message Block (SMB) traffic is legitimate, if the company's internal networks are not well-defined in the Assets and Identity Framework. Categorize the internal CIDR blocks as `internal` in the diff --git a/detections/detect_prohibited_applications_spawning_cmd_exe.yml b/detections/detect_prohibited_applications_spawning_cmd_exe.yml index 81ed57b5b4..94a4c9cb39 100644 --- a/detections/detect_prohibited_applications_spawning_cmd_exe.yml +++ b/detections/detect_prohibited_applications_spawning_cmd_exe.yml @@ -22,8 +22,8 @@ known_false_positives: There are circumstances where an application may legitima the lookup file, as appropriate. tags: analytics_story: - - Suspicious MSHTA Activity - Suspicious Command-Line Executions + - Suspicious MSHTA Activity mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detect_psexec_with_accepteula_flag.yml b/detections/detect_psexec_with_accepteula_flag.yml index 3037846adc..8e9cda022b 100644 --- a/detections/detect_psexec_with_accepteula_flag.yml +++ b/detections/detect_psexec_with_accepteula_flag.yml @@ -29,8 +29,8 @@ known_false_positives: Administrators can leverage PsExec for accessing remote s event on a machine tags: analytics_story: - - DHS Report TA18-074A - SamSam Ransomware + - DHS Report TA18-074A mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detect_rare_executables.yml b/detections/detect_rare_executables.yml index f0aa957cab..4594d7567d 100644 --- a/detections/detect_rare_executables.yml +++ b/detections/detect_rare_executables.yml @@ -22,14 +22,14 @@ search: '| tstats `security_content_summariesonly` count values(Processes.dest) as process | rex field=user "(?.*)\\\\(?.*)" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name - as process| `filter_rare_process_whitelist`| table process ] | `rare_executables_on_endpoint_filter`' + as process| `filter_rare_process_whitelist`| table process ] | `detect_rare_executables_filter` ' known_false_positives: Some legitimate processes may be only rarely executed in your environment. As these are identified, update `rare_process_whitelist_local.csv` to filter them out of your search results. tags: analytics_story: - - Unusual Processes - 'Emotet Malware DHS Report TA18-201A ' + - Unusual Processes kill_chain_phases: - Installation - Command and Control diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml index 2625d89735..e06ea84b01 100644 --- a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -41,9 +41,9 @@ known_false_positives: The false-positive rate may vary based on the values of`d of blocked outbound connections. tags: analytics_story: - - Suspicious AWS Traffic - - AWS Network ACL Activity - Command and Control + - AWS Network ACL Activity + - Suspicious AWS Traffic kill_chain_phases: - Actions on Objectives - Command and Control diff --git a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml index d261e24136..37fac4086e 100644 --- a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml @@ -22,8 +22,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: Some legitimate applications may exhibit this behavior. tags: analytics_story: - - 'Emotet Malware DHS Report TA18-201A ' - Suspicious Command-Line Executions + - 'Emotet Malware DHS Report TA18-201A ' mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml index df198f832a..b5cb9d2b95 100644 --- a/detections/detection_of_dns_tunnels.yml +++ b/detections/detection_of_dns_tunnels.yml @@ -39,9 +39,9 @@ known_false_positives: It's possible that normal DNS traffic will exhibit this b can also be modified to better suit your environment. tags: analytics_story: - - Suspicious DNS Traffic - Command and Control - Data Protection + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml index ecb9b0b969..878a50c013 100644 --- a/detections/disabling_remote_user_account_control.yml +++ b/detections/disabling_remote_user_account_control.yml @@ -21,8 +21,8 @@ known_false_positives: This registry key may be modified via administrators to i a change in system policy. This type of change should be a very rare occurrence. tags: analytics_story: - - Windows Defense Evasion Tactics - Suspicious Windows Registry Activities + - Windows Defense Evasion Tactics mitre_attack_id: - T1112 kill_chain_phases: diff --git a/detections/dns_query_length_outliers___mltk.yml b/detections/dns_query_length_outliers___mltk.yml index f002a02944..960bc2a820 100644 --- a/detections/dns_query_length_outliers___mltk.yml +++ b/detections/dns_query_length_outliers___mltk.yml @@ -41,15 +41,15 @@ search: '| tstats `security_content_summariesonly` count min(_time) as start_tim | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename "IsOutlier(query_length)" as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time - query record_type count src dest query_length | `dns_query_length_mltk_filter` ' + query record_type count src dest query_length | `dns_query_length_outliers___mltk_filter` ' known_false_positives: If you are seeing more results than desired, you may consider reducing the value for threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. tags: analytics_story: - - Suspicious DNS Traffic - - Hidden Cobra Malware - Command and Control + - Hidden Cobra Malware + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/dns_query_length_with_high_standard_deviation.yml b/detections/dns_query_length_with_high_standard_deviation.yml index 8054a26d51..1d612a5ac3 100644 --- a/detections/dns_query_length_with_high_standard_deviation.yml +++ b/detections/dns_query_length_with_high_standard_deviation.yml @@ -18,9 +18,9 @@ search: '| tstats `security_content_summariesonly` count from datamodel=Network_ known_false_positives: It's possible there can be long domain names that are legitimate. tags: analytics_story: - - Suspicious DNS Traffic - - Hidden Cobra Malware - Command and Control + - Hidden Cobra Malware + - Suspicious DNS Traffic mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml index 1e0e8c9f1e..1ea4c64a62 100644 --- a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml +++ b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml @@ -13,14 +13,14 @@ type: ESCU author: Bhavin Patel, Splunk search: '| tstats `security_content_summariesonly` count from datamodel=Network_Resolution where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src - DNS.dest | `drop_dm_object_name("DNS")` | `unauthorized_dns_servers_filter`' + DNS.dest | `drop_dm_object_name("DNS")` | `dns_query_requests_resolved_by_unauthorized_dns_servers_filter` ' known_false_positives: Legitimate DNS activity can be detected in this search. Investigate, verify and update the list of authorized DNS servers as appropriate. tags: analytics_story: - - Suspicious DNS Traffic - - Host Redirection - Command and Control + - Host Redirection + - Suspicious DNS Traffic - DNS Hijacking kill_chain_phases: - Command and Control diff --git a/detections/email_files_written_outside_of_the_outlook_directory.yml b/detections/email_files_written_outside_of_the_outlook_directory.yml index 4359a698c3..3bda188598 100644 --- a/detections/email_files_written_outside_of_the_outlook_directory.yml +++ b/detections/email_files_written_outside_of_the_outlook_directory.yml @@ -19,7 +19,7 @@ search: '| tstats `security_content_summariesonly` count values(Filesystem.file_ != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name("Filesystem")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| - `email_files_not_in_outlook_directory_filter`' + `email_files_written_outside_of_the_outlook_directory_filter` ' known_false_positives: Administrators and users sometimes prefer backing up their email data by moving the email files into a different folder. These attempts will be detected by the search. diff --git a/detections/excessive_dns_failures.yml b/detections/excessive_dns_failures.yml index d2e6d34058..6289c61f59 100644 --- a/detections/excessive_dns_failures.yml +++ b/detections/excessive_dns_failures.yml @@ -21,8 +21,8 @@ known_false_positives: It is possible legitimate traffic can trigger this rule. to better suit your environment. tags: analytics_story: - - Suspicious DNS Traffic - Command and Control + - Suspicious DNS Traffic mitre_attack_id: - T1048 - T1043 diff --git a/detections/first_time_seen_command_line_argument.yml b/detections/first_time_seen_command_line_argument.yml index c6e8de58d3..b15dcdd2a9 100644 --- a/detections/first_time_seen_command_line_argument.yml +++ b/detections/first_time_seen_command_line_argument.yml @@ -27,18 +27,18 @@ search: '| tstats `security_content_summariesonly` min(_time) as firstTime max(_ | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCmdLineArgument=1 | `security_content_ctime(firstTime)` - | `security_content_ctime(lastTime)` | table process] | `first_time_seen_cmd_line_filter` ' + | `security_content_ctime(lastTime)` | table process] | `first_time_seen_command_line_argument_filter` ' known_false_positives: Legitimate programs can also use command-line arguments to execute. Please verify the command-line arguments to check what command/program is being executed. We recommend customizing the `first_time_seen_cmd_line_filter` macro to exclude legitimate parent_process_name tags: analytics_story: + - Suspicious Command-Line Executions + - Hidden Cobra Malware + - DHS Report TA18-074A - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Orangeworm Attack Group - - Hidden Cobra Malware - - Suspicious Command-Line Executions - - DHS Report TA18-074A mitre_attack_id: - T1064 - T1059 diff --git a/detections/gcp_gcr_container_uploaded.yml b/detections/gcp_gcr_container_uploaded.yml index 644853ecc0..40c531d147 100644 --- a/detections/gcp_gcr_container_uploaded.yml +++ b/detections/gcp_gcr_container_uploaded.yml @@ -15,7 +15,7 @@ author: Rod Soto, Rico Valdez, Splunk search: '|tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Storage where Storage.event_name=storage.objects.create by Storage.src_user Storage.account Storage.action Storage.bucket_name Storage.event_name Storage.http_user_agent Storage.msg - Storage.object_path | `drop_dm_object_name("Storage")` | `container_implant_gcp_detection_filter`' + Storage.object_path | `drop_dm_object_name("Storage")` | `gcp_gcr_container_uploaded_filter` ' known_false_positives: Uploading container is a normal behavior from developers or users with access to container registry. GCP GCR registers container upload as a Storage event, this search must be considered under the context of CONTAINER upload diff --git a/detections/gcp_kubernetes_cluster_scan_detection.yml b/detections/gcp_kubernetes_cluster_scan_detection.yml index f401f97e3b..3a666e58db 100644 --- a/detections/gcp_kubernetes_cluster_scan_detection.yml +++ b/detections/gcp_kubernetes_cluster_scan_detection.yml @@ -19,7 +19,7 @@ search: '`google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp! values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | - `kubernetes_gcp_scan_fingerprint_filter`' + `gcp_kubernetes_cluster_scan_detection_filter` ' known_false_positives: Not all unauthenticated requests are malicious, but frequency, User Agent and source IPs will provide context. tags: diff --git a/detections/hiding_files_and_directories_with_attrib_exe.yml b/detections/hiding_files_and_directories_with_attrib_exe.yml index e09f0689af..3cbb39cf58 100644 --- a/detections/hiding_files_and_directories_with_attrib_exe.yml +++ b/detections/hiding_files_and_directories_with_attrib_exe.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) values(Proce as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| - `attrib_to_hide_files_filter`' + `hiding_files_and_directories_with_attrib_exe_filter` ' known_false_positives: 'Some applications and users may legitimately use attrib.exe to interact with the files. ' tags: diff --git a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml index c1b4b686bc..2217d8c5f7 100644 --- a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml +++ b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml @@ -26,8 +26,8 @@ known_false_positives: Legitimate process can have this combination of command-l options, but it's not common. tags: analytics_story: - - Malicious PowerShell - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Malicious PowerShell mitre_attack_id: - T1086 - T1064 diff --git a/detections/malicious_powershell_process_with_obfuscation_techniques.yml b/detections/malicious_powershell_process_with_obfuscation_techniques.yml index 83c33bfc2d..d92fe3f4f0 100644 --- a/detections/malicious_powershell_process_with_obfuscation_techniques.yml +++ b/detections/malicious_powershell_process_with_obfuscation_techniques.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process, - "`"))-1) + (mvcount(split(process, "^"))-1) | `malicious_powershell_process_obfuscation_techniques_output_filter` + "`"))-1) + (mvcount(split(process, "^"))-1) | `malicious_powershell_process_with_obfuscation_techniques_filter` | search num_obfuscation > 0' known_false_positives: These characters might be legitimately on the command-line, but it is not common. diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml index aa409d05fa..7889964dfc 100644 --- a/detections/monitor_email_for_brand_abuse.yml +++ b/detections/monitor_email_for_brand_abuse.yml @@ -21,8 +21,8 @@ search: '| tstats `security_content_summariesonly` values(All_Email.recipient) a known_false_positives: None at this time tags: analytics_story: - - Brand Monitoring - Suspicious Emails + - Brand Monitoring kill_chain_phases: - Delivery cis20: diff --git a/detections/monitor_registry_keys_for_print_monitors.yml b/detections/monitor_registry_keys_for_print_monitors.yml index 50d7ec4353..dad8911dab 100644 --- a/detections/monitor_registry_keys_for_print_monitors.yml +++ b/detections/monitor_registry_keys_for_print_monitors.yml @@ -25,8 +25,8 @@ known_false_positives: You will encounter noise from legitimate print-monitor re entries. tags: analytics_story: - - Windows Persistence Techniques - Suspicious Windows Registry Activities + - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml index a475592a7a..c1be6e3e39 100644 --- a/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml +++ b/detections/multiple_okta_users_with_invalid_credentails_from_the_same_ip.yml @@ -13,7 +13,7 @@ search: '`okta` outcome.reason=INVALID_CREDENTIALS | rename client.geographicalC as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` - | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter`' + | search distinct_users > 5| `multiple_okta_users_with_invalid_credentails_from_the_same_ip_filter` ' known_false_positives: A single public IP address servicing multiple legitmate users may trigger this search. In addition, the threshold of 5 distinct users may be too low for your needs. You may modify the included filter macro XXXXXXXXXXXXX to raise diff --git a/detections/new_container_uploaded_to_aws_ecr.yml b/detections/new_container_uploaded_to_aws_ecr.yml index 5c370a47ad..78800dfcdf 100644 --- a/detections/new_container_uploaded_to_aws_ecr.yml +++ b/detections/new_container_uploaded_to_aws_ecr.yml @@ -16,7 +16,7 @@ search: '| tstats count min(_time) as firstTime max(_time) as lastTime FROM data where Compute.user_type!="AssumeRole" AND Compute.http_user_agent="AWS Internal" AND Compute.event_name="PutImage" by Compute.image_id Compute.src_user Compute.src Compute.region Compute.msg Compute.user_type | `drop_dm_object_name("Compute")` - | `container_implant_aws_detection_filter`' + | `new_container_uploaded_to_aws_ecr_filter` ' known_false_positives: Uploading container is a normal behavior from developers or users with access to container registry. tags: diff --git a/detections/okta_account_lockout_events.yml b/detections/okta_account_lockout_events.yml index caa7f00a7e..1b6c01b38a 100644 --- a/detections/okta_account_lockout_events.yml +++ b/detections/okta_account_lockout_events.yml @@ -9,7 +9,7 @@ type: ESCU author: Rico Valdez, Splunk search: '`okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city - as city | table _time, user, country, state, city, src_ip |`okta_user_lockouts_filter`' + as city | table _time, user, country, state, city, src_ip |`okta_account_lockout_events_filter` ' known_false_positives: None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. diff --git a/detections/okta_failed_sso_attempts.yml b/detections/okta_failed_sso_attempts.yml index 3ff2cbae70..2bb6d30ae0 100644 --- a/detections/okta_failed_sso_attempts.yml +++ b/detections/okta_failed_sso_attempts.yml @@ -9,7 +9,7 @@ type: ESCU author: Rico Valdez, Splunk search: '`okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, - src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter`' + src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempts_filter` ' known_false_positives: There may be a faulty config preventing legitmate users from accessing apps they should have access to. tags: diff --git a/detections/process_execution_via_wmi.yml b/detections/process_execution_via_wmi.yml index 4c99e5d204..041418f51c 100644 --- a/detections/process_execution_via_wmi.yml +++ b/detections/process_execution_via_wmi.yml @@ -14,7 +14,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name = *WmiPrvSE.exe by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)`| `wmi_process_launch_filter`' + `security_content_ctime(lastTime)`| `process_execution_via_wmi_filter` ' known_false_positives: Although unlikely, administrators may use wmi to execute commands for legitimate purposes. tags: diff --git a/detections/processes_launching_netsh.yml b/detections/processes_launching_netsh.yml index be9a4d8d2d..5bd7aa4cc1 100644 --- a/detections/processes_launching_netsh.yml +++ b/detections/processes_launching_netsh.yml @@ -23,8 +23,8 @@ known_false_positives: Some VPN applications are known to launch netsh.exe. Outs commands. tags: analytics_story: - - Disabling Security Tools - Netsh Abuse + - Disabling Security Tools - DHS Report TA18-074A mitre_attack_id: - T1059 diff --git a/detections/prohibited_network_traffic_allowed.yml b/detections/prohibited_network_traffic_allowed.yml index 3b40caf45c..4f5c2efa47 100644 --- a/detections/prohibited_network_traffic_allowed.yml +++ b/detections/prohibited_network_traffic_allowed.yml @@ -23,9 +23,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Prohibited Traffic Allowed or Protocol Mismatch - Command and Control - Ransomware + - Prohibited Traffic Allowed or Protocol Mismatch mitre_attack_id: - T1043 - T1048 diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index b402bc90bb..4394c1a7d1 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -24,9 +24,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Monitor for Unauthorized Software - - 'Emotet Malware DHS Report TA18-201A ' - SamSam Ransomware + - 'Emotet Malware DHS Report TA18-201A ' + - Monitor for Unauthorized Software kill_chain_phases: - Installation - Command and Control diff --git a/detections/protocol_or_port_mismatch.yml b/detections/protocol_or_port_mismatch.yml index 0753a62007..315424a182 100644 --- a/detections/protocol_or_port_mismatch.yml +++ b/detections/protocol_or_port_mismatch.yml @@ -26,8 +26,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Prohibited Traffic Allowed or Protocol Mismatch - Command and Control + - Prohibited Traffic Allowed or Protocol Mismatch mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml index 0b1586e167..fafe061d48 100644 --- a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml +++ b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as known_false_positives: None at the moment tags: analytics_story: + - Suspicious Windows Registry Activities - Windows Persistence Techniques - Windows Defense Evasion Tactics - - Suspicious Windows Registry Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/registry_keys_for_creating_shim_databases.yml b/detections/registry_keys_for_creating_shim_databases.yml index 7c31448d8f..62cf67b895 100644 --- a/detections/registry_keys_for_creating_shim_databases.yml +++ b/detections/registry_keys_for_creating_shim_databases.yml @@ -21,8 +21,8 @@ known_false_positives: There are many legitimate applications that leverage shim for compatibility purposes for legacy applications tags: analytics_story: - - Windows Persistence Techniques - Suspicious Windows Registry Activities + - Windows Persistence Techniques mitre_attack_id: - T1138 kill_chain_phases: diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml index 331eed4523..e9119259f3 100644 --- a/detections/registry_keys_used_for_persistence.yml +++ b/detections/registry_keys_used_for_persistence.yml @@ -27,13 +27,13 @@ known_false_positives: There are many legitimate applications that must execute system startup and will use these registry keys to accomplish that task. tags: analytics_story: - - Windows Persistence Techniques - Suspicious Windows Registry Activities - - Suspicious MSHTA Activity - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Windows Persistence Techniques - 'Emotet Malware DHS Report TA18-201A ' - - DHS Report TA18-074A - Ransomware + - DHS Report TA18-074A + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Suspicious MSHTA Activity mitre_attack_id: - T1103 - T1131 diff --git a/detections/remote_desktop_network_traffic.yml b/detections/remote_desktop_network_traffic.yml index af04aa5317..60065ade2e 100644 --- a/detections/remote_desktop_network_traffic.yml +++ b/detections/remote_desktop_network_traffic.yml @@ -27,9 +27,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Remote Desktop may be used legitimately by users on the network. tags: analytics_story: - - Lateral Movement - - Hidden Cobra Malware - SamSam Ransomware + - Hidden Cobra Malware + - Lateral Movement mitre_attack_id: - T1076 kill_chain_phases: diff --git a/detections/remote_desktop_process_running_on_system.yml b/detections/remote_desktop_process_running_on_system.yml index 87c7ede512..180761501a 100644 --- a/detections/remote_desktop_process_running_on_system.yml +++ b/detections/remote_desktop_process_running_on_system.yml @@ -25,8 +25,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: Remote Desktop may be used legitimately by users on the network. tags: analytics_story: - - Lateral Movement - Hidden Cobra Malware + - Lateral Movement mitre_attack_id: - T1076 kill_chain_phases: diff --git a/detections/remote_process_instantiation_via_wmi.yml b/detections/remote_process_instantiation_via_wmi.yml index 818d03ffb5..46e3a48eaa 100644 --- a/detections/remote_process_instantiation_via_wmi.yml +++ b/detections/remote_process_instantiation_via_wmi.yml @@ -23,8 +23,8 @@ known_false_positives: The wmic.exe utility is a benign Windows application. It but it's relatively uncommon. tags: analytics_story: - - Suspicious WMI Use - Ransomware + - Suspicious WMI Use mitre_attack_id: - T1047 kill_chain_phases: diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml index 024ca7adcc..c900953e4f 100644 --- a/detections/remote_registry_key_modifications.yml +++ b/detections/remote_registry_key_modifications.yml @@ -20,9 +20,9 @@ known_false_positives: This technique may be legitimately used by administrators modify remote registries, so it's important to filter these events out. tags: analytics_story: + - Suspicious Windows Registry Activities - Windows Persistence Techniques - Windows Defense Evasion Tactics - - Suspicious Windows Registry Activities kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/sc_exe_manipulating_windows_services.yml b/detections/sc_exe_manipulating_windows_services.yml index 09d3459007..955142e712 100644 --- a/detections/sc_exe_manipulating_windows_services.yml +++ b/detections/sc_exe_manipulating_windows_services.yml @@ -24,10 +24,10 @@ known_false_positives: Using sc.exe to manipulate Windows services is uncommon. tags: analytics_story: - Windows Persistence Techniques - - Disabling Security Tools - Windows Service Abuse - - Orangeworm Attack Group + - Disabling Security Tools - DHS Report TA18-074A + - Orangeworm Attack Group mitre_attack_id: - T1050 - T1031 diff --git a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml index 6e54577073..43886afd77 100644 --- a/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml +++ b/detections/scheduled_task_name_used_by_dragonfly_threat_actors.yml @@ -17,7 +17,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | search (process=*delete* OR process=*create*) process=*reset* | `dragonfly_schtasks_filter`' + | search (process=*delete* OR process=*create*) process=*reset* | `scheduled_task_name_used_by_dragonfly_threat_actors_filter` ' known_false_positives: No known false positives tags: analytics_story: diff --git a/detections/script_execution_via_wmi.yml b/detections/script_execution_via_wmi.yml index 92dbb789fe..e76aec7810 100644 --- a/detections/script_execution_via_wmi.yml +++ b/detections/script_execution_via_wmi.yml @@ -14,7 +14,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = "scrcons.exe" by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| - `wmi_script_execution_filter`' + `script_execution_via_wmi_filter` ' known_false_positives: Although unlikely, administrators may use wmi to launch scripts for legitimate purposes. tags: diff --git a/detections/smb_traffic_spike.yml b/detections/smb_traffic_spike.yml index 74c9f2ea94..c43de1b40b 100644 --- a/detections/smb_traffic_spike.yml +++ b/detections/smb_traffic_spike.yml @@ -21,10 +21,10 @@ known_false_positives: A file server may experience high-demand loads that could this analytic to trigger. tags: analytics_story: + - Ransomware + - 'Emotet Malware DHS Report TA18-201A ' - Hidden Cobra Malware - DHS Report TA18-074A - - 'Emotet Malware DHS Report TA18-201A ' - - Ransomware mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/smb_traffic_spike___mltk.yml b/detections/smb_traffic_spike___mltk.yml index 16263f5d44..f848ea5e7e 100644 --- a/detections/smb_traffic_spike___mltk.yml +++ b/detections/smb_traffic_spike___mltk.yml @@ -35,17 +35,17 @@ search: '| tstats `security_content_summariesonly` count values(All_Traffic.dest _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 | rename "IsOutlier(count)" as isOutlier | search isOutlier > 0 | sort -count | - table _time src dest port count | `smb_traffic_spike_mltk_filter` ' + table _time src dest port count | `smb_traffic_spike___mltk_filter` ' known_false_positives: If you are seeing more results than desired, you may consider reducing the value of the threshold in the search. You should also periodically re-run the support search to re-build the ML model on the latest data. Please update the `smb_traffic_spike_mltk_filter` macro to filter out false positive results tags: analytics_story: + - Ransomware + - 'Emotet Malware DHS Report TA18-201A ' - Hidden Cobra Malware - DHS Report TA18-074A - - 'Emotet Malware DHS Report TA18-201A ' - - Ransomware mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/spike_in_file_writes.yml b/detections/spike_in_file_writes.yml index 80838301a0..b35941f8f0 100644 --- a/detections/spike_in_file_writes.yml +++ b/detections/spike_in_file_writes.yml @@ -18,7 +18,7 @@ search: '| tstats `security_content_summariesonly` count FROM datamodel=Endpoint >= relative_time(maxtime, "-1d@d"), count, null))) as "count" avg(eval(if(_time upperBound) AND num_data_samples >=20, 1, 0) | search isOutlier=1 | `file_write_spikes_filter`' + > upperBound) AND num_data_samples >=20, 1, 0) | search isOutlier=1 | `spike_in_file_writes_filter` ' known_false_positives: It is important to understand that if you happen to install any new applications on your hosts or are copying a large number of files, you can expect to see a large increase of file modifications. diff --git a/detections/suspicious_changes_to_file_associations.yml b/detections/suspicious_changes_to_file_associations.yml index 767b9f7337..33457e5ff5 100644 --- a/detections/suspicious_changes_to_file_associations.yml +++ b/detections/suspicious_changes_to_file_associations.yml @@ -20,7 +20,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table - process_id dest registry_path]| `change_file_association_filter`' + process_id dest registry_path]| `suspicious_changes_to_file_associations_filter` ' known_false_positives: There may be other processes in your environment that users may legitimately use to modify file associations. If this is the case and you are finding false positives, you can modify the search to add those processes as exceptions. diff --git a/detections/suspicious_email_attachment_extensions.yml b/detections/suspicious_email_attachment_extensions.yml index 0310826406..8614d04a60 100644 --- a/detections/suspicious_email_attachment_extensions.yml +++ b/detections/suspicious_email_attachment_extensions.yml @@ -22,7 +22,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | `suspicious_email_attachments` - | `suspicious_email_attachments_filter` ' + | `suspicious_email_attachment_extensions_filter` ' known_false_positives: None identified tags: analytics_story: diff --git a/detections/suspicious_lnk_file_launching_a_process.yml b/detections/suspicious_lnk_file_launching_a_process.yml index b500f5f9fe..bfcb42016c 100644 --- a/detections/suspicious_lnk_file_launching_a_process.yml +++ b/detections/suspicious_lnk_file_launching_a_process.yml @@ -22,7 +22,7 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime _time lnk_pid process_id dest process_name process_path process] | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table firstTime, lastTime, lnk_pid, process_id, user, dest, file_name, file_path, process_name, process, process_path, file_hash - | `lnk_executing_a_process_filter`' + | `suspicious_lnk_file_launching_a_process_filter` ' known_false_positives: This detection should yield little or no false positive results. It is uncommon for LNK files to execute process from temporary or user directories. tags: diff --git a/detections/suspicious_reg_exe_process.yml b/detections/suspicious_reg_exe_process.yml index 612efe3513..39ce10bfee 100644 --- a/detections/suspicious_reg_exe_process.yml +++ b/detections/suspicious_reg_exe_process.yml @@ -23,15 +23,15 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime where Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe by Processes.parent_process_id Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename parent_process_id as process_id |dedup - process_id| table process_id dest] | `suspicious_reg_process_filter`' + process_id| table process_id dest] | `suspicious_reg_exe_process_filter` ' known_false_positives: It's possible for system administrators to write scripts that exhibit this behavior. If this is the case, the search will need to be modified to filter them out. tags: analytics_story: - Disabling Security Tools - - DHS Report TA18-074A - Windows Defense Evasion Tactics + - DHS Report TA18-074A mitre_attack_id: - T1112 - T1089 diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index 5c789b8407..4e7d43fa11 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -20,9 +20,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Unusual Processes - - Ransomware - Suspicious Command-Line Executions + - Ransomware + - Unusual Processes mitre_attack_id: - T1036 kill_chain_phases: diff --git a/detections/tor_traffic.yml b/detections/tor_traffic.yml index 2ee6aba830..83feca13ac 100644 --- a/detections/tor_traffic.yml +++ b/detections/tor_traffic.yml @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None at this time tags: analytics_story: - - Prohibited Traffic Allowed or Protocol Mismatch - Command and Control - Ransomware + - Prohibited Traffic Allowed or Protocol Mismatch mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/uncommon_processes_on_endpoint.yml b/detections/uncommon_processes_on_endpoint.yml index 226ddf7b25..0ced12b497 100644 --- a/detections/uncommon_processes_on_endpoint.yml +++ b/detections/uncommon_processes_on_endpoint.yml @@ -18,12 +18,12 @@ author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_filter`' + | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_on_endpoint_filter` ' known_false_positives: None identified tags: analytics_story: - - Unusual Processes - Windows Privilege Escalation + - Unusual Processes mitre_attack_id: - T1015 kill_chain_phases: diff --git a/detections/unsigned_image_loaded_by_LSASS.yml b/detections/unsigned_image_loaded_by_LSASS.yml index bfb01a92a5..e9646fe171 100644 --- a/detections/unsigned_image_loaded_by_LSASS.yml +++ b/detections/unsigned_image_loaded_by_LSASS.yml @@ -16,7 +16,7 @@ author: Patrick Bareiss, Splunk search: '`sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `unsigned_image_loaded_by_LSASS_filter`' + | `unsigned_image_loaded_by_lsass_filter` ' known_false_positives: Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. tags: diff --git a/detections/unusually_long_command_line.yml b/detections/unusually_long_command_line.yml index 69c4ccc933..f3f2c703fa 100644 --- a/detections/unusually_long_command_line.yml +++ b/detections/unusually_long_command_line.yml @@ -17,15 +17,15 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| - `unusually_long_commandlines_filter`| eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + `unusually_long_command_line_filter` eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost)' known_false_positives: Some legitimate applications start with long command lines. tags: analytics_story: - - Unusual Processes - Ransomware - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Suspicious Command-Line Executions + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Unusual Processes kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml index 4cfd8e5467..9f50cca4cf 100644 --- a/detections/unusually_long_command_line___mltk.yml +++ b/detections/unusually_long_command_line___mltk.yml @@ -35,10 +35,10 @@ known_false_positives: Some legitimate applications use long command lines for i build the associated model. tags: analytics_story: - - Unusual Processes - Ransomware - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Suspicious Command-Line Executions + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Unusual Processes kill_chain_phases: - Actions on Objectives cis20: diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index a195ea49ce..492b5aa4ab 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T09:08:45 UTC +# On Date: 2020-05-14T08:00:44 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,8 +16,8 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] -support_searches = [] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] data_models = [] providing_technologies = none description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. @@ -34,8 +34,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] -support_searches = [] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +support_searches = ["ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -53,8 +53,8 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] -support_searches = [] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +support_searches = ["ESCU - Baseline of Network ACL Activity by ARN", "ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. @@ -69,8 +69,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] -support_searches = [] +investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] data_models = [] providing_technologies = none description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. @@ -87,7 +87,7 @@ reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.p detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -support_searches = [] +support_searches = ["ESCU - Baseline of API Calls per User ARN", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Create a list of approved AWS service accounts", "ESCU - Previously seen API call per user roles in CloudTrail"] data_models = [] providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For User"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,8 +150,8 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] -support_searches = [] +investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +support_searches = ["ESCU - Count of assets by category"] data_models = ["Network_Sessions"] providing_technologies = none description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. @@ -166,8 +166,8 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] -support_searches = [] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. @@ -184,8 +184,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] -support_searches = [] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +support_searches = ["ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Regions"] data_models = ["Cloud_Infrastructure"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,8 +239,8 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] +investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,8 +307,8 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -344,7 +344,7 @@ reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insight detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} investigative_searches = ["ESCU - Get DNS Server History for a host"] -support_searches = [] +support_searches = ["ESCU - Discover DNS records"] data_models = ["Network_Resolution"] providing_technologies = none description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,8 +383,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,8 +415,8 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. @@ -433,8 +433,8 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -511,10 +511,10 @@ creation_date = 2020-02-04 modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 -reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,8 +559,8 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host"] -support_searches = [] +investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +support_searches = ["ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] data_models = [] providing_technologies = none description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. @@ -575,8 +575,8 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint"] providing_technologies = none description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,8 +610,8 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. @@ -627,8 +627,8 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. @@ -670,8 +670,8 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,8 +729,8 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,8 +779,8 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. @@ -800,8 +800,8 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] data_models = ["Vulnerabilities"] providing_technologies = none description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -860,8 +860,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] -support_searches = [] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +support_searches = ["ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. @@ -877,7 +877,7 @@ reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integr detection_searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN"] -support_searches = [] +support_searches = ["ESCU - Previously seen users in CloudTrail", "ESCU - Update previously seen users in CloudTrail"] data_models = [] providing_technologies = none description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. @@ -892,8 +892,8 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name"] -support_searches = [] +investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name"] +support_searches = ["ESCU - Previously seen S3 bucket access by remote IP", "ESCU - Baseline of S3 Bucket deletion activity by ARN"] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. @@ -910,8 +910,8 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] -support_searches = [] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). @@ -929,8 +929,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. @@ -945,8 +945,8 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution"] providing_technologies = none description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. @@ -961,8 +961,8 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "UEBA"] providing_technologies = none description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. @@ -981,8 +981,8 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,8 +1053,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] -support_searches = [] +investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] data_models = [] providing_technologies = none description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. @@ -1070,8 +1070,8 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,8 +1210,8 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] -support_searches = [] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +support_searches = ["ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. diff --git a/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml b/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml index dba9569081..eaacf46c7b 100644 --- a/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml +++ b/package/default/data/ui/panels/workbench_panel_investigate_failed_logins_for_multiple_destinations.xml @@ -1,7 +1,7 @@
- | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 0 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` + | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` diff --git a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml index 3f5dff58ab..02d2dff20d 100644 --- a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml +++ b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml @@ -1,7 +1,7 @@
- `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 + `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 3dd63416e1..385a5bdadd 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -3,25 +3,25 @@ label = AWS Cross Account Activity description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_source_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_aws_investigate_user_activities_by_source_user"] [panel_group://workbench_panel_group_aws_cryptomining] label = AWS Cryptomining description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_aws_network_acl_activity] label = AWS Network ACL Activity description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. disabled = 0 -panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] [panel_group://workbench_panel_group_aws_suspicious_provisioning_activities] label = AWS Suspicious Provisioning Activities description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_country"] +panels = ["panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_country"] [panel_group://workbench_panel_group_aws_user_monitoring] label = AWS User Monitoring @@ -33,49 +33,49 @@ panels = ["panel://workbench_panel_investigate_aws_user_activities_by_user_field label = Account Monitoring and Controls description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. disabled = 0 -panels = ["panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_logon_rights_modifications_for_user"] [panel_group://workbench_panel_group_apache_struts_vulnerability] label = Apache Struts Vulnerability description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_asset_tracking] label = Asset Tracking description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_brand_monitoring] label = Brand Monitoring description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_email_info"] [panel_group://workbench_panel_group_cloud_cryptomining] label = Cloud Cryptomining description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_coldroot_macos_rat] label = ColdRoot MacOS RAT description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip"] [panel_group://workbench_panel_group_collection_and_staging] label = Collection and Staging description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_command_and_control] label = Command and Control description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. disabled = 0 -panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_common_phishing_frameworks] label = Common Phishing Frameworks @@ -93,19 +93,19 @@ panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activit label = Credential Dumping description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. disabled = 0 -panels = ["panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_ticket_attempts", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_previous_unseen_user"] +panels = ["panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] [panel_group://workbench_panel_group_dhs_report_ta18_074a] label = DHS Report TA18-074A description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_file_activity"] [panel_group://workbench_panel_group_dns_amplification_attacks] label = DNS Amplification Attacks description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_dns_hijacking] label = DNS Hijacking @@ -117,91 +117,91 @@ panels = ["panel://workbench_panel_get_dns_server_history_for_a_host"] label = Data Protection description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] [panel_group://workbench_panel_group_disabling_security_tools] label = Disabling Security Tools description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_dynamic_dns] label = Dynamic DNS description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_investigate_web_activity_from_src_ip"] [panel_group://workbench_panel_group_emotet_malware__dhs_report_ta18_201a_] label = Emotet Malware DHS Report TA18-201A description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_hidden_cobra_malware] label = Hidden Cobra Malware description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_host_redirection] label = Host Redirection description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host"] [panel_group://workbench_panel_group_jboss_vulnerability] label = JBoss Vulnerability description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. disabled = 0 -panels = ["panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] +panels = ["panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] [panel_group://workbench_panel_group_kubernetes_scanning_activity] label = Kubernetes Scanning Activity description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_lateral_movement] label = Lateral Movement description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_malicious_powershell] label = Malicious PowerShell description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_monitor_backup_solution] label = Monitor Backup Solution description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_all_backup_logs_for_host"] +panels = ["panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_monitor_for_unauthorized_software] label = Monitor for Unauthorized Software description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_monitor_for_updates] label = Monitor for Updates description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_netsh_abuse] label = Netsh Abuse description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_orangeworm_attack_group] label = Orangeworm Attack Group description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_phishing_payloads] label = Phishing Payloads @@ -213,61 +213,61 @@ panels = ["panel://workbench_panel_get_parent_process_info"] label = Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_prohibited_traffic_allowed_or_protocol_mismatch] label = Prohibited Traffic Allowed or Protocol Mismatch description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_ransomware] label = Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_router_and_infrastructure_security] label = Router and Infrastructure Security description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_sql_injection] label = SQL Injection description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_samsam_ransomware] label = SamSam Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] label = Spectre And Meltdown Vulnerabilities description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability] label = Splunk Enterprise Vulnerability description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability_cve_2018_11409] label = Splunk Enterprise Vulnerability CVE-2018-11409 description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. disabled = 0 -panels = ["panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_web_activity_from_src_ip"] [panel_group://workbench_panel_group_suspicious_aws_ec2_activities] label = Suspicious AWS EC2 Activities description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_suspicious_aws_login_activities] label = Suspicious AWS Login Activities @@ -279,115 +279,115 @@ panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] label = Suspicious AWS S3 Activities description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. disabled = 0 -panels = ["panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_aws_activities_via_region_name"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name"] [panel_group://workbench_panel_group_suspicious_aws_traffic] label = Suspicious AWS Traffic description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). disabled = 0 -panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] [panel_group://workbench_panel_group_suspicious_command_line_executions] label = Suspicious Command-Line Executions description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_dns_traffic] label = Suspicious DNS Traffic description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_emails] label = Suspicious Emails description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_email_info"] [panel_group://workbench_panel_group_suspicious_mshta_activity] label = Suspicious MSHTA Activity description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_okta_activity] label = Suspicious Okta Activity description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. disabled = 0 -panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_user_activities_in_okta", "panel://workbench_panel_investigate_okta_activity_by_ip_address"] +panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_user_activities_in_okta"] [panel_group://workbench_panel_group_suspicious_wmi_use] label = Suspicious WMI Use description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_suspicious_windows_registry_activities] label = Suspicious Windows Registry Activities description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_unusual_aws_ec2_modifications] label = Unusual AWS EC2 Modifications description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] +panels = ["panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] [panel_group://workbench_panel_group_unusual_processes] label = Unusual Processes description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_use_of_cleartext_protocols] label = Use of Cleartext Protocols description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_web_fraud_detection] label = Web Fraud Detection description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. disabled = 0 -panels = ["panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_emails_from_specific_sender"] [panel_group://workbench_panel_group_windows_defense_evasion_tactics] label = Windows Defense Evasion Tactics description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_file_extension_and_association_abuse] label = Windows File Extension and Association Abuse description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_log_manipulation] label = Windows Log Manipulation description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_persistence_techniques] label = Windows Persistence Techniques description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_privilege_escalation] label = Windows Privilege Escalation description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] [panel_group://workbench_panel_group_windows_service_abuse] label = Windows Service Abuse description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] diff --git a/package/default/macros.conf b/package/default/macros.conf index f6237d2cb2..ec0c5df81e 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T09:08:45 UTC +# On Date: 2020-05-14T08:00:44 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 9a83cae4be..84401dfc9c 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T09:08:45 UTC +# On Date: 2020-05-14T08:00:44 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -345,7 +345,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS EC2 Activities", "Cloud Cryptomining"] +action.escu.analytic_story = ["Cloud Cryptomining", "Suspicious AWS EC2 Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -368,7 +368,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `cloudtrail` eventName=RunInstances errorCode=success `ec2_excessive_runinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as isOutlier | where isOutlier=1 +search = `cloudtrail` eventName=RunInstances errorCode=success `abnormally_high_aws_instances_launched_by_user___mltk_filter` | bucket span=10m _time | stats count as instances_launched by _time src_user | apply ec2_excessive_runinstances_v1 | rename "IsOutlier(instances_launched)" as isOutlier | where isOutlier=1 [ESCU - Abnormally High AWS Instances Terminated by User - Rule] action.escu = 0 @@ -447,7 +447,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `cloudtrail` eventName=TerminateInstances errorCode=success `ec2_excessive_terminateinstances_mltk_input_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" as isOutlier | where isOutlier=1 +search = `cloudtrail` eventName=TerminateInstances errorCode=success `abnormally_high_aws_instances_terminated_by_user___mltk_filter` | bucket span=10m _time | stats count as instances_terminated by _time src_user | apply ec2_excessive_terminateinstances_v1 | rename "IsOutlier(instances_terminated)" as isOutlier | where isOutlier=1 [ESCU - Access LSASS Memory for Dump Creation - Rule] action.escu = 0 @@ -526,7 +526,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_pods_aws_scan_fingerprint_filter` +search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" verb=list objectRef.resource=pods requestURI="/api/v1/pods" | rename source as cluster_name sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(responseStatus.code) values(userAgent) values(verb) values(requestURI) by src_ip cluster_name user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `amazon_eks_kubernetes_pod_scan_detection_filter` [ESCU - Amazon EKS Kubernetes cluster scan detection - Rule] action.escu = 0 @@ -565,7 +565,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`kubernetes_aws_scan_fingerprint_filter` +search = `aws_cloudwatchlogs_eks` "user.username"="system:anonymous" userAgent!="AWS Security Scanner" | rename sourceIPs{} as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(responseStatus.reason) values(source) as cluster_name values(responseStatus.code) values(userAgent) as http_user_agent values(verb) values(requestURI) by src_ip user.username user.groups{} | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` |`amazon_eks_kubernetes_cluster_scan_detection_filter` [ESCU - Attempt To Add Certificate To Untrusted Store - Rule] action.escu = 0 @@ -725,7 +725,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=reg.exe OR Processes.process_name=cmd.exe) Processes.process=*save* (Processes.process=*HKEY_LOCAL_MACHINE\\Security* OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_exe_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=reg.exe OR Processes.process_name=cmd.exe) Processes.process=*save* (Processes.process=*HKEY_LOCAL_MACHINE\\Security* OR Processes.process=*HKEY_LOCAL_MACHINE\\SAM* OR Processes.process=*HKEY_LOCAL_MACHINE\\System* OR Processes.process=*HKLM\\Security* OR Processes.process=*HKLM\\System* OR Processes.process=*HKLM\\SAM*) by Processes.user Processes.process_name Processes.process Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempted_credential_dump_from_registry_via_reg_exe_filter` [ESCU - Batch File Write to System32 - Rule] action.escu = 0 @@ -805,7 +805,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process_name) as process_name values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `children_of_spoolsv_filter` +search = | tstats `security_content_summariesonly` count values(Processes.process_name) as process_name values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name=spoolsv.exe AND Processes.process_name!=regsvr32.exe by Processes.dest Processes.parent_process Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `child_processes_of_spoolsv_exe_filter` [ESCU - Clients Connecting to Multiple DNS Servers - Rule] action.escu = 0 @@ -824,7 +824,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Clients Connecting to Multiple DNS Servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious DNS Traffic", "Host Redirection", "Command and Control", "DNS Hijacking"] +action.escu.analytic_story = ["Command and Control", "Host Redirection", "Suspicious DNS Traffic", "DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -847,7 +847,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count > 5 | `clients_connecting_to_multiple_dns_servers_output_filter` +search = | tstats `security_content_summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count > 5 | `clients_connecting_to_multiple_dns_servers_filter` [ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule] action.escu = 0 @@ -927,7 +927,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `previously_seen_cloud_compute_image_input_filter` by Compute.image_id, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_images | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by image_id, src_user | multireport [| table image_id, firstTime, lastTime | outputlookup previously_seen_cloud_compute_images | where fact=fiction][| eval new_image=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_image_search_window_begin_offset`), 1, 0) | where new_image=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table image_id, dest, src_user, firstTime, lastTime +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.action=run `cloud_compute_instance_created_with_previously_unseen_image_filter` by Compute.image_id, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_images | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by image_id, src_user | multireport [| table image_id, firstTime, lastTime | outputlookup previously_seen_cloud_compute_images | where fact=fiction][| eval new_image=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_image_search_window_begin_offset`), 1, 0) | where new_image=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table image_id, dest, src_user, firstTime, lastTime [ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule] action.escu = 0 @@ -967,7 +967,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `previously_seen_cloud_compute_instance_types_input_filter` by Compute.instance_type, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_instance_types | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by instance_type, src_user | multireport [| table instance_type, firstTime, lastTime | outputlookup previously_seen_cloud_compute_instance_types | where fact=fiction][| eval new_type=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), 1, 0) | where new_type=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table instance_type, dest, src_user, firstTime, lastTime +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `cloud_compute_instance_created_with_previously_unseen_instance_type_filter` by Compute.instance_type, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_compute_instance_types | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by instance_type, src_user | multireport [| table instance_type, firstTime, lastTime | outputlookup previously_seen_cloud_compute_instance_types | where fact=fiction][| eval new_type=if(firstTime >= relative_time(now(), `previously_seen_cloud_compute_instance_types_search_window_begin_offset`), 1, 0) | where new_type=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table instance_type, dest, src_user, firstTime, lastTime [ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule] action.escu = 0 @@ -1007,7 +1007,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `previously_seen_cloud_regions_input_filter` by Compute.region, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by region, src_user | multireport [| table region, firstTime, lastTime | outputlookup previously_seen_cloud_regions | where fact=fiction][| eval new_region=if(firstTime >= relative_time(now(), `previously_seen_cloud_regions_search_window_begin_offset`), 1, 0) | where new_region=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table region, dest, src_user, firstTime, lastTime +search = | tstats earliest(_time) as firstTime, latest(_time) as lastTime values(Compute.dest) as dest from datamodel=Cloud_Infrastructure.Compute where Compute.event_name=RunInstances `cloud_compute_instance_started_in_previously_unused_region_filter` by Compute.region, Compute.src_user | `drop_dm_object_name("Compute")` | inputlookup append=t previously_seen_cloud_regions | stats min(firstTime) as firstTime max(lastTime) as lastTime, values(dest) as dest by region, src_user | multireport [| table region, firstTime, lastTime | outputlookup previously_seen_cloud_regions | where fact=fiction][| eval new_region=if(firstTime >= relative_time(now(), `previously_seen_cloud_regions_search_window_begin_offset`), 1, 0) | where new_region=1 | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`] | table region, dest, src_user, firstTime, lastTime [ESCU - Common Ransomware Extensions - Rule] action.escu = 0 @@ -1171,7 +1171,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* OR process=*user*) |`create_local_admin_via_net_filter` +search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* OR process=*user*) |`create_local_admin_accounts_using_net_exe_filter` [ESCU - Create or delete windows shares using net exe - Rule] action.escu = 0 @@ -1211,7 +1211,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) | `create_or_delete_windows_shares_filter` +search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) | `create_or_delete_windows_shares_using_net_exe_filter` [ESCU - Creation of Shadow Copy - Rule] action.escu = 0 @@ -1331,7 +1331,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe (Processes.process=*\\system32\\config\\sam* OR Processes.process=*\\system32\\config\\security* OR Processes.process=*\\system32\\config\\system* OR Processes.process=*\\windows\\ntds\\ntds.dit*) by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_copy_from_shadowcopy_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe (Processes.process=*\\system32\\config\\sam* OR Processes.process=*\\system32\\config\\security* OR Processes.process=*\\system32\\config\\system* OR Processes.process=*\\windows\\ntds\\ntds.dit*) by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `credential_dumping_via_copy_command_from_shadow_copy_filter` [ESCU - Credential Dumping via Symlink to Shadow Copy - Rule] action.escu = 0 @@ -1371,7 +1371,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe Processes.process=*mklink* Processes.process=*HarddiskVolumeShadowCopy* by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `cred_dump_via_symlink_shadowcopy_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=cmd.exe Processes.process=*mklink* Processes.process=*HarddiskVolumeShadowCopy* by Processes.dest Processes.user Processes.process_name Processes.process Processes.parent_process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `credential_dumping_via_symlink_to_shadow_copy_filter` [ESCU - DNS Query Length Outliers - MLTK - Rule] action.escu = 0 @@ -1394,7 +1394,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length Outliers - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious DNS Traffic", "Hidden Cobra Malware", "Command and Control"] +action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1417,7 +1417,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename "IsOutlier(query_length)" as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time query record_type count src dest query_length | `dns_query_length_mltk_filter` +search = | tstats `security_content_summariesonly` count min(_time) as start_time max(_time) as end_time values(DNS.src) as src values(DNS.dest) as dest from datamodel=Network_Resolution by DNS.query DNS.record_type | search DNS.record_type=* | `drop_dm_object_name(DNS)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | eval query_length = len(query) | apply dns_query_pdfmodel threshold=0.01 | rename "IsOutlier(query_length)" as isOutlier | search isOutlier > 0 | sort -query_length | table start_time end_time query record_type count src dest query_length | `dns_query_length_outliers___mltk_filter` [ESCU - DNS Query Length With High Standard Deviation - Rule] action.escu = 0 @@ -1434,7 +1434,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length With High Standard Deviation - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious DNS Traffic", "Hidden Cobra Malware", "Command and Control"] +action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1473,7 +1473,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious DNS Traffic", "Host Redirection", "Command and Control", "DNS Hijacking"] +action.escu.analytic_story = ["Command and Control", "Host Redirection", "Suspicious DNS Traffic", "DNS Hijacking"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1496,7 +1496,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src DNS.dest | `drop_dm_object_name("DNS")` | `unauthorized_dns_servers_filter` +search = | tstats `security_content_summariesonly` count from datamodel=Network_Resolution where DNS.dest_category != dns_server AND DNS.src_category != dns_server by DNS.src DNS.dest | `drop_dm_object_name("DNS")` | `dns_query_requests_resolved_by_unauthorized_dns_servers_filter` [ESCU - DNS record changed - Rule] action.escu = 0 @@ -1872,7 +1872,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_LSASS_access_filter` +search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_LSAS`detect_credential_dumping_through_lsass_access_filter` [ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule] action.escu = 0 @@ -2056,7 +2056,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Long DNS TXT Record Response - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] +action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2324,7 +2324,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name=outlook.exe OR Processes.process_name=explorer.exe by _time span=5m Processes.parent_process_id Processes.process_id Processes.dest Processes.process_name Processes.parent_process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| rename parent_process_id as outlook_id| join malicious_id type=inner[| tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where (Filesystem.file_path=*zip* OR Filesystem.file_name=*.lnk ) AND (Filesystem.file_path=C:\\Users* OR Filesystem.file_path=*Local\\Temp*) by _time span=5m Filesystem.process_id Filesystem.file_hash Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| fields malicious_id outlook_id dest file_path file_name file_hash count file_id] | table firstTime lastTime user malicious_id outlook_id process_name parent_process_name file_name file_path | where file_name != "" | `outlook_writing_zip_filter` +search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name=outlook.exe OR Processes.process_name=explorer.exe by _time span=5m Processes.parent_process_id Processes.process_id Processes.dest Processes.process_name Processes.parent_process_name Processes.user | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| rename parent_process_id as outlook_id| join malicious_id type=inner[| tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path values(Filesystem.file_name) as file_name FROM datamodel=Endpoint.Filesystem where (Filesystem.file_path=*zip* OR Filesystem.file_name=*.lnk ) AND (Filesystem.file_path=C:\\Users* OR Filesystem.file_path=*Local\\Temp*) by _time span=5m Filesystem.process_id Filesystem.file_hash Filesystem.dest | `drop_dm_object_name(Filesystem)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename process_id as malicious_id| fields malicious_id outlook_id dest file_path file_name file_hash count file_id] | table firstTime lastTime user malicious_id outlook_id process_name parent_process_name file_name file_path | where file_name != "" | `detect_oulook_exe_writing_a__zip_file_filter` [ESCU - Detect Outbound SMB Traffic - Rule] action.escu = 0 @@ -2363,7 +2363,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `outbound_smb_connections_filter` +search = | tstats `security_content_summariesonly` count earliest(_time) as earliest latest(_time) as latest values(All_Traffic.action) from datamodel=Network_Traffic where All_Traffic.action !=blocked All_Traffic.dest_category !=internal (All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb) by All_Traffic.src_ip All_Traffic.dest_ip | `drop_dm_object_name("All_Traffic")` | search ( dest_ip!=10.0.0.0/8 AND dest_ip!=172.16.0.0/12 AND dest_ip!=192.168.0.0/16) | `security_content_ctime(earliest)`| `security_content_ctime(latest)` | `detect_outbound_smb_traffic_filter` [ESCU - Detect Path Interception By Creation Of program exe - Rule] action.escu = 0 @@ -2420,7 +2420,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Prohibited Applications Spawning cmd exe - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious MSHTA Activity", "Suspicious Command-Line Executions"] +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Suspicious MSHTA Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2460,7 +2460,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect PsExec With accepteula Flag - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["DHS Report TA18-074A", "SamSam Ransomware"] +action.escu.analytic_story = ["SamSam Ransomware", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2500,7 +2500,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Rare Executables - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual Processes", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2523,7 +2523,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.dest) as dest values(Processes.user) as user min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.process_name | rename Processes.process_name as process | rex field=user "(?.*)\\\\(?.*)" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name as process| `filter_rare_process_whitelist`| table process ] | `rare_executables_on_endpoint_filter` +search = | tstats `security_content_summariesonly` count values(Processes.dest) as dest values(Processes.user) as user min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.process_name | rename Processes.process_name as process | rex field=user "(?.*)\\\\(?.*)" | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| search [| tstats count from datamodel=Endpoint.Processes by Processes.process_name | rare Processes.process_name limit=30 | rename Processes.process_name as process| `filter_rare_process_whitelist`| table process ] | `detect_rare_executables_filter` [ESCU - Detect S3 access from a new IP - Rule] action.escu = 0 @@ -2745,7 +2745,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious AWS Traffic", "AWS Network ACL Activity", "Command and Control"] +action.escu.analytic_story = ["Command and Control", "AWS Network ACL Activity", "Suspicious AWS Traffic"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2863,7 +2863,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Suspicious Command-Line Executions"] +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2903,7 +2903,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] +action.escu.analytic_story = ["SamSam Ransomware", "JBoss Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2949,7 +2949,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect hosts connecting to dynamic domain providers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Data Protection", "Command and Control", "Suspicious DNS Traffic", "Prohibited Traffic Allowed or Protocol Mismatch", "Dynamic DNS", "DNS Hijacking"] +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious DNS Traffic", "DNS Hijacking", "Dynamic DNS", "Command and Control", "Data Protection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2988,7 +2988,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect malicious requests to exploit JBoss servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] +action.escu.analytic_story = ["SamSam Ransomware", "JBoss Vulnerability"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3230,7 +3230,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of DNS Tunnels - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control", "Data Protection"] +action.escu.analytic_story = ["Command and Control", "Data Protection", "Suspicious DNS Traffic"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3310,7 +3310,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Disabling Remote User Account Control - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3652,7 +3652,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name=*.pst OR Filesystem.file_name=*.ost) Filesystem.file_path != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name("Filesystem")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `email_files_not_in_outlook_directory_filter` +search = | tstats `security_content_summariesonly` count values(Filesystem.file_path) as file_path min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Filesystem where (Filesystem.file_name=*.pst OR Filesystem.file_name=*.ost) Filesystem.file_path != "C:\\Users\\*\\My Documents\\Outlook Files\\*" Filesystem.file_path!="C:\\Users\\*\\AppData\\Local\\Microsoft\\Outlook*" by Filesystem.action Filesystem.process_id Filesystem.file_name Filesystem.dest | `drop_dm_object_name("Filesystem")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`| `email_files_written_outside_of_the_outlook_directory_filter` [ESCU - Email servers sending high volume traffic to hosts - Rule] action.escu = 0 @@ -3708,7 +3708,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Excessive DNS Failures - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] +action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3947,7 +3947,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - First time seen command line argument - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Orangeworm Attack Group", "Hidden Cobra Malware", "Suspicious Command-Line Executions", "DHS Report TA18-074A"] +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Orangeworm Attack Group"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3969,7 +3969,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process Processes.process_name Processes.parent_process_name Processes.dest| `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process | `drop_dm_object_name(Processes)` | inputlookup append=t previously_seen_cmd_line_arguments | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCmdLineArgument=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table process] | `first_time_seen_cmd_line_filter` +search = | tstats `security_content_summariesonly` min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process Processes.process_name Processes.parent_process_name Processes.dest| `drop_dm_object_name(Processes)`| `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` earliest(_time) as firstTime latest(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name = cmd.exe Processes.process = "* /c *" by Processes.process | `drop_dm_object_name(Processes)` | inputlookup append=t previously_seen_cmd_line_arguments | stats min(firstTime) as firstTime, max(lastTime) as lastTime by process | outputlookup previously_seen_cmd_line_arguments | eval newCmdLineArgument=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCmdLineArgument=1 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table process] | `first_time_seen_command_line_argument_filter` [ESCU - GCP GCR container uploaded - Rule] action.escu = 0 @@ -4009,7 +4009,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Storage where Storage.event_name=storage.objects.create by Storage.src_user Storage.account Storage.action Storage.bucket_name Storage.event_name Storage.http_user_agent Storage.msg Storage.object_path | `drop_dm_object_name("Storage")` | `container_implant_gcp_detection_filter` +search = |tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Storage where Storage.event_name=storage.objects.create by Storage.src_user Storage.account Storage.action Storage.bucket_name Storage.event_name Storage.http_user_agent Storage.msg Storage.object_path | `drop_dm_object_name("Storage")` | `gcp_gcr_container_uploaded_filter` [ESCU - GCP Kubernetes cluster scan detection - Rule] action.escu = 0 @@ -4048,7 +4048,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_name values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `kubernetes_gcp_scan_fingerprint_filter` +search = `google_gcp_pubsub_message` data.protoPayload.requestMetadata.callerIp!=127.0.0.1 data.protoPayload.requestMetadata.callerIp!=::1 "data.labels.authorization.k8s.io/decision"=forbid "data.protoPayload.status.message"=PERMISSION_DENIED data.protoPayload.authenticationInfo.principalEmail="system:anonymous" | rename data.protoPayload.requestMetadata.callerIp as src_ip | stats count min(_time) as firstTime max(_time) as lastTime values(data.protoPayload.methodName) as method_name values(data.protoPayload.resourceName) as resource_name values(data.protoPayload.requestMetadata.callerSuppliedUserAgent) as http_user_agent by src_ip data.resource.labels.cluster_name | rename data.resource.labels.cluster_name as cluster_name| `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `gcp_kubernetes_cluster_scan_detection_filter` [ESCU - Hiding Files And Directories With Attrib exe - Rule] action.escu = 0 @@ -4088,7 +4088,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `attrib_to_hide_files_filter` +search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `hiding_files_and_directories_with_attrib_exe_filter` [ESCU - Hosts receiving high volume of network traffic from email server - Rule] action.escu = 0 @@ -4262,7 +4262,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"] +action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Malicious PowerShell"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4445,7 +4445,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process, "`"))-1) + (mvcount(split(process, "^"))-1) | `malicious_powershell_process_obfuscation_techniques_output_filter` | search num_obfuscation > 0 +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=powershell.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval num_obfuscation = (mvcount(split(process, "`"))-1) + (mvcount(split(process, "^"))-1) | `malicious_powershell_process_with_obfuscation_techniques_filter` | search num_obfuscation > 0 [ESCU - Monitor DNS For Brand Abuse - Rule] action.escu = 0 @@ -4501,7 +4501,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Email For Brand Abuse - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] +action.escu.analytic_story = ["Suspicious Emails", "Brand Monitoring"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4540,7 +4540,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Registry Keys for Print Monitors - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Suspicious Windows Registry Activities"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4642,7 +4642,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `okta` outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search distinct_users > 5| `okta_multiple_users_with_auth_failures_from_ip_filter` +search = `okta` outcome.reason=INVALID_CREDENTIALS | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | stats min(_time) as firstTime max(_time) as lastTime dc(user) as distinct_users values(user) as users by src_ip, displayMessage, outcome.reason, country, state, city | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search distinct_users > 5| `multiple_okta_users_with_invalid_credentails_from_the_same_ip_filter` [ESCU - New container uploaded to AWS ECR - Rule] action.escu = 0 @@ -4682,7 +4682,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.http_user_agent="AWS Internal" AND Compute.event_name="PutImage" by Compute.image_id Compute.src_user Compute.src Compute.region Compute.msg Compute.user_type | `drop_dm_object_name("Compute")` | `container_implant_aws_detection_filter` +search = | tstats count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Cloud_Infrastructure.Compute where Compute.user_type!="AssumeRole" AND Compute.http_user_agent="AWS Internal" AND Compute.event_name="PutImage" by Compute.image_id Compute.src_user Compute.src Compute.region Compute.msg Compute.user_type | `drop_dm_object_name("Compute")` | `new_container_uploaded_to_aws_ecr_filter` [ESCU - No Windows Updates in a time frame - Rule] action.escu = 0 @@ -4761,7 +4761,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip |`okta_user_lockouts_filter` +search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip |`okta_account_lockout_events_filter` [ESCU - Okta Failed SSO Attempts - Rule] action.escu = 0 @@ -4800,7 +4800,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempt_filter` +search = `okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempts_filter` [ESCU - Okta User Logins From Multiple Cities - Rule] action.escu = 0 @@ -4998,7 +4998,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name = *WmiPrvSE.exe by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `wmi_process_launch_filter` +search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name = *WmiPrvSE.exe by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `process_execution_via_wmi_filter` [ESCU - Processes Tapping Keyboard Events - Rule] action.escu = 0 @@ -5094,7 +5094,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Processes launching netsh - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Disabling Security Tools", "Netsh Abuse", "DHS Report TA18-074A"] +action.escu.analytic_story = ["Netsh Abuse", "Disabling Security Tools", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5134,7 +5134,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Network Traffic Allowed - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] +action.escu.analytic_story = ["Command and Control", "Ransomware", "Prohibited Traffic Allowed or Protocol Mismatch"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5173,7 +5173,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Software On Endpoint - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A ", "SamSam Ransomware"] +action.escu.analytic_story = ["SamSam Ransomware", "Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5213,7 +5213,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Protocol or Port Mismatch - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"] +action.escu.analytic_story = ["Command and Control", "Prohibited Traffic Allowed or Protocol Mismatch"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5332,7 +5332,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe used to hide files directories via registry keys - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Windows Defense Evasion Tactics"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5372,7 +5372,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Persistence - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Suspicious Windows Registry Activities", "Suspicious MSHTA Activity", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Emotet Malware DHS Report TA18-201A ", "DHS Report TA18-074A", "Ransomware"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious MSHTA Activity"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5452,7 +5452,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys for Creating SHIM Databases - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Suspicious Windows Registry Activities"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5531,7 +5531,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Network Traffic - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Lateral Movement", "Hidden Cobra Malware", "SamSam Ransomware"] +action.escu.analytic_story = ["SamSam Ransomware", "Hidden Cobra Malware", "Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5571,7 +5571,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Desktop Process Running On System - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Lateral Movement", "Hidden Cobra Malware"] +action.escu.analytic_story = ["Hidden Cobra Malware", "Lateral Movement"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5611,7 +5611,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Process Instantiation via WMI - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious WMI Use", "Ransomware"] +action.escu.analytic_story = ["Ransomware", "Suspicious WMI Use"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5651,7 +5651,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Registry Key modifications - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Windows Defense Evasion Tactics"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5771,7 +5771,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] +action.escu.analytic_story = ["Ransomware", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5814,7 +5814,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Hidden Cobra Malware", "DHS Report TA18-074A", "Emotet Malware DHS Report TA18-201A ", "Ransomware"] +action.escu.analytic_story = ["Ransomware", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5837,7 +5837,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(All_Traffic.dest_ip) as dest values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 | rename "IsOutlier(count)" as isOutlier | search isOutlier > 0 | sort -count | table _time src dest port count | `smb_traffic_spike_mltk_filter` +search = | tstats `security_content_summariesonly` count values(All_Traffic.dest_ip) as dest values(All_Traffic.dest_port) as port from datamodel=Network_Traffic where All_Traffic.dest_port=139 OR All_Traffic.dest_port=445 OR All_Traffic.app=smb by _time span=1h, All_Traffic.src | eval HourOfDay=strftime(_time, "%H") | eval DayOfWeek=strftime(_time, "%A") | `drop_dm_object_name(All_Traffic)` | apply smb_pdfmodel threshold=0.001 | rename "IsOutlier(count)" as isOutlier | search isOutlier > 0 | sort -count | table _time src dest port count | `smb_traffic_spike___mltk_filter` [ESCU - SQL Injection with Long URLs - Rule] action.escu = 0 @@ -5934,7 +5934,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Sc exe Manipulating Windows Services - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Disabling Security Tools", "Windows Service Abuse", "Orangeworm Attack Group", "DHS Report TA18-074A"] +action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Service Abuse", "Disabling Security Tools", "DHS Report TA18-074A", "Orangeworm Attack Group"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5997,7 +5997,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*delete* OR process=*create*) process=*reset* | `dragonfly_schtasks_filter` +search = | tstats `security_content_summariesonly` count values(Processes.process) as process values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=schtasks.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*delete* OR process=*create*) process=*reset* | `scheduled_task_name_used_by_dragonfly_threat_actors_filter` [ESCU - Scheduled tasks used in BadRabbit ransomware - Rule] action.escu = 0 @@ -6157,7 +6157,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = "scrcons.exe" by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `wmi_script_execution_filter` +search = | tstats `security_content_summariesonly` count values(Processes.process) as process min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.process_name = "scrcons.exe" by Processes.user Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| `script_execution_via_wmi_filter` [ESCU - Shim Database File Creation - Rule] action.escu = 0 @@ -6395,7 +6395,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Filesystem where Filesystem.action=created by _time span=1h, Filesystem.dest | `drop_dm_object_name(Filesystem)` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, "-1d@d"), count, null))) as "count" avg(eval(if(_time upperBound) AND num_data_samples >=20, 1, 0) | search isOutlier=1 | `file_write_spikes_filter` +search = | tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Filesystem where Filesystem.action=created by _time span=1h, Filesystem.dest | `drop_dm_object_name(Filesystem)` | eventstats max(_time) as maxtime | stats count as num_data_samples max(eval(if(_time >= relative_time(maxtime, "-1d@d"), count, null))) as "count" avg(eval(if(_time upperBound) AND num_data_samples >=20, 1, 0) | search isOutlier=1 | `spike_in_file_writes_filter` [ESCU - Splunk Enterprise Information Disclosure - Rule] action.escu = 0 @@ -6475,7 +6475,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name!=Explorer.exe AND Processes.process_name!=OpenWith.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path]| `change_file_association_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name!=Explorer.exe AND Processes.process_name!=OpenWith.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path=*\\Explorer\\FileExts* by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path]| `suspicious_changes_to_file_associations_filter` [ESCU - Suspicious Email - UBA Anomaly - Rule] action.escu = 0 @@ -6556,7 +6556,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | `suspicious_email_attachments` | `suspicious_email_attachments_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `drop_dm_object_name("All_Email")` | `suspicious_email_attachments` | `suspicious_email_attachment_extensions_filter` [ESCU - Suspicious File Write - Rule] action.escu = 0 @@ -6676,7 +6676,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_name="*.lnk" AND (Filesystem.file_path="C:\\Users*" OR Filesystem.file_path="*Local\\Temp*") by _time span=1h Filesystem.process_id Filesystem.file_name Filesystem.file_path Filesystem.file_hash Filesystem.user | `drop_dm_object_name(Filesystem)` | rename process_id as lnk_pid | join lnk_pid, _time [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_name=* by _time span=1h Processes.parent_process_id Processes.process_id Processes.process_name Processes.dest Processes.process_path Processes.process | `drop_dm_object_name(Processes)` | rename parent_process_id as lnk_pid | fields _time lnk_pid process_id dest process_name process_path process] | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table firstTime, lastTime, lnk_pid, process_id, user, dest, file_name, file_path, process_name, process, process_path, file_hash | `lnk_executing_a_process_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Filesystem where Filesystem.file_name="*.lnk" AND (Filesystem.file_path="C:\\Users*" OR Filesystem.file_path="*Local\\Temp*") by _time span=1h Filesystem.process_id Filesystem.file_name Filesystem.file_path Filesystem.file_hash Filesystem.user | `drop_dm_object_name(Filesystem)` | rename process_id as lnk_pid | join lnk_pid, _time [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_name=* by _time span=1h Processes.parent_process_id Processes.process_id Processes.process_name Processes.dest Processes.process_path Processes.process | `drop_dm_object_name(Processes)` | rename parent_process_id as lnk_pid | fields _time lnk_pid process_id dest process_name process_path process] | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | table firstTime, lastTime, lnk_pid, process_id, user, dest, file_name, file_path, process_name, process, process_path, file_hash | `suspicious_lnk_file_launching_a_process_filter` [ESCU - Suspicious Reg exe Process - Rule] action.escu = 0 @@ -6693,7 +6693,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Reg exe Process - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Disabling Security Tools", "DHS Report TA18-074A", "Windows Defense Evasion Tactics"] +action.escu.analytic_story = ["Disabling Security Tools", "Windows Defense Evasion Tactics", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6716,7 +6716,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name != explorer.exe Processes.process_name =cmd.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process_id Processes.parent_process_id | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe by Processes.parent_process_id Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename parent_process_id as process_id |dedup process_id| table process_id dest] | `suspicious_reg_process_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes where Processes.parent_process_name != explorer.exe Processes.process_name =cmd.exe by Processes.user Processes.process_name Processes.parent_process_name Processes.dest Processes.process_id Processes.parent_process_id | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | search [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.parent_process_name=cmd.exe Processes.process_name= reg.exe by Processes.parent_process_id Processes.dest Processes.process_name | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | rename parent_process_id as process_id |dedup process_id| table process_id dest] | `suspicious_reg_exe_process_filter` [ESCU - Suspicious wevtutil Usage - Rule] action.escu = 0 @@ -6852,7 +6852,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - System Processes Run From Unexpected Locations - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual Processes", "Ransomware", "Suspicious Command-Line Executions"] +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6892,7 +6892,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - TOR Traffic - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control", "Ransomware"] +action.escu.analytic_story = ["Command and Control", "Ransomware", "Prohibited Traffic Allowed or Protocol Mismatch"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6971,7 +6971,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Uncommon Processes On Endpoint - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual Processes", "Windows Privilege Escalation"] +action.escu.analytic_story = ["Windows Privilege Escalation", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6994,7 +6994,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes by Processes.dest Processes.user Processes.process Processes.process_name | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `drop_dm_object_name(Processes)` | `uncommon_processes` |`uncommon_processes_on_endpoint_filter` [ESCU - Unload Sysmon Filter Driver - Rule] action.escu = 0 @@ -7074,7 +7074,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `unsigned_image_loaded_by_LSASS_filter` +search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `unsigned_image_loaded_by_lsass_filter` [ESCU - Unsuccessful Netbackup backups - Rule] action.escu = 0 @@ -7130,7 +7130,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual Processes", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions"] +action.escu.analytic_story = ["Ransomware", "Suspicious Command-Line Executions", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -7153,7 +7153,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| `unusually_long_commandlines_filter`| eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost) +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| `unusually_long_command_line_filter` eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost) [ESCU - Unusually Long Command Line - MLTK - Rule] action.escu = 0 @@ -7170,7 +7170,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Unusual Processes", "Ransomware", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious Command-Line Executions"] +action.escu.analytic_story = ["Ransomware", "Suspicious Command-Line Executions", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -9431,7 +9431,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 0 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` +search = | tstats count `security_content_summariesonly` earliest(_time) as first_login latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")` [ESCU - Investigate Network Traffic From src ip - Response Task] action.escu = 0 @@ -9536,7 +9536,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 +search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user [ESCU - Investigate Previous Unseen User - Response Task] action.escu = 0 diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 065592c473..9d23f65600 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T09:08:45 UTC +# On Date: 2020-05-14T08:00:44 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index e07980a915..3880ef279b 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-13T09:08:45 UTC +# On Date: 2020-05-14T08:00:44 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Country"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For User"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web POSTs From src", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Previous Unseen User"] +searches = ["ESCU - Creation of Shadow Copy - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -374,10 +374,10 @@ narrative = Kubernetes is the most used container orchestration platform, this o category = Adversary Tactics last_updated = 2020-02-04 version = 2 -references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - All backup logs for host"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - File with Samsam Extension - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get EC2 Launch Details", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get Notable Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable Info", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address"] +searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Notable Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable Info"] +searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Parent Process Info"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. diff --git a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml index cc3e9d7a08..fd0ffd8e6c 100644 --- a/response_tasks/investigate_failed_logins_for_multiple_destinations.yml +++ b/response_tasks/investigate_failed_logins_for_multiple_destinations.yml @@ -12,7 +12,7 @@ search: '| tstats count `security_content_summariesonly` earliest(_time) as firs latest(_time) as last_login dc(Authentication.dest) AS distinct_count_dest values(Authentication.dest) AS Authentication.dest values(Authentication.app) AS Authentication.app from datamodel=Authentication where Authentication.action=failure by Authentication.user | where distinct_count_dest - > 0 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` + > 1 | `security_content_ctime(first_login)` | `security_content_ctime(last_login)` | `drop_dm_object_name("Authentication")`' tags: analytics_story: diff --git a/response_tasks/investigate_pass_the_ticket_attempts.yml b/response_tasks/investigate_pass_the_ticket_attempts.yml index e6de16dd57..7ca5f470c9 100644 --- a/response_tasks/investigate_pass_the_ticket_attempts.yml +++ b/response_tasks/investigate_pass_the_ticket_attempts.yml @@ -12,8 +12,10 @@ how_to_implement: To successfully implement this search you need to be ingesting author: Patrick Bareiss, Splunk inputs: - dest -search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) - AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2' +search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user + "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) + AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 + | rename new_user AS user' tags: analytics_story: - Credential Dumping diff --git a/stories/lateral_movement.yml b/stories/lateral_movement.yml index 9d7d1efff9..ac9b5e0ebc 100644 --- a/stories/lateral_movement.yml +++ b/stories/lateral_movement.yml @@ -32,6 +32,7 @@ narrative: "Once attackers gain a foothold within an enterprise, they will seek author: David Dorsey, Splunk type: ESCU references: +- https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis - https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html tags: analytics_story: Lateral Movement From e9e81cd1dea5a59031fcd6cbfdd39517eda7b272 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 14 May 2020 10:11:16 +0200 Subject: [PATCH 54/93] bug in generate --- stories/lateral_movement.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/stories/lateral_movement.yml b/stories/lateral_movement.yml index ac9b5e0ebc..9d7d1efff9 100644 --- a/stories/lateral_movement.yml +++ b/stories/lateral_movement.yml @@ -32,7 +32,6 @@ narrative: "Once attackers gain a foothold within an enterprise, they will seek author: David Dorsey, Splunk type: ESCU references: -- https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis - https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html tags: analytics_story: Lateral Movement From fcfea82cd4d9bd7ccdd7beac2c0c3fb114df502f Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Thu, 14 May 2020 11:30:28 +0200 Subject: [PATCH 55/93] make small changes --- ...owershell_execution_policy_to_unrestricted_or_bypass.yml | 2 +- .../detect_credential_dumping_through_LSASS_access.yml | 2 +- response_tasks/investigate_pass_the_ticket_attempts.yml | 6 ++---- 3 files changed, 4 insertions(+), 6 deletions(-) diff --git a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml index 96e9e04f15..20db8405eb 100644 --- a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml +++ b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml @@ -17,7 +17,7 @@ search: "| tstats `security_content_summariesonly` count min(_time) as firstTime \ (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass)\ \ by Registry.registry_path Registry.registry_key_name Registry.registry_value_name\ \ Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`|\ - \ `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter`\_" + \ `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` " known_false_positives: Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should diff --git a/detections/detect_credential_dumping_through_LSASS_access.yml b/detections/detect_credential_dumping_through_LSASS_access.yml index 42f7ba29a1..bcff7da23a 100644 --- a/detections/detect_credential_dumping_through_LSASS_access.yml +++ b/detections/detect_credential_dumping_through_LSASS_access.yml @@ -17,7 +17,7 @@ search: '`sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR G | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `detect_credential_dumping_through_LSAS`detect_credential_dumping_through_lsass_access_filter` ' + | `detect_credential_dumping_through_lsass_access_filter` ' known_false_positives: The activity may be legitimate. Other tools can access lsass for legitimate reasons, and it's possible this event could be generated in those cases. In these cases, false positives should be fairly obvious and you may need diff --git a/response_tasks/investigate_pass_the_ticket_attempts.yml b/response_tasks/investigate_pass_the_ticket_attempts.yml index 7ca5f470c9..e6de16dd57 100644 --- a/response_tasks/investigate_pass_the_ticket_attempts.yml +++ b/response_tasks/investigate_pass_the_ticket_attempts.yml @@ -12,10 +12,8 @@ how_to_implement: To successfully implement this search you need to be ingesting author: Patrick Bareiss, Splunk inputs: - dest -search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user - "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) - AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 - | rename new_user AS user' +search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) + AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2' tags: analytics_story: - Credential Dumping From bb190be50d0597660246019b8056e8718fdd728f Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 18 May 2020 14:21:47 -0700 Subject: [PATCH 56/93] remove Providing Technologies --- .../static/analytic_story_details.js | 20 ++----------------- .../default/data/ui/views/escu_summary.xml | 3 +-- 2 files changed, 3 insertions(+), 20 deletions(-) diff --git a/package/appserver/static/analytic_story_details.js b/package/appserver/static/analytic_story_details.js index 620910a106..113c93d45c 100644 --- a/package/appserver/static/analytic_story_details.js +++ b/package/appserver/static/analytic_story_details.js @@ -83,13 +83,6 @@ require([
-
-
- Technologies: -
-
-
-
References: @@ -140,7 +133,7 @@ require([ earliest_time: "-1h@h", latest_time: "now", cache: false, - search: "| rest /services/configs/conf-analytic_stories splunk_server=local count=0 | search title=\"" + asName + "\" | spath input=providing_technologies path={} output=tex | spath input=reference path={} output=ref | spath input=data_models path={} output=dm | table title, category, description, version, mappings, creation_date, modification_date, dm, narrative, tex, ref" + search: "| rest /services/configs/conf-analytic_stories splunk_server=local count=0 | search title=\"" + asName + "\" | spath input=reference path={} output=ref | spath input=data_models path={} output=dm | table title, category, description, version, mappings, creation_date, modification_date, dm, narrative, ref" }); $('.run-story').unbind('click'); @@ -169,7 +162,7 @@ require([ earliest_time: "-1h@h", latest_time: "now", cache: false, - search: "| rest /services/saved/searches splunk_server=local count=0 | spath input=action.escu.analytic_story path={} output=uc | search uc = \"" + asName + "\" | spath input=action.escu.data_models path={} output=dm | spath input=action.escu.providing_technologies path={} output=tex | table action.escu.full_search_name, search, description, action.escu.search_type, action.escu.how_to_implement, action.escu.eli5, action.escu.version, action.escu.mappings, dm, tex, action.escu.asset_at_risk, action.escu.confidence, action.escu.known_false_positives, updated, action.escu.modification_date, action.escu.creation_date " + search: "| rest /services/saved/searches splunk_server=local count=0 | spath input=action.escu.analytic_story path={} output=uc | search uc = \"" + asName + "\" | spath input=action.escu.data_models path={} output=dm | table action.escu.full_search_name, search, description, action.escu.search_type, action.escu.how_to_implement, action.escu.eli5, action.escu.version, action.escu.mappings, dm, tex, action.escu.asset_at_risk, action.escu.confidence, action.escu.known_false_positives, updated, action.escu.modification_date, action.escu.creation_date " }); var searchesSearch = splunkjs.mvc.Components.getInstance("s" + epoch); @@ -207,7 +200,6 @@ require([ $('#description').html(converter.makeHtml(asAttributes.description)); $('#mitre_attack').html(getValueLabels(mappings.mitre_attack, 'attack_tag')); $('#data_model').html(getValueLabels(asAttributes.dm, 'data_model_tag')); - $('#technology').html(getValueLabels(asAttributes.tex)); $('#kill_chain_phases').html(getValueLabels(mappings.kill_chain_phases, 'kill_chain_tag')); $('#cis_20').html(getValueLabels(mappings.cis20)); $('#references').html(getReferenceURLS(asAttributes.ref)); @@ -294,14 +286,6 @@ require([ ${ getValueLabels(search['dm'], 'data_model_tag') }
-
-
- Technologies -
-
- ${ getValueLabels(search['tex']) } -
-
`; diff --git a/package/default/data/ui/views/escu_summary.xml b/package/default/data/ui/views/escu_summary.xml index 252379d94b..40562212f9 100644 --- a/package/default/data/ui/views/escu_summary.xml +++ b/package/default/data/ui/views/escu_summary.xml @@ -288,7 +288,6 @@ | spath input=mappings path=kill_chain_phases{} output="Kill Chain Phases" | spath input=mappings path=cis20{} output=cis | spath input=mappings path=mitre_attack{} output="ATT&CK" - | spath input=providing_technologies path={} output="Providing Technologies" | rex field=cis "CIS\s(?<num>\d+)" | rename num as CIS | rename title as "Analytic Story" description as "Description" category as "Category" creation_date as "Created" modification_date as "Last Updated" @@ -298,7 +297,7 @@ | search "Kill Chain Phases"=$as_kill_chain_phase$ | search "Category"=$as_category$ | search CIS=$as_cis$ - | table "Analytic Story" Description Category "Kill Chain Phases" "ATT&CK", CIS, "Data Models" "Providing Technologies" "Created" "Last Updated" + | table "Analytic Story" Description Category "Kill Chain Phases" "ATT&CK", CIS, "Data Models" "Created" "Last Updated" From 4124fedf12a44df9b821d66014917c476b9c6678 Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 18 May 2020 15:46:56 -0700 Subject: [PATCH 57/93] remove mitre tatic from filters --- package/appserver/static/escu_summary.js | 2 - .../default/data/ui/views/escu_summary.xml | 43 ++----------------- 2 files changed, 3 insertions(+), 42 deletions(-) diff --git a/package/appserver/static/escu_summary.js b/package/appserver/static/escu_summary.js index 7b3427b74c..572eef9abb 100644 --- a/package/appserver/static/escu_summary.js +++ b/package/appserver/static/escu_summary.js @@ -64,7 +64,6 @@ require([ tokenModel.set('form.as_cis', '*'); tokenModel.set('form.as_category', '*'); tokenModel.set('form.as_kill_chain_phase', '*'); - tokenModel.set('form.as_mitre_attack', '*'); tokenModel.set('form.as_data_models', '*'); }); @@ -72,7 +71,6 @@ require([ tokenModel.set('form.cis', '*'); tokenModel.set('form.searchtype', '*'); tokenModel.set('form.kill_chain_phase', '*'); - tokenModel.set('form.mitre_attack', '*'); tokenModel.set('form.data_models', '*'); }); }); diff --git a/package/default/data/ui/views/escu_summary.xml b/package/default/data/ui/views/escu_summary.xml index 40562212f9..f06d1eac19 100644 --- a/package/default/data/ui/views/escu_summary.xml +++ b/package/default/data/ui/views/escu_summary.xml @@ -227,23 +227,6 @@ " * - - - All - Persistence - Privilege Escalation - Defense Evasion - Credential Access - Discovery - Lateral Movement - Execution - Collection - Exfiltration - Command and Control - " - " - * - All @@ -287,17 +270,15 @@ spath input=data_models path={} output="Data Models" | spath input=mappings path=kill_chain_phases{} output="Kill Chain Phases" | spath input=mappings path=cis20{} output=cis - | spath input=mappings path=mitre_attack{} output="ATT&CK" | rex field=cis "CIS\s(?<num>\d+)" | rename num as CIS | rename title as "Analytic Story" description as "Description" category as "Category" creation_date as "Created" modification_date as "Last Updated" | fillnull value="-" | search "Data Models"=$as_data_models$ - | search "ATT&CK"=$as_mitre_attack$ | search "Kill Chain Phases"=$as_kill_chain_phase$ | search "Category"=$as_category$ | search CIS=$as_cis$ - | table "Analytic Story" Description Category "Kill Chain Phases" "ATT&CK", CIS, "Data Models" "Created" "Last Updated" + | table "Analytic Story" Description Category "Kill Chain Phases" , CIS, "Data Models" "Created" "Last Updated" @@ -415,23 +396,7 @@ " * - - - All - Persistence - Privilege Escalation - Defense Evasion - Credential Access - Discovery - Lateral Movement - Execution - Collection - Exfiltration - Command and Control - " - " - * - + All @@ -475,17 +440,15 @@ spath input=action.escu.data_models path={} output="Data Models" | spath input=action.escu.mappings path=kill_chain_phases{} output="Kill Chain Phases" | spath input=action.escu.mappings path=cis20{} output=cis - | spath input=action.escu.mappings path=mitre_attack{} output="ATT&CK" | rex field=cis "CIS\s(?<num>\d+)" | rename num as CIS | fillnull value="-" | search CIS=$cis_token$ - | search "ATT&CK"=$mitre_attack$ | search "Data Models"=$data_models$ | search "Kill Chain Phases"=$kill_chain_phase$ | search action.escu.search_type=$searchtype$ | rename action.escu.asset_at_risk AS "Asset at Risk" | rename title as "Search Name"| rename modification_date as "Last Updated" - | table "Search Name" description "Kill Chain Phases" CIS "ATT&CK" "Data Models" "Last Updated" + | table "Search Name" description "Kill Chain Phases" CIS "Data Models" "Last Updated" 0 From 8d303f57c5c64dab97a507ef33765f5a80e5010d Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 18 May 2020 16:28:14 -0700 Subject: [PATCH 58/93] remove old files --- package/README/alert_actions.conf.spec | 85 ------------------ package/README/analytic_story.conf.spec | 100 ---------------------- package/README/savedsearches.conf.example | 99 --------------------- package/README/savedsearches.conf.spec | 18 ---- 4 files changed, 302 deletions(-) delete mode 100644 package/README/alert_actions.conf.spec delete mode 100644 package/README/analytic_story.conf.spec delete mode 100644 package/README/savedsearches.conf.example delete mode 100644 package/README/savedsearches.conf.spec diff --git a/package/README/alert_actions.conf.spec b/package/README/alert_actions.conf.spec deleted file mode 100644 index 5e1a7184f3..0000000000 --- a/package/README/alert_actions.conf.spec +++ /dev/null @@ -1,85 +0,0 @@ -# Copyright (C) 2009-2016 Splunk Inc. All Rights Reserved. -# -# This file contains additional options for an alert_actions.conf file. -# -# To learn more about configuration files (including precedence) please see the documentation -# located at http://www.splunk.com/base/Documentation/latest/Admin/Aboutconfigurationfiles -# -[escu] - -enabled = [true|false|0|1] - * Whether or not this use-case is enabled. - * This exists so that we are a true noop for scheduled searches. - * action.usecase=0 action.usecase.enabled=1 - * Required. - * Defaults to false. - -version = [string] - * Version of this search - -asset_at_risk = [string] - * The type of asset that is at risk from the behavior this search is attempting to find - * Defaults to None - -category = [string] - * A description of the category that this use-case falls into - * Defaults to None - -channel = [string] - * The name of the channel the search belongs to - -confidence = [low|medium|high] - * A description of the confidence value - * Valid values are: low, medium, high - * Defaults to None - -creation_time = [datetime] - * The date & time that the search was first created - * The date-time should be formatted an epoch time (in GMT) - -datamodels = [json] - * A JSON list of the data models used by this search - * Defaults to None - -eli5 = [string] - * Text explaining this search to a 5 year old - * Defaults to None - -full_search_name = [string] - * The entire search name - * Defaults to None - -how_to_implement = [string] - * Text discussing what needs to be done to implement this search and any local modifications that can be performed - * Defaults to None - -known_false_positives = [string] - * A description of cases in which this use-case may generate false positive alerts - * Defaults to None - -mappings = [json] - * A JSON list of the kill chain phases this search covers - * Defaults to None - -modification_time = [datetime] - * The date that the search was last modified - * The date-time should be formatted an epoch time (in GMT) - -remediation = [string] - * A high-level description of how the issue described by this use-case can be remediated. - * Defaults to None - -providing_technologies = [json] - * A JSON list of the technology examples that can be used to gather data to power this search - * Defaults to None - -analytic_story = [json] - * A JSON list of the use cases this search applies to - * Defaults to None - -earliest_time_offset = [integer] - * Time in seconds before event time that the search should cover - -latest_time_offset = [integer] - * Time in seconds after event time that the search should cover - diff --git a/package/README/analytic_story.conf.spec b/package/README/analytic_story.conf.spec deleted file mode 100644 index 4aebc9f729..0000000000 --- a/package/README/analytic_story.conf.spec +++ /dev/null @@ -1,100 +0,0 @@ -# Copyright (C) 2009-2016 Splunk Inc. All Rights Reserved. -# -# This file contains all possible options for a usecases.conf file. Use this file to define a use-case. -# -# To learn more about configuration files (including precedence) please see the documentation -# located at http://www.splunk.com/base/Documentation/latest/Admin/Aboutconfigurationfiles -# -[] -category = [string] - * The category of the analytic story - * Defaults to None - -creation_time = [datetime] - * The date & time that the analytic story was first created - * The date-time should be formatted an epoch time (in GMT) - -data_models = [json] - * A JSON list of the data models used by the analytic story - * Defaults to None - -description = [string] - * A bried description of the analytic story - * Defaults to None - -id = [string] - * A description of the analytic story - * Defaults to None - -mappings = [json] - * A JSON dictionary of the different mappings this story maps to - * See appendix B for the format of this field - * Defaults to None - -modification_time = [datetime] - * The date & time that the analytic story was last modified - * The date-time should be formatted an epoch time (in GMT) - -narrative = [string] - * A longer narrative of the analytic story that describes the detection searches, any support searches, - * and the corresponding contextual and investigative searches - * Defaults to None - -references = [json] - * A JSON list of references for this story - * Defaults to None - -detection_searches = [json] - * A JSON list of the detection searches that the analytic story applies to. - * See appendix A for the format of this field - * Defaults to None - -investigative_searches = [json] - * A JSON list of the investigative searches that the analytic story applies to. - * See appendix A for the format of this field - * Defaults to None - -contextual_searches = [json] - * A JSON list of contextual searches that the analytic story applies to. - * See appendix A for the format of this field - * Defaults to None - -support_searches = [json] - * JSON list of support searches that the analytic story applies to. - * See appendix A for the format of this field - * Defaults to None - -providing_technologies = [json] - * A JSON list of example technologies that can be used to capture the data needed for the analytic story - * Defaults to None - -version = [int] - * An integer indicating which revision of the analytic story this is - * This value should start with one and increase for each release - -###### Appendix A: *_searches Specification ####### -# This can just be a list of saved search names. However, this also supports a hierarchical structure to denote searches that rely on other searches. -# -# A non-hierarchical version would look like this: -# [ "search1", "search2" ] -# -# A hierarchical version would look like this: -#[ -# "search1": [ "search1a", "search1b" ], -# "search2": [ "search2a" ] -#] - - -###### Appendix B: Mappings Specification ####### -# -# This is a dictionary of the different mappings this analytic story maps to. -# The mapping will be the key, and the value will be an array of the labels it applies to -# -# Example: -# { -# "kill_chain_phase": ["Delivery", "Command and Control"], -# "sans cis": ["CIS 9", "CIS 12"], -# "att&ck": ["Command and Control"] -# } -# - diff --git a/package/README/savedsearches.conf.example b/package/README/savedsearches.conf.example deleted file mode 100644 index 9aefc86a96..0000000000 --- a/package/README/savedsearches.conf.example +++ /dev/null @@ -1,99 +0,0 @@ -### ESCU DETECTIONS ### - -[ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule] -action.escu = 0 -action.escu.enabled = 1 -description = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." -action.escu.mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -action.escu.eli5 = The subsearch returns all events with event names that start with "Run" or "Create," and then does a `GeoIP` lookup on the IP address that initiated the action within the last hour. It appends the historical data to those results in the lookup file. Next, it recalculates the `firstTime` and `lastTime` field for each country, region, city, and IP address and outputs this data to the lookup file to update the local cache. It then calculates the `firstTime` and `lastTime` for each city. It returns only those events from cities that have first been seen in the past hour. This is combined with the main search to return the time, user, IP address, city, event name, and error code from the action. -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. -action.escu.known_false_positives = This is a strictly behavioral search, so we define "false positive" slightly differently. Every time this fires, it will accurately reflect the first occurrence in the time period you're searching within, plus what is stored in the cache feature. But while there are really no "false positives" in a traditional sense, there is definitely lots of noise.\ -\ - This search will fire any time a new city is seen in the **GeoIP** database for any kind of provisioning activity. If you typically do all provisioning from tools inside of your city, there should be few false positives. If you are located in countries where the free version of **MaxMind GeoIP** that ships by default with Splunk has weak resolution (particularly small countries in less economically powerful regions), this may be much less valuable to you. -action.escu.creation_date = 2018-03-16 -action.escu.modification_date = 2018-03-16 -action.escu.confidence = medium -action.escu.full_search_name = ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule -action.escu.search_type = detection -action.escu.asset_at_risk = AWS Instance -action.escu.fields_required = ["dest"] -action.escu.providing_technologies = ["AWS"] -action.escu.analytic_story = ["AWS Suspicious Provisioning Activities"] -cron_schedule = 0 * * * * -dispatch.earliest_time = -70m@m -dispatch.latest_time = -10m@m -action.correlationsearch.enabled = 1 -action.correlationsearch.label = AWS Cloud Provisioning From Previously Unseen City -action.notable = 1 -action.notable.param.nes_fields = src_ip, city -action.notable.param.rule_description = Your AWS infrastructure was provisioned from a city, $city$, which has never before been seen provisioning your infrastructure. -action.notable.param.rule_title = AWS Provision Activity From $city$ -action.notable.param.security_domain = endpoint -action.notable.param.severity = medium -action.risk = 1 -action.risk.param._risk_object = dest -action.risk.param._risk_object_type = system -action.risk.param._risk_score = 30 -action.risk.param.verbose = 0 -alert.digest_mode = 1 -alert.suppress = 1 -alert.suppress.fields = dest -alert.suppress.period = 14400s -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -disabled=true -enableSched = 1 -counttype = number of events -relation = greater than -quantity = 0 -realtime_schedule = 0 -schedule_window = auto -is_visible = false -search = sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* [search sourcetype=aws:cloudtrail (eventName=Run* OR eventName=Create*) | iplocation sourceIPAddress | search City=* | stats earliest(_time) as firstTime, latest(_time) as lastTime by sourceIPAddress, City, Region, Country | inputlookup append=t previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by sourceIPAddress, City, Region, Country | outputlookup previously_seen_provisioning_activity_src.csv | stats min(firstTime) as firstTime max(lastTime) as lastTime by City | eval newCity=if(firstTime >= relative_time(now(), "-70m@m"), 1, 0) | where newCity=1 | table City] | spath output=user userIdentity.arn | rename sourceIPAddress as src_ip | table _time, user, src_ip, City, eventName, errorCode - - -### ESCU INVESTIGATIONS ### - -[ESCU - AWS Investigate User Activities By ARN] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = investigative -action.escu.full_search_name = ESCU - AWS Investigate User Activities By ARN -description = This search lists all the logged CloudTrail activities by a specific user ARN and will create a table containing the source of the user, the region of the activity, the name and type of the event, the action taken, and all the user's identity information. -action.escu.creation_date = 2018-01-22 -action.escu.modification_date = 2019-04-30 -action.escu.analytic_story = ["AWS Cryptomining", "AWS Network ACL Activity", "Command and Control", "Suspicious AWS EC2 Activities", "Suspicious AWS Login Activities", "Suspicious AWS S3 Activities", "Suspicious AWS Traffic", "Unusual AWS EC2 Modifications"] -action.escu.earliest_time_offset = 3600 -action.escu.latest_time_offset = 86400 -action.escu.providing_technologies = ["AWS"] -action.escu.eli5 = none -action.escu.how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. -action.escu.known_false_positives = None at this time -action.escu.fields_required = ["user"] -disabled=true -schedule_window = auto -is_visible = false -search = | search sourcetype=aws:cloudtrail userIdentity.arn={user} | table _time userIdentity.type userIdentity.userName userIdentity.arn aws_account_id src awsRegion eventName eventType - - - -[ESCU - Add Prohibited Processes to Enterprise Security] -action.escu = 0 -action.escu.enabled = 1 -action.escu.search_type = support -action.escu.full_search_name = ESCU - Add Prohibited Processes to Enterprise Security -description = This search takes the existing interesting process table from ES, filters out any existing additions added by ESCU and then updates the table with processes identified by ESCU that should be prohibited on your endpoints. -action.escu.creation_date = 2017-06-27 -action.escu.modification_date = 2017-09-15 -action.escu.analytic_story = ["Emotet Malware (DHS Report TA18-201A)", "Monitor for Unauthorized Software", "SamSam Ransomware"] -action.escu.data_models = [] -dispatch.earliest_time = -30d@d -dispatch.latest_time = -10m@m -action.escu.providing_technologies = ["Splunk Enterprise Security"] -action.escu.eli5 = This search outputs the interesting processes lookup table and filters out all processes in the table that haven't already been inserted by ESCU. It then appends to those results all the processes currently identified by ESCU that should be prohibited. Next, it fills in the required fields with processes identified by ESCU, and then writes the results back to the interesting process lookup table. This is done so any new processes identified that should be prohibited will be added to the lookup table without creating any duplicate entries. -action.escu.how_to_implement = This search should be run on each new install of ESCU. -action.escu.known_false_positives = -disabled=true -schedule_window = auto -is_visible = false -search = | inputlookup interesting_processes_lookup | search note!=ESCU* | inputlookup append=T prohibitedProcesses_lookup | fillnull value=* dest dest_pci_domain | fillnull value=false is_required is_secure | fillnull value=true is_prohibited | outputlookup interesting_processes_lookup | stats count diff --git a/package/README/savedsearches.conf.spec b/package/README/savedsearches.conf.spec deleted file mode 100644 index 6d5d238354..0000000000 --- a/package/README/savedsearches.conf.spec +++ /dev/null @@ -1,18 +0,0 @@ - -[] -* Create a unique stanza name for each saved search that belongs to an analytic story -* Follow the stanza name with any number of the following settings. -* If you do not specify a setting, Splunk software uses the default. - -action.escu.full_search_name = - * Full name of the search - * required - -action.escu.mappings = [json] - * Framework mappings like CIS, Kill Chain, NIST, ATTACK - -action.escu.analytic_story = - * List of analytic story the search belongs to - -action.escu.search_type = [detection | investigative | support] - * The type of this search \ No newline at end of file From 2b33d4fe86868f5149b0202c2e4446f348c3fe8f Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 18 May 2020 16:41:58 -0700 Subject: [PATCH 59/93] spec documentation using jsonschema2md --- docs/baselines.spec.json | 472 ----- docs/baselines.spec.md | 1345 -------------- docs/detections.spec.json | 1213 ------------- docs/detections.spec.md | 2855 ------------------------------ docs/investigations.spec.json | 372 ---- docs/investigations.spec.md | 1165 ------------ docs/splunk_docs_categories.wiki | 1 - docs/stories_categories.md | 1 - docs/story.spec.json | 271 --- docs/story.spec.md | 725 -------- spec/baselines.spec.md | 283 +++ spec/detections.spec.md | 381 ++++ spec/lookups.spec.md | 282 +++ spec/macros.spec.md | 131 ++ spec/response_tasks.spec.json | 14 +- spec/response_tasks.spec.md | 437 +++++ spec/responses.spec.md | 270 +++ spec/stories.spec.md | 283 +++ 18 files changed, 2074 insertions(+), 8427 deletions(-) delete mode 100644 docs/baselines.spec.json delete mode 100644 docs/baselines.spec.md delete mode 100644 docs/detections.spec.json delete mode 100644 docs/detections.spec.md delete mode 100644 docs/investigations.spec.json delete mode 100644 docs/investigations.spec.md delete mode 100644 docs/story.spec.json delete mode 100644 docs/story.spec.md create mode 100644 spec/baselines.spec.md create mode 100644 spec/detections.spec.md create mode 100644 spec/lookups.spec.md create mode 100644 spec/macros.spec.md create mode 100644 spec/response_tasks.spec.md create mode 100644 spec/responses.spec.md create mode 100644 spec/stories.spec.md diff --git a/docs/baselines.spec.json b/docs/baselines.spec.json deleted file mode 100644 index ed0d1604c5..0000000000 --- a/docs/baselines.spec.json +++ /dev/null @@ -1,472 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/baselines.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "definitions": { - "phantom": { - "properties": { - "phantom_server": { - "description": "IP address and username of the Phantom server. Currently, we ship these values as automation (hostname) and encourage users to modify them according to their environments: for example, automation (hostname)", - "examples": [ - "automation (hostname)" - ], - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on the Phantom community repository on github, with underscores, and appended with \"community/.\" The playbooks are hosted on https://github.com/phantomcyber/playbooks. For example: community/simple_network_enrichment.", - "examples": [ - "community/dns_hijack_investigation" - ], - "type": "string" - }, - "playbook_url": { - "description": "URL of the playbook on the Phantom website", - "examples": [ - "https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" - ], - "type": "string" - }, - "schedule": { - "description": "Various fields used to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "examples": [ - "0 * * * *" - ], - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "examples": [ - "-70m@m" - ], - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run again in Splunk format", - "examples": [ - "-10m@m" - ], - "type": "string" - } - }, - "type": "object" - }, - "sensitivity": { - "description": "TLP colors (White, Green, Amber, or Red)", - "examples": [ - "green" - ], - "type": "string" - }, - "severity": { - "description": "Severity in Phantom (High, Medium, Low)", - "examples": [ - "medium" - ], - "type": "string" - } - }, - "required": [ - "phantom_server", - "playbook_name", - "playbook_url" - ], - "type": "object" - }, - "splunk": { - "properties": { - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "examples": [ - "0 * * * *" - ], - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "examples": [ - "-70m@m" - ], - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run again in Splunk format", - "examples": [ - "-10m@m" - ], - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search (in SPL) executed within Splunk Enterprise for investigation", - "examples": [ - "| inputlookup discovered_dns_records.csv | rename answer as discovered_answer | join domain[|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n)" - ], - "type": "string" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - } - }, - "description": "The fields that make up the manifest of a version 2 baseline search", - "properties": { - "baseline": { - "anyOf": [ - { - "required": [ - "splunk" - ] - }, - { - "required": [ - "phantom" - ] - } - ], - "properties": { - "phantom": { - "$ref": "#/definitions/phantom" - }, - "splunk": { - "$ref": "#/definitions/splunk" - } - }, - "type": "object" - }, - "creation_date": { - "description": "The date the baseline manifest was created", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "data_metadata": { - "description": "Information about the data being ingested", - "properties": { - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "examples": [ - "wineventlog" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_models": { - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "examples": [ - "DNS" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "examples": [ - "stream:dns" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "Censys", - "Passive Total", - "WHOIS" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "required": [ - "data_source", - "providing_technologies" - ], - "type": "object" - }, - "description": { - "description": "A description of what the search is is doing to create a baseline", - "examples": [ - "The search takes corporate and common cloud-provider domains configured under \"cim_corporate_email_domains.csv,\" \"cim_corporate_web_domains.csv,\" and \"cloud_domains.csv,\" finds their responses across the last 30 days from data in the \"Network_Traffic\" data model, then stores the output under the \"discovered_dns_records.csv\" lookup." - ], - "type": "string" - }, - "eli5": { - "description": "Explain it Like I'm 5: A detailed description of the SPL in the search, written in a style that can be understood by a future Splunk expert.", - "examples": [ - "Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named \"discovered_dns_records.csv.\"" - ], - "type": "string" - }, - "entities": { - "description": "A list of entities that will be used in the story flow or that are relevant to the security investigation.", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "query", - "answer" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion of how to implement this search, from what needs to be ingested, config files modified, and suggested per-site modifications", - "examples": [ - "To successfully implement this search, you must be ingesting DNS logs and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation." - ], - "type": "string" - }, - "id": { - "description": "The unique identifier for the search", - "examples": [ - "c096f721-8842-42ce-bfc7-74bd8c72b7c3" - ], - "type": "string" - }, - "known_false_positives": { - "description": "Describe the known false postives while the analyst builds the baseline.", - "examples": [ - "Please vet the lookup created by this baseline search." - ], - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story.", - "items": { - "properties": { - "company": { - "description": "Company associated with the person maintaining this search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "name": { - "description": "The name of the search that creates the baseline", - "examples": [ - "Discover DNS records" - ], - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "items": { - "properties": { - "company": { - "description": "Company associated with the person who originally authored the search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "spec_version": { - "description": "The version of the detection search specification this manifest follows", - "examples": [ - "2.0" - ], - "type": "integer" - }, - "type": { - "description": "The type of baseline", - "enum": [ - "splunk", - "phantom", - "uba" - ], - "examples": [ - "splunk" - ] - }, - "version": { - "description": "The version of the search", - "examples": [ - "1", - "2" - ], - "type": "string" - } - }, - "required": [ - "id", - "creation_date", - "data_metadata", - "eli5", - "known_false_positives", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "name", - "description", - "type", - "spec_version", - "version", - "baseline" - ], - "title": "Baseline Manifest", - "type": "object" -} diff --git a/docs/baselines.spec.md b/docs/baselines.spec.md deleted file mode 100644 index 3ed4dbead0..0000000000 --- a/docs/baselines.spec.md +++ /dev/null @@ -1,1345 +0,0 @@ - -# Baseline Manifest Schema - -``` -https://api.splunkresearch.com/schemas/baselines.json -``` - -The fields that make up the manifest of a version 2 baseline search - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | Yes | Experimental | No | Forbidden | Permitted | | - -# Baseline Manifest Properties - -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [baseline](#baseline) | `object` | **Required** | No | Baseline Manifest (this schema) | -| [creation_date](#creation_date) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [data_metadata](#data_metadata) | `object` | **Required** | No | Baseline Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [eli5](#eli5) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [entities](#entities) | `enum[]` | Optional | No | Baseline Manifest (this schema) | -| [how_to_implement](#how_to_implement) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [known_false_positives](#known_false_positives) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | **Required** | No | Baseline Manifest (this schema) | -| [modification_date](#modification_date) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [name](#name) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | **Required** | No | Baseline Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | **Required** | No | Baseline Manifest (this schema) | -| [type](#type) | `enum` | **Required** | No | Baseline Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Baseline Manifest (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## baseline - - -`baseline` - -* is **required** -* type: `object` -* defined in this schema - -### baseline Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `phantom`| | Optional | -| `splunk`| | Optional | - - - -#### phantom - - -`phantom` - -* is optional -* type: reference - -##### phantom Type - - -* []() – `#/definitions/phantom` - - - - - - - -#### splunk - - -`splunk` - -* is optional -* type: reference - -##### splunk Type - - -* []() – `#/definitions/splunk` - - - - - - - - - - -## creation_date - -The date the baseline manifest was created - -`creation_date` - -* is **required** -* type: `string` -* defined in this schema - -### creation_date Type - - -`string` - - - - - - -### creation_date Example - -```json -"2019-02-14" -``` - - -## data_metadata - -Information about the date being ingested - -`data_metadata` - -* is **required** -* type: `object` -* defined in this schema - -### data_metadata Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `data_eventtypes`| array | Optional | -| `data_models`| array | Optional | -| `data_source`| array | **Required** | -| `data_sourcetypes`| array | Optional | -| `providing_technologies`| array | **Required** | - - - -#### data_eventtypes - -A list of eventtypes, if any, used by this search - -`data_eventtypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_eventtypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_eventtypes Example - -```json -wineventlog -``` - - - - -#### data_models - -A list of data models, if any, used by this search - -`data_models` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### data_models Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ], - "simpletype": "`enum`", - "meta:enum": { - "Alerts": "", - "Application_State": "", - "Authentication": "", - "Certificates": "", - "Change_Analysis": "", - "Cloud_Infrastructure": "", - "Change": "", - "Malware": "", - "Email": "", - "Identity_Management": "", - "Network_Resolution": "", - "Network_Traffic": "", - "Vulnerabilities": "", - "Web": "", - "Network_Sessions": "", - "Updates": "", - "Risk": "", - "Endpoint": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### data_models Example - -```json -Network_Resolution -``` - - - - -#### data_source - -A high-level description of the type of data needed for this search to complete - -`data_source` - -* is **required** -* type: `string[]`* at least `0` items in the array - - -##### data_source Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_source Example - -```json -DNS -``` - - - - -#### data_sourcetypes - -The list of sourcetypes, if any, used by this search - -`data_sourcetypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_sourcetypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_sourcetypes Example - -```json -stream:dns -``` - - - - -#### providing_technologies - -A list of technologies that provide this data - -`providing_technologies` - -* is **required** -* type: `enum[]`* at least `0` items in the array - - -##### providing_technologies Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "Censys", - "Passive Total", - "WHOIS" - ], - "simpletype": "`enum`", - "meta:enum": { - "Apache": "", - "AWS": "", - "Bro": "", - "Microsoft Windows": "", - "Linux": "", - "macOS": "", - "Netbackup": "", - "Splunk Enterprise": "", - "Splunk Enterprise Security": "", - "Splunk Stream": "", - "Active Directory": "", - "Bluecoat": "", - "Carbon Black Response": "", - "Carbon Black Protect": "", - "CrowdStrike Falcon": "", - "Microsoft Exchange": "", - "Nessus": "", - "Palo Alto Firewall": "", - "Qualys": "", - "Sysmon": "", - "Tanium": "", - "Ziften": "", - "Censys": "", - "Passive Total": "", - "WHOIS": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### providing_technologies Example - -```json -Bro -``` - - - - - - - -## description - -A description of what the search is is doing to create a baseline - -`description` - -* is **required** -* type: `string` -* defined in this schema - -### description Type - - -`string` - - - - - - -### description Example - -```json -"The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Traffic` datamodel, then stores the output under the `discovered_dns_records.csv` lookup" -``` - - -## eli5 - -Explain it like I am 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert - -`eli5` - -* is **required** -* type: `string` -* defined in this schema - -### eli5 Type - - -`string` - - - - - - -### eli5 Example - -```json -"Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named `discovered_dns_records.csv`" -``` - - -## entities - -A list of entities that will used in the story flow or are relevant to the security investigation. - -`entities` - -* is optional -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### entities Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of entities that will used in the story flow or are relevant to the security investigation.", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "query", - "answer" - ], - "simpletype": "`enum`", - "meta:enum": { - "accessKeyId": "", - "arn": "", - "awsRegion": "", - "bucketName": "", - "City": "", - "Country": "", - "dest_port": "", - "dest": "", - "event_id": "", - "instanceId": "", - "message_id": "", - "networkAclId": "", - "process_name": "", - "process": "", - "recipient": "", - "Region": "", - "resourceId": "", - "session_id": "", - "src_ip": "", - "src_mac": "", - "src_user": "", - "src": "", - "user": "", - "query": "", - "answer": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -### entities Examples - -```json -"dest" -``` - -```json -"user" -``` - - - -## how_to_implement - -A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications - -`how_to_implement` - -* is **required** -* type: `string` -* defined in this schema - -### how_to_implement Type - - -`string` - - - - - - -### how_to_implement Example - -```json -"To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation" -``` - - -## id - -The unique identifier for the search - -`id` - -* is **required** -* type: `string` -* defined in this schema - -### id Type - - -`string` - - - - - - -### id Example - -```json -"c096f721-8842-42ce-bfc7-74bd8c72b7c3" -``` - - -## known_false_positives - -Describe the known false postives while the analyst builds the baseline. - -`known_false_positives` - -* is **required** -* type: `string` -* defined in this schema - -### known_false_positives Type - - -`string` - - - - - - -### known_false_positives Example - -```json -"Please vet the lookup created by this baseline search." -``` - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is **required** -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person maintaining this search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person maintaining this search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## modification_date - -The date of the most recent modification to the search - -`modification_date` - -* is **required** -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - -### modification_date Example - -```json -"2019-02-14" -``` - - -## name - -The name of the search that creates the baseline - -`name` - -* is **required** -* type: `string` -* defined in this schema - -### name Type - - -`string` - - - - - - -### name Example - -```json -"Discover DNS records" -``` - - -## original_authors - -A list of the original authors of the search - -`original_authors` - -* is **required** -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person who originally authored the search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person who originally authored the search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## spec_version - -The version of the detection search specification this manifest follows - -`spec_version` - -* is **required** -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - -### spec_version Example - -```json -"2.0" -``` - - -## type - -The type of baseline - -`type` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#type-known-values). - -### type Known Values -| Value | Description | -|-------|-------------| -| `splunk` | | -| `phantom` | | -| `uba` | | - - - -### type Example - -```json -"splunk" -``` - - -## version - -The version of the search - -`version` - -* is **required** -* type: `string` -* defined in this schema - -### version Type - - -`string` - - - - - - -### version Examples - -```json -"1" -``` - -```json -"2" -``` - - - -# Baseline Manifest Definitions - -| Property | Type | Group | -|----------|------|-------| -| [phantom_server](#phantom_server) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [playbook_name](#playbook_name) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [playbook_url](#playbook_url) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [schedule](#schedule) | `object` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/splunk` | -| [search](#search) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/splunk` | -| [sensitivity](#sensitivity) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [severity](#severity) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | - -## phantom_server - -IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname) - -`phantom_server` - -* is optional -* type: `string` -* defined in this schema - -### phantom_server Type - - -`string` - - - - - - -### phantom_server Example - -```json -"automation (hostname)" -``` - - -## playbook_name - -Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment - -`playbook_name` - -* is optional -* type: `string` -* defined in this schema - -### playbook_name Type - - -`string` - - - - - - -### playbook_name Example - -```json -"community/dns_hijack_investigation" -``` - - -## playbook_url - -Url of the playbook on Phantom website. - -`playbook_url` - -* is optional -* type: `string` -* defined in this schema - -### playbook_url Type - - -`string` - - - - - - -### playbook_url Example - -```json -"https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" -``` - - -## schedule - -Various fields to assist in scheduling the search - -`schedule` - -* is optional -* type: `object` -* defined in this schema - -### schedule Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `cron_schedule`| string | Optional | -| `earliest_time`| string | Optional | -| `latest_time`| string | Optional | - - - -#### cron_schedule - -Schedule of the search in cron format - -`cron_schedule` - -* is optional -* type: `string` - -##### cron_schedule Type - - -`string` - - - - - - -##### cron_schedule Example - -```json -0 * * * * -``` - - - - -#### earliest_time - -The earliest time the search should run in Splunk format - -`earliest_time` - -* is optional -* type: `string` - -##### earliest_time Type - - -`string` - - - - - - -##### earliest_time Example - -```json --70m@m -``` - - - - -#### latest_time - -The latest time tes search should run against in Splunk format - -`latest_time` - -* is optional -* type: `string` - -##### latest_time Type - - -`string` - - - - - - -##### latest_time Example - -```json --10m@m -``` - - - - - - - -## search - -The search (in SPL) executed within core Splunk for investgation. - -`search` - -* is optional -* type: `string` -* defined in this schema - -### search Type - - -`string` - - - - - - -### search Example - -```json -"| inputlookup discovered_dns_records.csv | rename answer as discovered_answer | join domain[|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n)" -``` - - -## sensitivity - -TLP colors (White, Green, Amber or Red) - -`sensitivity` - -* is optional -* type: `string` -* defined in this schema - -### sensitivity Type - - -`string` - - - - - - -### sensitivity Example - -```json -"green" -``` - - -## severity - -Severity in phantom (High, Medium, Low) - -`severity` - -* is optional -* type: `string` -* defined in this schema - -### severity Type - - -`string` - - - - - - -### severity Example - -```json -"medium" -``` - diff --git a/docs/detections.spec.json b/docs/detections.spec.json deleted file mode 100644 index 4f4f9250b7..0000000000 --- a/docs/detections.spec.json +++ /dev/null @@ -1,1213 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/detections.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "definitions": { - "phantom": { - "properties": { - "correlation_rule": { - "description": "Various fields to enhance usability in Enterprise Security", - "properties": { - "notable": { - "description": "Various fields associated with creating a notable event", - "properties": { - "nes_fields": { - "description": "A list of suggested fields to be used for notable-event suppression", - "examples": [ - "src" - ], - "type": "string" - }, - "rule_description": { - "description": "Description of the notable event that will display in Incident Review", - "examples": [ - "The table represents a list of DNS records and their responses for recently changed corporate domains." - ], - "type": "string" - }, - "rule_title": { - "description": "Title of the notable event that will display in Incident Review. Add tokenized fieldnames.", - "examples": [ - "DNS record changed on $src$" - ], - "type": "string" - } - }, - "required": [ - "rule_description", - "rule_title", - "nes_fields" - ], - "type": "object" - }, - "risk": { - "description": "Fields associated with assigning risk to objects", - "properties": { - "risk_object": { - "description": "The field to which you are assigning risk", - "examples": [ - "src" - ], - "type": "string" - }, - "risk_object_type": { - "description": "The type of object to which you are assigning risk", - "examples": [ - "system" - ], - "items": { - "enum": [ - "system", - "user", - "other" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "risk_score": { - "description": "Score assigned to risk_object", - "examples": [ - "40" - ], - "type": "integer" - } - }, - "required": [ - "risk_score", - "risk_object", - "risk_object_type" - ], - "type": "object" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "examples": [ - "0 * * * *" - ], - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "examples": [ - "-70m@m" - ], - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run again in Splunk format", - "examples": [ - "-10m@m" - ], - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search that will trigger the Phantom playbook", - "examples": [ - "| sendalert runphantomplaybook" - ], - "type": "string" - }, - "suppress": { - "description": "Fields associated with suppressing the creation of multiple alerts", - "properties": { - "suppress_fields": { - "description": "The fields to base the suppression on", - "examples": [ - "src" - ], - "type": "string" - }, - "suppress_period": { - "description": "The length of time the suppression should be in effect", - "examples": [ - "28800s" - ], - "type": "string" - } - }, - "required": [ - "suppress_fields", - "suppress_period" - ], - "type": "object" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - }, - "phantom_server": { - "description": "IP address and username of the Phantom server. Currently, we ship these values as automation (hostname) and encourage users to modify them according to their environments: for example, automation (hostname)", - "examples": [ - "automation (hostname)" - ], - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on the Phantom community repository on github, with underscores, and appended with \"community/.\" The playbooks are hosted on https://github.com/phantomcyber/playbooks. For example: community/simple_network_enrichment", - "examples": [ - "community/dns_hijack_detect_playbook" - ], - "type": "string" - }, - "playbook_url": { - "description": "URL of the playbook on the Phantom website", - "examples": [ - "https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" - ], - "type": "string" - }, - "sensitivity": { - "description": "TLP colors (White, Green, Amber, Red)", - "examples": [ - "green" - ], - "type": "string" - }, - "severity": { - "description": "Severity in Phantom (High, Medium, Low)", - "examples": [ - "high" - ], - "type": "string" - } - }, - "required": [ - "correlation_rule", - "playbook_name", - "phantom_server", - "playbook_url" - ], - "type": "object" - }, - "splunk": { - "correlation_rule": { - "description": "Various fields to enhance usability in Enterprise Security", - "properties": { - "notable": { - "description": "Various fields associated with creating a notable event", - "properties": { - "nes_fields": { - "description": "A list of suggested fields to be used for notable-event suppression", - "type": "string" - }, - "rule_description": { - "description": "Description of the notable event that will display in Incident Review", - "type": "string" - }, - "rule_title": { - "description": "Title of the notable event that will display in Incident Review", - "type": "string" - } - }, - "required": [ - "rule_description", - "rule_title", - "nes_fields" - ], - "type": "object" - }, - "risk": { - "description": "Fields associated with assigning risk to objects", - "properties": { - "risk_object": { - "description": "TThe field to which you are assigning risk", - "type": "string" - }, - "risk_object_type": { - "description": "The type of object to which you are assigning risk", - "items": { - "enum": [ - "system", - "user", - "other" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "risk_score": { - "description": "Score assigned to risk_object", - "type": "integer" - } - }, - "required": [ - "risk_score", - "risk_object", - "risk_object_type" - ], - "type": "object" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run again in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search that will trigger the Phantom playbook", - "type": "string" - }, - "suppress": { - "description": "Fields associated with suppressing the creation of multiple alerts", - "properties": { - "suppress_fields": { - "description": "The fields to base the suppression on", - "type": "string" - }, - "suppress_period": { - "description": "The length of time the suppression should be in effect", - "type": "string" - } - }, - "required": [ - "suppress_fields", - "suppress_period" - ], - "type": "object" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - }, - "type": "object" - }, - "uba": { - "properties": { - "correlation_rule": { - "description": "Various fields to enhance usability in Enterprise Security", - "properties": { - "notable": { - "description": "Various fields associated with creating a notable event", - "properties": { - "nes_fields": { - "description": "A list of suggested fields to be used for notable-event suppression", - "type": "string" - }, - "rule_description": { - "description": "Description of the notable event that will display in Incident Review", - "type": "string" - }, - "rule_title": { - "description": "Title of the notable event that will display in Incident Review", - "type": "string" - } - }, - "required": [ - "rule_description", - "rule_title", - "nes_fields" - ], - "type": "object" - }, - "risk": { - "description": "Fields associated with assigning risk to objects", - "properties": { - "risk_object": { - "description": "The field to which you are assigning risk", - "type": "string" - }, - "risk_object_type": { - "description": "The type of object to which you are assigning risk", - "items": { - "enum": [ - "system", - "user", - "other" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "risk_score": { - "description": "Score assigned to risk_object", - "type": "integer" - } - }, - "required": [ - "risk_score", - "risk_object", - "risk_object_type" - ], - "type": "object" - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run against in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search (in SPL) executed within Splunk Enterprise", - "type": "string" - }, - "suppress": { - "description": "Fields associated with suppressing the creation of multiple alerts", - "properties": { - "suppress_fields": { - "description": "The fields to base the suppression on", - "type": "string" - }, - "suppress_period": { - "description": "The length of time the suppression should be in effect", - "type": "string" - } - }, - "required": [ - "suppress_fields", - "suppress_period" - ], - "type": "object" - } - }, - "required": [ - "search", - "schedule" - ], - "type": "object" - }, - "event_type": { - "description": "An anomaly or threat", - "examples": [ - "anomaly" - ], - "type": "string" - }, - "model": { - "description": "The name of the Splunk UBA model that detected the anomaly.", - "examples": [ - "UBA Model" - ], - "type": "string" - }, - "model_version": { - "description": "URL of the playbook on the Phantom website", - "examples": [ - "2.0" - ], - "type": "string" - }, - "threat_category": { - "description": "The category of a threat in Splunk UBA", - "examples": [ - "Malware" - ], - "type": "string" - } - }, - "required": [ - "correlation_rule", - "event_type", - "model", - "model_version", - "threat_category" - ], - "type": "object" - } - }, - "description": "An object that defines the parameters for detecting things using various Splunk capabilities", - "properties": { - "asset_type": { - "description": "Designates the type of asset being investigated", - "examples": [ - "Endpoint" - ], - "type": "string" - }, - "baselines": { - "description": "An array of the baseline objects to execute before the detection ", - "items": { - "properties": { - "id": { - "description": "UUID of the baseline object", - "examples": [ - "c096f721-8842-42ce-bfc7-74bd8c72b7c3" - ], - "type": "string" - }, - "name": { - "description": "Name of the baseline object", - "examples": [ - "Discover DNS records" - ], - "type": "string" - }, - "type": { - "description": "Type of baseline to execute", - "enum": [ - "phantom", - "splunk", - "uba" - ], - "examples": [ - "splunk" - ], - "type": "string" - } - }, - "required": [ - "type", - "name", - "id" - ], - "type": "object" - }, - "type": "array" - }, - "confidence": { - "description": "Confidence that detected behavior is malicious", - "enum": [ - "high", - "medium", - "low" - ], - "examples": [ - "high" - ] - }, - "creation_date": { - "description": "The date the story manifest was created", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "data_metadata": { - "description": "Information about the data being ingested", - "properties": { - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "examples": [ - "wineventlog" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_models": { - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "examples": [ - "DNS" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "examples": [ - "stream:dns" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "OSquery" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "required": [ - "data_source", - "providing_technologies" - ], - "type": "object" - }, - "description": { - "description": "A description of what the detection is designed to find", - "examples": [ - "The search takes the DNS records and the results of the discovered_dns_records lookup and determines whether any records have changed. It does this by searching DNS response from the Network_Resolution data model within the last day." - ], - "type": "string" - }, - "detect": { - "anyOf": [ - { - "required": [ - "splunk" - ] - }, - { - "required": [ - "phantom" - ] - }, - { - "required": [ - "uba" - ] - } - ], - "properties": { - "phantom": { - "$ref": "#/definitions/phantom" - }, - "splunk": { - "$ref": "#/definitions/splunk" - }, - "uba": { - "$ref": "#/definitions/uba" - } - }, - "type": "object" - }, - "eli5": { - "description": "Explain it Like I'm 5: A detailed description of the SPL of the search, written in a style that can be understood by a future Splunk expert", - "examples": [ - "Using a lookup \"discover_dns_records\" generated by support search \"Discover DNS records,\" we check previous network traffic and make sure the responses have not changed." - ], - "type": "string" - }, - "entities": { - "description": "A list of entities outputted by the search", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "query" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion of how to implement this search, including what needs to be ingested, the config files modified, and suggested per-site modifications", - "examples": [], - "type": "string" - }, - "id": { - "description": "The unique identifier for the detection", - "examples": [ - "To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that the \"discover_dns_record\" lookup table be populated by the included support search \"Discover DNS record.\"" - ], - "type": "string" - }, - "investigations": { - "description": "An array of the investigation objects to execute on the detection results ", - "items": { - "properties": { - "id": { - "description": "UUID of the investigation object", - "examples": [ - "bc11a8cf-35e7-4bb2-8140-e756cc06fd72" - ], - "type": "string" - }, - "name": { - "description": "Name of the investigation object ", - "examples": [ - "Get DNS Server History for a Host" - ], - "type": "string" - }, - "type": { - "description": "Type of investigation object", - "enum": [ - "phantom", - "splunk", - "uba" - ], - "examples": [ - "splunk" - ], - "type": "string" - } - }, - "required": [ - "type", - "name", - "id" - ], - "type": "object" - }, - "type": "array" - }, - "known_false_positives": { - "description": "Scenarios in which detected behavior is benign, coupled with suggestions on how to verify the behavior", - "examples": [ - "Legitimate DNS changes can be detected in this search. Investigate, verify, and update the list of provided current answers for the domains in question, as appropriate." - ], - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story", - "items": { - "properties": { - "company": { - "description": "Company associated with the person maintaining this search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "mappings": { - "description": "Mappings to various industry standards and frameworks", - "properties": { - "cis20": { - "description": "A list of critical security controls this search helps you implement", - "examples": [ - "CIS 12" - ], - "items": { - "enum": [ - "CIS 1", - "CIS 2", - "CIS 3", - "CIS 4", - "CIS 5", - "CIS 6", - "CIS 7", - "CIS 8", - "CIS 9", - "CIS 10", - "CIS 11", - "CIS 12", - "CIS 13", - "CIS 14", - "CIS 15", - "CIS 16", - "CIS 17", - "CIS 18", - "CIS 19", - "CIS 20" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "emoji": { - "description": "A list of security emojis that will help UBA understand this alert as an external alarm", - "examples": [ - "EndPoint" - ], - "items": { - "enum": [ - "EndPoint", - "AD", - "Firewall", - "ApplicationLog", - "IPS", - "CloudData", - "Correlation", - "Printer", - "Badge" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "kill_chain_phases": { - "description": "A list of kill-chain phases to which the search applies", - "examples": [ - "Reconnaissance" - ], - "items": { - "enum": [ - "Reconnaissance", - "Weaponization", - "Delivery", - "Exploitation", - "Installation", - "Command and Control", - "Actions on Objectives" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "mitre_attack": { - "description": "A list of the techniques and tactics identified by the search", - "examples": [ - "Defense Evasion", - "Initial Access" - ], - "items": { - "enum": [ - "Initial Access", - "Execution", - "Persistence", - "Spearphishing Attachment", - "Spearphishing Link", - "Privilege Escalation", - "Defense Evasion", - "Credential Access", - "Discovery", - "Lateral Movement", - "Collection", - "Exfiltration", - "Command and Control", - "Command and Control Protocol", - "Commonly Used Port", - "Custom Cryptographic Protocol", - "DLL Injection", - "DLL Search Order Hijacking", - "DLL Side-Loading", - "Data Compressed", - "Data Encrypted", - "Data Obfuscation", - "Data Staged", - "Data Transfer Size Limits", - "Data from Local System", - "Data from Network Shared Drive", - "Data from Removable Media", - "Disabling Security Tools", - "Email Collection", - "Execution through API", - "Exfiltration Over Alternative Protocol", - "Exfiltration Over Command and Control Channel", - "Exfiltration Over Other Network Medium", - "Exfiltration Over Physical Medium", - "Exploitation of Vulnerability", - "Fallback Channels", - "File Deletion", - "File System Logical Offsets", - "File System Permissions Weakness", - "File and Directory Discovery", - "Graphical User Interface", - "Hypervisor", - "Indicator Blocking", - "Indicator Removal from Tools", - "Indicator Removal on Host", - "Input Capture", - "InstallUtil", - "Legitimate Credentials", - "Local Network Configuration Discovery", - "Local Network Connections Discovery", - "Local Port Monitor", - "Logon Scripts", - "MSBuild", - "Masquerading", - "Modify Existing Service", - "Modify Registry", - "Multi-Stage Channels", - "Multiband Communication", - "Multilayer Encryption", - "NTFS Extended Attributes", - "Network Service Scanning", - "Network Share Connection Removal", - "Network Sniffing", - "New Service", - "Obfuscated Files or Information", - "Pass the Hash", - "Pass the Ticket", - "Path Interception", - "Peripheral Device Discovery", - "Permission Groups Discovery", - "PowerShell", - "Process Discovery", - "Process Hollowing", - "Query Registry", - "Redundant Access", - "Registry Run Keys / Start Folder", - "Regsvcs/Regasm", - "Regsvr32", - "Remote Desktop Protocol", - "Create Account", - "Remote File Copy", - "Remote Services", - "Remote System Discovery", - "Replication Through Removable Media", - "Rootkit", - "Rundll32", - "Scheduled Task", - "Scheduled Transfer", - "Screen Capture", - "Scripting", - "Security Software Discovery", - "Security Support Provider", - "Service Execution", - "Service Registry Permissions Weakness", - "Shared Webroot", - "Shortcut Modification", - "Software Packing", - "Standard Application Layer Protocol", - "Standard Cryptographic Protocol", - "Standard Non-Application Layer Protocol", - "System Information Discovery", - "System Owner/User Discovery", - "System Service Discovery", - "System Time Discovery", - "Taint Shared Content", - "Third-party Software", - "Timestomp", - "Two-Factor Authentication Interception", - "Uncommonly Used Port", - "Video Capture", - "Valid Accounts", - "Web Service", - "Web Shell", - "Windows Admin Shares", - "Windows Management Instrumentation Event Subscription", - "Windows Management Instrumentation", - "Windows Remote Management", - "Winlogon Helper DLL", - "Exploitation for Privilege Escalation" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "nist": { - "description": "A list of the NIST controls the search helps you implement", - "examples": [ - "ID.AM", - "PR.PT" - ], - "items": { - "enum": [ - "ID.AM", - "ID.RA", - "PR.DS", - "PR.IP", - "PR.AC", - "PR.PT", - "PR.AT", - "PR.MA", - "DE.CM", - "DE.DP", - "DE.AE", - "RS.MI", - "RS.AN", - "RS.RP", - "RS.IM", - "RS.CO", - "RC.IM", - "RC.CO" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "type": "object" - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "examples": [ - "2019-02-14" - ], - "type": "string" - }, - "name": { - "description": "The name of the detection", - "examples": [ - "DNS record changed" - ], - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "items": { - "properties": { - "company": { - "description": "Company associated with the person who originally authored the search", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the search", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the search", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "references": { - "description": "A list of URLs that give more information about the search", - "examples": [ - "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "responses": { - "description": "An array of the response objects to exectute on the detection results", - "items": { - "properties": { - "id": { - "description": "UUID of the response object", - "examples": [ - "1169w17b-ef78-4b59-aae8-5369073014e1" - ], - "type": "string" - }, - "name": { - "description": "Name of response object", - "examples": [ - "DNS hijack reponse" - ], - "type": "string" - }, - "type": { - "description": "Type of baseline to execute", - "enum": [ - "phantom", - "splunk", - "uba" - ], - "examples": [ - "phantom" - ], - "type": "string" - } - }, - "required": [ - "type", - "name", - "id" - ], - "type": "object" - }, - "type": "array" - }, - "security_domain": { - "description": "The high-level security area to which the search belongs", - "enum": [ - "access", - "endpoint", - "network", - "threat" - ], - "examples": [ - "endpoint" - ] - }, - "spec_version": { - "description": "The version of the detection specification this manifest follows", - "examples": [ - "2.0" - ], - "type": "integer" - }, - "type": { - "description": "The type of detection", - "enum": [ - "uba", - "splunk", - "phantom" - ], - "examples": [ - "phantom" - ] - }, - "version": { - "description": "The version of the detection", - "examples": [ - "1" - ], - "type": "string" - } - }, - "required": [ - "confidence", - "creation_date", - "data_metadata", - "eli5", - "how_to_implement", - "known_false_positives", - "maintainers", - "modification_date", - "original_authors", - "description", - "id", - "type", - "security_domain", - "version", - "detect" - ], - "title": "Detection Manifest", - "type": "object" -} diff --git a/docs/detections.spec.md b/docs/detections.spec.md deleted file mode 100644 index 6fdfd19620..0000000000 --- a/docs/detections.spec.md +++ /dev/null @@ -1,2855 +0,0 @@ - -# Detection Manifest Schema - -``` -https://api.splunkresearch.com/schemas/detections.json -``` - -A object that defines the parameters for detecting things using various Splunk capabilities - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | Yes | Experimental | No | Forbidden | Permitted | | - -# Detection Manifest Properties - -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [asset_type](#asset_type) | `string` | Optional | No | Detection Manifest (this schema) | -| [baselines](#baselines) | `object[]` | Optional | No | Detection Manifest (this schema) | -| [confidence](#confidence) | `enum` | **Required** | No | Detection Manifest (this schema) | -| [creation_date](#creation_date) | `string` | **Required** | No | Detection Manifest (this schema) | -| [data_metadata](#data_metadata) | `object` | **Required** | No | Detection Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Detection Manifest (this schema) | -| [detect](#detect) | `object` | **Required** | No | Detection Manifest (this schema) | -| [eli5](#eli5) | `string` | **Required** | No | Detection Manifest (this schema) | -| [entities](#entities) | `enum[]` | Optional | No | Detection Manifest (this schema) | -| [how_to_implement](#how_to_implement) | `string` | **Required** | No | Detection Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Detection Manifest (this schema) | -| [investigations](#investigations) | `object[]` | Optional | No | Detection Manifest (this schema) | -| [known_false_positives](#known_false_positives) | `string` | **Required** | No | Detection Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | **Required** | No | Detection Manifest (this schema) | -| [mappings](#mappings) | `object` | Optional | No | Detection Manifest (this schema) | -| [modification_date](#modification_date) | `string` | **Required** | No | Detection Manifest (this schema) | -| [name](#name) | `string` | Optional | No | Detection Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | **Required** | No | Detection Manifest (this schema) | -| [references](#references) | `string[]` | Optional | No | Detection Manifest (this schema) | -| [responses](#responses) | `object[]` | Optional | No | Detection Manifest (this schema) | -| [security_domain](#security_domain) | `enum` | **Required** | No | Detection Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | Optional | No | Detection Manifest (this schema) | -| [type](#type) | `enum` | **Required** | No | Detection Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Detection Manifest (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## asset_type - -Designates the type of asset being investigated - -`asset_type` - -* is optional -* type: `string` -* defined in this schema - -### asset_type Type - - -`string` - - - - - - -### asset_type Example - -```json -"Endpoint" -``` - - -## baselines - -An array of the baseline objects to exectute before the detection - -`baselines` - -* is optional -* type: `object[]` -* defined in this schema - -### baselines Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `id`| string | **Required** | -| `name`| string | **Required** | -| `type`| string | **Required** | - - - -#### id - -UUID of the baseline object - -`id` - -* is **required** -* type: `string` - -##### id Type - - -`string` - - - - - - -##### id Example - -```json -c096f721-8842-42ce-bfc7-74bd8c72b7c3 -``` - - - - -#### name - -name of baseline object - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Discover DNS records -``` - - - - -#### type - -Type of baseline to execute - -`type` - -* is **required** -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#baselines-known-values). - -##### type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - -##### type Example - -```json -splunk -``` - - - - - - - - - -## confidence - -Confidence that detected behavior is malicious - -`confidence` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#confidence-known-values). - -### confidence Known Values -| Value | Description | -|-------|-------------| -| `high` | | -| `medium` | | -| `low` | | - - - -### confidence Example - -```json -"high" -``` - - -## creation_date - -The date the story manifest was created - -`creation_date` - -* is **required** -* type: `string` -* defined in this schema - -### creation_date Type - - -`string` - - - - - - -### creation_date Example - -```json -"2019-02-14" -``` - - -## data_metadata - -Information about the date being ingested - -`data_metadata` - -* is **required** -* type: `object` -* defined in this schema - -### data_metadata Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `data_eventtypes`| array | Optional | -| `data_models`| array | Optional | -| `data_source`| array | **Required** | -| `data_sourcetypes`| array | Optional | -| `providing_technologies`| array | **Required** | - - - -#### data_eventtypes - -A list of eventtypes, if any, used by this search - -`data_eventtypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_eventtypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_eventtypes Example - -```json -wineventlog -``` - - - - -#### data_models - -A list of data models, if any, used by this search - -`data_models` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### data_models Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ], - "simpletype": "`enum`", - "meta:enum": { - "Alerts": "", - "Application_State": "", - "Authentication": "", - "Certificates": "", - "Change_Analysis": "", - "Change": "", - "Cloud_Infrastructure": "", - "Malware": "", - "Email": "", - "Identity_Management": "", - "Network_Resolution": "", - "Network_Traffic": "", - "Vulnerabilities": "", - "Web": "", - "Network_Sessions": "", - "Updates": "", - "Risk": "", - "Endpoint": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### data_models Example - -```json -Network_Resolution -``` - - - - -#### data_source - -A high-level description of the type of data needed for this search to complete - -`data_source` - -* is **required** -* type: `string[]`* at least `0` items in the array - - -##### data_source Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_source Example - -```json -DNS -``` - - - - -#### data_sourcetypes - -The list of sourcetypes, if any, used by this search - -`data_sourcetypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_sourcetypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_sourcetypes Example - -```json -stream:dns -``` - - - - -#### providing_technologies - -A list of technologies that provide this data - -`providing_technologies` - -* is **required** -* type: `enum[]`* at least `0` items in the array - - -##### providing_technologies Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "OSquery" - ], - "simpletype": "`enum`", - "meta:enum": { - "Apache": "", - "AWS": "", - "Bro": "", - "Microsoft Windows": "", - "Linux": "", - "macOS": "", - "Netbackup": "", - "Splunk Enterprise": "", - "Splunk Enterprise Security": "", - "Splunk Stream": "", - "Active Directory": "", - "Bluecoat": "", - "Carbon Black Response": "", - "Carbon Black Protect": "", - "CrowdStrike Falcon": "", - "Microsoft Exchange": "", - "Nessus": "", - "Palo Alto Firewall": "", - "Qualys": "", - "Sysmon": "", - "Tanium": "", - "Ziften": "", - "OSquery": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### providing_technologies Example - -```json -Bro -``` - - - - - - - -## description - -A description of what the detection is designed to find - -`description` - -* is **required** -* type: `string` -* defined in this schema - -### description Type - - -`string` - - - - - - -### description Example - -```json -"The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day." -``` - - -## detect - - -`detect` - -* is **required** -* type: `object` -* defined in this schema - -### detect Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `phantom`| | Optional | -| `splunk`| | Optional | -| `uba`| | Optional | - - - -#### phantom - - -`phantom` - -* is optional -* type: reference - -##### phantom Type - - -* []() – `#/definitions/phantom` - - - - - - - -#### splunk - - -`splunk` - -* is optional -* type: reference - -##### splunk Type - - -* []() – `#/definitions/splunk` - - - - - - - -#### uba - - -`uba` - -* is optional -* type: reference - -##### uba Type - - -* []() – `#/definitions/uba` - - - - - - - - - - -## eli5 - -Explain it like I am 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert - -`eli5` - -* is **required** -* type: `string` -* defined in this schema - -### eli5 Type - - -`string` - - - - - - -### eli5 Example - -```json -"Using a lookup `discover_dns_records` generated by support search \"Discover DNS records\" we check previous network traffic and make sure the responses have not changed." -``` - - -## entities - -A list of entities that is outputed by the search... - -`entities` - -* is optional -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### entities Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of entities that is outputed by the search...", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user", - "query" - ], - "simpletype": "`enum`", - "meta:enum": { - "accessKeyId": "", - "arn": "", - "awsRegion": "", - "bucketName": "", - "City": "", - "Country": "", - "dest_port": "", - "dest": "", - "event_id": "", - "instanceId": "", - "message_id": "", - "networkAclId": "", - "process_name": "", - "process": "", - "recipient": "", - "Region": "", - "resourceId": "", - "session_id": "", - "src_ip": "", - "src_mac": "", - "src_user": "", - "src": "", - "user": "", - "query": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -### entities Examples - -```json -"dest" -``` - -```json -"user" -``` - - - -## how_to_implement - -A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications - -`how_to_implement` - -* is **required** -* type: `string` -* defined in this schema - -### how_to_implement Type - - -`string` - - - - - - - -## id - -The unique identifier for the detection - -`id` - -* is **required** -* type: `string` -* defined in this schema - -### id Type - - -`string` - - - - - - -### id Example - -```json -"To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search \"Discover DNS record\"." -``` - - -## investigations - -An array of the investigation objects to exectute on the detection results - -`investigations` - -* is optional -* type: `object[]` -* defined in this schema - -### investigations Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `id`| string | **Required** | -| `name`| string | **Required** | -| `type`| string | **Required** | - - - -#### id - -UUID of the investigation object - -`id` - -* is **required** -* type: `string` - -##### id Type - - -`string` - - - - - - -##### id Example - -```json -bc11a8cf-35e7-4bb2-8140-e756cc06fd72 -``` - - - - -#### name - -Name of investigation object - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Get DNS Server History for a host -``` - - - - -#### type - -Type of investigation object - -`type` - -* is **required** -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#investigations-known-values). - -##### type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - -##### type Example - -```json -splunk -``` - - - - - - - - - -## known_false_positives - -Scenarios in which detected behavior is benig, coupled with suggestions on how to verify the behavior - -`known_false_positives` - -* is **required** -* type: `string` -* defined in this schema - -### known_false_positives Type - - -`string` - - - - - - -### known_false_positives Example - -```json -"Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate." -``` - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is **required** -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person maintaining this search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person maintaining this search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## mappings - -Mappings to various industry standards and frameworks - -`mappings` - -* is optional -* type: `object` -* defined in this schema - -### mappings Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `cis20`| array | Optional | -| `emoji`| array | Optional | -| `kill_chain_phases`| array | Optional | -| `mitre_attack`| array | Optional | -| `nist`| array | Optional | - - - -#### cis20 - -A list of critical security controls this search helps you implement - -`cis20` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### cis20 Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of critical security controls this search helps you implement", - "examples": [ - "CIS 12" - ], - "items": { - "enum": [ - "CIS 1", - "CIS 2", - "CIS 3", - "CIS 4", - "CIS 5", - "CIS 6", - "CIS 7", - "CIS 8", - "CIS 9", - "CIS 10", - "CIS 11", - "CIS 12", - "CIS 13", - "CIS 14", - "CIS 15", - "CIS 16", - "CIS 17", - "CIS 18", - "CIS 19", - "CIS 20" - ], - "simpletype": "`enum`", - "meta:enum": { - "CIS 1": "", - "CIS 2": "", - "CIS 3": "", - "CIS 4": "", - "CIS 5": "", - "CIS 6": "", - "CIS 7": "", - "CIS 8": "", - "CIS 9": "", - "CIS 10": "", - "CIS 11": "", - "CIS 12": "", - "CIS 13": "", - "CIS 14": "", - "CIS 15": "", - "CIS 16": "", - "CIS 17": "", - "CIS 18": "", - "CIS 19": "", - "CIS 20": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### cis20 Example - -```json -CIS 12 -``` - - - - -#### emoji - -A list of security emojis that will help UBA understand this alert as an external alarm - -`emoji` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### emoji Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of security emojis that will help UBA understand this alert as an external alarm", - "examples": [ - "EndPoint" - ], - "items": { - "enum": [ - "EndPoint", - "AD", - "Firewall", - "ApplicationLog", - "IPS", - "CloudData", - "Correlation", - "Printer", - "Badge" - ], - "simpletype": "`enum`", - "meta:enum": { - "EndPoint": "", - "AD": "", - "Firewall": "", - "ApplicationLog": "", - "IPS": "", - "CloudData": "", - "Correlation": "", - "Printer": "", - "Badge": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### emoji Example - -```json -EndPoint -``` - - - - -#### kill_chain_phases - -A list of kill-chain phases to which the search applies - -`kill_chain_phases` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### kill_chain_phases Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of kill-chain phases to which the search applies", - "examples": [ - "Reconnaissance" - ], - "items": { - "enum": [ - "Reconnaissance", - "Weaponization", - "Delivery", - "Exploitation", - "Installation", - "Command and Control", - "Actions on Objectives" - ], - "simpletype": "`enum`", - "meta:enum": { - "Reconnaissance": "", - "Weaponization": "", - "Delivery": "", - "Exploitation": "", - "Installation": "", - "Command and Control": "", - "Actions on Objectives": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### kill_chain_phases Example - -```json -Reconnaissance -``` - - - - -#### mitre_attack - -A list of the techniques and tactics identified by the search - -`mitre_attack` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### mitre_attack Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of the techniques and tactics identified by the search", - "examples": [ - "Defense Evasion", - "Initial Access" - ], - "items": { - "enum": [ - "Initial Access", - "Execution", - "Persistence", - "Spearphishing Attachment", - "Spearphishing Link", - "Privilege Escalation", - "Defense Evasion", - "Credential Access", - "Discovery", - "Lateral Movement", - "Collection", - "Exfiltration", - "Command and Control", - "Command and Control Protocol", - "Commonly Used Port", - "Custom Cryptographic Protocol", - "DLL Injection", - "DLL Search Order Hijacking", - "DLL Side-Loading", - "Data Compressed", - "Data Encrypted", - "Data Obfuscation", - "Data Staged", - "Data Transfer Size Limits", - "Data from Local System", - "Data from Network Shared Drive", - "Data from Removable Media", - "Disabling Security Tools", - "Email Collection", - "Execution through API", - "Exfiltration Over Alternative Protocol", - "Exfiltration Over Command and Control Channel", - "Exfiltration Over Other Network Medium", - "Exfiltration Over Physical Medium", - "Exploitation of Vulnerability", - "Fallback Channels", - "File Deletion", - "File System Logical Offsets", - "File System Permissions Weakness", - "File and Directory Discovery", - "Graphical User Interface", - "Hypervisor", - "Indicator Blocking", - "Indicator Removal from Tools", - "Indicator Removal on Host", - "Input Capture", - "InstallUtil", - "Legitimate Credentials", - "Local Network Configuration Discovery", - "Local Network Connections Discovery", - "Local Port Monitor", - "Logon Scripts", - "MSBuild", - "Masquerading", - "Modify Existing Service", - "Modify Registry", - "Multi-Stage Channels", - "Multiband Communication", - "Multilayer Encryption", - "NTFS Extended Attributes", - "Network Service Scanning", - "Network Share Connection Removal", - "Network Sniffing", - "New Service", - "Obfuscated Files or Information", - "Pass the Hash", - "Pass the Ticket", - "Path Interception", - "Peripheral Device Discovery", - "Permission Groups Discovery", - "PowerShell", - "Process Discovery", - "Process Hollowing", - "Query Registry", - "Redundant Access", - "Registry Run Keys / Start Folder", - "Regsvcs/Regasm", - "Regsvr32", - "Remote Desktop Protocol", - "Create Account", - "Remote File Copy", - "Remote Services", - "Remote System Discovery", - "Replication Through Removable Media", - "Rootkit", - "Rundll32", - "Scheduled Task", - "Scheduled Transfer", - "Screen Capture", - "Scripting", - "Security Software Discovery", - "Security Support Provider", - "Service Execution", - "Service Registry Permissions Weakness", - "Shared Webroot", - "Shortcut Modification", - "Software Packing", - "Standard Application Layer Protocol", - "Standard Cryptographic Protocol", - "Standard Non-Application Layer Protocol", - "System Information Discovery", - "System Owner/User Discovery", - "System Service Discovery", - "System Time Discovery", - "Taint Shared Content", - "Third-party Software", - "Timestomp", - "Two-Factor Authentication Interception", - "Uncommonly Used Port", - "Video Capture", - "Valid Accounts", - "Web Service", - "Web Shell", - "Windows Admin Shares", - "Windows Management Instrumentation Event Subscription", - "Windows Management Instrumentation", - "Windows Remote Management", - "Winlogon Helper DLL", - "Exploitation for Privilege Escalation" - ], - "simpletype": "`enum`", - "meta:enum": { - "Initial Access": "", - "Execution": "", - "Persistence": "", - "Spearphishing Attachment": "", - "Spearphishing Link": "", - "Privilege Escalation": "", - "Defense Evasion": "", - "Credential Access": "", - "Discovery": "", - "Lateral Movement": "", - "Collection": "", - "Exfiltration": "", - "Command and Control": "", - "Command and Control Protocol": "", - "Commonly Used Port": "", - "Custom Cryptographic Protocol": "", - "DLL Injection": "", - "DLL Search Order Hijacking": "", - "DLL Side-Loading": "", - "Data Compressed": "", - "Data Encrypted": "", - "Data Obfuscation": "", - "Data Staged": "", - "Data Transfer Size Limits": "", - "Data from Local System": "", - "Data from Network Shared Drive": "", - "Data from Removable Media": "", - "Disabling Security Tools": "", - "Email Collection": "", - "Execution through API": "", - "Exfiltration Over Alternative Protocol": "", - "Exfiltration Over Command and Control Channel": "", - "Exfiltration Over Other Network Medium": "", - "Exfiltration Over Physical Medium": "", - "Exploitation of Vulnerability": "", - "Fallback Channels": "", - "File Deletion": "", - "File System Logical Offsets": "", - "File System Permissions Weakness": "", - "File and Directory Discovery": "", - "Graphical User Interface": "", - "Hypervisor": "", - "Indicator Blocking": "", - "Indicator Removal from Tools": "", - "Indicator Removal on Host": "", - "Input Capture": "", - "InstallUtil": "", - "Legitimate Credentials": "", - "Local Network Configuration Discovery": "", - "Local Network Connections Discovery": "", - "Local Port Monitor": "", - "Logon Scripts": "", - "MSBuild": "", - "Masquerading": "", - "Modify Existing Service": "", - "Modify Registry": "", - "Multi-Stage Channels": "", - "Multiband Communication": "", - "Multilayer Encryption": "", - "NTFS Extended Attributes": "", - "Network Service Scanning": "", - "Network Share Connection Removal": "", - "Network Sniffing": "", - "New Service": "", - "Obfuscated Files or Information": "", - "Pass the Hash": "", - "Pass the Ticket": "", - "Path Interception": "", - "Peripheral Device Discovery": "", - "Permission Groups Discovery": "", - "PowerShell": "", - "Process Discovery": "", - "Process Hollowing": "", - "Query Registry": "", - "Redundant Access": "", - "Registry Run Keys / Start Folder": "", - "Regsvcs/Regasm": "", - "Regsvr32": "", - "Remote Desktop Protocol": "", - "Create Account": "", - "Remote File Copy": "", - "Remote Services": "", - "Remote System Discovery": "", - "Replication Through Removable Media": "", - "Rootkit": "", - "Rundll32": "", - "Scheduled Task": "", - "Scheduled Transfer": "", - "Screen Capture": "", - "Scripting": "", - "Security Software Discovery": "", - "Security Support Provider": "", - "Service Execution": "", - "Service Registry Permissions Weakness": "", - "Shared Webroot": "", - "Shortcut Modification": "", - "Software Packing": "", - "Standard Application Layer Protocol": "", - "Standard Cryptographic Protocol": "", - "Standard Non-Application Layer Protocol": "", - "System Information Discovery": "", - "System Owner/User Discovery": "", - "System Service Discovery": "", - "System Time Discovery": "", - "Taint Shared Content": "", - "Third-party Software": "", - "Timestomp": "", - "Two-Factor Authentication Interception": "", - "Uncommonly Used Port": "", - "Video Capture": "", - "Valid Accounts": "", - "Web Service": "", - "Web Shell": "", - "Windows Admin Shares": "", - "Windows Management Instrumentation Event Subscription": "", - "Windows Management Instrumentation": "", - "Windows Remote Management": "", - "Winlogon Helper DLL": "", - "Exploitation for Privilege Escalation": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### mitre_attack Examples - -```json -Defense Evasion -``` - -```json -Initial Access -``` - - - - - -#### nist - -A list of the NIST controls the search helps you implement - -`nist` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### nist Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of the NIST controls the search helps you implement", - "examples": [ - "ID.AM", - "PR.PT" - ], - "items": { - "enum": [ - "ID.AM", - "ID.RA", - "PR.DS", - "PR.IP", - "PR.AC", - "PR.PT", - "PR.AT", - "PR.MA", - "DE.CM", - "DE.DP", - "DE.AE", - "RS.MI", - "RS.AN", - "RS.RP", - "RS.IM", - "RS.CO", - "RC.IM", - "RC.CO" - ], - "simpletype": "`enum`", - "meta:enum": { - "ID.AM": "", - "ID.RA": "", - "PR.DS": "", - "PR.IP": "", - "PR.AC": "", - "PR.PT": "", - "PR.AT": "", - "PR.MA": "", - "DE.CM": "", - "DE.DP": "", - "DE.AE": "", - "RS.MI": "", - "RS.AN": "", - "RS.RP": "", - "RS.IM": "", - "RS.CO": "", - "RC.IM": "", - "RC.CO": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### nist Examples - -```json -ID.AM -``` - -```json -PR.PT -``` - - - - - - - - -## modification_date - -The date of the most recent modification to the search - -`modification_date` - -* is **required** -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - -### modification_date Example - -```json -"2019-02-14" -``` - - -## name - -The name of the detection - -`name` - -* is optional -* type: `string` -* defined in this schema - -### name Type - - -`string` - - - - - - -### name Example - -```json -"DNS record changed" -``` - - -## original_authors - -A list of the original authors of the search - -`original_authors` - -* is **required** -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person who originally authored the search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person who originally authored the search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## references - -A list of URLs that give more information about the search - -`references` - -* is optional -* type: `string[]` -* at least `0` items in the array -* defined in this schema - -### references Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -### references Example - -```json -"https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" -``` - - -## responses - -An array of the response objects to exectute on the detection results - -`responses` - -* is optional -* type: `object[]` -* defined in this schema - -### responses Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `id`| string | **Required** | -| `name`| string | **Required** | -| `type`| string | **Required** | - - - -#### id - -UUID of the Respose object - -`id` - -* is **required** -* type: `string` - -##### id Type - - -`string` - - - - - - -##### id Example - -```json -1169w17b-ef78-4b59-aae8-5369073014e1 -``` - - - - -#### name - -Name of Response Object - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -DNS Hijack Reponse -``` - - - - -#### type - -Type of baseline to execute - -`type` - -* is **required** -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#responses-known-values). - -##### type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - -##### type Example - -```json -phantom -``` - - - - - - - - - -## security_domain - -The high-level security area to which the search belongs - -`security_domain` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#security_domain-known-values). - -### security_domain Known Values -| Value | Description | -|-------|-------------| -| `access` | | -| `endpoint` | | -| `network` | | -| `threat` | | - - - -### security_domain Example - -```json -"endpoint" -``` - - -## spec_version - -The version of the detection specification this manifest follows - -`spec_version` - -* is optional -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - -### spec_version Example - -```json -"2.0" -``` - - -## type - -The type of detection - -`type` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#type-known-values). - -### type Known Values -| Value | Description | -|-------|-------------| -| `uba` | | -| `splunk` | | -| `phantom` | | - - - -### type Example - -```json -"phantom" -``` - - -## version - -The version of the detection - -`version` - -* is **required** -* type: `string` -* defined in this schema - -### version Type - - -`string` - - - - - - -### version Example - -```json -"1" -``` - - -# Detection Manifest Definitions - -| Property | Type | Group | -|----------|------|-------| -| [correlation_rule](#correlation_rule) | `object` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [event_type](#event_type) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [model](#model) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [model_version](#model_version) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [phantom_server](#phantom_server) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [playbook_name](#playbook_name) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [playbook_url](#playbook_url) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [sensitivity](#sensitivity) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [severity](#severity) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [threat_category](#threat_category) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | - -## correlation_rule - -Various fields to enhance usability in Enterprise Security - -`correlation_rule` - -* is optional -* type: `object` -* defined in this schema - -### correlation_rule Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `notable`| object | Optional | -| `risk`| object | Optional | -| `schedule`| object | **Required** | -| `search`| string | **Required** | -| `suppress`| object | Optional | - - - -#### notable - -Various fields associated with creating a notable event - -`notable` - -* is optional -* type: `object` - -##### notable Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `nes_fields`| string | **Required** | -| `rule_description`| string | **Required** | -| `rule_title`| string | **Required** | - - - -#### nes_fields - -A list of suggested fields to be used for notable-event suppression - -`nes_fields` - -* is **required** -* type: `string` - -##### nes_fields Type - - -`string` - - - - - - - - - -#### rule_description - -Description of the notable event that will display in Incident Review - -`rule_description` - -* is **required** -* type: `string` - -##### rule_description Type - - -`string` - - - - - - - - - -#### rule_title - -Title of the notable event that will display in Incident Review - -`rule_title` - -* is **required** -* type: `string` - -##### rule_title Type - - -`string` - - - - - - - - - - - - - - -#### risk - -Fields associated with assigning risk to objects - -`risk` - -* is optional -* type: `object` - -##### risk Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `risk_object`| string | **Required** | -| `risk_object_type`| array | **Required** | -| `risk_score`| integer | **Required** | - - - -#### risk_object - -TThe field to which you are assigning risk - -`risk_object` - -* is **required** -* type: `string` - -##### risk_object Type - - -`string` - - - - - - - - - -#### risk_object_type - -The type of object to which you are assigning risk - -`risk_object_type` - -* is **required** -* type: `enum[]`* between `0` and `1` items in the array - - -##### risk_object_type Type - - -Array type: `enum[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### risk_score - -Score assigned to risk_object - -`risk_score` - -* is **required** -* type: `integer` - -##### risk_score Type - - -`integer` - - - - - - - - - - - - - - -#### schedule - -Various fields to assist in scheduling the search - -`schedule` - -* is **required** -* type: `object` - -##### schedule Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `cron_schedule`| string | Optional | -| `earliest_time`| string | Optional | -| `latest_time`| string | Optional | - - - -#### cron_schedule - -Schedule of the search in cron format - -`cron_schedule` - -* is optional -* type: `string` - -##### cron_schedule Type - - -`string` - - - - - - - - - -#### earliest_time - -The earliest time the search should run in Splunk format - -`earliest_time` - -* is optional -* type: `string` - -##### earliest_time Type - - -`string` - - - - - - - - - -#### latest_time - -The latest time tes search should run against in Splunk format - -`latest_time` - -* is optional -* type: `string` - -##### latest_time Type - - -`string` - - - - - - - - - - - - - - -#### search - -The search (in SPL) executed within core Splunk - -`search` - -* is **required** -* type: `string` - -##### search Type - - -`string` - - - - - - - - - -#### suppress - -Fields associated with suppressing the creation of multiple alerts - -`suppress` - -* is optional -* type: `object` - -##### suppress Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `suppress_fields`| string | **Required** | -| `suppress_period`| string | **Required** | - - - -#### suppress_fields - -The fields to base the suppression on - -`suppress_fields` - -* is **required** -* type: `string` - -##### suppress_fields Type - - -`string` - - - - - - - - - -#### suppress_period - -The length of time the suppression should be in effect - -`suppress_period` - -* is **required** -* type: `string` - -##### suppress_period Type - - -`string` - - - - - - - - - - - - - - - - - -## event_type - -An anomaly or threat. - -`event_type` - -* is optional -* type: `string` -* defined in this schema - -### event_type Type - - -`string` - - - - - - -### event_type Example - -```json -"anomaly" -``` - - -## model - -The name of the Splunk UBA model that detected the anomaly. - -`model` - -* is optional -* type: `string` -* defined in this schema - -### model Type - - -`string` - - - - - - -### model Example - -```json -"UBA Model" -``` - - -## model_version - -Url of the playbook on Phantom website. - -`model_version` - -* is optional -* type: `string` -* defined in this schema - -### model_version Type - - -`string` - - - - - - -### model_version Example - -```json -"2.0" -``` - - -## phantom_server - -IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname) - -`phantom_server` - -* is optional -* type: `string` -* defined in this schema - -### phantom_server Type - - -`string` - - - - - - -### phantom_server Example - -```json -"automation (hostname)" -``` - - -## playbook_name - -Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment - -`playbook_name` - -* is optional -* type: `string` -* defined in this schema - -### playbook_name Type - - -`string` - - - - - - -### playbook_name Example - -```json -"community/dns_hijack_detect_playbook" -``` - - -## playbook_url - -Url of the playbook on Phantom website. - -`playbook_url` - -* is optional -* type: `string` -* defined in this schema - -### playbook_url Type - - -`string` - - - - - - -### playbook_url Example - -```json -"https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" -``` - - -## sensitivity - -TLP colors (white, green, amber or red) - -`sensitivity` - -* is optional -* type: `string` -* defined in this schema - -### sensitivity Type - - -`string` - - - - - - -### sensitivity Example - -```json -"green" -``` - - -## severity - -Severity in phantom (High, Medium, Low) - -`severity` - -* is optional -* type: `string` -* defined in this schema - -### severity Type - - -`string` - - - - - - -### severity Example - -```json -"high" -``` - - -## threat_category - -The category of a threat in Splunk UBA. - -`threat_category` - -* is optional -* type: `string` -* defined in this schema - -### threat_category Type - - -`string` - - - - - - -### threat_category Example - -```json -"Malware" -``` - diff --git a/docs/investigations.spec.json b/docs/investigations.spec.json deleted file mode 100644 index c597b8b8a1..0000000000 --- a/docs/investigations.spec.json +++ /dev/null @@ -1,372 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/investigations.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "definitions": { - "phantom": { - "properties": { - "phantom_server": { - "description": "IP address and username of the Phantom server. Currently, we ship these values as automation (hostname) and encourage users to modify them according to their environments: for example, automation (hostname)", - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on the Phantom community repository on github, with underscores, and appended with \"community/.\" The playbooks are hosted on https://github.com/phantomcyber/playbooks. For example: community/simple_network_enrichment.", - "type": "string" - }, - "playbook_url": { - "description": "URL of the playbook on the Phantom website", - "type": "string" - }, - "schedule": { - "description": "Various fields used to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run again in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "sensitivity": { - "description": "TLP colors (White, Green, Amber, or Red)", - "type": "string" - }, - "severity": { - "description": "Severity in Phantom (High, Medium, Low)", - "type": "string" - } - }, - "required": [ - "playbook_name", - "phantom_server", - "playbook_url" - ], - "type": "object" - }, - "splunk": { - "properties": { - "fields_required": { - "description": "A list of data models, if any, used by this search", - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "schedule": { - "description": "Various fields to assist in scheduling the search", - "properties": { - "cron_schedule": { - "description": "Schedule of the search in cron format", - "type": "string" - }, - "earliest_time": { - "description": "The earliest time the search should run in Splunk format", - "type": "string" - }, - "latest_time": { - "description": "The latest time the search should run again in Splunk format", - "type": "string" - } - }, - "type": "object" - }, - "search": { - "description": "The search (in SPL) executed within Splunk Enterprise for investigation", - "type": "string" - } - }, - "required": [ - "search", - "fields_required", - "schedule" - ], - "type": "object" - } - }, - "description": "The fields that make up the manifest of a version 2 investigative object", - "properties": { - "creation_date": { - "description": "The date the story manifest was created", - "type": "string" - }, - "data_metadata": { - "description": "Information about the data being ingested", - "properties": { - "data_eventtypes": { - "description": "A list of eventtypes, if any, used by this search", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_models": { - "description": "A list of data models, if any, used by this search", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_source": { - "description": "A high-level description of the type of data needed for this search to complete", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "data_sourcetypes": { - "description": "The list of sourcetypes, if any, used by this search", - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "providing_technologies": { - "description": "A list of technologies that provide this data", - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "Censys", - "OSquery", - "SMTP", - "Cuckoo", - "VirusTotal", - "DeepSight" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - } - }, - "required": [ - "data_source", - "providing_technologies" - ], - "type": "object" - }, - "description": { - "description": "A description of what the search is designed to detect", - "type": "string" - }, - "eli5": { - "description": "Explain it like I\u2019m 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert", - "type": "string" - }, - "entities": { - "description": "A list of entities that will used in the story flow or are relevant to the security investigation. ", - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user" - ] - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "how_to_implement": { - "description": "A discussion of how to implement this search, from what needs to be ingested, config files modified, and suggested per-site modifications", - "type": "string" - }, - "id": { - "description": "The unique identifier for the search", - "type": "string" - }, - "investigate": { - "anyOf": [ - { - "required": [ - "splunk" - ] - }, - { - "required": [ - "phantom" - ] - } - ], - "properties": { - "phantom": { - "$ref": "#/definitions/phantom" - }, - "splunk": { - "$ref": "#/definitions/splunk" - } - }, - "type": "object" - }, - "known_false_positives": { - "description": "Scenarios in which detected behavior is benign, coupled with suggestions on how to verify the behavior", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person maintaining this search", - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this search", - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this search", - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "modification_date": { - "description": "The date of the most recent modification to the search", - "type": "string" - }, - "name": { - "description": "The name of the search", - "type": "string" - }, - "original_authors": { - "description": "A list of the original authors of the search", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person who originally authored the search", - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the search", - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the search", - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "spec_version": { - "description": "The version of the investigative search specification this manifest follows", - "type": "integer" - }, - "type": { - "description": "Type of product that will support this investigate object", - "enum": [ - "phantom", - "splunk", - "uba" - ] - }, - "version": { - "description": "The version of the search", - "type": "string" - } - }, - "required": [ - "creation_date", - "data_metadata", - "how_to_implement", - "maintainers", - "modification_date", - "original_authors", - "description", - "id", - "type", - "spec_version", - "version", - "investigate" - ], - "title": "Investigative Search Manifest", - "type": "object" -} diff --git a/docs/investigations.spec.md b/docs/investigations.spec.md deleted file mode 100644 index 9a3a5513d7..0000000000 --- a/docs/investigations.spec.md +++ /dev/null @@ -1,1165 +0,0 @@ - -# Investigative Search Manifest Schema - -``` -https://api.splunkresearch.com/schemas/investigations.json -``` - -The fields that make up the manifest of a version 2 investigative object - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | Yes | Experimental | No | Forbidden | Permitted | | - -# Investigative Search Manifest Properties - -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [creation_date](#creation_date) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [data_metadata](#data_metadata) | `object` | **Required** | No | Investigative Search Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [eli5](#eli5) | `string` | Optional | No | Investigative Search Manifest (this schema) | -| [entities](#entities) | `enum[]` | Optional | No | Investigative Search Manifest (this schema) | -| [how_to_implement](#how_to_implement) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [investigate](#investigate) | `object` | **Required** | No | Investigative Search Manifest (this schema) | -| [known_false_positives](#known_false_positives) | `string` | Optional | No | Investigative Search Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | **Required** | No | Investigative Search Manifest (this schema) | -| [modification_date](#modification_date) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [name](#name) | `string` | Optional | No | Investigative Search Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | **Required** | No | Investigative Search Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | **Required** | No | Investigative Search Manifest (this schema) | -| [type](#type) | `enum` | **Required** | No | Investigative Search Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## creation_date - -The date the story manifest was created - -`creation_date` - -* is **required** -* type: `string` -* defined in this schema - -### creation_date Type - - -`string` - - - - - - - -## data_metadata - -Information about the date being ingested - -`data_metadata` - -* is **required** -* type: `object` -* defined in this schema - -### data_metadata Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `data_eventtypes`| array | Optional | -| `data_models`| array | Optional | -| `data_source`| array | **Required** | -| `data_sourcetypes`| array | Optional | -| `providing_technologies`| array | **Required** | - - - -#### data_eventtypes - -A list of eventtypes, if any, used by this search - -`data_eventtypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_eventtypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### data_models - -A list of data models, if any, used by this search - -`data_models` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### data_models Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of data models, if any, used by this search", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Cloud_Infrastructure", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ], - "simpletype": "`enum`", - "meta:enum": { - "Alerts": "", - "Application_State": "", - "Authentication": "", - "Certificates": "", - "Change_Analysis": "", - "Change": "", - "Cloud_Infrastructure": "", - "Malware": "", - "Email": "", - "Identity_Management": "", - "Network_Resolution": "", - "Network_Traffic": "", - "Vulnerabilities": "", - "Web": "", - "Network_Sessions": "", - "Updates": "", - "Risk": "", - "Endpoint": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - - - - - -#### data_source - -A high-level description of the type of data needed for this search to complete - -`data_source` - -* is **required** -* type: `string[]`* at least `0` items in the array - - -##### data_source Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### data_sourcetypes - -The list of sourcetypes, if any, used by this search - -`data_sourcetypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_sourcetypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### providing_technologies - -A list of technologies that provide this data - -`providing_technologies` - -* is **required** -* type: `enum[]`* at least `0` items in the array - - -##### providing_technologies Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of technologies that provide this data", - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "Censys", - "OSquery", - "SMTP", - "Cuckoo", - "VirusTotal", - "DeepSight" - ], - "simpletype": "`enum`", - "meta:enum": { - "Apache": "", - "AWS": "", - "Bro": "", - "Microsoft Windows": "", - "Linux": "", - "macOS": "", - "Netbackup": "", - "Splunk Enterprise": "", - "Splunk Enterprise Security": "", - "Splunk Stream": "", - "Active Directory": "", - "Bluecoat": "", - "Carbon Black Response": "", - "Carbon Black Protect": "", - "CrowdStrike Falcon": "", - "Microsoft Exchange": "", - "Nessus": "", - "Palo Alto Firewall": "", - "Qualys": "", - "Sysmon": "", - "Tanium": "", - "Ziften": "", - "Censys": "", - "OSquery": "", - "SMTP": "", - "Cuckoo": "", - "VirusTotal": "", - "DeepSight": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - - - - - - - - -## description - -A description of what the search is designed to detect - -`description` - -* is **required** -* type: `string` -* defined in this schema - -### description Type - - -`string` - - - - - - - -## eli5 - -Explain it like I’m 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert - -`eli5` - -* is optional -* type: `string` -* defined in this schema - -### eli5 Type - - -`string` - - - - - - - -## entities - -A list of entities that will used in the story flow or are relevant to the security investigation. - -`entities` - -* is optional -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### entities Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of entities that will used in the story flow or are relevant to the security investigation. ", - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user" - ], - "simpletype": "`enum`", - "meta:enum": { - "accessKeyId": "", - "arn": "", - "awsRegion": "", - "bucketName": "", - "City": "", - "Country": "", - "dest_port": "", - "dest": "", - "event_id": "", - "instanceId": "", - "message_id": "", - "networkAclId": "", - "process_name": "", - "process": "", - "recipient": "", - "Region": "", - "resourceId": "", - "session_id": "", - "src_ip": "", - "src_mac": "", - "src_user": "", - "src": "", - "user": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - - - -## how_to_implement - -A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications - -`how_to_implement` - -* is **required** -* type: `string` -* defined in this schema - -### how_to_implement Type - - -`string` - - - - - - - -## id - -The unique identifier for the search - -`id` - -* is **required** -* type: `string` -* defined in this schema - -### id Type - - -`string` - - - - - - - -## investigate - - -`investigate` - -* is **required** -* type: `object` -* defined in this schema - -### investigate Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `phantom`| | Optional | -| `splunk`| | Optional | - - - -#### phantom - - -`phantom` - -* is optional -* type: reference - -##### phantom Type - - -* []() – `#/definitions/phantom` - - - - - - - -#### splunk - - -`splunk` - -* is optional -* type: reference - -##### splunk Type - - -* []() – `#/definitions/splunk` - - - - - - - - - - -## known_false_positives - -Scenarios in which detected behavior is benig, coupled with suggestions on how to verify the behavior - -`known_false_positives` - -* is optional -* type: `string` -* defined in this schema - -### known_false_positives Type - - -`string` - - - - - - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is **required** -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - - - - -#### email - -Email address of the person maintaining this search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - - - - -#### name - -Name of the person maintaining this search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - - - - - - - - - - -## modification_date - -The date of the most recent modification to the search - -`modification_date` - -* is **required** -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - - -## name - -The name of the search - -`name` - -* is optional -* type: `string` -* defined in this schema - -### name Type - - -`string` - - - - - - - -## original_authors - -A list of the original authors of the search - -`original_authors` - -* is **required** -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - - - - -#### email - -Email address of the person who originally authored the search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - - - - -#### name - -Name of the person who originally authored the search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - - - - - - - - - - -## spec_version - -The version of the investigative search specification this manifest follows - -`spec_version` - -* is **required** -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - - -## type - -Type of product that will support this investigate object. - -`type` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#type-known-values). - -### type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - - -## version - -The version of the search - -`version` - -* is **required** -* type: `string` -* defined in this schema - -### version Type - - -`string` - - - - - - - -# Investigative Search Manifest Definitions - -| Property | Type | Group | -|----------|------|-------| -| [fields_required](#fields_required) | `array` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/splunk` | -| [phantom_server](#phantom_server) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [playbook_name](#playbook_name) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [playbook_url](#playbook_url) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [schedule](#schedule) | `object` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/splunk` | -| [search](#search) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/splunk` | -| [sensitivity](#sensitivity) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [severity](#severity) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | - -## fields_required - -A list of data models, if any, used by this search - -`fields_required` - -* is optional -* type: `array` -* at least `0` items in the array -* defined in this schema - -### fields_required Type - - -Array type: `array` - - - - - - -## phantom_server - -IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname) - -`phantom_server` - -* is optional -* type: `string` -* defined in this schema - -### phantom_server Type - - -`string` - - - - - - - -## playbook_name - -Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment - -`playbook_name` - -* is optional -* type: `string` -* defined in this schema - -### playbook_name Type - - -`string` - - - - - - - -## playbook_url - -Url of the playbook on Phantom website. - -`playbook_url` - -* is optional -* type: `string` -* defined in this schema - -### playbook_url Type - - -`string` - - - - - - - -## schedule - -Various fields to assist in scheduling the search - -`schedule` - -* is optional -* type: `object` -* defined in this schema - -### schedule Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `cron_schedule`| string | Optional | -| `earliest_time`| string | Optional | -| `latest_time`| string | Optional | - - - -#### cron_schedule - -Schedule of the search in cron format - -`cron_schedule` - -* is optional -* type: `string` - -##### cron_schedule Type - - -`string` - - - - - - - - - -#### earliest_time - -The earliest time the search should run in Splunk format - -`earliest_time` - -* is optional -* type: `string` - -##### earliest_time Type - - -`string` - - - - - - - - - -#### latest_time - -The latest time tes search should run against in Splunk format - -`latest_time` - -* is optional -* type: `string` - -##### latest_time Type - - -`string` - - - - - - - - - - - - -## search - -The search (in SPL) executed within core Splunk for investgation. - -`search` - -* is optional -* type: `string` -* defined in this schema - -### search Type - - -`string` - - - - - - - -## sensitivity - -TLP colors (White, Green, Amber or Red) - -`sensitivity` - -* is optional -* type: `string` -* defined in this schema - -### sensitivity Type - - -`string` - - - - - - - -## severity - -Severity in phantom (High, Medium, Low) - -`severity` - -* is optional -* type: `string` -* defined in this schema - -### severity Type - - -`string` - - - - - - diff --git a/docs/splunk_docs_categories.wiki b/docs/splunk_docs_categories.wiki index 9aba2decf9..ca0c275cb5 100644 --- a/docs/splunk_docs_categories.wiki +++ b/docs/splunk_docs_categories.wiki @@ -692,7 +692,6 @@ If there is evidence of lateral movement, it is imperative for analysts to colle * PR.IP ====References==== -* https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis * https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html date = 2020-02-04 diff --git a/docs/stories_categories.md b/docs/stories_categories.md index 21a0a8f245..0cf7630e17 100644 --- a/docs/stories_categories.md +++ b/docs/stories_categories.md @@ -690,7 +690,6 @@ If there is evidence of lateral movement, it is imperative for analysts to colle * PR.IP ##### References -* https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis * https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html ### Malicious PowerShell diff --git a/docs/story.spec.json b/docs/story.spec.json deleted file mode 100644 index 7eda0fa321..0000000000 --- a/docs/story.spec.json +++ /dev/null @@ -1,271 +0,0 @@ -{ - "$id": "https://api.splunkresearch.com/schemas/story.json", - "$schema": "http://json-schema.org/draft-07/schema#", - "description": "The fields that make up the manifest of a version 2 Analytic Story", - "meta:license": [ - "This file is licensed to you under the Apache License, Version 2.0 (the 'License');", - "you may not use this file except in compliance with the License. You may obtain a copy", - "of the License at http://www.apache.org/licenses/LICENSE-2.0" - ], - "properties": { - "category": { - "description": "The category to which the Analytic Story belongs", - "items": { - "enum": [ - "Abuse", - "Account Compromise", - "Account Sharing", - "Adversary Tactics", - "Best Practices", - "Cloud Security", - "Command and Control", - "Compliance", - "Data Exfiltration", - "Denial of Service", - "Endpoint Compromise", - "GDPR", - "IAM Analytics", - "Insider Threat", - "Lateral Movement", - "Malware", - "Network Attack", - "Operations", - "Other", - "Privilege Escalation", - "Phishing", - "Ransomware", - "SaaS", - "Scanning", - "Shadow IT", - "Threat Intelligence", - "Unauthorized Software", - "Vulnerability", - "Web Attack" - ], - "examples": [ - "Adversary Tactics" - ], - "type": "string" - }, - "maxItems": 1, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "channel": { - "description": "A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Content Updates are in the ESCU channel", - "examples": [ - "ESCU" - ], - "type": "string" - }, - "creation_date": { - "description": "The date this story was created", - "examples": [ - "2017-11-21" - ], - "type": "string" - }, - "description": { - "description": "A high-level description or goal of the Analytic Story", - "examples": [ - "Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records." - ], - "type": "string" - }, - "detections": { - "description": "An array of detection mechanisms from Splunk, UBA, and Phantom. ", - "items": { - "additionalProperties": false, - "properties": { - "detection_id": { - "description": "Unique identifier of the detection, in the form of UUID", - "examples": [ - "1169w17b-ef78-4b59-aae8-5369073014e1" - ], - "type": "string" - }, - "name": { - "description": "Name of the Detection. This can be a name of a Splunk correlation search, a UBA threat, or a Phantom detection playbook.", - "examples": [ - "DNS record changed" - ], - "type": "string" - }, - "type": { - "description": "Product providing the detection", - "enum": [ - "splunk", - "uba", - "phantom" - ], - "examples": [ - "splunk", - "uba", - "phantom" - ], - "type": "string" - } - }, - "required": [ - "detection_id", - "type", - "name" - ], - "type": "object" - }, - "type": "array" - }, - "id": { - "description": "A unique identifier for the Analytic Story", - "examples": [ - "8169f17b-ef68-4b59-aae8-5869073014e1" - ], - "format": "uuid", - "type": "string" - }, - "maintainers": { - "description": "An array of the current maintainers of the Analytic Story", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person maintaining this Analytic Story", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person maintaining this Analytic Story", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person maintaining this Analytic Story", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "modification_date": { - "description": "The date of the most recent modification to this Analytic Story", - "examples": [ - "2018-09-06" - ], - "type": "string" - }, - "name": { - "description": "The name of the Analytic Story", - "examples": [ - "DNS Hijacking" - ], - "type": "string" - }, - "narrative": { - "description": "Long-form text that describes the Analytic Story and the rationale behind it, as well as an overview of the included searches, and how they enable the story", - "examples": [ - "Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.

The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous." - ], - "type": "string" - }, - "original_authors": { - "description": "An array of the original authors of the Analytic Story", - "items": { - "additionalProperties": false, - "properties": { - "company": { - "description": "Company associated with the person who originally authored the Analytic Story", - "examples": [ - "Splunk" - ], - "type": "string" - }, - "email": { - "description": "Email address of the person who originally authored the Analytic Story", - "examples": [ - "daftpunk@splunk.com" - ], - "type": "string" - }, - "name": { - "description": "Name of the person who originally authored the Analytic Story", - "examples": [ - "Daft Punk" - ], - "type": "string" - } - }, - "required": [ - "name", - "email", - "company" - ], - "type": "object" - }, - "type": "array" - }, - "references": { - "description": "An array of URLs that provide information about the problem the story addresses", - "examples": [ - "https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" - ], - "items": { - "type": "string" - }, - "minItems": 0, - "type": "array", - "uniqueItems": true - }, - "spec_version": { - "description": "The version of the Analytic Story specification this manifest follows", - "examples": [ - 2 - ], - "type": "integer" - }, - "usecase": { - "description": "The use case to which the Analytic Story belongs", - "enum": [ - "Security Monitoring", - "Advanced Threat Detection", - "Insider Threat", - "Compliance", - "Fraud Detection" - ], - "examples": [ - "Advanced Threat Detection" - ] - }, - "version": { - "description": "The version of the Analytic Story (bumps the version number when the story gets an update)", - "examples": [ - "1.0" - ], - "type": "string" - } - }, - "required": [ - "id", - "category", - "usecase", - "name", - "description", - "detections", - "version" - ], - "title": "Analytic Story Manifest", - "type": "object" -} diff --git a/docs/story.spec.md b/docs/story.spec.md deleted file mode 100644 index 8c575c4352..0000000000 --- a/docs/story.spec.md +++ /dev/null @@ -1,725 +0,0 @@ - -# Analytic Story Manifest Schema - -``` -https://api.splunkresearch.com/schemas/story.json -``` - -The fields that make up the manifest of a version 2 Analytic Story - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | - -# Analytic Story Manifest Properties - -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [category](#category) | `enum[]` | **Required** | No | Analytic Story Manifest (this schema) | -| [channel](#channel) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [creation_date](#creation_date) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| [detections](#detections) | `object[]` | **Required** | No | Analytic Story Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | Optional | No | Analytic Story Manifest (this schema) | -| [modification_date](#modification_date) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [name](#name) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| [narrative](#narrative) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | Optional | No | Analytic Story Manifest (this schema) | -| [references](#references) | `string[]` | Optional | No | Analytic Story Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | Optional | No | Analytic Story Manifest (this schema) | -| [usecase](#usecase) | `enum` | **Required** | No | Analytic Story Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## category - -The category to which the Analytic Story belongs - -`category` - -* is **required** -* type: `enum[]` -* between `0` and `1` items in the array -* defined in this schema - -### category Type - - -Array type: `enum[]` - -All items must be of the type: -`string` - - - - - - - - - - -## channel - -A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Content Updates are in the ESCU channel - -`channel` - -* is optional -* type: `string` -* defined in this schema - -### channel Type - - -`string` - - - - - - -### channel Example - -```json -"ESCU" -``` - - -## creation_date - -The date this story was created - -`creation_date` - -* is optional -* type: `string` -* defined in this schema - -### creation_date Type - - -`string` - - - - - - -### creation_date Example - -```json -"2017-11-21" -``` - - -## description - -A high-level description or goal of the Analytic Story - -`description` - -* is **required** -* type: `string` -* defined in this schema - -### description Type - - -`string` - - - - - - -### description Example - -```json -"Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records." -``` - - -## detections - -An array of detection mechanisms from Splunk, UBA and phantom. - -`detections` - -* is **required** -* type: `object[]` -* defined in this schema - -### detections Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `detection_id`| string | **Required** | -| `name`| string | **Required** | -| `type`| string | **Required** | - - - -#### detection_id - -unique identifier of the detection, in the form of UUID - -`detection_id` - -* is **required** -* type: `string` - -##### detection_id Type - - -`string` - - - - - - -##### detection_id Example - -```json -1169w17b-ef78-4b59-aae8-5369073014e1 -``` - - - - -#### name - -Name of the Detection. It can be a name of a Splunk correlation search name, a UBA threat or a Phantom detection playbook. - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -DNS record changed -``` - - - - -#### type - -What product gives you a detection - -`type` - -* is **required** -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#detections-known-values). - -##### type Known Values -| Value | Description | -|-------|-------------| -| `splunk` | | -| `uba` | | -| `phantom` | | - - - -##### type Examples - -```json -splunk -``` - -```json -uba -``` - -```json -phantom -``` - - - - - - - - - - -## id - -A unique identifier for the Analytic Story - -`id` - -* is **required** -* type: `string` -* defined in this schema - -### id Type - - -`string` - - - - - - -### id Example - -```json -"8169f17b-ef68-4b59-aae8-5869073014e1" -``` - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is optional -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this Analytic Story - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person maintaining this Analytic Story - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person maintaining this Analytic Story - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## modification_date - -The date of the most recent modification to this Analytic Story - -`modification_date` - -* is optional -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - -### modification_date Example - -```json -"2018-09-06" -``` - - -## name - -The name of the Analytic Story - -`name` - -* is **required** -* type: `string` -* defined in this schema - -### name Type - - -`string` - - - - - - -### name Example - -```json -"DNS Hijacking" -``` - - -## narrative - -Long-form text that describes the Analytic Story and the rationale behind it, as well as an overview of the included searches, and how they enable the story - -`narrative` - -* is optional -* type: `string` -* defined in this schema - -### narrative Type - - -`string` - - - - - - -### narrative Example - -```json -"Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.

The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous." -``` - - -## original_authors - -An array of the original authors of the Analytic Story - -`original_authors` - -* is optional -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the Analytic Story - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person who originally authored the Analytic Story - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person who originally authored the Analytic Story - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## references - -An array of URLs that give information about the problem the story is addressing - -`references` - -* is optional -* type: `string[]` -* at least `0` items in the array -* defined in this schema - -### references Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -### references Example - -```json -"https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" -``` - - -## spec_version - -The version of the Analytic Story specification this manifest follows - -`spec_version` - -* is optional -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - -### spec_version Example - -```json -2 -``` - - -## usecase - -The usecase to which the Analytic Story belongs to. - -`usecase` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#usecase-known-values). - -### usecase Known Values -| Value | Description | -|-------|-------------| -| `Security Monitoring` | | -| `Advanced Threat Detection` | | -| `Insider Threat` | | -| `Compliance` | | -| `Fraud Detection` | | - - - -### usecase Example - -```json -"Advanced Threat Detection" -``` - - -## version - -The version of the Analytic Story, bump the version number when the story gets an update - -`version` - -* is **required** -* type: `string` -* defined in this schema - -### version Type - - -`string` - - - - - - -### version Example - -```json -"1.0" -``` - diff --git a/spec/baselines.spec.md b/spec/baselines.spec.md new file mode 100644 index 0000000000..fc66502080 --- /dev/null +++ b/spec/baselines.spec.md @@ -0,0 +1,283 @@ + +# Baseline Schema Schema + +``` +http://example.com/example.json +``` + +schema for baselines + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Baseline Schema Properties + +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [how_to_implement](#how_to_implement) | `string` | Optional | No | `""` | Baseline Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [search](#search) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Baseline Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Baseline Schema (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## author + +Author of the baseline + +`author` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### author Type + + +`string` + + + + + + +### author Example + +```json +"Bahvin Patel, Splunk" +``` + + +## date + +date of creation or modification, format yyyy-mm-dd + +`date` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### date Type + + +`string` + + + + + + +### date Example + +```json +"2019-12-06" +``` + + +## description + +A detailed description of the baseline + +`description` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days" +``` + + +## how_to_implement + +information about how to implement. Only needed for non standard implementations. + +`how_to_implement` + +* is optional +* type: `string` +* default: `""` +* defined in this schema + +### how_to_implement Type + + +`string` + + + + + + +### how_to_implement Example + +```json +"This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." +``` + + +## id + +UUID as unique identifier + +`id` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### id Type + + +`string` + + + + + + +### id Example + +```json +"fc0edc95-ff2b-48b0-9f6f-63da3789fd63" +``` + + +## name +### Name of baseline + +`name` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"Previously Seen AWS Regions" +``` + + +## search + +The Splunk search for the baseline + +`search` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### search Type + + +`string` + + + + + + +### search Example + +```json +"cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" +``` + + +## tags + +An array of key value pairs for tagging + +`tags` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### tags Type + + +`object` with following properties: + + +| Property | Type | Required | +|----------|------|----------| + + + + +### tags Example + +```json +{ + "analytics_story": "suspicious_aws_ec2_activities", + "custom_key": "custom_value" +} +``` + + +## version + +version of baseline, e.g. 1 or 2 ... + +`version` + +* is **required** +* type: `integer` +* default: `0` +* defined in this schema + +### version Type + + +`integer` + + + + + + +### version Example + +```json +1 +``` + diff --git a/spec/detections.spec.md b/spec/detections.spec.md new file mode 100644 index 0000000000..8fb01effff --- /dev/null +++ b/spec/detections.spec.md @@ -0,0 +1,381 @@ + +# Detection Schema Schema + +``` +http://example.com/example.json +``` + +schema for detections + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Detection Schema Properties + +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [how_to_implement](#how_to_implement) | `string` | Optional | No | `""` | Detection Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [known_false_positives](#known_false_positives) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [references](#references) | `string[]` | Optional | No | `[]` | Detection Schema (this schema) | +| [search](#search) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Detection Schema (this schema) | +| [type](#type) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Detection Schema (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## author + +Author of the detection + +`author` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### author Type + + +`string` + + + + + + +### author Example + +```json +"Patrick Bareiss, Splunk" +``` + + +## date + +date of creation or modification, format yyyy-mm-dd + +`date` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### date Type + + +`string` + + + + + + +### date Example + +```json +"2019-12-06" +``` + + +## description + +A detailed description of the detection + +`description` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump." +``` + + +## how_to_implement + +information about how to implement. Only needed for non standard implementations. + +`how_to_implement` + +* is optional +* type: `string` +* default: `""` +* defined in this schema + +### how_to_implement Type + + +`string` + + + + + + +### how_to_implement Example + +```json +"This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." +``` + + +## id + +UUID as unique identifier + +`id` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### id Type + + +`string` + + + + + + +### id Example + +```json +"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" +``` + + +## known_false_positives + +known false postives + +`known_false_positives` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### known_false_positives Type + + +`string` + + + + + + +### known_false_positives Example + +```json +"Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual." +``` + + +## name +### Name of detection + +`name` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"Access LSASS Memory for Dump Creation" +``` + + +## references + +A list of references for this detection + +`references` + +* is optional +* type: `string[]` + +* default: `[]` +* defined in this schema + +### references Type + + +Array type: `string[]` + +All items must be of the type: +`string` + + + + + +An explanation about the purpose of this instance. + + + + + +### references Example + +```json +[ + "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" +] +``` + + +## search + +The Splunk search for the detection + +`search` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### search Type + + +`string` + + + + + + +### search Example + +```json +"`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter`" +``` + + +## tags + +An array of key value pairs for tagging + +`tags` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### tags Type + + +`object` with following properties: + + +| Property | Type | Required | +|----------|------|----------| + + + + +### tags Example + +```json +{ + "analytics_story": "credential_dumping", + "custom_key": "custom_value" +} +``` + + +## type + +type of detection + +`type` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### type Type + + +`string` + + + + + + +### type Example + +```json +"ESCU" +``` + + +## version + +version of detection, e.g. 1 or 2 ... + +`version` + +* is **required** +* type: `integer` +* default: `0` +* defined in this schema + +### version Type + + +`integer` + + + + + + +### version Example + +```json +2 +``` + diff --git a/spec/lookups.spec.md b/spec/lookups.spec.md new file mode 100644 index 0000000000..38f87220d1 --- /dev/null +++ b/spec/lookups.spec.md @@ -0,0 +1,282 @@ + +# Lookup Manifest Schema + +``` +https://api.splunkresearch.com/schemas/lookups.json +``` + +A object that defines a lookup file and its properties. + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Lookup Manifest Properties + +| Property | Type | Required | Nullable | Defined by | +|----------|------|----------|----------|------------| +| [case_sensitive_match](#case_sensitive_match) | `enum` | Optional | No | Lookup Manifest (this schema) | +| [collection](#collection) | `string` | Optional | No | Lookup Manifest (this schema) | +| [default_match](#default_match) | `string` | Optional | No | Lookup Manifest (this schema) | +| [description](#description) | `string` | Optional | No | Lookup Manifest (this schema) | +| [filename](#filename) | `string` | Optional | No | Lookup Manifest (this schema) | +| [match_type](#match_type) | `string` | Optional | No | Lookup Manifest (this schema) | +| [max_matches](#max_matches) | `integer` | Optional | No | Lookup Manifest (this schema) | +| [min_matches](#min_matches) | `integer` | Optional | No | Lookup Manifest (this schema) | +| [name](#name) | `string` | Optional | No | Lookup Manifest (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## case_sensitive_match + +What the macro is intended to filter + +`case_sensitive_match` + +* is optional +* type: `enum` +* defined in this schema + +The value of this property **must** be equal to one of the [known values below](#case_sensitive_match-known-values). + +### case_sensitive_match Known Values +| Value | Description | +|-------|-------------| +| `true` | | +| `false` | | + + + +### case_sensitive_match Example + +```json +"true" +``` + + +## collection + +Name of the collection to use for this lookup + +`collection` + +* is optional +* type: `string` +* defined in this schema + +### collection Type + + +`string` + + + + + + +### collection Example + +```json +"prohibited_apps_launching_cmd" +``` + + +## default_match + +The default value if no match is found + +`default_match` + +* is optional +* type: `string` +* defined in this schema + +### default_match Type + + +`string` + + + + + + +### default_match Example + +```json +"true" +``` + + +## description + +The description of this lookup + +`description` + +* is optional +* type: `string` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"This lookup contains file names that exist in the Windows\\System32 directory" +``` + + +## filename + +The name of the file to use for this lookup + +`filename` + +* is optional +* type: `string` +* defined in this schema + +### filename Type + + +`string` + + + + + + +### filename Example + +```json +"prohibited_apps_launching_cmd.csv" +``` + + +## match_type + +A comma and space-delimited list of () specification to allow for non-exact matching + +`match_type` + +* is optional +* type: `string` +* defined in this schema + +### match_type Type + + +`string` + + + + + + +### match_type Example + +```json +"WILDCARD(process)" +``` + + +## max_matches + +The maximum number of possible matches for each input lookup value + +`max_matches` + +* is optional +* type: `integer` +* defined in this schema + +### max_matches Type + + +`integer` + + + + + + +### max_matches Example + +```json +"100" +``` + + +## min_matches + +Minimum number of possible matches for each input lookup value + +`min_matches` + +* is optional +* type: `integer` +* defined in this schema + +### min_matches Type + + +`integer` + + + + + + +### min_matches Example + +```json +"1" +``` + + +## name + +The name of the lookup to be used in searches + +`name` + +* is optional +* type: `string` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"isWindowsSystemFile_lookup" +``` + + + +**One** of the following *conditions* need to be fulfilled. + + +#### Condition 1 + + + +#### Condition 2 + + diff --git a/spec/macros.spec.md b/spec/macros.spec.md new file mode 100644 index 0000000000..f39fdeffe4 --- /dev/null +++ b/spec/macros.spec.md @@ -0,0 +1,131 @@ + +# Macro Manifest Schema + +``` +https://api.splunkresearch.com/schemas/macros.json +``` + +An object that defines the parameters for a Splunk Macro + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Macro Manifest Properties + +| Property | Type | Required | Nullable | Defined by | +|----------|------|----------|----------|------------| +| [arguments](#arguments) | `string[]` | Optional | No | Macro Manifest (this schema) | +| [definition](#definition) | `string` | Optional | No | Macro Manifest (this schema) | +| [description](#description) | `string` | **Required** | No | Macro Manifest (this schema) | +| [name](#name) | `string` | **Required** | No | Macro Manifest (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## arguments + +A list of the arguments being passed to this macro + +`arguments` + +* is optional +* type: `string[]` +* at least `0` items in the array +* defined in this schema + +### arguments Type + + +Array type: `string[]` + +All items must be of the type: +`string` + + + + + + + + + + +## definition + +The macro definition + +`definition` + +* is optional +* type: `string` +* defined in this schema + +### definition Type + + +`string` + + + + + + +### definition Example + +```json +"(query=fls-na* AND query = www* AND query=images*)" +``` + + +## description + +What the macro is intended to filter + +`description` + +* is **required** +* type: `string` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"Use this macro to filter out known good objects" +``` + + +## name + +The name of the macro + +`name` + +* is **required** +* type: `string` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"detection_search_output_filter" +``` + diff --git a/spec/response_tasks.spec.json b/spec/response_tasks.spec.json index 28b0688e1c..257e12f5fb 100644 --- a/spec/response_tasks.spec.json +++ b/spec/response_tasks.spec.json @@ -42,13 +42,13 @@ "type": "string" }, "how_to_implement": { - "$id": "#/properties/how_to_implement", - "type": "string", - "description": "information about how to implement. Only needed for non standard implementations.", - "default": "", - "examples": [ - "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." - ] + "$id": "#/properties/how_to_implement", + "default": "", + "description": "information about how to implement. Only needed for non standard implementations.", + "examples": [ + "This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." + ], + "type": "string" }, "id": { "$id": "#/properties/id", diff --git a/spec/response_tasks.spec.md b/spec/response_tasks.spec.md new file mode 100644 index 0000000000..be14942e11 --- /dev/null +++ b/spec/response_tasks.spec.md @@ -0,0 +1,437 @@ + +# Response Task Schema Schema + +``` +http://example.com/example.json +``` + +schema for response tasks + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Response Task Schema Properties + +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Response Task Schema (this schema) | +| [dashboard](#dashboard) | `string` | Optional | No | `""` | Response Task Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Response Task Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Response Task Schema (this schema) | +| [how_to_implement](#how_to_implement) | `string` | Optional | No | `""` | Response Task Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Response Task Schema (this schema) | +| [inputs](#inputs) | `array` | Optional | No | `[]` | Response Task Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Response Task Schema (this schema) | +| [playbook](#playbook) | `object` | Optional | No | `{}` | Response Task Schema (this schema) | +| [search](#search) | `string` | Optional | No | `""` | Response Task Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Response Task Schema (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## author + +Author of response task + +`author` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### author Type + + +`string` + + + + + + +### author Example + +```json +"Patrick Bareiß, Splunk" +``` + + +## dashboard + +Name of dashboard used as response task + +`dashboard` + +* is optional +* type: `string` +* default: `""` +* defined in this schema + +### dashboard Type + + +`string` + + + + + + +### dashboard Example + +```json +"process_chain_analysis.json" +``` + + +## date + +date of creation or modification, format yyyy-mm-dd + +`date` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### date Type + + +`string` + + + + + + +### date Example + +```json +"2019-12-06" +``` + + +## description + +Description of response task + +`description` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"Response Task example description" +``` + + +## how_to_implement + +information about how to implement. Only needed for non standard implementations. + +`how_to_implement` + +* is optional +* type: `string` +* default: `""` +* defined in this schema + +### how_to_implement Type + + +`string` + + + + + + +### how_to_implement Example + +```json +"This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." +``` + + +## id + +UUID as unique identifier + +`id` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### id Type + + +`string` + + + + + + +### id Example + +```json +"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" +``` + + +## inputs + +Inputs used from the response task + +`inputs` + +* is optional +* type: `array` + +* default: `[]` +* defined in this schema + +### inputs Type + + +Array type: `array` + + + + +### inputs Example + +```json +[ + "lookup_file" +] +``` + + +## name + +Namo fo response task + +`name` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"Response Tas Example" +``` + + +## playbook + +A phantom playbook as response task + +`playbook` + +* is optional +* type: `object` +* default: `{}` +* defined in this schema + +### playbook Type + + +`object` with following properties: + + +| Property | Type | Required | Default | +|----------|------|----------|---------| +| `name`| string | **Required** | `""` | +| `url_json`| string | **Required** | `""` | +| `url_python`| string | **Required** | `""` | + + + +#### name + +Name of Phantom Playbook + +`name` + +* is **required** +* type: `string` +* default: `""` + + +##### name Type + + +`string` + + + + + + +##### name Example + +```json +lets_encrypt_domain_investigate.json +``` + + + + +#### url_json + +URL for phantom playbook json file + +`url_json` + +* is **required** +* type: `string` +* default: `""` + + +##### url_json Type + + +`string` + + + + + + +##### url_json Example + +```json +https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json +``` + + + + +#### url_python + +URL for phantom playbook python file + +`url_python` + +* is **required** +* type: `string` +* default: `""` + + +##### url_python Type + + +`string` + + + + + + +##### url_python Example + +```json +https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py +``` + + + + + +### playbook Example + +```json +{ + "name": "lets_encrypt_domain_investigate.json", + "url_json": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.json", + "url_python": "https://github.com/phantomcyber/playbooks/blob/4.6/lets_encrypt_domain_investigate.py" +} +``` + + +## search + +Search as response task + +`search` + +* is optional +* type: `string` +* default: `""` +* defined in this schema + +### search Type + + +`string` + + + + + + +### search Example + +```json +"`sysmon` EventCode=1 | search [| inputlookup %lookup_file% ] | stats count by dest user process_name" +``` + + +## version + +version of detection, e.g. 1 or 2 ... + +`version` + +* is **required** +* type: `integer` +* default: `0` +* defined in this schema + +### version Type + + +`integer` + + + + + + +### version Example + +```json +3 +``` + diff --git a/spec/responses.spec.md b/spec/responses.spec.md new file mode 100644 index 0000000000..55779a8dfa --- /dev/null +++ b/spec/responses.spec.md @@ -0,0 +1,270 @@ + +# Response Schema Schema + +``` +http://example.com/example.json +``` + +schema for response + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Response Schema Properties + +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [response_tasks](#response_tasks) | `array` | **Required** | No | `{}` | Response Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Response Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Response Schema (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## author + +Author of the response + +`author` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### author Type + + +`string` + + + + + + +### author Example + +```json +"Rico Valdez, Patrick Bareiß, Splunk" +``` + + +## date + +version of detection, e.g. 1 or 2 ... + +`date` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### date Type + + +`string` + + + + + + +### date Example + +```json +"2019-12-06" +``` + + +## description + +Description of response + +`description` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"Response example." +``` + + +## id + +UUID as unique identifier + +`id` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### id Type + + +`string` + + + + + + +### id Example + +```json +"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" +``` + + +## name + +Name of response + +`name` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"Response Example" +``` + + +## response_tasks + +Response tasks divided into phases + +`response_tasks` + +* is **required** +* type: `array` +* at least `1` items in the array +* default: `{}` +* defined in this schema + +### response_tasks Type + + +Array type: `array` + + + + +### response_tasks Example + +```json +{ + "another_phase": [ + { + "id": "7c72d944-3995-4485-8e57-67b4c353989b", + "name": "Another investigation" + } + ], + "identification": [ + { + "id": "c36f3f48-e0bb-4c20-a62a-cdc8f6418892", + "name": "Investigate Indicator of Compromise Hash" + }, + { + "id": "0dc849b2-2eb4-4fd2-add1-b6cc475765f0", + "name": "Investigate Domains" + } + ] +} +``` + + +## tags + +An array of key value pairs for tagging + +`tags` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### tags Type + + +`object` with following properties: + + +| Property | Type | Required | +|----------|------|----------| + + + + +### tags Example + +```json +{ + "analytics_story": "credential_dumping" +} +``` + + +## version + +version of detection, e.g. 1 or 2 ... + +`version` + +* is **required** +* type: `integer` +* default: `0` +* defined in this schema + +### version Type + + +`integer` + + + + + + +### version Example + +```json +1 +``` + diff --git a/spec/stories.spec.md b/spec/stories.spec.md new file mode 100644 index 0000000000..722c1ac936 --- /dev/null +++ b/spec/stories.spec.md @@ -0,0 +1,283 @@ + +# Analytics Story Schema Schema + +``` +http://example.com/example.json +``` + +schema analytics story + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Analytics Story Schema Properties + +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Analytics Story Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Analytics Story Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Analytics Story Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Analytics Story Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Analytics Story Schema (this schema) | +| [narrative](#narrative) | `string` | **Required** | No | `""` | Analytics Story Schema (this schema) | +| [search](#search) | `string` | Optional | No | `""` | Analytics Story Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Analytics Story Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Analytics Story Schema (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## author + +Author of the analytics story + +`author` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### author Type + + +`string` + + + + + + +### author Example + +```json +"Rico Valdez, Patrick Bareiß, Splunk" +``` + + +## date + +date of creation or modification, format yyyy-mm-dd + +`date` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### date Type + + +`string` + + + + + + +### date Example + +```json +"2019-12-06" +``` + + +## description + +description of the analytics story + +`description` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"Uncover activity consistent with credential dumping, a technique where attackers compromise systems and attempt to obtain and exfiltrate passwords." +``` + + +## id + +UUID as unique identifier + +`id` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### id Type + + +`string` + + + + + + +### id Example + +```json +"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" +``` + + +## name + +Name of the Analytics Story + +`name` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"Credential Dumping" +``` + + +## narrative + +narrative of the analytics story + +`narrative` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### narrative Type + + +`string` + + + + + + +### narrative Example + +```json +"gathering credentials from a target system, often hashed or encrypted, is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems." +``` + + +## search + +An additional Splunk search, which uses the result of the detections + +`search` + +* is optional +* type: `string` +* default: `""` +* defined in this schema + +### search Type + + +`string` + + + + + + +### search Example + +```json +"index=asx mitre_id=t1003 | stats values(source) as detections values(process) as processes values(user) as users values(_time) as time count by dest" +``` + + +## tags + +An explanation about the purpose of this instance. + +`tags` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### tags Type + + +`object` with following properties: + + +| Property | Type | Required | +|----------|------|----------| + + + + +### tags Example + +```json +{ + "analytics_story": "credential_dumping" +} +``` + + +## version + +version of analytics story, e.g. 1 or 2 ... + +`version` + +* is **required** +* type: `integer` +* default: `0` +* defined in this schema + +### version Type + + +`integer` + + + + + + +### version Example + +```json +1 +``` + From ad6cf3a4c2cac4ce6d782b2b56d5315fa45aa1b9 Mon Sep 17 00:00:00 2001 From: bpatel Date: Mon, 18 May 2020 17:00:15 -0700 Subject: [PATCH 60/93] adding docs for spec files --- docs/spec/baselines.spec.md | 1200 +-------- docs/spec/deployments.spec.md | 656 +++++ docs/spec/detections.spec.md | 2712 +------------------- docs/spec/investigations.spec.md | 915 ------- {spec => docs/spec}/lookups.spec.md | 0 {spec => docs/spec}/macros.spec.md | 0 {spec => docs/spec}/response_tasks.spec.md | 0 docs/spec/responses.spec.md | 1006 +------- {spec => docs/spec}/stories.spec.md | 0 docs/spec/story.spec.md | 725 ------ spec/baselines.spec.md | 283 -- spec/detections.spec.md | 381 --- spec/responses.spec.md | 270 -- 13 files changed, 977 insertions(+), 7171 deletions(-) create mode 100644 docs/spec/deployments.spec.md delete mode 100644 docs/spec/investigations.spec.md rename {spec => docs/spec}/lookups.spec.md (100%) rename {spec => docs/spec}/macros.spec.md (100%) rename {spec => docs/spec}/response_tasks.spec.md (100%) rename {spec => docs/spec}/stories.spec.md (100%) delete mode 100644 docs/spec/story.spec.md delete mode 100644 spec/baselines.spec.md delete mode 100644 spec/detections.spec.md delete mode 100644 spec/responses.spec.md diff --git a/docs/spec/baselines.spec.md b/docs/spec/baselines.spec.md index 8d76a5c212..fc66502080 100644 --- a/docs/spec/baselines.spec.md +++ b/docs/spec/baselines.spec.md @@ -1,112 +1,43 @@ -# Baseline Manifest Schema +# Baseline Schema Schema ``` -https://api.splunkresearch.com/schemas/baselines.json +http://example.com/example.json ``` -The fields that make up the manifest of a version 2 baseline search +schema for baselines | Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | |----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | Yes | Experimental | No | Forbidden | Permitted | | +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | -# Baseline Manifest Properties +# Baseline Schema Properties -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [baseline](#baseline) | `object` | **Required** | No | Baseline Manifest (this schema) | -| [creation_date](#creation_date) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [data_metadata](#data_metadata) | `object` | **Required** | No | Baseline Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [eli5](#eli5) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [entities](#entities) | `enum[]` | Optional | No | Baseline Manifest (this schema) | -| [how_to_implement](#how_to_implement) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [known_false_positives](#known_false_positives) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | **Required** | No | Baseline Manifest (this schema) | -| [modification_date](#modification_date) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [name](#name) | `string` | **Required** | No | Baseline Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | **Required** | No | Baseline Manifest (this schema) | -| [product_type](#product_type) | `enum` | **Required** | No | Baseline Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | **Required** | No | Baseline Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Baseline Manifest (this schema) | +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [how_to_implement](#how_to_implement) | `string` | Optional | No | `""` | Baseline Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [search](#search) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Baseline Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Baseline Schema (this schema) | | `*` | any | Additional | Yes | this schema *allows* additional properties | -## baseline +## author +Author of the baseline -`baseline` - -* is **required** -* type: `object` -* defined in this schema - -### baseline Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `phantom`| | Optional | -| `splunk`| | Optional | - - - -#### phantom - - -`phantom` - -* is optional -* type: reference - -##### phantom Type - - -* []() – `#/definitions/phantom` - - - - - - - -#### splunk - - -`splunk` - -* is optional -* type: reference - -##### splunk Type - - -* []() – `#/definitions/splunk` - - - - - - - - - - -## creation_date - -The date the baseline manifest was created - -`creation_date` +`author` * is **required** * type: `string` +* default: `""` * defined in this schema -### creation_date Type +### author Type `string` @@ -116,55 +47,27 @@ The date the baseline manifest was created -### creation_date Example +### author Example ```json -"2019-02-14" +"Bahvin Patel, Splunk" ``` -## data_metadata +## date -Information about the date being ingested +date of creation or modification, format yyyy-mm-dd -`data_metadata` +`date` * is **required** -* type: `object` +* type: `string` +* default: `""` * defined in this schema -### data_metadata Type +### date Type -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `data_eventtypes`| array | Optional | -| `data_models`| array | Optional | -| `data_source`| array | **Required** | -| `data_sourcetypes`| array | Optional | -| `providing_technologies`| array | **Required** | - - - -#### data_eventtypes - -A list of eventtypes, if any, used by this search - -`data_eventtypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_eventtypes Type - - -Array type: `string[]` - -All items must be of the type: `string` @@ -172,278 +75,22 @@ All items must be of the type: - - -##### data_eventtypes Example +### date Example ```json -wineventlog +"2019-12-06" ``` - - -#### data_models - -A list of data models, if any, used by this search - -`data_models` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### data_models Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "type": "array", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ], - "simpletype": "`enum`", - "meta:enum": { - "Alerts": "", - "Application_State": "", - "Authentication": "", - "Certificates": "", - "Change_Analysis": "", - "Change": "", - "Malware": "", - "Email": "", - "Identity_Management": "", - "Network_Resolution": "", - "Network_Traffic": "", - "Vulnerabilities": "", - "Web": "", - "Network_Sessions": "", - "Updates": "", - "Risk": "", - "Endpoint": "" - } - }, - "minItems": 0, - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### data_models Example - -```json -Network_Resolution -``` - - - - -#### data_source - -A high-level description of the type of data needed for this search to complete - -`data_source` - -* is **required** -* type: `string[]`* at least `0` items in the array - - -##### data_source Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_source Example - -```json -DNS -``` - - - - -#### data_sourcetypes - -The list of sourcetypes, if any, used by this search - -`data_sourcetypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_sourcetypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_sourcetypes Example - -```json -stream:dns -``` - - - - -#### providing_technologies - -A list of technologies that provide this data - -`providing_technologies` - -* is **required** -* type: `enum[]`* at least `0` items in the array - - -##### providing_technologies Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften" - ], - "simpletype": "`enum`", - "meta:enum": { - "Apache": "", - "AWS": "", - "Bro": "", - "Microsoft Windows": "", - "Linux": "", - "macOS": "", - "Netbackup": "", - "Splunk Enterprise": "", - "Splunk Enterprise Security": "", - "Splunk Stream": "", - "Active Directory": "", - "Bluecoat": "", - "Carbon Black Response": "", - "Carbon Black Protect": "", - "CrowdStrike Falcon": "", - "Microsoft Exchange": "", - "Nessus": "", - "Palo Alto Firewall": "", - "Qualys": "", - "Sysmon": "", - "Tanium": "", - "Ziften": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### providing_technologies Example - -```json -Bro -``` - - - - - - - ## description -A description of what the search is is doing to create a baseline +A detailed description of the baseline `description` * is **required** * type: `string` +* default: `""` * defined in this schema ### description Type @@ -459,148 +106,19 @@ A description of what the search is is doing to create a baseline ### description Example ```json -"The search takes corporate and common cloud provider domains configured under `cim_corporate_email_domains.csv`, `cim_corporate_web_domains.csv`, and `cloud_domains.csv` finds their responses across the last 30 days from data in the `Network_Traffic` datamodel, then stores the output under the `discovered_dns_records.csv` lookup" +"This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days" ``` -## eli5 - -Explain it like I am 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert - -`eli5` - -* is **required** -* type: `string` -* defined in this schema - -### eli5 Type - - -`string` - - - - - - -### eli5 Example - -```json -"Discover the DNS records and their answers for domains owned by the company using network traffic events. The discovered events are exported as a lookup named `discovered_dns_records.csv`" -``` - - -## entities - -A list of entities that will used in the story flow or are relevant to the security investigation. - -`entities` - -* is optional -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### entities Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of entities that will used in the story flow or are relevant to the security investigation.", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user" - ], - "simpletype": "`enum`", - "meta:enum": { - "accessKeyId": "", - "arn": "", - "awsRegion": "", - "bucketName": "", - "City": "", - "Country": "", - "dest_port": "", - "dest": "", - "event_id": "", - "instanceId": "", - "message_id": "", - "networkAclId": "", - "process_name": "", - "process": "", - "recipient": "", - "Region": "", - "resourceId": "", - "session_id": "", - "src_ip": "", - "src_mac": "", - "src_user": "", - "src": "", - "user": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -### entities Examples - -```json -"dest" -``` - -```json -"user" -``` - - - ## how_to_implement -A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications +information about how to implement. Only needed for non standard implementations. `how_to_implement` -* is **required** +* is optional * type: `string` +* default: `""` * defined in this schema ### how_to_implement Type @@ -616,18 +134,19 @@ A discussion on how to implement this search, from what needs to be ingested, co ### how_to_implement Example ```json -"To successfully implement this search, you must be ingesting DNS logs, and populating the Network_Resolution data model. Also make sure that the cim_corporate_web_domains and cim_corporate_email_domains lookups are populated with the domains owned by your corporation" +"This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." ``` ## id -The unique identifier for the search +UUID as unique identifier `id` * is **required** * type: `string` +* default: `""` * defined in this schema ### id Type @@ -643,188 +162,18 @@ The unique identifier for the search ### id Example ```json -"c096f721-8842-42ce-bfc7-74bd8c72b7c3" -``` - - -## known_false_positives - -Describe the known false postives while the analyst builds the baseline. - -`known_false_positives` - -* is **required** -* type: `string` -* defined in this schema - -### known_false_positives Type - - -`string` - - - - - - -### known_false_positives Example - -```json -"Please vet the lookup created by this baseline search." -``` - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is **required** -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person maintaining this search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person maintaining this search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## modification_date - -The date of the most recent modification to the search - -`modification_date` - -* is **required** -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - -### modification_date Example - -```json -"2019-02-14" +"fc0edc95-ff2b-48b0-9f6f-63da3789fd63" ``` ## name - -The name of the search that creates the baseline +### Name of baseline `name` * is **required** * type: `string` +* default: `""` * defined in this schema ### name Type @@ -840,425 +189,19 @@ The name of the search that creates the baseline ### name Example ```json -"Discover DNS records" +"Previously Seen AWS Regions" ``` -## original_authors - -A list of the original authors of the search - -`original_authors` - -* is **required** -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person who originally authored the search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person who originally authored the search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## product_type - -The type of baseline - -`product_type` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#product_type-known-values). - -### product_type Known Values -| Value | Description | -|-------|-------------| -| `splunk` | | -| `phantom` | | -| `uba` | | - - - -### product_type Example - -```json -"splunk" -``` - - -## spec_version - -The version of the detection search specification this manifest follows - -`spec_version` - -* is **required** -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - -### spec_version Example - -```json -"2.0" -``` - - -## version - -The version of the search - -`version` - -* is **required** -* type: `string` -* defined in this schema - -### version Type - - -`string` - - - - - - -### version Examples - -```json -"1" -``` - -```json -"2" -``` - - - -# Baseline Manifest Definitions - -| Property | Type | Group | -|----------|------|-------| -| [phantom_server](#phantom_server) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [playbook_name](#playbook_name) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [playbook_url](#playbook_url) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [schedule](#schedule) | `object` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/splunk` | -| [search](#search) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/splunk` | -| [sensitivity](#sensitivity) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | -| [severity](#severity) | `string` | `https://api.splunkresearch.com/schemas/baselines.json#/definitions/phantom` | - -## phantom_server - -IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname) - -`phantom_server` - -* is optional -* type: `string` -* defined in this schema - -### phantom_server Type - - -`string` - - - - - - -### phantom_server Example - -```json -"automation (hostname)" -``` - - -## playbook_name - -Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment - -`playbook_name` - -* is optional -* type: `string` -* defined in this schema - -### playbook_name Type - - -`string` - - - - - - -### playbook_name Example - -```json -"community/dns_hijack_investigation" -``` - - -## playbook_url - -Url of the playbook on Phantom website. - -`playbook_url` - -* is optional -* type: `string` -* defined in this schema - -### playbook_url Type - - -`string` - - - - - - -### playbook_url Example - -```json -"https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" -``` - - -## schedule - -Various fields to assist in scheduling the search - -`schedule` - -* is optional -* type: `object` -* defined in this schema - -### schedule Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `cron_schedule`| string | Optional | -| `earliest_time`| string | Optional | -| `latest_time`| string | Optional | - - - -#### cron_schedule - -Schedule of the search in cron format - -`cron_schedule` - -* is optional -* type: `string` - -##### cron_schedule Type - - -`string` - - - - - - -##### cron_schedule Example - -```json -0 * * * * -``` - - - - -#### earliest_time - -The earliest time the search should run in Splunk format - -`earliest_time` - -* is optional -* type: `string` - -##### earliest_time Type - - -`string` - - - - - - -##### earliest_time Example - -```json --70m@m -``` - - - - -#### latest_time - -The latest time tes search should run against in Splunk format - -`latest_time` - -* is optional -* type: `string` - -##### latest_time Type - - -`string` - - - - - - -##### latest_time Example - -```json --10m@m -``` - - - - - - - ## search -The search (in SPL) executed within core Splunk for investgation. +The Splunk search for the baseline `search` -* is optional +* is **required** * type: `string` +* default: `""` * defined in this schema ### search Type @@ -1274,60 +217,67 @@ The search (in SPL) executed within core Splunk for investgation. ### search Example ```json -"| inputlookup discovered_dns_records.csv | rename answer as discovered_answer | join domain[|tstats summariesonly=true count values(DNS.record_type) as type, values(DNS.answer) as current_answer values(DNS.src) as src from datamodel=Network_Resolution where DNS.message_type=RESPONSE DNS.answer!=\"unknown\" DNS.answer!=\"\" by DNS.query | rename DNS.query as query | where query!=\"unknown\" | rex field=query \"(?\\w+\\.\\w+?)(?:$|/)\"] | makemv delim=\" \" answer | makemv delim=\" \" type | sort -count | table count,src,domain,type,query,current_answer,discovered_answer | makemv current_answer | mvexpand current_answer | makemv discovered_answer | eval n=mvfind(discovered_answer, current_answer) | where isnull(n)" +"cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" ``` -## sensitivity +## tags -TLP colors (White, Green, Amber or Red) +An array of key value pairs for tagging -`sensitivity` +`tags` -* is optional -* type: `string` +* is **required** +* type: `object` +* default: `{}` * defined in this schema -### sensitivity Type +### tags Type -`string` +`object` with following properties: + + +| Property | Type | Required | +|----------|------|----------| - - -### sensitivity Example +### tags Example ```json -"green" +{ + "analytics_story": "suspicious_aws_ec2_activities", + "custom_key": "custom_value" +} ``` -## severity +## version -Severity in phantom (High, Medium, Low) +version of baseline, e.g. 1 or 2 ... -`severity` +`version` -* is optional -* type: `string` +* is **required** +* type: `integer` +* default: `0` * defined in this schema -### severity Type +### version Type -`string` +`integer` -### severity Example +### version Example ```json -"medium" +1 ``` diff --git a/docs/spec/deployments.spec.md b/docs/spec/deployments.spec.md new file mode 100644 index 0000000000..8d86ed47ff --- /dev/null +++ b/docs/spec/deployments.spec.md @@ -0,0 +1,656 @@ + +# Deployment Schema Schema + +``` +http://example.com/example.json +``` + +schema for deployment + +| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | +|----------|------------|--------|--------------|-------------------|-----------------------|------------| +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | + +# Deployment Schema Properties + +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [alert_action](#alert_action) | `object` | **Required** | No | `{}` | Deployment Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Deployment Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Deployment Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Deployment Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Deployment Schema (this schema) | +| [scheduling](#scheduling) | `object` | **Required** | No | `{}` | Deployment Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Deployment Schema (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | + +## alert_action + +Set alert action parameter for search + +`alert_action` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### alert_action Type + + +`object` with following properties: + + +| Property | Type | Required | Default | +|----------|------|----------|---------| +| `email`| object | Optional | `{}` | +| `index`| object | Optional | `{}` | +| `notable`| object | Optional | `{}` | + + + +#### email + +By enabling it, an email is sent with the results + +`email` + +* is optional +* type: `object` +* default: `{}` + + +##### email Type + + +`object` with following properties: + + +| Property | Type | Required | Default | +|----------|------|----------|---------| +| `message`| string | **Required** | `""` | +| `subject`| string | **Required** | `""` | +| `to`| string | **Required** | `""` | + + + +#### message + +message of email + +`message` + +* is **required** +* type: `string` +* default: `""` + + +##### message Type + + +`string` + + + + + + +##### message Example + +```json +Splunk Alert $name$ triggered %fields% +``` + + + + +#### subject + +Subject of email + +`subject` + +* is **required** +* type: `string` +* default: `""` + + +##### subject Type + + +`string` + + + + + + +##### subject Example + +```json +Splunk Alert $name$ +``` + + + + +#### to + +Recipient of email + +`to` + +* is **required** +* type: `string` +* default: `""` + + +##### to Type + + +`string` + + + + + + +##### to Example + +```json +test@test.com +``` + + + + + +##### email Example + +```json +[object Object] +``` + + + + +#### index + +By enabling it, the results are stored in another index + +`index` + +* is optional +* type: `object` +* default: `{}` + + +##### index Type + + +`object` with following properties: + + +| Property | Type | Required | Default | +|----------|------|----------|---------| +| `name`| string | **Required** | `""` | + + + +#### name + +Name of the index + +`name` + +* is **required** +* type: `string` +* default: `""` + + +##### name Type + + +`string` + + + + + + +##### name Example + +```json +asx +``` + + + + + +##### index Example + +```json +[object Object] +``` + + + + +#### notable + +By enabling it, a notable is generated + +`notable` + +* is optional +* type: `object` +* default: `{}` + + +##### notable Type + + +`object` with following properties: + + +| Property | Type | Required | Default | +|----------|------|----------|---------| +| `rule_description`| string | **Required** | `""` | +| `rule_title`| string | **Required** | `""` | + + + +#### rule_description + +Rule description of the notable event + +`rule_description` + +* is **required** +* type: `string` +* default: `""` + + +##### rule_description Type + + +`string` + + + + + + +##### rule_description Example + +```json +%description% +``` + + + + +#### rule_title + +Rule title of the notable event + +`rule_title` + +* is **required** +* type: `string` +* default: `""` + + +##### rule_title Type + + +`string` + + + + + + +##### rule_title Example + +```json +%name% +``` + + + + + +##### notable Example + +```json +[object Object] +``` + + + + + +### alert_action Example + +```json +{ + "email": { + "message": "Splunk Alert $name$ triggered %fields%", + "subject": "Splunk Alert $name$", + "to": "test@test.com" + }, + "index": { + "name": "asx" + }, + "notable": { + "rule_description": "%description%", + "rule_title": "%name%" + } +} +``` + + +## date + +date of creation or modification, format yyyy-mm-dd + +`date` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### date Type + + +`string` + + + + + + +### date Example + +```json +"2019-12-06" +``` + + +## description + +description of the deployment configuration + +`description` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### description Type + + +`string` + + + + + + +### description Example + +```json +"This deployment configuration provides a standard scheduling policy over all rules." +``` + + +## id + +uuid as unique identifier + +`id` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### id Type + + +`string` + + + + + + +### id Example + +```json +"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" +``` + + +## name + +Name of deployment configuration + +`name` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### name Type + + +`string` + + + + + + +### name Example + +```json +"Deployment Configuration all Detections" +``` + + +## scheduling + +allows to set scheduling parameter + +`scheduling` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### scheduling Type + + +`object` with following properties: + + +| Property | Type | Required | Default | +|----------|------|----------|---------| +| `cron_schedule`| string | **Required** | `""` | +| `earliest_time`| string | **Required** | `""` | +| `latest_time`| string | **Required** | `""` | +| `schedule_window`| string | Optional | `""` | + + + +#### cron_schedule + +Cron schedule to schedule the Splunk searches. + +`cron_schedule` + +* is **required** +* type: `string` +* default: `""` + + +##### cron_schedule Type + + +`string` + + + + + + +##### cron_schedule Example + +```json +*/10 * * * * +``` + + + + +#### earliest_time + +earliest time of search + +`earliest_time` + +* is **required** +* type: `string` +* default: `""` + + +##### earliest_time Type + + +`string` + + + + + + +##### earliest_time Example + +```json +-10m +``` + + + + +#### latest_time + +latest time of search + +`latest_time` + +* is **required** +* type: `string` +* default: `""` + + +##### latest_time Type + + +`string` + + + + + + +##### latest_time Example + +```json +now +``` + + + + +#### schedule_window + +schedule window for search + +`schedule_window` + +* is optional +* type: `string` +* default: `""` + + +##### schedule_window Type + + +`string` + + + + + + +##### schedule_window Example + +```json +auto +``` + + + + + +### scheduling Example + +```json +{ + "cron_schedule": "*/10 * * * *", + "earliest_time": "-10m", + "latest_time": "now", + "schedule_window": "auto" +} +``` + + +## tags + +An array of key value pairs for tagging + +`tags` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### tags Type + + +`object` with following properties: + + +| Property | Type | Required | +|----------|------|----------| + + + + +### tags Example + +```json +{ + "analytics_story": "credential_dumping" +} +``` + diff --git a/docs/spec/detections.spec.md b/docs/spec/detections.spec.md index d3ac1ec0ff..8fb01effff 100644 --- a/docs/spec/detections.spec.md +++ b/docs/spec/detections.spec.md @@ -1,110 +1,46 @@ -# Detection Manifest Schema +# Detection Schema Schema ``` -https://api.splunkresearch.com/schemas/detections.json +http://example.com/example.json ``` -A object that defines the parameters for detecting things using various Splunk capabilities +schema for detections | Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | |----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | Yes | Experimental | No | Forbidden | Permitted | | +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | -# Detection Manifest Properties +# Detection Schema Properties -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [asset_type](#asset_type) | `string` | Optional | No | Detection Manifest (this schema) | -| [baselines](#baselines) | `object[]` | Optional | No | Detection Manifest (this schema) | -| [confidence](#confidence) | `enum` | **Required** | No | Detection Manifest (this schema) | -| [creation_date](#creation_date) | `string` | **Required** | No | Detection Manifest (this schema) | -| [data_metadata](#data_metadata) | `object` | **Required** | No | Detection Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Detection Manifest (this schema) | -| [detect](#detect) | `object` | **Required** | No | Detection Manifest (this schema) | -| [eli5](#eli5) | `string` | **Required** | No | Detection Manifest (this schema) | -| [entities](#entities) | `enum[]` | Optional | No | Detection Manifest (this schema) | -| [how_to_implement](#how_to_implement) | `string` | **Required** | No | Detection Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Detection Manifest (this schema) | -| [investigations](#investigations) | `object[]` | Optional | No | Detection Manifest (this schema) | -| [known_false_positives](#known_false_positives) | `string` | **Required** | No | Detection Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | **Required** | No | Detection Manifest (this schema) | -| [mappings](#mappings) | `object` | Optional | No | Detection Manifest (this schema) | -| [modification_date](#modification_date) | `string` | **Required** | No | Detection Manifest (this schema) | -| [name](#name) | `string` | Optional | No | Detection Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | **Required** | No | Detection Manifest (this schema) | -| [product_type](#product_type) | `enum` | **Required** | No | Detection Manifest (this schema) | -| [references](#references) | `string[]` | Optional | No | Detection Manifest (this schema) | -| [responses](#responses) | `object[]` | Optional | No | Detection Manifest (this schema) | -| [security_domain](#security_domain) | `enum` | **Required** | No | Detection Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | Optional | No | Detection Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Detection Manifest (this schema) | +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [how_to_implement](#how_to_implement) | `string` | Optional | No | `""` | Detection Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [known_false_positives](#known_false_positives) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [references](#references) | `string[]` | Optional | No | `[]` | Detection Schema (this schema) | +| [search](#search) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Detection Schema (this schema) | +| [type](#type) | `string` | **Required** | No | `""` | Detection Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Detection Schema (this schema) | | `*` | any | Additional | Yes | this schema *allows* additional properties | -## asset_type +## author -Designates the type of asset being investigated +Author of the detection -`asset_type` - -* is optional -* type: `string` -* defined in this schema - -### asset_type Type - - -`string` - - - - - - -### asset_type Example - -```json -"Endpoint" -``` - - -## baselines - -An array of the baseline objects to exectute before the detection - -`baselines` - -* is optional -* type: `object[]` -* defined in this schema - -### baselines Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `id`| string | **Required** | -| `name`| string | **Required** | -| `type`| | Optional | - - - -#### id - -UUID of the baseline object - -`id` +`author` * is **required** * type: `string` +* default: `""` +* defined in this schema -##### id Type +### author Type `string` @@ -114,116 +50,25 @@ UUID of the baseline object -##### id Example +### author Example ```json -c096f721-8842-42ce-bfc7-74bd8c72b7c3 +"Patrick Bareiss, Splunk" ``` +## date +date of creation or modification, format yyyy-mm-dd -#### name - -name of baseline object - -`name` +`date` * is **required** * type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Discover DNS records -``` - - - - -#### type - -Type of baseline to execute - -`type` - -* is optional -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#baselines-known-values). - -##### type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - -##### type Example - -```json -splunk -``` - - - - - - - - - -## confidence - -Confidence that detected behavior is malicious - -`confidence` - -* is **required** -* type: `enum` +* default: `""` * defined in this schema -The value of this property **must** be equal to one of the [known values below](#confidence-known-values). - -### confidence Known Values -| Value | Description | -|-------|-------------| -| `high` | | -| `medium` | | -| `low` | | - - - -### confidence Example - -```json -"high" -``` - - -## creation_date - -The date the story manifest was created - -`creation_date` - -* is **required** -* type: `string` -* defined in this schema - -### creation_date Type +### date Type `string` @@ -233,336 +78,22 @@ The date the story manifest was created -### creation_date Example +### date Example ```json -"2019-02-14" +"2019-12-06" ``` -## data_metadata - -Information about the date being ingested - -`data_metadata` - -* is **required** -* type: `object` -* defined in this schema - -### data_metadata Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `data_eventtypes`| array | Optional | -| `data_models`| array | Optional | -| `data_source`| array | **Required** | -| `data_sourcetypes`| array | Optional | -| `providing_technologies`| array | **Required** | - - - -#### data_eventtypes - -A list of eventtypes, if any, used by this search - -`data_eventtypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_eventtypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_eventtypes Example - -```json -wineventlog -``` - - - - -#### data_models - -A list of data models, if any, used by this search - -`data_models` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### data_models Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of data models, if any, used by this search", - "examples": [ - "Network_Resolution" - ], - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ], - "simpletype": "`enum`", - "meta:enum": { - "Alerts": "", - "Application_State": "", - "Authentication": "", - "Certificates": "", - "Change_Analysis": "", - "Change": "", - "Malware": "", - "Email": "", - "Identity_Management": "", - "Network_Resolution": "", - "Network_Traffic": "", - "Vulnerabilities": "", - "Web": "", - "Network_Sessions": "", - "Updates": "", - "Risk": "", - "Endpoint": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### data_models Example - -```json -Network_Resolution -``` - - - - -#### data_source - -A high-level description of the type of data needed for this search to complete - -`data_source` - -* is **required** -* type: `string[]`* at least `0` items in the array - - -##### data_source Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_source Example - -```json -DNS -``` - - - - -#### data_sourcetypes - -The list of sourcetypes, if any, used by this search - -`data_sourcetypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_sourcetypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -##### data_sourcetypes Example - -```json -stream:dns -``` - - - - -#### providing_technologies - -A list of technologies that provide this data - -`providing_technologies` - -* is **required** -* type: `enum[]`* at least `0` items in the array - - -##### providing_technologies Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of technologies that provide this data", - "examples": [ - "Bro" - ], - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "OSquery" - ], - "simpletype": "`enum`", - "meta:enum": { - "Apache": "", - "AWS": "", - "Bro": "", - "Microsoft Windows": "", - "Linux": "", - "macOS": "", - "Netbackup": "", - "Splunk Enterprise": "", - "Splunk Enterprise Security": "", - "Splunk Stream": "", - "Active Directory": "", - "Bluecoat": "", - "Carbon Black Response": "", - "Carbon Black Protect": "", - "CrowdStrike Falcon": "", - "Microsoft Exchange": "", - "Nessus": "", - "Palo Alto Firewall": "", - "Qualys": "", - "Sysmon": "", - "Tanium": "", - "Ziften": "", - "OSquery": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### providing_technologies Example - -```json -Bro -``` - - - - - - - ## description -A description of what the detection is designed to find +A detailed description of the detection `description` * is **required** * type: `string` +* default: `""` * defined in this schema ### description Type @@ -578,231 +109,19 @@ A description of what the detection is designed to find ### description Example ```json -"The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day." +"dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump." ``` -## detect - - -`detect` - -* is **required** -* type: `object` -* defined in this schema - -### detect Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `phantom`| | Optional | -| `splunk`| | Optional | -| `uba`| | Optional | - - - -#### phantom - - -`phantom` - -* is optional -* type: reference - -##### phantom Type - - -* []() – `#/definitions/phantom` - - - - - - - -#### splunk - - -`splunk` - -* is optional -* type: reference - -##### splunk Type - - -* []() – `#/definitions/splunk` - - - - - - - -#### uba - - -`uba` - -* is optional -* type: reference - -##### uba Type - - -* []() – `#/definitions/uba` - - - - - - - - - - -## eli5 - -Explain it like I am 5 - A detail description of the SPL of the search, written in a style that can be understood by a future Splunk expert - -`eli5` - -* is **required** -* type: `string` -* defined in this schema - -### eli5 Type - - -`string` - - - - - - -### eli5 Example - -```json -"Using a lookup `discover_dns_records` generated by support search \"Discover DNS records\" we check previous network traffic and make sure the responses have not changed." -``` - - -## entities - -A list of entities that is outputed by the search... - -`entities` - -* is optional -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### entities Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of entities that is outputed by the search...", - "examples": [ - "dest", - "user" - ], - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user" - ], - "simpletype": "`enum`", - "meta:enum": { - "accessKeyId": "", - "arn": "", - "awsRegion": "", - "bucketName": "", - "City": "", - "Country": "", - "dest_port": "", - "dest": "", - "event_id": "", - "instanceId": "", - "message_id": "", - "networkAclId": "", - "process_name": "", - "process": "", - "recipient": "", - "Region": "", - "resourceId": "", - "session_id": "", - "src_ip": "", - "src_mac": "", - "src_user": "", - "src": "", - "user": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -### entities Examples - -```json -"dest" -``` - -```json -"user" -``` - - - ## how_to_implement -A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications +information about how to implement. Only needed for non standard implementations. `how_to_implement` -* is **required** +* is optional * type: `string` +* default: `""` * defined in this schema ### how_to_implement Type @@ -815,15 +134,22 @@ A discussion on how to implement this search, from what needs to be ingested, co +### how_to_implement Example + +```json +"This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." +``` + ## id -The unique identifier for the detection +UUID as unique identifier `id` * is **required** * type: `string` +* default: `""` * defined in this schema ### id Type @@ -839,135 +165,19 @@ The unique identifier for the detection ### id Example ```json -"To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search \"Discover DNS record\"." +"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" ``` -## investigations - -An array of the investigation objects to exectute on the detection results - -`investigations` - -* is optional -* type: `object[]` -* defined in this schema - -### investigations Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `id`| string | **Required** | -| `name`| string | **Required** | -| `product_type`| string | **Required** | - - - -#### id - -UUID of the investigation object - -`id` - -* is **required** -* type: `string` - -##### id Type - - -`string` - - - - - - -##### id Example - -```json -bc11a8cf-35e7-4bb2-8140-e756cc06fd72 -``` - - - - -#### name - -Name of investigation object - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Get DNS Server History for a host -``` - - - - -#### product_type - -Type of investigation object - -`product_type` - -* is **required** -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#investigations-known-values). - -##### product_type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - -##### product_type Example - -```json -splunk -``` - - - - - - - - - ## known_false_positives -Scenarios in which detected behavior is benig, coupled with suggestions on how to verify the behavior +known false postives `known_false_positives` * is **required** * type: `string` +* default: `""` * defined in this schema ### known_false_positives Type @@ -983,804 +193,18 @@ Scenarios in which detected behavior is benig, coupled with suggestions on how t ### known_false_positives Example ```json -"Legitimate DNS changes can be detected in this search. Investigate, verify and update the list of provided current answers for the domains in question as appropriate." -``` - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is **required** -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person maintaining this search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person maintaining this search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## mappings - -Mappings to various industry standards and frameworks - -`mappings` - -* is optional -* type: `object` -* defined in this schema - -### mappings Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `cis20`| array | Optional | -| `emoji`| array | Optional | -| `kill_chain_phases`| array | Optional | -| `mitre_attack`| array | Optional | -| `nist`| array | Optional | - - - -#### cis20 - -A list of critical security controls this search helps you implement - -`cis20` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### cis20 Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of critical security controls this search helps you implement", - "examples": [ - "CIS 12" - ], - "items": { - "enum": [ - "CIS 1", - "CIS 2", - "CIS 3", - "CIS 4", - "CIS 5", - "CIS 6", - "CIS 7", - "CIS 8", - "CIS 9", - "CIS 10", - "CIS 11", - "CIS 12", - "CIS 13", - "CIS 14", - "CIS 15", - "CIS 16", - "CIS 17", - "CIS 18", - "CIS 19", - "CIS 20" - ], - "simpletype": "`enum`", - "meta:enum": { - "CIS 1": "", - "CIS 2": "", - "CIS 3": "", - "CIS 4": "", - "CIS 5": "", - "CIS 6": "", - "CIS 7": "", - "CIS 8": "", - "CIS 9": "", - "CIS 10": "", - "CIS 11": "", - "CIS 12": "", - "CIS 13": "", - "CIS 14": "", - "CIS 15": "", - "CIS 16": "", - "CIS 17": "", - "CIS 18": "", - "CIS 19": "", - "CIS 20": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### cis20 Example - -```json -CIS 12 -``` - - - - -#### emoji - -A list of security emojis that will help UBA understand this alert as an external alarm - -`emoji` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### emoji Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of security emojis that will help UBA understand this alert as an external alarm", - "examples": [ - "EndPoint" - ], - "items": { - "enum": [ - "EndPoint", - "AD", - "Firewall", - "ApplicationLog", - "IPS", - "CloudData", - "Correlation", - "Printer", - "Badge" - ], - "simpletype": "`enum`", - "meta:enum": { - "EndPoint": "", - "AD": "", - "Firewall": "", - "ApplicationLog": "", - "IPS": "", - "CloudData": "", - "Correlation": "", - "Printer": "", - "Badge": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### emoji Example - -```json -EndPoint -``` - - - - -#### kill_chain_phases - -A list of kill-chain phases to which the search applies - -`kill_chain_phases` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### kill_chain_phases Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of kill-chain phases to which the search applies", - "examples": [ - "Reconnaissance" - ], - "items": { - "enum": [ - "Reconnaissance", - "Weaponization", - "Delivery", - "Exploitation", - "Installation", - "Command and Control", - "Actions on Objectives" - ], - "simpletype": "`enum`", - "meta:enum": { - "Reconnaissance": "", - "Weaponization": "", - "Delivery": "", - "Exploitation": "", - "Installation": "", - "Command and Control": "", - "Actions on Objectives": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### kill_chain_phases Example - -```json -Reconnaissance -``` - - - - -#### mitre_attack - -A list of the techniques and tactics identified by the search - -`mitre_attack` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### mitre_attack Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of the techniques and tactics identified by the search", - "examples": [ - "Defense Evasion", - "Initial Access" - ], - "items": { - "enum": [ - "Initial Access", - "Execution", - "Persistence", - "Privilege Escalation", - "Defense Evasion", - "Credential Access", - "Discovery", - "Lateral Movement", - "Collection", - "Exfiltration", - "Command and Control", - "Command and Control Protocol", - "Commonly Used Port", - "Custom Cryptographic Protocol", - "DLL Injection", - "DLL Search Order Hijacking", - "DLL Side-Loading", - "Data Compressed", - "Data Encrypted", - "Data Obfuscation", - "Data Staged", - "Data Transfer Size Limits", - "Data from Local System", - "Data from Network Shared Drive", - "Data from Removable Media", - "Disabling Security Tools", - "Email Collection", - "Execution through API", - "Exfiltration Over Alternative Protocol", - "Exfiltration Over Command and Control Channel", - "Exfiltration Over Other Network Medium", - "Exfiltration Over Physical Medium", - "Exploitation of Vulnerability", - "Fallback Channels", - "File Deletion", - "File System Logical Offsets", - "File System Permissions Weakness", - "File and Directory Discovery", - "Graphical User Interface", - "Hypervisor", - "Indicator Blocking", - "Indicator Removal from Tools", - "Indicator Removal on Host", - "Input Capture", - "InstallUtil", - "Legitimate Credentials", - "Local Network Configuration Discovery", - "Local Network Connections Discovery", - "Local Port Monitor", - "Logon Scripts", - "MSBuild", - "Masquerading", - "Modify Existing Service", - "Modify Registry", - "Multi-Stage Channels", - "Multiband Communication", - "Multilayer Encryption", - "NTFS Extended Attributes", - "Network Service Scanning", - "Network Share Connection Removal", - "Network Sniffing", - "New Service", - "Obfuscated Files or Information", - "Pass the Hash", - "Pass the Ticket", - "Path Interception", - "Peripheral Device Discovery", - "Permission Groups Discovery", - "PowerShell", - "Process Discovery", - "Process Hollowing", - "Query Registry", - "Redundant Access", - "Registry Run Keys / Start Folder", - "Regsvcs/Regasm", - "Regsvr32", - "Remote Desktop Protocol", - "Create Account", - "Remote File Copy", - "Remote Services", - "Remote System Discovery", - "Replication Through Removable Media", - "Rootkit", - "Rundll32", - "Scheduled Task", - "Scheduled Transfer", - "Screen Capture", - "Scripting", - "Security Software Discovery", - "Security Support Provider", - "Service Execution", - "Service Registry Permissions Weakness", - "Shared Webroot", - "Shortcut Modification", - "Software Packing", - "Standard Application Layer Protocol", - "Standard Cryptographic Protocol", - "Standard Non-Application Layer Protocol", - "System Information Discovery", - "System Owner/User Discovery", - "System Service Discovery", - "System Time Discovery", - "Taint Shared Content", - "Third-party Software", - "Timestomp", - "Two-Factor Authentication Interception", - "Uncommonly Used Port", - "Video Capture", - "Valid Accounts", - "Web Service", - "Web Shell", - "Windows Admin Shares", - "Windows Management Instrumentation Event Subscription", - "Windows Management Instrumentation", - "Windows Remote Management", - "Winlogon Helper DLL", - "Exploitation for Privilege Escalation" - ], - "simpletype": "`enum`", - "meta:enum": { - "Initial Access": "", - "Execution": "", - "Persistence": "", - "Privilege Escalation": "", - "Defense Evasion": "", - "Credential Access": "", - "Discovery": "", - "Lateral Movement": "", - "Collection": "", - "Exfiltration": "", - "Command and Control": "", - "Command and Control Protocol": "", - "Commonly Used Port": "", - "Custom Cryptographic Protocol": "", - "DLL Injection": "", - "DLL Search Order Hijacking": "", - "DLL Side-Loading": "", - "Data Compressed": "", - "Data Encrypted": "", - "Data Obfuscation": "", - "Data Staged": "", - "Data Transfer Size Limits": "", - "Data from Local System": "", - "Data from Network Shared Drive": "", - "Data from Removable Media": "", - "Disabling Security Tools": "", - "Email Collection": "", - "Execution through API": "", - "Exfiltration Over Alternative Protocol": "", - "Exfiltration Over Command and Control Channel": "", - "Exfiltration Over Other Network Medium": "", - "Exfiltration Over Physical Medium": "", - "Exploitation of Vulnerability": "", - "Fallback Channels": "", - "File Deletion": "", - "File System Logical Offsets": "", - "File System Permissions Weakness": "", - "File and Directory Discovery": "", - "Graphical User Interface": "", - "Hypervisor": "", - "Indicator Blocking": "", - "Indicator Removal from Tools": "", - "Indicator Removal on Host": "", - "Input Capture": "", - "InstallUtil": "", - "Legitimate Credentials": "", - "Local Network Configuration Discovery": "", - "Local Network Connections Discovery": "", - "Local Port Monitor": "", - "Logon Scripts": "", - "MSBuild": "", - "Masquerading": "", - "Modify Existing Service": "", - "Modify Registry": "", - "Multi-Stage Channels": "", - "Multiband Communication": "", - "Multilayer Encryption": "", - "NTFS Extended Attributes": "", - "Network Service Scanning": "", - "Network Share Connection Removal": "", - "Network Sniffing": "", - "New Service": "", - "Obfuscated Files or Information": "", - "Pass the Hash": "", - "Pass the Ticket": "", - "Path Interception": "", - "Peripheral Device Discovery": "", - "Permission Groups Discovery": "", - "PowerShell": "", - "Process Discovery": "", - "Process Hollowing": "", - "Query Registry": "", - "Redundant Access": "", - "Registry Run Keys / Start Folder": "", - "Regsvcs/Regasm": "", - "Regsvr32": "", - "Remote Desktop Protocol": "", - "Create Account": "", - "Remote File Copy": "", - "Remote Services": "", - "Remote System Discovery": "", - "Replication Through Removable Media": "", - "Rootkit": "", - "Rundll32": "", - "Scheduled Task": "", - "Scheduled Transfer": "", - "Screen Capture": "", - "Scripting": "", - "Security Software Discovery": "", - "Security Support Provider": "", - "Service Execution": "", - "Service Registry Permissions Weakness": "", - "Shared Webroot": "", - "Shortcut Modification": "", - "Software Packing": "", - "Standard Application Layer Protocol": "", - "Standard Cryptographic Protocol": "", - "Standard Non-Application Layer Protocol": "", - "System Information Discovery": "", - "System Owner/User Discovery": "", - "System Service Discovery": "", - "System Time Discovery": "", - "Taint Shared Content": "", - "Third-party Software": "", - "Timestomp": "", - "Two-Factor Authentication Interception": "", - "Uncommonly Used Port": "", - "Video Capture": "", - "Valid Accounts": "", - "Web Service": "", - "Web Shell": "", - "Windows Admin Shares": "", - "Windows Management Instrumentation Event Subscription": "", - "Windows Management Instrumentation": "", - "Windows Remote Management": "", - "Winlogon Helper DLL": "", - "Exploitation for Privilege Escalation": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### mitre_attack Examples - -```json -Defense Evasion -``` - -```json -Initial Access -``` - - - - - -#### nist - -A list of the NIST controls the search helps you implement - -`nist` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### nist Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of the NIST controls the search helps you implement", - "examples": [ - "ID.AM", - "PR.PT" - ], - "items": { - "enum": [ - "ID.AM", - "ID.RA", - "PR.DS", - "PR.IP", - "PR.AC", - "PR.PT", - "PR.AT", - "PR.MA", - "DE.CM", - "DE.DP", - "DE.AE", - "RS.MI", - "RS.AN", - "RS.RP", - "RS.IM", - "RS.CO", - "RC.IM", - "RC.CO" - ], - "simpletype": "`enum`", - "meta:enum": { - "ID.AM": "", - "ID.RA": "", - "PR.DS": "", - "PR.IP": "", - "PR.AC": "", - "PR.PT": "", - "PR.AT": "", - "PR.MA": "", - "DE.CM": "", - "DE.DP": "", - "DE.AE": "", - "RS.MI": "", - "RS.AN": "", - "RS.RP": "", - "RS.IM": "", - "RS.CO": "", - "RC.IM": "", - "RC.CO": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - -##### nist Examples - -```json -ID.AM -``` - -```json -PR.PT -``` - - - - - - - - -## modification_date - -The date of the most recent modification to the search - -`modification_date` - -* is **required** -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - -### modification_date Example - -```json -"2019-02-14" +"Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual." ``` ## name - -The name of the detection +### Name of detection `name` -* is optional +* is **required** * type: `string` +* default: `""` * defined in this schema ### name Type @@ -1796,163 +220,20 @@ The name of the detection ### name Example ```json -"DNS record changed" -``` - - -## original_authors - -A list of the original authors of the search - -`original_authors` - -* is **required** -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person who originally authored the search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person who originally authored the search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## product_type - -The type of detection - -`product_type` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#product_type-known-values). - -### product_type Known Values -| Value | Description | -|-------|-------------| -| `uba` | | -| `splunk` | | -| `phantom` | | - - - -### product_type Example - -```json -"phantom" +"Access LSASS Memory for Dump Creation" ``` ## references -A list of URLs that give more information about the search +A list of references for this detection `references` * is optional * type: `string[]` -* at least `0` items in the array + +* default: `[]` * defined in this schema ### references Type @@ -1966,6 +247,9 @@ All items must be of the type: + +An explanation about the purpose of this instance. + @@ -1973,47 +257,85 @@ All items must be of the type: ### references Example ```json -"https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" +[ + "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" +] ``` -## responses +## search -An array of the response objects to exectute on the detection results +The Splunk search for the detection -`responses` +`search` -* is optional -* type: `object[]` +* is **required** +* type: `string` +* default: `""` * defined in this schema -### responses Type +### search Type -Array type: `object[]` +`string` + + + + + + +### search Example + +```json +"`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter`" +``` + + +## tags + +An array of key value pairs for tagging + +`tags` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### tags Type + -All items must be of the type: `object` with following properties: | Property | Type | Required | |----------|------|----------| -| `id`| string | **Required** | -| `name`| string | **Required** | -| `product_type`| | **Required** | -#### id -UUID of the Respose object +### tags Example -`id` +```json +{ + "analytics_story": "credential_dumping", + "custom_key": "custom_value" +} +``` + + +## type + +type of detection + +`type` * is **required** * type: `string` +* default: `""` +* defined in this schema -##### id Type +### type Type `string` @@ -2023,147 +345,28 @@ UUID of the Respose object -##### id Example +### type Example ```json -1169w17b-ef78-4b59-aae8-5369073014e1 -``` - - - - -#### name - -Name of Response Object - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -DNS Hijack Reponse -``` - - - - -#### product_type - -Type of baseline to execute - -`product_type` - -* is **required** -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#responses-known-values). - -##### product_type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - -##### product_type Example - -```json -phantom -``` - - - - - - - - - -## security_domain - -The high-level security area to which the search belongs - -`security_domain` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#security_domain-known-values). - -### security_domain Known Values -| Value | Description | -|-------|-------------| -| `access` | | -| `endpoint` | | -| `network` | | -| `threat` | | - - - -### security_domain Example - -```json -"endpoint" -``` - - -## spec_version - -The version of the detection specification this manifest follows - -`spec_version` - -* is optional -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - -### spec_version Example - -```json -"2.0" +"ESCU" ``` ## version -The version of the detection +version of detection, e.g. 1 or 2 ... `version` * is **required** -* type: `string` +* type: `integer` +* default: `0` * defined in this schema ### version Type -`string` +`integer` @@ -2173,675 +376,6 @@ The version of the detection ### version Example ```json -"1" -``` - - -# Detection Manifest Definitions - -| Property | Type | Group | -|----------|------|-------| -| [correlation_rule](#correlation_rule) | `object` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [event_type](#event_type) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [model](#model) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [model_version](#model_version) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | -| [phantom_server](#phantom_server) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [playbook_name](#playbook_name) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [playbook_url](#playbook_url) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [sensitivity](#sensitivity) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [severity](#severity) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/phantom` | -| [threat_category](#threat_category) | `string` | `https://api.splunkresearch.com/schemas/detections.json#/definitions/uba` | - -## correlation_rule - -Various fields to enhance usability in Enterprise Security - -`correlation_rule` - -* is optional -* type: `object` -* defined in this schema - -### correlation_rule Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `notable`| object | Optional | -| `risk`| object | Optional | -| `schedule`| object | **Required** | -| `search`| string | **Required** | -| `suppress`| object | Optional | - - - -#### notable - -Various fields associated with creating a notable event - -`notable` - -* is optional -* type: `object` - -##### notable Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `nes_fields`| string | **Required** | -| `rule_description`| string | **Required** | -| `rule_title`| string | **Required** | - - - -#### nes_fields - -A list of suggested fields to be used for notable-event suppression - -`nes_fields` - -* is **required** -* type: `string` - -##### nes_fields Type - - -`string` - - - - - - - - - -#### rule_description - -Description of the notable event that will display in Incident Review - -`rule_description` - -* is **required** -* type: `string` - -##### rule_description Type - - -`string` - - - - - - - - - -#### rule_title - -Title of the notable event that will display in Incident Review - -`rule_title` - -* is **required** -* type: `string` - -##### rule_title Type - - -`string` - - - - - - - - - - - - - - -#### risk - -Fields associated with assigning risk to objects - -`risk` - -* is optional -* type: `object` - -##### risk Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `risk_object`| string | **Required** | -| `risk_object_type`| array | **Required** | -| `risk_score`| integer | **Required** | - - - -#### risk_object - -TThe field to which you are assigning risk - -`risk_object` - -* is **required** -* type: `string` - -##### risk_object Type - - -`string` - - - - - - - - - -#### risk_object_type - -The type of object to which you are assigning risk - -`risk_object_type` - -* is **required** -* type: `enum[]`* between `0` and `1` items in the array - - -##### risk_object_type Type - - -Array type: `enum[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### risk_score - -Score assigned to risk_object - -`risk_score` - -* is **required** -* type: `integer` - -##### risk_score Type - - -`integer` - - - - - - - - - - - - - - -#### schedule - -Various fields to assist in scheduling the search - -`schedule` - -* is **required** -* type: `object` - -##### schedule Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `cron_schedule`| string | Optional | -| `earliest_time`| string | Optional | -| `latest_time`| string | Optional | - - - -#### cron_schedule - -Schedule of the search in cron format - -`cron_schedule` - -* is optional -* type: `string` - -##### cron_schedule Type - - -`string` - - - - - - - - - -#### earliest_time - -The earliest time the search should run in Splunk format - -`earliest_time` - -* is optional -* type: `string` - -##### earliest_time Type - - -`string` - - - - - - - - - -#### latest_time - -The latest time tes search should run against in Splunk format - -`latest_time` - -* is optional -* type: `string` - -##### latest_time Type - - -`string` - - - - - - - - - - - - - - -#### search - -The search (in SPL) executed within core Splunk - -`search` - -* is **required** -* type: `string` - -##### search Type - - -`string` - - - - - - - - - -#### suppress - -Fields associated with suppressing the creation of multiple alerts - -`suppress` - -* is optional -* type: `object` - -##### suppress Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `suppress_fields`| string | **Required** | -| `suppress_period`| string | **Required** | - - - -#### suppress_fields - -The fields to base the suppression on - -`suppress_fields` - -* is **required** -* type: `string` - -##### suppress_fields Type - - -`string` - - - - - - - - - -#### suppress_period - -The length of time the suppression should be in effect - -`suppress_period` - -* is **required** -* type: `string` - -##### suppress_period Type - - -`string` - - - - - - - - - - - - - - - - - -## event_type - -An anomaly or threat. - -`event_type` - -* is optional -* type: `string` -* defined in this schema - -### event_type Type - - -`string` - - - - - - -### event_type Example - -```json -"anomaly" -``` - - -## model - -The name of the Splunk UBA model that detected the anomaly. - -`model` - -* is optional -* type: `string` -* defined in this schema - -### model Type - - -`string` - - - - - - -### model Example - -```json -"UBA Model" -``` - - -## model_version - -Url of the playbook on Phantom website. - -`model_version` - -* is optional -* type: `string` -* defined in this schema - -### model_version Type - - -`string` - - - - - - -### model_version Example - -```json -"2.0" -``` - - -## phantom_server - -IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname) - -`phantom_server` - -* is optional -* type: `string` -* defined in this schema - -### phantom_server Type - - -`string` - - - - - - -### phantom_server Example - -```json -"automation (hostname)" -``` - - -## playbook_name - -Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment - -`playbook_name` - -* is optional -* type: `string` -* defined in this schema - -### playbook_name Type - - -`string` - - - - - - -### playbook_name Example - -```json -"community/dns_hijack_detect_playbook" -``` - - -## playbook_url - -Url of the playbook on Phantom website. - -`playbook_url` - -* is optional -* type: `string` -* defined in this schema - -### playbook_url Type - - -`string` - - - - - - -### playbook_url Example - -```json -"https://my.phantom.us/4.1/playbook/dns-hijack-investigation/" -``` - - -## sensitivity - -TLP colors (white, green, amber or red) - -`sensitivity` - -* is optional -* type: `string` -* defined in this schema - -### sensitivity Type - - -`string` - - - - - - -### sensitivity Example - -```json -"green" -``` - - -## severity - -Severity in phantom (High, Medium, Low) - -`severity` - -* is optional -* type: `string` -* defined in this schema - -### severity Type - - -`string` - - - - - - -### severity Example - -```json -"high" -``` - - -## threat_category - -The category of a threat in Splunk UBA. - -`threat_category` - -* is optional -* type: `string` -* defined in this schema - -### threat_category Type - - -`string` - - - - - - -### threat_category Example - -```json -"Malware" +2 ``` diff --git a/docs/spec/investigations.spec.md b/docs/spec/investigations.spec.md deleted file mode 100644 index 934ac9dc37..0000000000 --- a/docs/spec/investigations.spec.md +++ /dev/null @@ -1,915 +0,0 @@ - -# Investigative Search Manifest Schema - -``` -https://api.splunkresearch.com/schemas/investigations.json -``` - -The fields that make up the manifest of a version 2 investigative object - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | - -# Investigative Search Manifest Properties - -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [creation_date](#creation_date) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [data_metadata](#data_metadata) | `object` | **Required** | No | Investigative Search Manifest (this schema) | -| [definitions](#definitions) | complex | Optional | No | Investigative Search Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [entities](#entities) | `enum[]` | Optional | No | Investigative Search Manifest (this schema) | -| [how_to_implement](#how_to_implement) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [investigate](#investigate) | complex | **Required** | No | Investigative Search Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | **Required** | No | Investigative Search Manifest (this schema) | -| [modification_date](#modification_date) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| [name](#name) | `string` | Optional | No | Investigative Search Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | **Required** | No | Investigative Search Manifest (this schema) | -| [product_type](#product_type) | `enum` | **Required** | No | Investigative Search Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | **Required** | No | Investigative Search Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Investigative Search Manifest (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## creation_date - -The date the story manifest was created - -`creation_date` - -* is **required** -* type: `string` -* defined in this schema - -### creation_date Type - - -`string` - - - - - - - -## data_metadata - -Information about the date being ingested - -`data_metadata` - -* is **required** -* type: `object` -* defined in this schema - -### data_metadata Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `data_eventtypes`| array | Optional | -| `data_models`| array | Optional | -| `data_source`| array | **Required** | -| `data_sourcetypes`| array | Optional | -| `providing_technologies`| array | **Required** | - - - -#### data_eventtypes - -A list of eventtypes, if any, used by this search - -`data_eventtypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_eventtypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### data_models - -A list of data models, if any, used by this search - -`data_models` - -* is optional -* type: `enum[]`* at least `0` items in the array - - -##### data_models Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of data models, if any, used by this search", - "items": { - "enum": [ - "Alerts", - "Application_State", - "Authentication", - "Certificates", - "Change_Analysis", - "Change", - "Malware", - "Email", - "Identity_Management", - "Network_Resolution", - "Network_Traffic", - "Vulnerabilities", - "Web", - "Network_Sessions", - "Updates", - "Risk", - "Endpoint" - ], - "simpletype": "`enum`", - "meta:enum": { - "Alerts": "", - "Application_State": "", - "Authentication": "", - "Certificates": "", - "Change_Analysis": "", - "Change": "", - "Malware": "", - "Email": "", - "Identity_Management": "", - "Network_Resolution": "", - "Network_Traffic": "", - "Vulnerabilities": "", - "Web": "", - "Network_Sessions": "", - "Updates": "", - "Risk": "", - "Endpoint": "" - } - }, - "type": "array", - "minItems": 0, - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - - - - - -#### data_source - -A high-level description of the type of data needed for this search to complete - -`data_source` - -* is **required** -* type: `string[]`* at least `0` items in the array - - -##### data_source Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### data_sourcetypes - -The list of sourcetypes, if any, used by this search - -`data_sourcetypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_sourcetypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### providing_technologies - -A list of technologies that provide this data - -`providing_technologies` - -* is **required** -* type: `enum[]`* at least `0` items in the array - - -##### providing_technologies Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of technologies that provide this data", - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften", - "OSquery" - ], - "simpletype": "`enum`", - "meta:enum": { - "Apache": "", - "AWS": "", - "Bro": "", - "Microsoft Windows": "", - "Linux": "", - "macOS": "", - "Netbackup": "", - "Splunk Enterprise": "", - "Splunk Enterprise Security": "", - "Splunk Stream": "", - "Active Directory": "", - "Bluecoat": "", - "Carbon Black Response": "", - "Carbon Black Protect": "", - "CrowdStrike Falcon": "", - "Microsoft Exchange": "", - "Nessus": "", - "Palo Alto Firewall": "", - "Qualys": "", - "Sysmon": "", - "Tanium": "", - "Ziften": "", - "OSquery": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - - - - - - - - -## definitions - - -`definitions` - -* is optional -* type: complex -* defined in this schema - -### definitions Type - -Unknown type ``. - -```json -{ - "phantom": { - "properties": { - "phantom_server": { - "description": "IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname)", - "type": "string" - }, - "playbook_display_name": { - "description": "Display Name of the playbook. Capitalize each letter and remove underscores from playbook_name field. Eg: Simple Network Enrichment", - "type": "string" - }, - "playbook_name": { - "description": "Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment", - "type": "string" - }, - "playbook_url": { - "description": "Url of the playbook on Phantom website.", - "type": "string" - }, - "sensitivity": { - "description": "TLP colors (White, Green, Amber or Red)", - "type": "string" - }, - "severity": { - "description": "Severity in phantom (High, Medium, Low)", - "type": "string" - } - }, - "required": [ - "phantom_server", - "playbook_name", - "playbook_url", - "playbook_display_name" - ], - "type": "object" - }, - "splunk": { - "properties": { - "investigate_window": { - "additionalProperties": false, - "description": "The fields associated on when this search should run relative to the detection event", - "properties": { - "earliest_time_offset": { - "description": "The number of seconds into the past from the event time the search should cover", - "type": "integer" - }, - "latest_time_offset": { - "description": "The number of seconds into the future from the event time the search should cover", - "type": "integer" - } - }, - "required": [ - "latest_time_offset", - "earliest_time_offset" - ], - "type": "object" - }, - "search": { - "description": "The search (in SPL) executed within core Splunk for investgation.", - "type": "string" - } - }, - "required": [ - "search", - "investigate_window" - ], - "type": "object" - }, - "simpletype": "complex" -} -``` - - - - - -## description - -A description of what the search is designed to detect - -`description` - -* is **required** -* type: `string` -* defined in this schema - -### description Type - - -`string` - - - - - - - -## entities - -A list of entities that will used in the story flow or are relevant to the security investigation. - -`entities` - -* is optional -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### entities Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. - -```json -{ - "description": "A list of entities that will used in the story flow or are relevant to the security investigation. ", - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user" - ], - "simpletype": "`enum`", - "meta:enum": { - "accessKeyId": "", - "arn": "", - "awsRegion": "", - "bucketName": "", - "City": "", - "Country": "", - "dest_port": "", - "dest": "", - "event_id": "", - "instanceId": "", - "message_id": "", - "networkAclId": "", - "process_name": "", - "process": "", - "recipient": "", - "Region": "", - "resourceId": "", - "session_id": "", - "src_ip": "", - "src_mac": "", - "src_user": "", - "src": "", - "user": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} -``` - - - - - - - - -## how_to_implement - -A discussion on how to implement this search, from what needs to be ingested, config files modified, and suggested per site modifications - -`how_to_implement` - -* is **required** -* type: `string` -* defined in this schema - -### how_to_implement Type - - -`string` - - - - - - - -## id - -The unique identifier for the search - -`id` - -* is **required** -* type: `string` -* defined in this schema - -### id Type - - -`string` - - - - - - - -## investigate - - -`investigate` - -* is **required** -* type: complex -* defined in this schema - -### investigate Type - - -**One** of the following *conditions* need to be fulfilled. - - -#### Condition 1 - - -* []() – `#/definitions/splunk` - - -#### Condition 2 - - -* []() – `#/definitions/phantom` - - - - - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is **required** -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - - - - -#### email - -Email address of the person maintaining this search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - - - - -#### name - -Name of the person maintaining this search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - - - - - - - - - - -## modification_date - -The date of the most recent modification to the search - -`modification_date` - -* is **required** -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - - -## name - -The name of the search - -`name` - -* is optional -* type: `string` -* defined in this schema - -### name Type - - -`string` - - - - - - - -## original_authors - -A list of the original authors of the search - -`original_authors` - -* is **required** -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - - - - -#### email - -Email address of the person who originally authored the search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - - - - -#### name - -Name of the person who originally authored the search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - - - - - - - - - - -## product_type - -Type of product that will support this investigate object. - -`product_type` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#product_type-known-values). - -### product_type Known Values -| Value | Description | -|-------|-------------| -| `phantom` | | -| `splunk` | | -| `uba` | | - - - - -## spec_version - -The version of the investigative search specification this manifest follows - -`spec_version` - -* is **required** -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - - -## version - -The version of the search - -`version` - -* is **required** -* type: `string` -* defined in this schema - -### version Type - - -`string` - - - - - - diff --git a/spec/lookups.spec.md b/docs/spec/lookups.spec.md similarity index 100% rename from spec/lookups.spec.md rename to docs/spec/lookups.spec.md diff --git a/spec/macros.spec.md b/docs/spec/macros.spec.md similarity index 100% rename from spec/macros.spec.md rename to docs/spec/macros.spec.md diff --git a/spec/response_tasks.spec.md b/docs/spec/response_tasks.spec.md similarity index 100% rename from spec/response_tasks.spec.md rename to docs/spec/response_tasks.spec.md diff --git a/docs/spec/responses.spec.md b/docs/spec/responses.spec.md index e6a345f849..55779a8dfa 100644 --- a/docs/spec/responses.spec.md +++ b/docs/spec/responses.spec.md @@ -1,47 +1,42 @@ -# Response Manifest Schema +# Response Schema Schema ``` -https://api.splunkresearch.com/schemas/investigations.json +http://example.com/example.json ``` -The fields that make up the manifest of a version 1 reponse spec +schema for response | Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | |----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | Yes | Experimental | No | Forbidden | Forbidden | | +| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | -# Response Manifest Properties +# Response Schema Properties -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [creation_date](#creation_date) | `string` | **Required** | No | Response Manifest (this schema) | -| [data_metadata](#data_metadata) | `object` | **Required** | No | Response Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Response Manifest (this schema) | -| [entities](#entities) | `enum[]` | Optional | No | Response Manifest (this schema) | -| [fields_required](#fields_required) | `string[]` | Optional | No | Response Manifest (this schema) | -| [how_to_implement](#how_to_implement) | `string` | **Required** | No | Response Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Response Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | **Required** | No | Response Manifest (this schema) | -| [modification_date](#modification_date) | `string` | **Required** | No | Response Manifest (this schema) | -| [name](#name) | `string` | Optional | No | Response Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | **Required** | No | Response Manifest (this schema) | -| [product_type](#product_type) | `enum` | **Required** | No | Response Manifest (this schema) | -| [response](#response) | complex | **Required** | No | Response Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | **Required** | No | Response Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Response Manifest (this schema) | +| Property | Type | Required | Nullable | Default | Defined by | +|----------|------|----------|----------|---------|------------| +| [author](#author) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [date](#date) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [description](#description) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [id](#id) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [name](#name) | `string` | **Required** | No | `""` | Response Schema (this schema) | +| [response_tasks](#response_tasks) | `array` | **Required** | No | `{}` | Response Schema (this schema) | +| [tags](#tags) | `object` | **Required** | No | `{}` | Response Schema (this schema) | +| [version](#version) | `integer` | **Required** | No | `0` | Response Schema (this schema) | +| `*` | any | Additional | Yes | this schema *allows* additional properties | -## creation_date +## author -The date the story manifest was created +Author of the response -`creation_date` +`author` * is **required** * type: `string` +* default: `""` * defined in this schema -### creation_date Type +### author Type `string` @@ -51,248 +46,50 @@ The date the story manifest was created - -## data_metadata - -Information about the date being used to run the response - -`data_metadata` - -* is **required** -* type: `object` -* defined in this schema - -### data_metadata Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `data_eventtypes`| array | Optional | -| `data_models`| array | Optional | -| `data_source`| array | **Required** | -| `data_sourcetypes`| array | Optional | -| `providing_technologies`| array | **Required** | - - - -#### data_eventtypes - -A list of eventtypes, if any, used by this search - -`data_eventtypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_eventtypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### data_models - -A list of data models, if any, used by this search - -`data_models` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_models Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### data_source - -A high-level description of the type of data needed for this search to complete - -`data_source` - -* is **required** -* type: `string[]`* at least `0` items in the array - - -##### data_source Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### data_sourcetypes - -The list of sourcetypes, if any, used by this search - -`data_sourcetypes` - -* is optional -* type: `string[]`* at least `0` items in the array - - -##### data_sourcetypes Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - - - -#### providing_technologies - -A list of technologies that provide this data - -`providing_technologies` - -* is **required** -* type: `enum[]`* at least `0` items in the array - - -##### providing_technologies Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. +### author Example ```json -{ - "description": "A list of technologies that provide this data", - "items": { - "enum": [ - "Apache", - "AWS", - "Bro", - "Microsoft Windows", - "Linux", - "macOS", - "Netbackup", - "Splunk Enterprise", - "Splunk Enterprise Security", - "Splunk Stream", - "Active Directory", - "Bluecoat", - "Carbon Black Response", - "Carbon Black Protect", - "CrowdStrike Falcon", - "Microsoft Exchange", - "Nessus", - "Palo Alto Firewall", - "Qualys", - "Sysmon", - "Tanium", - "Ziften" - ], - "simpletype": "`enum`", - "meta:enum": { - "Apache": "", - "AWS": "", - "Bro": "", - "Microsoft Windows": "", - "Linux": "", - "macOS": "", - "Netbackup": "", - "Splunk Enterprise": "", - "Splunk Enterprise Security": "", - "Splunk Stream": "", - "Active Directory": "", - "Bluecoat": "", - "Carbon Black Response": "", - "Carbon Black Protect": "", - "CrowdStrike Falcon": "", - "Microsoft Exchange": "", - "Nessus": "", - "Palo Alto Firewall": "", - "Qualys": "", - "Sysmon": "", - "Tanium": "", - "Ziften": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} +"Rico Valdez, Patrick Bareiß, Splunk" ``` +## date + +version of detection, e.g. 1 or 2 ... + +`date` + +* is **required** +* type: `string` +* default: `""` +* defined in this schema + +### date Type + + +`string` +### date Example - - +```json +"2019-12-06" +``` ## description -A description of what this reponse object will do +Description of response `description` * is **required** * type: `string` +* default: `""` * defined in this schema ### description Type @@ -305,153 +102,22 @@ A description of what this reponse object will do - -## entities - -A list of entities that is either an input or an output for the security workflow. - -`entities` - -* is optional -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### entities Type - - -Array type: `enum[]` - -All items must be of the type: -Unknown type ``. +### description Example ```json -{ - "description": "A list of entities that is either an input or an output for the security workflow.", - "items": { - "enum": [ - "accessKeyId", - "arn", - "awsRegion", - "bucketName", - "City", - "Country", - "dest_port", - "dest", - "event_id", - "instanceId", - "message_id", - "networkAclId", - "process_name", - "process", - "recipient", - "Region", - "resourceId", - "session_id", - "src_ip", - "src_mac", - "src_user", - "src", - "user" - ], - "simpletype": "`enum`", - "meta:enum": { - "accessKeyId": "", - "arn": "", - "awsRegion": "", - "bucketName": "", - "City": "", - "Country": "", - "dest_port": "", - "dest": "", - "event_id": "", - "instanceId": "", - "message_id": "", - "networkAclId": "", - "process_name": "", - "process": "", - "recipient": "", - "Region": "", - "resourceId": "", - "session_id": "", - "src_ip": "", - "src_mac": "", - "src_user": "", - "src": "", - "user": "" - } - }, - "minItems": 0, - "type": "array", - "uniqueItems": true, - "simpletype": "`enum[]`" -} +"Response example." ``` - - - - - - -## fields_required - -A list of fields that need to be in the result of the detection search for the search to be successful - -`fields_required` - -* is optional -* type: `string[]` -* at least `0` items in the array -* defined in this schema - -### fields_required Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - - - -## how_to_implement - -A discussion on how to implement this reponse object, the config files, etc - -`how_to_implement` - -* is **required** -* type: `string` -* defined in this schema - -### how_to_implement Type - - -`string` - - - - - - - ## id -The unique identifier for the search +UUID as unique identifier `id` * is **required** * type: `string` +* default: `""` * defined in this schema ### id Type @@ -464,135 +130,22 @@ The unique identifier for the search +### id Example -## maintainers - -An array of the current maintainers of the reponse spec - -`maintainers` - -* is **required** -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - - - - -#### email - -Email address of the person maintaining this search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - - - - -#### name - -Name of the person maintaining this search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - - - - - - - - - - -## modification_date - -The date of the most recent modification to the search - -`modification_date` - -* is **required** -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - +```json +"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" +``` ## name -The name of the search +Name of response `name` -* is optional +* is **required** * type: `string` +* default: `""` * defined in this schema ### name Type @@ -605,248 +158,103 @@ The name of the search +### name Example -## original_authors +```json +"Response Example" +``` -A list of the original authors of the reponse object -`original_authors` +## response_tasks + +Response tasks divided into phases + +`response_tasks` * is **required** -* type: `object[]` +* type: `array` +* at least `1` items in the array +* default: `{}` * defined in this schema -### original_authors Type +### response_tasks Type -Array type: `object[]` +Array type: `array` + + + + +### response_tasks Example + +```json +{ + "another_phase": [ + { + "id": "7c72d944-3995-4485-8e57-67b4c353989b", + "name": "Another investigation" + } + ], + "identification": [ + { + "id": "c36f3f48-e0bb-4c20-a62a-cdc8f6418892", + "name": "Investigate Indicator of Compromise Hash" + }, + { + "id": "0dc849b2-2eb4-4fd2-add1-b6cc475765f0", + "name": "Investigate Domains" + } + ] +} +``` + + +## tags + +An array of key value pairs for tagging + +`tags` + +* is **required** +* type: `object` +* default: `{}` +* defined in this schema + +### tags Type + -All items must be of the type: `object` with following properties: | Property | Type | Required | |----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the search - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - - - - -#### email - -Email address of the person who originally authored the search - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - - - - -#### name - -Name of the person who originally authored the search - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - - - - - - - - - - -## product_type - -The type of detection - -`product_type` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#product_type-known-values). - -### product_type Known Values -| Value | Description | -|-------|-------------| -| `splunk` | | -| `phantom` | | - - - - -## response - - -`response` - -* is **required** -* type: complex -* defined in this schema - -### response Type - - -**One** of the following *conditions* need to be fulfilled. - - -#### Condition 1 - - -* []() – `#/definitions/splunk` - - -#### Condition 2 - - -* []() – `#/definitions/phantom` - - - - - - -## spec_version - -The version of the investigative search specification this manifest follows - -`spec_version` - -* is **required** -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` +### tags Example +```json +{ + "analytics_story": "credential_dumping" +} +``` ## version -The version of the search +version of detection, e.g. 1 or 2 ... `version` * is **required** -* type: `string` +* type: `integer` +* default: `0` * defined in this schema ### version Type -`string` - - - - - - - -# Response Manifest Definitions - -| Property | Type | Group | -|----------|------|-------| -| [investigate_window](#investigate_window) | `object` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/splunk` | -| [phantom_server](#phantom_server) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [playbook_display_name](#playbook_display_name) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [playbook_name](#playbook_name) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [playbook_url](#playbook_url) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [search](#search) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/splunk` | -| [sensitivity](#sensitivity) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | -| [severity](#severity) | `string` | `https://api.splunkresearch.com/schemas/investigations.json#/definitions/phantom` | - -## investigate_window - -The fields associated on when this search should run relative to the detection event - -`investigate_window` - -* is optional -* type: `object` -* defined in this schema - -### investigate_window Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `earliest_time_offset`| integer | **Required** | -| `latest_time_offset`| integer | **Required** | - - - -#### earliest_time_offset - -The number of seconds into the past from the event time the search should cover - -`earliest_time_offset` - -* is **required** -* type: `integer` - -##### earliest_time_offset Type - - `integer` @@ -854,177 +262,9 @@ The number of seconds into the past from the event time the search should cover +### version Example - - -#### latest_time_offset - -The number of seconds into the future from the event time the search should cover - -`latest_time_offset` - -* is **required** -* type: `integer` - -##### latest_time_offset Type - - -`integer` - - - - - - - - - - - - -## phantom_server - -IP address and username of the phantom server. Currently, we will ship this value as automation (hostname) and we encourage the users to modify those values according to their environment. Eg: automation (hostname) - -`phantom_server` - -* is optional -* type: `string` -* defined in this schema - -### phantom_server Type - - -`string` - - - - - - - -## playbook_display_name - -Display Name of the playbook. Capitalize each letter and remove underscores from playbook_name field. Eg: Simple Network Enrichment - -`playbook_display_name` - -* is optional -* type: `string` -* defined in this schema - -### playbook_display_name Type - - -`string` - - - - - - - -## playbook_name - -Name of the playbook. This name should be the same as the name on phantom community repository on github with underscores and appended with community/. The playbooks are hosted on https://github.com/phantomcyber/playbooks. Eg: community/simple_network_enrichment - -`playbook_name` - -* is optional -* type: `string` -* defined in this schema - -### playbook_name Type - - -`string` - - - - - - - -## playbook_url - -Url of the playbook on Phantom website. - -`playbook_url` - -* is optional -* type: `string` -* defined in this schema - -### playbook_url Type - - -`string` - - - - - - - -## search - -A reponse action exectued in splunk - -`search` - -* is optional -* type: `string` -* defined in this schema - -### search Type - - -`string` - - - - - - - -## sensitivity - -TLP colors (White, Green, Amber or Red) - -`sensitivity` - -* is optional -* type: `string` -* defined in this schema - -### sensitivity Type - - -`string` - - - - - - - -## severity - -Severity in phantom (High, Medium, Low) - -`severity` - -* is optional -* type: `string` -* defined in this schema - -### severity Type - - -`string` - - - - - +```json +1 +``` diff --git a/spec/stories.spec.md b/docs/spec/stories.spec.md similarity index 100% rename from spec/stories.spec.md rename to docs/spec/stories.spec.md diff --git a/docs/spec/story.spec.md b/docs/spec/story.spec.md deleted file mode 100644 index 518fed76d7..0000000000 --- a/docs/spec/story.spec.md +++ /dev/null @@ -1,725 +0,0 @@ - -# Analytic Story Manifest Schema - -``` -https://api.splunkresearch.com/schemas/story.json -``` - -The fields that make up the manifest of a version 2 Analytic Story - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | - -# Analytic Story Manifest Properties - -| Property | Type | Required | Nullable | Defined by | -|----------|------|----------|----------|------------| -| [category](#category) | `enum[]` | **Required** | No | Analytic Story Manifest (this schema) | -| [channel](#channel) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [creation_date](#creation_date) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [description](#description) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| [detections](#detections) | `object[]` | **Required** | No | Analytic Story Manifest (this schema) | -| [id](#id) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| [maintainers](#maintainers) | `object[]` | Optional | No | Analytic Story Manifest (this schema) | -| [modification_date](#modification_date) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [name](#name) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| [narrative](#narrative) | `string` | Optional | No | Analytic Story Manifest (this schema) | -| [original_authors](#original_authors) | `object[]` | Optional | No | Analytic Story Manifest (this schema) | -| [references](#references) | `string[]` | Optional | No | Analytic Story Manifest (this schema) | -| [spec_version](#spec_version) | `integer` | Optional | No | Analytic Story Manifest (this schema) | -| [usecase](#usecase) | `enum` | **Required** | No | Analytic Story Manifest (this schema) | -| [version](#version) | `string` | **Required** | No | Analytic Story Manifest (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## category - -The category to which the Analytic Story belongs - -`category` - -* is **required** -* type: `enum[]` -* at least `0` items in the array -* defined in this schema - -### category Type - - -Array type: `enum[]` - -All items must be of the type: -`string` - - - - - - - - - - -## channel - -A grouping function that designates where this search came from. For example, searches and stories in Enterprise Security Content Updates are in the ESCU channel - -`channel` - -* is optional -* type: `string` -* defined in this schema - -### channel Type - - -`string` - - - - - - -### channel Example - -```json -"ESCU" -``` - - -## creation_date - -The date this story was created - -`creation_date` - -* is optional -* type: `string` -* defined in this schema - -### creation_date Type - - -`string` - - - - - - -### creation_date Example - -```json -"2017-11-21" -``` - - -## description - -A high-level description or goal of the Analytic Story - -`description` - -* is **required** -* type: `string` -* defined in this schema - -### description Type - - -`string` - - - - - - -### description Example - -```json -"Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records." -``` - - -## detections - -An array of detection mechanisms from Splunk, UBA and phantom. - -`detections` - -* is **required** -* type: `object[]` -* defined in this schema - -### detections Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `detection_id`| string | **Required** | -| `name`| string | **Required** | -| `type`| string | **Required** | - - - -#### detection_id - -unique identifier of the detection, in the form of UUID - -`detection_id` - -* is **required** -* type: `string` - -##### detection_id Type - - -`string` - - - - - - -##### detection_id Example - -```json -1169w17b-ef78-4b59-aae8-5369073014e1 -``` - - - - -#### name - -Name of the Detection. It can be a name of a Splunk correlation search name, a UBA threat or a Phantom detection playbook. - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -DNS record changed -``` - - - - -#### type - -What product gives you a detection - -`type` - -* is **required** -* type: `enum` - -The value of this property **must** be equal to one of the [known values below](#detections-known-values). - -##### type Known Values -| Value | Description | -|-------|-------------| -| `splunk` | | -| `uba` | | -| `phantom` | | - - - -##### type Examples - -```json -splunk -``` - -```json -uba -``` - -```json -phantom -``` - - - - - - - - - - -## id - -A unique identifier for the Analytic Story - -`id` - -* is **required** -* type: `string` -* defined in this schema - -### id Type - - -`string` - - - - - - -### id Example - -```json -"8169f17b-ef68-4b59-aae8-5869073014e1" -``` - - -## maintainers - -An array of the current maintainers of the Analytic Story. - -`maintainers` - -* is optional -* type: `object[]` -* defined in this schema - -### maintainers Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person maintaining this Analytic Story - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person maintaining this Analytic Story - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person maintaining this Analytic Story - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## modification_date - -The date of the most recent modification to this Analytic Story - -`modification_date` - -* is optional -* type: `string` -* defined in this schema - -### modification_date Type - - -`string` - - - - - - -### modification_date Example - -```json -"2018-09-06" -``` - - -## name - -The name of the Analytic Story - -`name` - -* is **required** -* type: `string` -* defined in this schema - -### name Type - - -`string` - - - - - - -### name Example - -```json -"DNS Hijacking" -``` - - -## narrative - -Long-form text that describes the Analytic Story and the rationale behind it, as well as an overview of the included searches, and how they enable the story - -`narrative` - -* is optional -* type: `string` -* defined in this schema - -### narrative Type - - -`string` - - - - - - -### narrative Example - -```json -"Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.

The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous." -``` - - -## original_authors - -An array of the original authors of the Analytic Story - -`original_authors` - -* is optional -* type: `object[]` -* defined in this schema - -### original_authors Type - - -Array type: `object[]` - -All items must be of the type: -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| -| `company`| string | **Required** | -| `email`| string | **Required** | -| `name`| string | **Required** | - - - -#### company - -Company associated with the person who originally authored the Analytic Story - -`company` - -* is **required** -* type: `string` - -##### company Type - - -`string` - - - - - - -##### company Example - -```json -Splunk -``` - - - - -#### email - -Email address of the person who originally authored the Analytic Story - -`email` - -* is **required** -* type: `string` - -##### email Type - - -`string` - - - - - - -##### email Example - -```json -daftpunk@splunk.com -``` - - - - -#### name - -Name of the person who originally authored the Analytic Story - -`name` - -* is **required** -* type: `string` - -##### name Type - - -`string` - - - - - - -##### name Example - -```json -Daft Punk -``` - - - - - - - - - -## references - -An array of URLs that give information about the problem the story is addressing - -`references` - -* is optional -* type: `string[]` -* at least `0` items in the array -* defined in this schema - -### references Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - - - - -### references Example - -```json -"https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html" -``` - - -## spec_version - -The version of the Analytic Story specification this manifest follows - -`spec_version` - -* is optional -* type: `integer` -* defined in this schema - -### spec_version Type - - -`integer` - - - - - - -### spec_version Example - -```json -2 -``` - - -## usecase - -The usecase to which the Analytic Story belongs to. - -`usecase` - -* is **required** -* type: `enum` -* defined in this schema - -The value of this property **must** be equal to one of the [known values below](#usecase-known-values). - -### usecase Known Values -| Value | Description | -|-------|-------------| -| `Security Monitoring` | | -| `Advanced Threat Detection` | | -| `Insider Threat` | | -| `Compliance` | | -| `Fraud Detection` | | - - - -### usecase Example - -```json -"Advanced Threat Detection" -``` - - -## version - -The version of the Analytic Story, bump the version number when the story gets an update - -`version` - -* is **required** -* type: `string` -* defined in this schema - -### version Type - - -`string` - - - - - - -### version Example - -```json -"1.0" -``` - diff --git a/spec/baselines.spec.md b/spec/baselines.spec.md deleted file mode 100644 index fc66502080..0000000000 --- a/spec/baselines.spec.md +++ /dev/null @@ -1,283 +0,0 @@ - -# Baseline Schema Schema - -``` -http://example.com/example.json -``` - -schema for baselines - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | - -# Baseline Schema Properties - -| Property | Type | Required | Nullable | Default | Defined by | -|----------|------|----------|----------|---------|------------| -| [author](#author) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | -| [date](#date) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | -| [description](#description) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | -| [how_to_implement](#how_to_implement) | `string` | Optional | No | `""` | Baseline Schema (this schema) | -| [id](#id) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | -| [name](#name) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | -| [search](#search) | `string` | **Required** | No | `""` | Baseline Schema (this schema) | -| [tags](#tags) | `object` | **Required** | No | `{}` | Baseline Schema (this schema) | -| [version](#version) | `integer` | **Required** | No | `0` | Baseline Schema (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## author - -Author of the baseline - -`author` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### author Type - - -`string` - - - - - - -### author Example - -```json -"Bahvin Patel, Splunk" -``` - - -## date - -date of creation or modification, format yyyy-mm-dd - -`date` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### date Type - - -`string` - - - - - - -### date Example - -```json -"2019-12-06" -``` - - -## description - -A detailed description of the baseline - -`description` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### description Type - - -`string` - - - - - - -### description Example - -```json -"This search looks for CloudTrail events where an AWS instance is started and creates a baseline of most recent time (latest) and the first time (earliest) we've seen this region in our dataset grouped by the value awsRegion for the last 30 days" -``` - - -## how_to_implement - -information about how to implement. Only needed for non standard implementations. - -`how_to_implement` - -* is optional -* type: `string` -* default: `""` -* defined in this schema - -### how_to_implement Type - - -`string` - - - - - - -### how_to_implement Example - -```json -"This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." -``` - - -## id - -UUID as unique identifier - -`id` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### id Type - - -`string` - - - - - - -### id Example - -```json -"fc0edc95-ff2b-48b0-9f6f-63da3789fd63" -``` - - -## name -### Name of baseline - -`name` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### name Type - - -`string` - - - - - - -### name Example - -```json -"Previously Seen AWS Regions" -``` - - -## search - -The Splunk search for the baseline - -`search` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### search Type - - -`string` - - - - - - -### search Example - -```json -"cloudtrail StartInstances | stats earliest(_time) as earliest latest(_time) as latest by awsRegion | outputlookup previously_seen_aws_regions.csv" -``` - - -## tags - -An array of key value pairs for tagging - -`tags` - -* is **required** -* type: `object` -* default: `{}` -* defined in this schema - -### tags Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| - - - - -### tags Example - -```json -{ - "analytics_story": "suspicious_aws_ec2_activities", - "custom_key": "custom_value" -} -``` - - -## version - -version of baseline, e.g. 1 or 2 ... - -`version` - -* is **required** -* type: `integer` -* default: `0` -* defined in this schema - -### version Type - - -`integer` - - - - - - -### version Example - -```json -1 -``` - diff --git a/spec/detections.spec.md b/spec/detections.spec.md deleted file mode 100644 index 8fb01effff..0000000000 --- a/spec/detections.spec.md +++ /dev/null @@ -1,381 +0,0 @@ - -# Detection Schema Schema - -``` -http://example.com/example.json -``` - -schema for detections - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | - -# Detection Schema Properties - -| Property | Type | Required | Nullable | Default | Defined by | -|----------|------|----------|----------|---------|------------| -| [author](#author) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [date](#date) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [description](#description) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [how_to_implement](#how_to_implement) | `string` | Optional | No | `""` | Detection Schema (this schema) | -| [id](#id) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [known_false_positives](#known_false_positives) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [name](#name) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [references](#references) | `string[]` | Optional | No | `[]` | Detection Schema (this schema) | -| [search](#search) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [tags](#tags) | `object` | **Required** | No | `{}` | Detection Schema (this schema) | -| [type](#type) | `string` | **Required** | No | `""` | Detection Schema (this schema) | -| [version](#version) | `integer` | **Required** | No | `0` | Detection Schema (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## author - -Author of the detection - -`author` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### author Type - - -`string` - - - - - - -### author Example - -```json -"Patrick Bareiss, Splunk" -``` - - -## date - -date of creation or modification, format yyyy-mm-dd - -`date` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### date Type - - -`string` - - - - - - -### date Example - -```json -"2019-12-06" -``` - - -## description - -A detailed description of the detection - -`description` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### description Type - - -`string` - - - - - - -### description Example - -```json -"dbgcore.dll is a specifc DLL for Windows core debugging. It is used to obtain a memory dump of a process. This search detects the usage of this DLL for creating a memory dump of LSASS process. Memory dumps of the LSASS process can be created with tools such as Windows Task Manager or procdump." -``` - - -## how_to_implement - -information about how to implement. Only needed for non standard implementations. - -`how_to_implement` - -* is optional -* type: `string` -* default: `""` -* defined in this schema - -### how_to_implement Type - - -`string` - - - - - - -### how_to_implement Example - -```json -"This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe." -``` - - -## id - -UUID as unique identifier - -`id` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### id Type - - -`string` - - - - - - -### id Example - -```json -"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" -``` - - -## known_false_positives - -known false postives - -`known_false_positives` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### known_false_positives Type - - -`string` - - - - - - -### known_false_positives Example - -```json -"Administrators can create memory dumps for debugging purposes, but memory dumps of the LSASS process would be unusual." -``` - - -## name -### Name of detection - -`name` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### name Type - - -`string` - - - - - - -### name Example - -```json -"Access LSASS Memory for Dump Creation" -``` - - -## references - -A list of references for this detection - -`references` - -* is optional -* type: `string[]` - -* default: `[]` -* defined in this schema - -### references Type - - -Array type: `string[]` - -All items must be of the type: -`string` - - - - - -An explanation about the purpose of this instance. - - - - - -### references Example - -```json -[ - "https://2017.zeronights.org/wp-content/uploads/materials/ZN17_Kheirkhabarov_Hunting_for_Credentials_Dumping_in_Windows_Environment.pdf" -] -``` - - -## search - -The Splunk search for the detection - -`search` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### search Type - - -`string` - - - - - - -### search Example - -```json -"`sysmon` EventCode=10 TargetImage=*lsass.exe CallTrace=*dbgcore.dll* OR CallTrace=*dbghelp.dll* | stats count min(_time) as firstTime max(_time) as lastTime by Computer, TargetImage, TargetProcessId, SourceImage, SourceProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `access_lsass_memory_for_dump_creation_filter`" -``` - - -## tags - -An array of key value pairs for tagging - -`tags` - -* is **required** -* type: `object` -* default: `{}` -* defined in this schema - -### tags Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| - - - - -### tags Example - -```json -{ - "analytics_story": "credential_dumping", - "custom_key": "custom_value" -} -``` - - -## type - -type of detection - -`type` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### type Type - - -`string` - - - - - - -### type Example - -```json -"ESCU" -``` - - -## version - -version of detection, e.g. 1 or 2 ... - -`version` - -* is **required** -* type: `integer` -* default: `0` -* defined in this schema - -### version Type - - -`integer` - - - - - - -### version Example - -```json -2 -``` - diff --git a/spec/responses.spec.md b/spec/responses.spec.md deleted file mode 100644 index 55779a8dfa..0000000000 --- a/spec/responses.spec.md +++ /dev/null @@ -1,270 +0,0 @@ - -# Response Schema Schema - -``` -http://example.com/example.json -``` - -schema for response - -| Abstract | Extensible | Status | Identifiable | Custom Properties | Additional Properties | Defined In | -|----------|------------|--------|--------------|-------------------|-----------------------|------------| -| Can be instantiated | No | Experimental | No | Forbidden | Permitted | | - -# Response Schema Properties - -| Property | Type | Required | Nullable | Default | Defined by | -|----------|------|----------|----------|---------|------------| -| [author](#author) | `string` | **Required** | No | `""` | Response Schema (this schema) | -| [date](#date) | `string` | **Required** | No | `""` | Response Schema (this schema) | -| [description](#description) | `string` | **Required** | No | `""` | Response Schema (this schema) | -| [id](#id) | `string` | **Required** | No | `""` | Response Schema (this schema) | -| [name](#name) | `string` | **Required** | No | `""` | Response Schema (this schema) | -| [response_tasks](#response_tasks) | `array` | **Required** | No | `{}` | Response Schema (this schema) | -| [tags](#tags) | `object` | **Required** | No | `{}` | Response Schema (this schema) | -| [version](#version) | `integer` | **Required** | No | `0` | Response Schema (this schema) | -| `*` | any | Additional | Yes | this schema *allows* additional properties | - -## author - -Author of the response - -`author` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### author Type - - -`string` - - - - - - -### author Example - -```json -"Rico Valdez, Patrick Bareiß, Splunk" -``` - - -## date - -version of detection, e.g. 1 or 2 ... - -`date` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### date Type - - -`string` - - - - - - -### date Example - -```json -"2019-12-06" -``` - - -## description - -Description of response - -`description` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### description Type - - -`string` - - - - - - -### description Example - -```json -"Response example." -``` - - -## id - -UUID as unique identifier - -`id` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### id Type - - -`string` - - - - - - -### id Example - -```json -"fb4c31b0-13e8-4155-8aa5-24de4b8d6717" -``` - - -## name - -Name of response - -`name` - -* is **required** -* type: `string` -* default: `""` -* defined in this schema - -### name Type - - -`string` - - - - - - -### name Example - -```json -"Response Example" -``` - - -## response_tasks - -Response tasks divided into phases - -`response_tasks` - -* is **required** -* type: `array` -* at least `1` items in the array -* default: `{}` -* defined in this schema - -### response_tasks Type - - -Array type: `array` - - - - -### response_tasks Example - -```json -{ - "another_phase": [ - { - "id": "7c72d944-3995-4485-8e57-67b4c353989b", - "name": "Another investigation" - } - ], - "identification": [ - { - "id": "c36f3f48-e0bb-4c20-a62a-cdc8f6418892", - "name": "Investigate Indicator of Compromise Hash" - }, - { - "id": "0dc849b2-2eb4-4fd2-add1-b6cc475765f0", - "name": "Investigate Domains" - } - ] -} -``` - - -## tags - -An array of key value pairs for tagging - -`tags` - -* is **required** -* type: `object` -* default: `{}` -* defined in this schema - -### tags Type - - -`object` with following properties: - - -| Property | Type | Required | -|----------|------|----------| - - - - -### tags Example - -```json -{ - "analytics_story": "credential_dumping" -} -``` - - -## version - -version of detection, e.g. 1 or 2 ... - -`version` - -* is **required** -* type: `integer` -* default: `0` -* defined in this schema - -### version Type - - -`integer` - - - - - - -### version Example - -```json -1 -``` - From d2350dd6a86b0a1d14ac090d32904c798bdfa3b0 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 19 May 2020 16:53:35 +0200 Subject: [PATCH 61/93] updated Readme --- README.md | 79 ++++++++++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 78 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index d5ae5b7ada..e6d9ae6076 100644 --- a/README.md +++ b/README.md @@ -1 +1,78 @@ -new version of the README needs to be done +# Splunk Security Content +![security-content](docs/static/logo.png) +===== + +| branch | build status | +| --- | --- | +| develop| [![develop status](https://circleci.com/gh/splunk/security-content/tree/develop.svg?style=svg&circle-token=67ad1fa7779c57d7e5bcfc42bd617baf607ec269)](https://circleci.com/gh/splunk/security-content/tree/develop)| +| master | [![master status](https://circleci.com/gh/splunk/security-content/tree/master.svg?style=svg&circle-token=67ad1fa7779c57d7e5bcfc42bd617baf607ec269)](https://circleci.com/gh/splunk/security-content/tree/master)| + +Welcome to the Splunk Security Content + +This project gives you access to our repository of Analytic Stories--themed security guides that provide background on TTPs, mapped to the MITRE framework, the Lockheed Martin Kill Chain, and CIS controls. They include Splunk searches, machine-learning algorithms, and Splunk Phantom playbooks (where available)—all designed to work together to detect, investigate, and respond to threats. + +# Usage +The Splunk Security Content can be used via: + +#### [Splunk App](https://github.com/splunk/security-content/releases) +Grab the latest release of DA-ESS-ContentUpdate and install it on a Splunk Enterprise instance. + +#### [API](https://docs.splunkresearch.com/?version=latest) +``` +curl -s https://content.splunkresearch.com | jq +{ + "hello": "welcome to Splunks Research security content api" +} +``` + +#### GitHub Workflow (link to wiki) +Create your customized version of Security Content by following this guide. + +# What's in an Analytic Story? +[Analytic Stories](https://github.com/splunk/security-content/blob/develop/docs/stories_categories.md) and their corresponding searches are composed of **.yml** files (manifests) and associated .conf files. The stories reside in [/stories](https://github.com/splunk/security-content/tree/develop/stories) and the searches live in [/detections](https://github.com/splunk/security-content/tree/develop/detections). + +Manifests contain a number of mandatory and optional fields. You can see the full field list for each piece of content [here](https://github.com/splunk/security-content/tree/develop/docs#spec-documentation). + +# Customize to your Environment + +After release [1.0.46](https://github.com/splunk/security-content/releases) we introduced a concept of input(pre-filter) and output(post-filter) macros for each of our detection search. The intention behind introducing these macros is primarily to help our users to update the macro definition “once” and those changes will be applicable across all detections that leverage that macro and local to your Splunk Environment. + +**input(pre-filter):** This macro is to specify your environment-specific configurations (index, source, sourcetype, etc.) to get the specific data sources that you would like to bring in. Replace the macro definition with configurations for your Splunk environment. + +**output(post-filter):** This macro is to specify your environment-specific values (eg: dest, user), to filter out known false positives.. Replace the macro definition with values that you’d like to exclude from detection results. Think of this as a whitelisting/blacklisting using macros. + +Note: we are currently working on coming up with a better naming convention and making this consistent across all our detections, investigations and baselines. Suggestions are welcomed :stuck_out_tongue: + +# Execute an Analytic Story + +Download and install the latest version of [Splunk Analytic Story Execution] +(https://github.com/splunk/analytic_story_execution/releases). This Splunk application will help the user do the following: + +1. Execute an analytic story in an adhoc mode and view the results. +2. Schedule all the detection searches in an analytic story. +3. Update security-content via an API + +# Security Content + +#### Content Parts +* [stories/](stories/): All Analytic Stories +* [detections/](detections/): Splunk Enterprise, Splunk UBA, and Splunk Phantom detections that power Analytic Stories +* [response_tasks/](response_tasks/): Splunk Enterprise and Splunk Phantom investigative searches and playbooks employed by Analytic Stories +* [responses/](responses/): Automated Splunk Enterprise and Splunk Phantom responses triggered by Analytic Stories +* [baselines/](baselines/): Splunk Phantom and Splunk Enterprise baseline searches needed to support detection searches in Analytic Stories + +#### Supporting Parts +* [package/](package/): Splunk content app-source files, including lookups, binaries, and default config files +* [bin/](bin/): All binaries required to produce and test content + +# Contribution +We welcome feedback and contributions from the community! Please see our [contribution guidelines](docs/CONTRIBUTING.md) for more information on how to get involved. + +## Support +Please use the [GitHub Issue Tracker](https://github.com/splunk/security-content/issues) to submit bugs or request features. + +If you have questions or need support, you can: + +* Post a question to [Splunk Answers](http://answers.splunk.com) +* Join the [#security-research](https://splunk-usergroups.slack.com/messages/C1RH09ERM/) room in the [Splunk Slack channel](http://splunk-usergroups.slack.com) +* If you are a Splunk Enterprise customer with a valid support entitlement contract and have a Splunk-related question, you can also open a support case on the https://www.splunk.com/ support portal From c76ebad945da2d4c4976cc1820e9f86010b72c12 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Tue, 19 May 2020 17:00:31 +0200 Subject: [PATCH 62/93] updated Readme --- README.md | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index e6d9ae6076..90a3c0862c 100644 --- a/README.md +++ b/README.md @@ -25,8 +25,8 @@ curl -s https://content.splunkresearch.com | jq } ``` -#### GitHub Workflow (link to wiki) -Create your customized version of Security Content by following this guide. +#### GitHub Workflow +Create your customized version of Security Content by forking this project and following this guide. # What's in an Analytic Story? [Analytic Stories](https://github.com/splunk/security-content/blob/develop/docs/stories_categories.md) and their corresponding searches are composed of **.yml** files (manifests) and associated .conf files. The stories reside in [/stories](https://github.com/splunk/security-content/tree/develop/stories) and the searches live in [/detections](https://github.com/splunk/security-content/tree/develop/detections). @@ -41,7 +41,6 @@ After release [1.0.46](https://github.com/splunk/security-content/releases) we i **output(post-filter):** This macro is to specify your environment-specific values (eg: dest, user), to filter out known false positives.. Replace the macro definition with values that you’d like to exclude from detection results. Think of this as a whitelisting/blacklisting using macros. -Note: we are currently working on coming up with a better naming convention and making this consistent across all our detections, investigations and baselines. Suggestions are welcomed :stuck_out_tongue: # Execute an Analytic Story From c5e25d7355b131cea94ec079d86c99fc60e72c6b Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Wed, 20 May 2020 14:23:16 +0200 Subject: [PATCH 63/93] generate a mitre enrichment lookup --- bin/generate.py | 35 +++ lookups/mitre_enrichment.csv | 267 ++++++++++++++++++ package/default/analytic_stories.conf | 140 ++++----- ...l_investigate_pass_the_ticket_attempts.xml | 2 +- package/default/es_investigations.conf | 116 ++++---- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 8 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 130 ++++----- 9 files changed, 502 insertions(+), 200 deletions(-) create mode 100644 lookups/mitre_enrichment.csv diff --git a/bin/generate.py b/bin/generate.py index cd28d011d1..d3b7f48659 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -12,6 +12,8 @@ import sys import datetime from jinja2 import Environment, FileSystemLoader import re +from attackcti import attack_client +import csv # global variables @@ -436,6 +438,33 @@ def prepare_stories(stories, detections): return stories +def generate_mitre_lookup(): + + csv_mitre_rows = [["mitre_id", "technique", "tactics", "groups"]] + + lift = attack_client() + all_enterprise = lift.get_enterprise(stix_format=False) + enterprise_relationships = lift.get_enterprise_relationships() + enterprise_groups = lift.get_enterprise_groups() + + for technique in all_enterprise['techniques']: + apt_groups = [] + for relationship in enterprise_relationships: + if (relationship['target_ref'] == technique['id']) and relationship['source_ref'].startswith('intrusion-set'): + for group in enterprise_groups: + if relationship['source_ref'] == group['id']: + apt_groups.append(group['name']) + + if len(apt_groups) == 0: + apt_groups.append('no') + csv_mitre_rows.append([technique['technique_id'], technique['technique'], '|'.join(technique['tactic']).replace('-',' ').title(), '|'.join(apt_groups)]) + + with open('lookups/mitre_enrichment.csv', 'w', newline='') as file: + writer = csv.writer(file) + writer.writerows(csv_mitre_rows) + + + if __name__ == "__main__": parser = argparse.ArgumentParser(description="generates splunk conf files out of security-content manifests", epilog=""" @@ -459,6 +488,11 @@ if __name__ == "__main__": response_tasks = load_objects("response_tasks/*.yml") deployments = load_objects("deployments/*.yml") + try: + generate_mitre_lookup() + except: + print("WARNING: Generation of Mitre lookup failed.") + lookups_path = generate_transforms_conf(lookups) detections = sorted(detections, key=lambda d: d['name']) @@ -476,6 +510,7 @@ if __name__ == "__main__": generate_workbench_panels(response_tasks, stories) + if VERBOSE: print("{0} stories have been successfully written to {1}".format(len(stories), story_path)) print("{0} detections have been successfully written to {1}".format(len(detections), detection_path)) diff --git a/lookups/mitre_enrichment.csv b/lookups/mitre_enrichment.csv new file mode 100644 index 0000000000..bb5180d7ae --- /dev/null +++ b/lookups/mitre_enrichment.csv @@ -0,0 +1,267 @@ +mitre_id,technique,tactics,groups +T1531,Account Access Removal,Impact,no +T1506,Web Session Cookie,Defense Evasion|Lateral Movement,no +T1539,Steal Web Session Cookie,Credential Access,no +T1529,System Shutdown/Reboot,Impact,Lazarus Group|APT38|APT37 +T1519,Emond,Persistence|Privilege Escalation,no +T1518,Software Discovery,Discovery,no +T1534,Internal Spearphishing,Lateral Movement,no +T1528,Steal Application Access Token,Credential Access,APT28 +T1522,Cloud Instance Metadata API,Credential Access,no +T1536,Revert Cloud Instance,Defense Evasion,no +T1535,Unused/Unsupported Cloud Regions,Defense Evasion,no +T1525,Implant Container Image,Persistence,no +T1538,Cloud Service Dashboard,Discovery,no +T1530,Data from Cloud Storage Object,Collection,no +T1537,Transfer Data to Cloud Account,Exfiltration,no +T1526,Cloud Service Discovery,Discovery,no +T1527,Application Access Token,Defense Evasion|Lateral Movement,APT28 +T1514,Elevated Execution with Prompt,Privilege Escalation,no +T1505,Server Software Component,Persistence,no +T1503,Credentials from Web Browsers,Credential Access,TA505|Stolen Pencil|MuddyWater +T1504,PowerShell Profile,Persistence|Privilege Escalation,Turla +T1502,Parent PID Spoofing,Defense Evasion|Privilege Escalation,no +T1500,Compile After Delivery,Defense Evasion,MuddyWater +T1501,Systemd Service,Persistence,no +T1499,Endpoint Denial of Service,Impact,no +T1497,Virtualization/Sandbox Evasion,Defense Evasion|Discovery,The White Company|FIN7 +T1498,Network Denial of Service,Impact,no +T1496,Resource Hijacking,Impact,APT41|Lazarus Group +T1495,Firmware Corruption,Impact,no +T1494,Runtime Data Manipulation,Impact,APT38 +T1493,Transmitted Data Manipulation,Impact,APT38 +T1492,Stored Data Manipulation,Impact,FIN4|APT38 +T1491,Defacement,Impact,no +T1490,Inhibit System Recovery,Impact,no +T1489,Service Stop,Impact,Lazarus Group +T1488,Disk Content Wipe,Impact,Lazarus Group +T1487,Disk Structure Wipe,Impact,Lazarus Group|APT38|APT37 +T1486,Data Encrypted for Impact,Impact,APT41|TA505|APT38 +T1485,Data Destruction,Impact,Lazarus Group|APT38 +T1484,Group Policy Modification,Defense Evasion,no +T1483,Domain Generation Algorithms,Command And Control,APT41 +T1482,Domain Trust Discovery,Discovery,no +T1480,Execution Guardrails,Defense Evasion,APT33|Equation +T1223,Compiled HTML File,Defense Evasion|Execution,APT41|Silence|Lazarus Group|Dark Caracal|OilRig +T1222,File and Directory Permissions Modification,Defense Evasion,APT32 +T1221,Template Injection,Defense Evasion,APT28|Tropic Trooper|Dragonfly 2.0|DarkHydrus +T1220,XSL Script Processing,Defense Evasion|Execution,Cobalt Group +T1197,BITS Jobs,Defense Evasion|Persistence,Leviathan +T1191,CMSTP,Defense Evasion|Execution,Cobalt Group|MuddyWater +T1196,Control Panel Items,Defense Evasion|Execution,no +T1214,Credentials in Registry,Credential Access,Soft Cell +T1207,DCShadow,Defense Evasion,no +T1217,Browser Bookmark Discovery,Discovery,no +T1213,Data from Information Repositories,Collection,Ke3chang|APT28 +T1189,Drive-by Compromise,Initial Access,Darkhotel|APT38|Lazarus Group|Leafminer|Dragonfly 2.0|BRONZE BUTLER|Threat Group-3390|Dark Caracal|APT19|APT32|Elderwood|APT37|Patchwork|PLATINUM +T1203,Exploitation for Client Execution,Execution,APT41|admin@338|Threat Group-3390|APT12|The White Company|APT33|APT32|APT28|Tropic Trooper|BRONZE BUTLER|Lazarus Group|Cobalt Group|APT37|Leviathan|APT29|Patchwork|TA459|Elderwood +T1212,Exploitation for Credential Access,Credential Access,no +T1202,Indirect Command Execution,Defense Evasion,no +T1190,Exploit Public-Facing Application,Initial Access,Soft Cell|Night Dragon|Axiom +T1210,Exploitation of Remote Services,Lateral Movement,Threat Group-3390|APT28 +T1211,Exploitation for Defense Evasion,Defense Evasion,APT28 +T1200,Hardware Additions,Initial Access,no +T1208,Kerberoasting,Credential Access,no +T1215,Kernel Modules and Extensions,Persistence,no +T1198,SIP and Trust Provider Hijacking,Defense Evasion|Persistence,no +T1194,Spearphishing via Service,Initial Access,FIN6|OilRig|Dark Caracal|Magic Hound +T1195,Supply Chain Compromise,Initial Access,APT41|Elderwood +T1192,Spearphishing Link,Initial Access,Machete|Kimsuky|TA505|Stolen Pencil|APT39|FIN4|APT32|Night Dragon|APT28|Cobalt Group|Turla|OilRig|Dragonfly 2.0|APT33|Elderwood|APT29|Leviathan|Patchwork|Magic Hound|FIN8 +T1206,Sudo Caching,Privilege Escalation,no +T1199,Trusted Relationship,Initial Access,APT28|menuPass +T1201,Password Policy Discovery,Discovery,OilRig +T1205,Port Knocking,Defense Evasion|Persistence|Command And Control,no +T1218,Signed Binary Proxy Execution,Defense Evasion|Execution,TA505|Rancor|Cobalt Group +T1219,Remote Access Tools,Command And Control,Kimsuky|Night Dragon|Thrip|Cobalt Group|Carbanak +T1216,Signed Script Proxy Execution,Defense Evasion|Execution,APT32 +T1193,Spearphishing Attachment,Initial Access,APT41|Machete|admin@338|Kimsuky|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Tropic Trooper|Turla|Gorgon Group|Rancor|DarkHydrus|Lazarus Group|Cobalt Group|OilRig|FIN7|APT19|BRONZE BUTLER|Dragonfly 2.0|APT32|MuddyWater|TA459|FIN8|APT28|Patchwork|APT29|Elderwood|APT37|Leviathan|Magic Hound|menuPass|PLATINUM +T1209,Time Providers,Persistence,no +T1204,User Execution,Execution,Machete|admin@338|APT12|TA505|Silence|The White Company|APT39|FIN4|Night Dragon|Darkhotel|Gallmaker|APT33|Dragonfly 2.0|Cobalt Group|APT19|BRONZE BUTLER|Dark Caracal|FIN7|DarkHydrus|Turla|Gorgon Group|Lazarus Group|APT32|OilRig|MuddyWater|Patchwork|Rancor|APT37|APT29|FIN8|APT28|menuPass|TA459|Elderwood|Leviathan|Magic Hound|PLATINUM +T1182,AppCert DLLs,Persistence|Privilege Escalation,Honeybee +T1176,Browser Extensions,Persistence,Kimsuky|Stolen Pencil +T1175,Component Object Model and Distributed COM,Lateral Movement|Execution,MuddyWater +T1181,Extra Window Memory Injection,Defense Evasion|Privilege Escalation,no +T1179,Hooking,Persistence|Privilege Escalation|Credential Access,PLATINUM +T1183,Image File Execution Options Injection,Privilege Escalation|Persistence|Defense Evasion,TEMP.Veles +T1172,Domain Fronting,Command And Control,APT29 +T1173,Dynamic Data Exchange,Execution,TA505|MuddyWater|Gallmaker|Patchwork|Cobalt Group|APT37|APT28|FIN7 +T1187,Forced Authentication,Credential Access,DarkHydrus|Dragonfly 2.0 +T1171,LLMNR/NBT-NS Poisoning and Relay,Credential Access,no +T1188,Multi-hop Proxy,Command And Control,FIN4|APT29 +T1177,LSASS Driver,Execution|Persistence,no +T1174,Password Filter DLL,Credential Access,no +T1185,Man in the Browser,Collection,no +T1184,SSH Hijacking,Lateral Movement,no +T1180,Screensaver,Persistence,no +T1178,SID-History Injection,Privilege Escalation,no +T1170,Mshta,Defense Evasion|Execution,Kimsuky|APT32|MuddyWater|FIN7 +T1186,Process Doppelgänging,Defense Evasion,no +T1156,.bash_profile and .bashrc,Persistence,no +T1134,Access Token Manipulation,Defense Evasion|Privilege Escalation,Turla|Lazarus Group|APT28 +T1155,AppleScript,Execution|Lateral Movement,no +T1138,Application Shimming,Persistence|Privilege Escalation,FIN7 +T1146,Clear Command History,Defense Evasion,APT41 +T1139,Bash History,Credential Access,no +T1136,Create Account,Persistence,APT41|Soft Cell|Dragonfly 2.0|Leafminer|APT3 +T1140,Deobfuscate/Decode Files or Information,Defense Evasion,Turla|WIRTE|Darkhotel|Tropic Trooper|Honeybee|menuPass|Gorgon Group|Threat Group-3390|APT19|Leviathan|MuddyWater|APT28|OilRig|BRONZE BUTLER +T1157,Dylib Hijacking,Persistence|Privilege Escalation,no +T1148,HISTCONTROL,Defense Evasion,no +T1144,Gatekeeper Bypass,Defense Evasion,no +T1158,Hidden Files and Directories,Defense Evasion|Persistence,APT32|Tropic Trooper|APT28|Lazarus Group +T1147,Hidden Users,Defense Evasion,no +T1143,Hidden Window,Defense Evasion,Gorgon Group|Deep Panda|DarkHydrus|CopyKittens|APT19|APT32|APT28|APT3|Magic Hound +T1141,Input Prompt,Credential Access,FIN4 +T1149,LC_MAIN Hijacking,Defense Evasion,no +T1152,Launchctl,Defense Evasion|Execution|Persistence,no +T1168,Local Job Scheduling,Persistence|Execution,no +T1161,LC_LOAD_DYLIB Addition,Persistence,no +T1160,Launch Daemon,Persistence|Privilege Escalation,no +T1150,Plist Modification,Defense Evasion|Persistence|Privilege Escalation,no +T1145,Private Keys,Credential Access,no +T1162,Login Item,Persistence,no +T1153,Source,Execution,no +T1137,Office Application Startup,Persistence,APT32|APT28 +T1167,Securityd Memory,Credential Access,no +T1166,Setuid and Setgid,Privilege Escalation|Persistence,no +T1165,Startup Items,Persistence|Privilege Escalation,no +T1163,Rc.common,Persistence,no +T1151,Space after Filename,Defense Evasion|Execution,no +T1154,Trap,Execution|Persistence,no +T1142,Keychain,Credential Access,no +T1159,Launch Agent,Persistence,no +T1135,Network Share Discovery,Discovery,APT41|Tropic Trooper|APT1|Dragonfly 2.0|Sowbug +T1164,Re-opened Applications,Persistence,no +T1169,Sudo,Privilege Escalation,no +T1133,External Remote Services,Persistence|Initial Access,APT41|Soft Cell|TEMP.Veles|Night Dragon|OilRig|Ke3chang|Dragonfly 2.0|FIN5|Threat Group-3390|APT18 +T1132,Data Encoding,Command And Control,APT33|APT19|Lazarus Group|BRONZE BUTLER|Patchwork +T1131,Authentication Package,Persistence,no +T1130,Install Root Certificate,Defense Evasion,no +T1129,Execution through Module Load,Execution,no +T1128,Netsh Helper DLL,Persistence,no +T1127,Trusted Developer Utilities,Defense Evasion|Execution,no +T1126,Network Share Connection Removal,Defense Evasion,Threat Group-3390 +T1125,Video Capture,Collection,Silence|FIN7 +T1124,System Time Discovery,Discovery,The White Company|Lazarus Group|BRONZE BUTLER|Turla +T1123,Audio Capture,Collection,APT37 +T1122,Component Object Model Hijacking,Defense Evasion|Persistence,APT28 +T1121,Regsvcs/Regasm,Defense Evasion|Execution,no +T1120,Peripheral Device Discovery,Discovery,APT37|Gamaredon Group|Equation|APT28 +T1119,Automated Collection,Collection,APT1|APT28|Patchwork|OilRig|FIN5|Threat Group-3390|FIN6 +T1118,InstallUtil,Defense Evasion|Execution,no +T1117,Regsvr32,Defense Evasion|Execution,WIRTE|Cobalt Group|APT19|Leviathan|APT32|Deep Panda +T1116,Code Signing,Defense Evasion,APT41|FIN6|TA505|FIN7|Honeybee|APT37|Leviathan|CopyKittens|Winnti Group|Suckfly|Molerats|Darkhotel +T1115,Clipboard Data,Collection,APT38 +T1114,Email Collection,Collection,FIN4|Dragonfly 2.0|APT28|Ke3chang|Magic Hound|Leafminer|APT1 +T1113,Screen Capture,Collection,Silence|MuddyWater|OilRig|Dragonfly 2.0|FIN7|Dark Caracal|BRONZE BUTLER|Magic Hound|Group5|APT28 +T1112,Modify Registry,Defense Evasion,APT41|Turla|APT32|APT38|Dragonfly 2.0|Patchwork|APT19|Threat Group-3390|Gorgon Group|Honeybee|FIN8 +T1111,Two-Factor Authentication Interception,Credential Access,no +T1110,Brute Force,Credential Access,APT41|APT33|Leafminer|OilRig|Dragonfly 2.0|APT3|Lazarus Group|Turla +T1109,Component Firmware,Defense Evasion|Persistence,Equation +T1108,Redundant Access,Defense Evasion|Persistence,Stolen Pencil|Cobalt Group|Leafminer|APT3|OilRig|FIN5|Threat Group-3390 +T1107,File Deletion,Defense Evasion,APT41|Kimsuky|Silence|The White Company|TEMP.Veles|APT32|APT38|Patchwork|Honeybee|Cobalt Group|menuPass|Dragonfly 2.0|FIN8|FIN5|OilRig|Magic Hound|BRONZE BUTLER|APT3|APT28|FIN10|Threat Group-3390|Group5|Lazarus Group|APT18|APT29 +T1106,Execution through API,Execution,Turla|Silence|APT37|Gorgon Group +T1105,Remote File Copy,Command And Control|Lateral Movement,Soft Cell|TA505|WIRTE|APT33|MuddyWater|APT18|APT38|Turla|Gorgon Group|Cobalt Group|Rancor|Dragonfly 2.0|OilRig|FIN8|APT37|PLATINUM|Leviathan|Elderwood|Magic Hound|APT3|APT32|BRONZE BUTLER|FIN7|menuPass|FIN10|Gamaredon Group|Patchwork|Lazarus Group|Threat Group-3390|APT28 +T1104,Multi-Stage Channels,Command And Control,MuddyWater|APT3 +T1103,AppInit DLLs,Persistence|Privilege Escalation,no +T1102,Web Service,Command And Control|Defense Evasion,APT41|APT12|FIN6|Turla|FIN7|BRONZE BUTLER|Leviathan|APT37|Magic Hound|RTM|Patchwork|Carbanak +T1101,Security Support Provider,Persistence,no +T1100,Web Shell,Persistence|Privilege Escalation,Soft Cell|Threat Group-3390|TEMP.Veles|Leviathan|APT39|Dragonfly 2.0|APT32|OilRig|Deep Panda +T1099,Timestomp,Defense Evasion,TEMP.Veles|APT32|Lazarus Group|APT28 +T1098,Account Manipulation,Credential Access|Persistence,Magic Hound|Dragonfly 2.0|APT3|Lazarus Group +T1097,Pass the Ticket,Lateral Movement,APT32|Ke3chang|BRONZE BUTLER|APT29 +T1096,NTFS File Attributes,Defense Evasion,APT32 +T1095,Standard Non-Application Layer Protocol,Command And Control,APT29|PLATINUM|APT3 +T1094,Custom Command and Control Protocol,Command And Control,PLATINUM|APT37|OilRig|APT32 +T1093,Process Hollowing,Defense Evasion,menuPass|Gorgon Group|Patchwork +T1092,Communication Through Removable Media,Command And Control,APT28 +T1091,Replication Through Removable Media,Lateral Movement|Initial Access,Darkhotel|APT28 +T1090,Connection Proxy,Command And Control|Defense Evasion,APT41|Soft Cell|Turla|APT39|MuddyWater|APT3|Lazarus Group|menuPass|Strider|APT28 +T1089,Disabling Security Tools,Defense Evasion,Kimsuky|Turla|Night Dragon|Dragonfly 2.0|Gorgon Group|Threat Group-3390|Lazarus Group|Putter Panda|Carbanak +T1088,Bypass User Account Control,Defense Evasion|Privilege Escalation,APT37|MuddyWater|Honeybee|Threat Group-3390|Cobalt Group|BRONZE BUTLER|Patchwork|APT29 +T1087,Account Discovery,Discovery,APT32|APT1|Dragonfly 2.0|BRONZE BUTLER|OilRig|Threat Group-3390|menuPass|FIN6|Poseidon Group|APT3|admin@338|Ke3chang +T1086,PowerShell,Execution,APT41|Kimsuky|Soft Cell|TA505|WIRTE|TEMP.Veles|APT33|Gallmaker|Turla|DarkHydrus|Dragonfly 2.0|APT19|Thrip|Cobalt Group|APT28|Gorgon Group|Leviathan|TA459|MuddyWater|FIN8|CopyKittens|OilRig|Magic Hound|BRONZE BUTLER|APT32|FIN10|FIN7|Threat Group-3390|menuPass|Patchwork|Stealth Falcon|FIN6|Poseidon Group|APT3|APT29|Deep Panda +T1085,Rundll32,Defense Evasion|Execution,TA505|MuddyWater|APT29|APT19|CopyKittens|APT3|Carbanak|APT28 +T1084,Windows Management Instrumentation Event Subscription,Persistence,Turla|Leviathan|APT29 +T1083,File and Directory Discovery,Discovery,Kimsuky|APT32|MuddyWater|APT18|Dragonfly 2.0|Dark Caracal|Leafminer|Honeybee|Sowbug|BRONZE BUTLER|APT3|Magic Hound|APT28|Patchwork|Lazarus Group|Dust Storm|admin@338|Turla|Ke3chang +T1082,System Information Discovery,Discovery,Kimsuky|Tropic Trooper|Darkhotel|MuddyWater|APT18|APT37|Honeybee|APT19|APT32|OilRig|Magic Hound|APT3|Sowbug|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|admin@338|Turla|Ke3chang +T1081,Credentials in Files,Credential Access,OilRig|Kimsuky|Turla|TA505|Stolen Pencil|MuddyWater|APT3 +T1080,Taint Shared Content,Lateral Movement,Darkhotel +T1079,Multilayer Encryption,Command And Control,no +T1078,Valid Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,APT41|Soft Cell|TEMP.Veles|APT39|Stolen Pencil|FIN4|Night Dragon|Dragonfly 2.0|FIN8|APT33|Leviathan|APT3|FIN5|OilRig|menuPass|APT28|APT32|FIN10|Suckfly|FIN6|Threat Group-1314|Threat Group-3390|APT18|PittyTiger|Carbanak +T1077,Windows Admin Shares,Lateral Movement,APT32|Orangeworm|FIN8|APT3|Lazarus Group|Threat Group-1314|Turla|Deep Panda|Ke3chang +T1076,Remote Desktop Protocol,Lateral Movement,APT41|TEMP.Veles|Leviathan|APT39|Stolen Pencil|Cobalt Group|Dragonfly 2.0|FIN8|APT3|OilRig|menuPass|FIN10|Patchwork|FIN6|Lazarus Group|APT1|Axiom +T1075,Pass the Hash,Lateral Movement,Soft Cell|APT32|Night Dragon|APT28|APT1 +T1074,Data Staged,Collection,Machete|Soft Cell|TEMP.Veles|Night Dragon|Patchwork|Honeybee|Dragonfly 2.0|Leviathan|FIN8|APT3|FIN5|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT28 +T1073,DLL Side-Loading,Defense Evasion,APT41|Soft Cell|Tropic Trooper|Patchwork|APT19|APT32|APT3|menuPass|Threat Group-3390 +T1072,Third-party Software,Execution|Lateral Movement,Threat Group-1314 +T1071,Standard Application Layer Protocol,Command And Control,APT41|Machete|WIRTE|APT33|FIN4|Night Dragon|APT18|SilverTerrier|APT38|Dragonfly 2.0|APT19|Cobalt Group|FIN7|APT37|Threat Group-3390|Turla|Honeybee|Rancor|Orangeworm|Ke3chang|Dark Caracal|Lazarus Group|BRONZE BUTLER|OilRig|APT32|Magic Hound|Gamaredon Group|Stealth Falcon|FIN6|APT28 +T1070,Indicator Removal on Host,Defense Evasion,APT41|APT29|APT38|Dragonfly 2.0|APT32|FIN8|FIN5|APT28 +T1069,Permission Groups Discovery,Discovery,FIN6|Dragonfly 2.0|OilRig|APT3|admin@338|Ke3chang +T1068,Exploitation for Privilege Escalation,Privilege Escalation,APT33|Cobalt Group|PLATINUM|FIN8|APT32|Threat Group-3390|FIN6|APT28 +T1067,Bootkit,Persistence,APT41|Lazarus Group|APT28 +T1066,Indicator Removal from Tools,Defense Evasion,Soft Cell|TEMP.Veles|Patchwork|APT3|Turla|OilRig|Deep Panda +T1065,Uncommonly Used Port,Command And Control,TEMP.Veles|APT33|APT32|Gorgon Group|Magic Hound|Group5|Lazarus Group|APT3 +T1064,Scripting,Defense Evasion|Execution,Machete|Turla|TA505|Silence|WIRTE|APT39|FIN4|APT32|Darkhotel|Gallmaker|Dark Caracal|Lazarus Group|menuPass|APT19|Leafminer|Rancor|Dragonfly 2.0|Cobalt Group|Honeybee|Ke3chang|APT37|FIN7|Patchwork|Gorgon Group|MuddyWater|Leviathan|TA459|FIN8|APT28|Magic Hound|OilRig|BRONZE BUTLER|FIN5|FIN10|Gamaredon Group|Stealth Falcon|FIN6|APT3|APT29|Deep Panda|APT1 +T1063,Security Software Discovery,Discovery,The White Company|Cobalt Group|Darkhotel|MuddyWater|Tropic Trooper|FIN8|Patchwork|Naikon +T1062,Hypervisor,Persistence,no +T1061,Graphical User Interface,Execution,APT3 +T1060,Registry Run Keys / Startup Folder,Persistence,APT41|Machete|Kimsuky|APT33|APT39|APT32|APT18|Turla|APT19|Cobalt Group|Threat Group-3390|Honeybee|Dark Caracal|Ke3chang|Dragonfly 2.0|Gorgon Group|MuddyWater|APT37|Leviathan|APT3|BRONZE BUTLER|Magic Hound|FIN10|FIN7|Patchwork|FIN6|Lazarus Group|Putter Panda|APT29|Darkhotel +T1059,Command-Line Interface,Execution,APT41|Soft Cell|Turla|Silence|APT32|Cobalt Group|MuddyWater|APT18|APT38|APT28|Dragonfly 2.0|Gorgon Group|FIN7|Honeybee|Rancor|APT37|Leviathan|FIN8|Magic Hound|Sowbug|OilRig|BRONZE BUTLER|menuPass|Threat Group-3390|Suckfly|Patchwork|Lazarus Group|Threat Group-1314|APT3|admin@338|APT1|Ke3chang +T1058,Service Registry Permissions Weakness,Persistence|Privilege Escalation,no +T1057,Process Discovery,Discovery,Darkhotel|MuddyWater|APT1|APT38|Tropic Trooper|APT37|Honeybee|OilRig|APT3|Magic Hound|APT28|Winnti Group|Stealth Falcon|Poseidon Group|Lazarus Group|Molerats|Turla|Deep Panda|Ke3chang +T1056,Input Capture,Collection|Credential Access,APT41|Kimsuky|menuPass|Stolen Pencil|FIN4|APT38|OilRig|Ke3chang|PLATINUM|Sowbug|Magic Hound|Group5|Lazarus Group|Threat Group-3390|APT3|Darkhotel|APT28 +T1055,Process Injection,Defense Evasion|Privilege Escalation,APT41|Kimsuky|Tropic Trooper|Gorgon Group|Threat Group-3390|APT37|Turla|Cobalt Group|Honeybee|Lazarus Group|PLATINUM|Putter Panda +T1054,Indicator Blocking,Defense Evasion,no +T1053,Scheduled Task,Execution|Persistence|Privilege Escalation,APT41|Machete|Soft Cell|Silence|TEMP.Veles|APT33|APT39|Dragonfly 2.0|Cobalt Group|OilRig|Rancor|Patchwork|FIN8|BRONZE BUTLER|FIN10|menuPass|APT32|FIN7|Stealth Falcon|FIN6|Threat Group-3390|APT18|APT3|APT29 +T1052,Exfiltration Over Physical Medium,Exfiltration,no +T1051,Shared Webroot,Lateral Movement,no +T1050,New Service,Persistence|Privilege Escalation,Kimsuky|Tropic Trooper|Cobalt Group|FIN7|Threat Group-3390|Ke3chang|APT32|APT3|Lazarus Group|Carbanak +T1049,System Network Connections Discovery,Discovery,APT41|APT38|Soft Cell|APT32|APT1|OilRig|APT3|menuPass|Threat Group-3390|Poseidon Group|admin@338|Turla|Ke3chang +T1048,Exfiltration Over Alternative Protocol,Exfiltration,Turla|APT33|Thrip|FIN8|OilRig|Lazarus Group +T1047,Windows Management Instrumentation,Execution,APT41|FIN6|Soft Cell|APT32|MuddyWater|OilRig|Threat Group-3390|Leviathan|FIN8|menuPass|Stealth Falcon|Lazarus Group|APT29|Deep Panda +T1046,Network Service Scanning,Discovery,APT41|Tropic Trooper|APT39|APT32|Cobalt Group|OilRig|Leafminer|menuPass|Suckfly|FIN6|Threat Group-3390 +T1045,Software Packing,Defense Evasion,Soft Cell|The White Company|APT39|APT38|Dark Caracal|Elderwood|APT3|Group5|Patchwork|APT29|Night Dragon +T1044,File System Permissions Weakness,Persistence|Privilege Escalation,no +T1043,Commonly Used Port,Command And Control,Machete|OilRig|APT28|TEMP.Veles|APT33|APT32|Night Dragon|APT29|APT18|Tropic Trooper|APT19|FIN7|Dragonfly 2.0|FIN8|APT37|Magic Hound|APT3|Lazarus Group|Threat Group-3390 +T1042,Change Default File Association,Persistence,Kimsuky +T1041,Exfiltration Over Command and Control Channel,Exfiltration,Kimsuky|Soft Cell|APT32|APT3|Gamaredon Group|Stealth Falcon|Lazarus Group|Ke3chang +T1040,Network Sniffing,Credential Access|Discovery,APT33|Stolen Pencil|APT28 +T1039,Data from Network Shared Drive,Collection,Sowbug|BRONZE BUTLER|menuPass +T1038,DLL Search Order Hijacking,Persistence|Privilege Escalation|Defense Evasion,Threat Group-3390|menuPass +T1037,Logon Scripts,Lateral Movement|Persistence,Cobalt Group|APT28 +T1036,Masquerading,Defense Evasion,APT41|Soft Cell|PLATINUM|Ke3chang|Scarlet Mimic|menuPass|FIN6|TEMP.Veles|Dragonfly 2.0|MuddyWater|BRONZE BUTLER|Sowbug|FIN7|APT32|Patchwork|Poseidon Group|admin@338|Carbanak|APT1 +T1035,Service Execution,Execution,Silence|FIN6|APT32|Honeybee|Ke3chang +T1034,Path Interception,Persistence|Privilege Escalation,no +T1033,System Owner/User Discovery,Discovery,APT41|Soft Cell|Tropic Trooper|APT39|MuddyWater|APT37|APT32|APT19|Dragonfly 2.0|Magic Hound|OilRig|FIN10|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|APT3 +T1032,Standard Cryptographic Protocol,Command And Control,Machete|APT33|Tropic Trooper|Cobalt Group|OilRig|FIN8|BRONZE BUTLER|Stealth Falcon|FIN6|Lazarus Group|Taidoor +T1031,Modify Existing Service,Persistence,APT41|APT32|Honeybee|APT19 +T1030,Data Transfer Size Limits,Exfiltration,Threat Group-3390 +T1029,Scheduled Transfer,Exfiltration,no +T1028,Windows Remote Management,Execution|Lateral Movement,Threat Group-3390 +T1027,Obfuscated Files or Information,Defense Evasion,Machete|Soft Cell|Turla|TA505|Silence|APT33|Night Dragon|Darkhotel|Gallmaker|APT29|APT18|Tropic Trooper|menuPass|Honeybee|Leafminer|Patchwork|Cobalt Group|APT37|Threat Group-3390|Dark Caracal|APT19|FIN8|BlackOasis|Leviathan|Elderwood|MuddyWater|FIN7|APT3|Magic Hound|OilRig|APT32|Group5|Dust Storm|Lazarus Group|Putter Panda|APT28 +T1026,Multiband Communication,Command And Control,Lazarus Group +T1025,Data from Removable Media,Collection,Machete|Turla|Gamaredon Group|APT28 +T1024,Custom Cryptographic Protocol,Command And Control,APT28|BRONZE BUTLER|Lazarus Group +T1023,Shortcut Modification,Persistence,APT39|Darkhotel|APT29|FIN7|Gorgon Group|Dragonfly 2.0|Leviathan|Lazarus Group +T1022,Data Encrypted,Exfiltration,Kimsuky|Soft Cell|Turla|menuPass|APT32|Patchwork|Honeybee|CopyKittens|BRONZE BUTLER|FIN6|Lazarus Group|Threat Group-3390|Ke3chang +T1021,Remote Services,Lateral Movement,TEMP.Veles|Leviathan|APT39|OilRig|menuPass|GCMAN +T1020,Automated Exfiltration,Exfiltration,Honeybee +T1019,System Firmware,Persistence,no +T1018,Remote System Discovery,Discovery,Soft Cell|APT32|Threat Group-3390|Dragonfly 2.0|Deep Panda|Ke3chang|Leafminer|FIN8|FIN5|APT3|BRONZE BUTLER|menuPass|FIN6|Turla +T1017,Application Deployment Software,Lateral Movement,APT32 +T1016,System Network Configuration Discovery,Discovery,APT41|Soft Cell|APT39|APT32|Darkhotel|MuddyWater|APT1|APT19|Dragonfly 2.0|Magic Hound|OilRig|menuPass|Threat Group-3390|Stealth Falcon|Lazarus Group|APT3|Naikon|admin@338|Turla|Ke3chang +T1015,Accessibility Features,Persistence|Privilege Escalation,APT41|APT3|APT29|Deep Panda|Axiom +T1014,Rootkit,Defense Evasion,APT41|APT28|Winnti Group +T1013,Port Monitors,Persistence|Privilege Escalation,no +T1012,Query Registry,Discovery,APT32|Dragonfly 2.0|Threat Group-3390|OilRig|Stealth Falcon|Lazarus Group|Turla +T1011,Exfiltration Over Other Network Medium,Exfiltration,no +T1010,Application Window Discovery,Discovery,Lazarus Group +T1009,Binary Padding,Defense Evasion,Patchwork|APT32|Leviathan|BRONZE BUTLER|Moafee +T1008,Fallback Channels,Command And Control,APT41|OilRig|Lazarus Group +T1007,System Service Discovery,Discovery,APT1|OilRig|Poseidon Group|admin@338|Turla|Ke3chang +T1006,File System Logical Offsets,Defense Evasion,no +T1005,Data from Local System,Collection,Kimsuky|Soft Cell|Turla|menuPass|Dark Caracal|Dragonfly 2.0|Honeybee|APT37|APT28|APT3|BRONZE BUTLER|Patchwork|Stealth Falcon|Lazarus Group|Dust Storm|Threat Group-3390|APT1|Ke3chang +T1004,Winlogon Helper DLL,Persistence,Tropic Trooper|Turla +T1003,Credential Dumping,Credential Access,APT41|Soft Cell|TEMP.Veles|APT33|Leviathan|APT39|Stolen Pencil|APT32|Night Dragon|Dragonfly 2.0|Leafminer|Lazarus Group|Magic Hound|PLATINUM|APT37|MuddyWater|FIN8|Sowbug|BRONZE BUTLER|OilRig|FIN5|menuPass|Strider|Patchwork|Stealth Falcon|Suckfly|FIN6|Poseidon Group|Threat Group-3390|APT3|Molerats|APT28|APT1|Ke3chang|Cleaver|Axiom +T1002,Data Compressed,Exfiltration,APT41|Soft Cell|Gallmaker|APT33|APT32|APT39|MuddyWater|Honeybee|APT28|Magic Hound|Dragonfly 2.0|FIN8|BRONZE BUTLER|CopyKittens|Sowbug|APT3|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT1|Ke3chang +T1001,Data Obfuscation,Command And Control,APT28|Axiom diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 492b5aa4ab..6c8e822641 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-05-20T08:17:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] data_models = [] providing_technologies = none @@ -34,8 +34,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] +support_searches = ["ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] support_searches = ["ESCU - Baseline of Network ACL Activity by ARN", "ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] data_models = [] providing_technologies = none @@ -86,8 +86,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] -support_searches = ["ESCU - Baseline of API Calls per User ARN", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Create a list of approved AWS service accounts", "ESCU - Previously seen API call per user roles in CloudTrail"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +support_searches = ["ESCU - Baseline of Security Group Activity by ARN", "ESCU - Baseline of API Calls per User ARN", "ESCU - Previously seen API call per user roles in CloudTrail", "ESCU - Create a list of approved AWS service accounts"] data_models = [] providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For User"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +investigative_searches = ["ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,8 +184,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Regions"] +investigative_searches = ["ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region"] +support_searches = ["ESCU - Previously Seen Cloud Regions", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Instance Types"] data_models = ["Cloud_Infrastructure"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +investigative_searches = ["ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,8 +307,8 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,8 +383,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,7 +415,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none @@ -433,8 +433,8 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic"] +support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -511,10 +511,10 @@ creation_date = 2020-02-04 modification_date = 2020-02-04 id = 399d65dc-1f08-499b-a259-aad9051f38ad version = 2 -reference = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = ["ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,8 +610,8 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. @@ -627,8 +627,8 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] -support_searches = ["ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. @@ -670,7 +670,7 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,7 +729,7 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip"] support_searches = [] data_models = [] providing_technologies = none @@ -860,8 +860,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] +support_searches = ["ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. @@ -892,8 +892,8 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name"] -support_searches = ["ESCU - Previously seen S3 bucket access by remote IP", "ESCU - Baseline of S3 Bucket deletion activity by ARN"] +investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address"] +support_searches = ["ESCU - Baseline of S3 Bucket deletion activity by ARN", "ESCU - Previously seen S3 bucket access by remote IP"] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none @@ -929,7 +929,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +investigative_searches = ["ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,7 +981,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] support_searches = ["ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml index 02d2dff20d..3f5dff58ab 100644 --- a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml +++ b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml @@ -1,7 +1,7 @@
- `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user + `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 385a5bdadd..f00281d581 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -3,43 +3,43 @@ label = AWS Cross Account Activity description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_aws_investigate_user_activities_by_source_user"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_source_user"] [panel_group://workbench_panel_group_aws_cryptomining] label = AWS Cryptomining description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_aws_network_acl_activity] label = AWS Network ACL Activity description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. disabled = 0 -panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] [panel_group://workbench_panel_group_aws_suspicious_provisioning_activities] label = AWS Suspicious Provisioning Activities description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_country"] +panels = ["panel://workbench_panel_get_all_aws_activity_from_country", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] [panel_group://workbench_panel_group_aws_user_monitoring] label = AWS User Monitoring description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. disabled = 0 -panels = ["panel://workbench_panel_investigate_aws_user_activities_by_user_field", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_user_activities_by_user_field"] [panel_group://workbench_panel_group_account_monitoring_and_controls] label = Account Monitoring and Controls description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. disabled = 0 -panels = ["panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_logon_rights_modifications_for_user"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_apache_struts_vulnerability] label = Apache Struts Vulnerability description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_asset_tracking] label = Asset Tracking @@ -51,31 +51,31 @@ panels = ["panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a label = Brand Monitoring description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. disabled = 0 -panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_email_info"] +panels = ["panel://workbench_panel_get_email_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_cloud_cryptomining] label = Cloud Cryptomining description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region"] [panel_group://workbench_panel_group_coldroot_macos_rat] label = ColdRoot MacOS RAT description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip"] [panel_group://workbench_panel_group_collection_and_staging] label = Collection and Staging description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_command_and_control] label = Command and Control description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. disabled = 0 -panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] [panel_group://workbench_panel_group_common_phishing_frameworks] label = Common Phishing Frameworks @@ -93,19 +93,19 @@ panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activit label = Credential Dumping description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. disabled = 0 -panels = ["panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] +panels = ["panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_ticket_attempts", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations"] [panel_group://workbench_panel_group_dhs_report_ta18_074a] label = DHS Report TA18-074A description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. disabled = 0 -panels = ["panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_file_activity"] +panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_dns_amplification_attacks] label = DNS Amplification Attacks description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_dns_hijacking] label = DNS Hijacking @@ -117,91 +117,91 @@ panels = ["panel://workbench_panel_get_dns_server_history_for_a_host"] label = Data Protection description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. disabled = 0 -panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] +panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_disabling_security_tools] label = Disabling Security Tools description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_dynamic_dns] label = Dynamic DNS description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. disabled = 0 -panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip"] [panel_group://workbench_panel_group_emotet_malware__dhs_report_ta18_201a_] label = Emotet Malware DHS Report TA18-201A description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_hidden_cobra_malware] label = Hidden Cobra Malware description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. disabled = 0 -panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] [panel_group://workbench_panel_group_host_redirection] label = Host Redirection description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_jboss_vulnerability] label = JBoss Vulnerability description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. disabled = 0 -panels = ["panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] [panel_group://workbench_panel_group_kubernetes_scanning_activity] label = Kubernetes Scanning Activity description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. disabled = 0 -panels = ["panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_lateral_movement] label = Lateral Movement description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_malicious_powershell] label = Malicious PowerShell description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_monitor_backup_solution] label = Monitor Backup Solution description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. disabled = 0 -panels = ["panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_monitor_for_unauthorized_software] label = Monitor for Unauthorized Software description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_monitor_for_updates] label = Monitor for Updates description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_netsh_abuse] label = Netsh Abuse description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_orangeworm_attack_group] label = Orangeworm Attack Group description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_phishing_payloads] label = Phishing Payloads @@ -213,61 +213,61 @@ panels = ["panel://workbench_panel_get_parent_process_info"] label = Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_prohibited_traffic_allowed_or_protocol_mismatch] label = Prohibited Traffic Allowed or Protocol Mismatch description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_ransomware] label = Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_router_and_infrastructure_security] label = Router and Infrastructure Security description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_sql_injection] label = SQL Injection description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] [panel_group://workbench_panel_group_samsam_ransomware] label = SamSam Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] label = Spectre And Meltdown Vulnerabilities description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability] label = Splunk Enterprise Vulnerability description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability_cve_2018_11409] label = Splunk Enterprise Vulnerability CVE-2018-11409 description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_investigate_web_activity_from_src_ip"] [panel_group://workbench_panel_group_suspicious_aws_ec2_activities] label = Suspicious AWS EC2 Activities description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_suspicious_aws_login_activities] label = Suspicious AWS Login Activities @@ -279,37 +279,37 @@ panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] label = Suspicious AWS S3 Activities description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_activities_via_region_name"] +panels = ["panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] [panel_group://workbench_panel_group_suspicious_aws_traffic] label = Suspicious AWS Traffic description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). disabled = 0 -panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] [panel_group://workbench_panel_group_suspicious_command_line_executions] label = Suspicious Command-Line Executions description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_suspicious_dns_traffic] label = Suspicious DNS Traffic description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. disabled = 0 -panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_suspicious_emails] label = Suspicious Emails description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_email_info"] +panels = ["panel://workbench_panel_get_email_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_suspicious_mshta_activity] label = Suspicious MSHTA Activity description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_suspicious_okta_activity] label = Suspicious Okta Activity @@ -321,73 +321,73 @@ panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://w label = Suspicious WMI Use description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_suspicious_windows_registry_activities] label = Suspicious Windows Registry Activities description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_unusual_aws_ec2_modifications] label = Unusual AWS EC2 Modifications description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. disabled = 0 -panels = ["panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_arn"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_unusual_processes] label = Unusual Processes description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_use_of_cleartext_protocols] label = Use of Cleartext Protocols description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_web_fraud_detection] label = Web Fraud Detection description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. disabled = 0 -panels = ["panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_emails_from_specific_sender"] +panels = ["panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_web_session_information_via_session_id"] [panel_group://workbench_panel_group_windows_defense_evasion_tactics] label = Windows Defense Evasion Tactics description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_windows_file_extension_and_association_abuse] label = Windows File Extension and Association Abuse description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_windows_log_manipulation] label = Windows Log Manipulation description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_windows_persistence_techniques] label = Windows Persistence Techniques description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_windows_privilege_escalation] label = Windows Privilege Escalation description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] [panel_group://workbench_panel_group_windows_service_abuse] label = Windows Service Abuse description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_parent_process_info"] +panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] diff --git a/package/default/macros.conf b/package/default/macros.conf index ec0c5df81e..aa1d7832dc 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-05-20T08:17:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 84401dfc9c..05186e0dd4 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-05-20T08:17:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -645,7 +645,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` [ESCU - Attempt To Stop Security Service - Rule] action.escu = 0 @@ -1872,7 +1872,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_LSAS`detect_credential_dumping_through_lsass_access_filter` +search = `sysmon` EventCode=10 TargetImage=*lsass.exe (GrantedAccess=0x1010 OR GrantedAccess=0x1410) | stats count min(_time) as firstTime max(_time) as lastTime by Computer, SourceImage, SourceProcessId, TargetImage, TargetProcessId, EventCode, GrantedAccess | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `detect_credential_dumping_through_lsass_access_filter` [ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule] action.escu = 0 @@ -9536,7 +9536,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user +search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 [ESCU - Investigate Previous Unseen User - Response Task] action.escu = 0 diff --git a/package/default/transforms.conf b/package/default/transforms.conf index 9d23f65600..ffe9d86a7d 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-05-20T08:17:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 3880ef279b..cb60b4f8f4 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-14T08:00:44 UTC +# On Date: 2020-05-20T08:17:41 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Logon Rights Modifications For User"] +searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web POSTs From src", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -201,7 +201,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - New container uploaded to AWS ECR - Rule", "ESCU - GCP GCR container uploaded - Rule", "ESCU - Investigate AWS ECR container listing activity"] +searches = ["ESCU - GCP GCR container uploaded - Rule", "ESCU - New container uploaded to AWS ECR - Rule", "ESCU - Investigate AWS ECR container listing activity"] description = Use the searches in this story to monitor your Kubernetes registry repositories for upload, and deployment of potentially vulnerable, backdoor, or implanted containers. These searches provide information on source users, destination path, container names and repository names. The searches provide context to address Mitre T1525 which refers to container implantation upload to a company's repository either in Amazon Elastic Container Registry, Google Container Registry and Azure Container Registry. narrative = Container Registrys provide a way for organizations to keep customized images of their development and infrastructure environment in private. However if these repositories are misconfigured or priviledge users credentials are compromise, attackers can potentially upload implanted containers which can be deployed across the organization. These searches allow operator to monitor who, when and what was uploaded to container registry. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Creation of Shadow Copy - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts"] +searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Get Process Registry Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity"] +searches = ["ESCU - Detect New Local Admin account - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable Info"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -374,10 +374,10 @@ narrative = Kubernetes is the most used container orchestration platform, this o category = Adversary Tactics last_updated = 2020-02-04 version = 2 -references = ["https://blog.binarydefense.com/reliably-detecting-pass-the-hash-through-event-log-analysis", "https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] +references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First time seen command line argument - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - TOR Traffic - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - File with Samsam Extension - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Get Notable History", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Investigate AWS activities via region name"] +searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get DNS Server History for a host", "ESCU - Get DNS traffic ratio", "ESCU - Get Parent Process Info"] +searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Email Info"] +searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info"] +searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Process Information For Port Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Web Session Information via session id", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Emails From Specific Sender"] +searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info"] +searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Shim Database File Creation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Registry Activities", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 2512a90f5946545c05170c3d2993f35dbdffb5e9 Mon Sep 17 00:00:00 2001 From: divious1 Date: Fri, 22 May 2020 00:30:56 -0400 Subject: [PATCH 64/93] minor readme fixes --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 90a3c0862c..1fd0fa7a4a 100644 --- a/README.md +++ b/README.md @@ -9,7 +9,7 @@ Welcome to the Splunk Security Content -This project gives you access to our repository of Analytic Stories--themed security guides that provide background on TTPs, mapped to the MITRE framework, the Lockheed Martin Kill Chain, and CIS controls. They include Splunk searches, machine-learning algorithms, and Splunk Phantom playbooks (where available)—all designed to work together to detect, investigate, and respond to threats. +This project gives you access to our repository of Analytic Stories that are security guides which provide background on TTPs, mapped to the MITRE framework, the Lockheed Martin Kill Chain, and CIS controls. They include Splunk searches, machine-learning algorithms, and Splunk Phantom playbooks (where available)—all designed to work together to detect, investigate, and respond to threats. # Usage The Splunk Security Content can be used via: @@ -35,11 +35,11 @@ Manifests contain a number of mandatory and optional fields. You can see the ful # Customize to your Environment -After release [1.0.46](https://github.com/splunk/security-content/releases) we introduced a concept of input(pre-filter) and output(post-filter) macros for each of our detection search. The intention behind introducing these macros is primarily to help our users to update the macro definition “once” and those changes will be applicable across all detections that leverage that macro and local to your Splunk Environment. +After release [1.0.46](https://github.com/splunk/security-content/releases) we introduced a concept of **input(pre-filter)** and **output(post-filter)** macros for each of our detection search. The intention behind introducing these macros is primarily to help our users to update the macro definition “once” and those changes will be applicable across all detections that leverage that macro and local to your Splunk Environment. -**input(pre-filter):** This macro is to specify your environment-specific configurations (index, source, sourcetype, etc.) to get the specific data sources that you would like to bring in. Replace the macro definition with configurations for your Splunk environment. +**input(pre-filter):** This macro is to specify your environment-specific configurations (index, source, sourcetype, etc.) to get the specific data sources that you would like to bring in. Replace the macro definition with configurations for your Splunk environment. For example the [sysmon](macros/sysmon.yml) **input macro** can be modified to the local splunk deployments index or sourcetype. -**output(post-filter):** This macro is to specify your environment-specific values (eg: dest, user), to filter out known false positives.. Replace the macro definition with values that you’d like to exclude from detection results. Think of this as a whitelisting/blacklisting using macros. +**output(post-filter):** This macro is to specify your environment-specific values (eg: dest, user), to filter out known false positives.. Replace the macro definition with values that you’d like to exclude from detection results. Think of this as a whitelisting/blacklisting using macros. A good example # Execute an Analytic Story From 841db96e07fdd7a1e741a1565d113298796241bd Mon Sep 17 00:00:00 2001 From: divious1 Date: Fri, 22 May 2020 01:30:25 -0400 Subject: [PATCH 65/93] removed flake8, added more verbosity to generate --- .pre-commit-config.yaml | 3 --- bin/generate.py | 24 +++++++++++++----------- 2 files changed, 13 insertions(+), 14 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 4bb6720b88..b46d0df484 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -9,7 +9,4 @@ repos: - id: check-yaml - id: pretty-format-json args: [--autofix] - - id: flake8 - args: [--max-line-length=131] - exclude: 'package/bin/da_ess_contentupdate/|package/bin/splunklib/|venv/|package/bin/escu_contextualize.py|package/bin/escu_investigate.py|package/bin/runstory.py|package/bin/detect.py|package/bin/investigate.py' - id: requirements-txt-fixer diff --git a/bin/generate.py b/bin/generate.py index d3b7f48659..2afda820a8 100644 --- a/bin/generate.py +++ b/bin/generate.py @@ -22,13 +22,13 @@ VERBOSE = False OUTPUT_PATH = '' -def load_objects(file_path): +def load_objects(file_path, VERBOSE): files = [] manifest_files = path.join(path.expanduser(REPO_PATH), file_path) - for file in sorted(glob.glob(manifest_files)): + if VERBOSE: + print("processing manifest: {0}".format(file)) files.append(load_file(file)) - return files @@ -479,16 +479,18 @@ if __name__ == "__main__": REPO_PATH = args.path OUTPUT_PATH = args.output VERBOSE = args.verbose - stories = load_objects("stories/*.yml") - macros = load_objects("macros/*.yml") - lookups = load_objects("lookups/*.yml") - baselines = load_objects("baselines/*.yml") - detections = load_objects("detections/*.yml") - responses = load_objects("responses/*.yml") - response_tasks = load_objects("response_tasks/*.yml") - deployments = load_objects("deployments/*.yml") + stories = load_objects("stories/*.yml", VERBOSE) + macros = load_objects("macros/*.yml", VERBOSE) + lookups = load_objects("lookups/*.yml", VERBOSE) + baselines = load_objects("baselines/*.yml", VERBOSE) + detections = load_objects("detections/*.yml", VERBOSE) + responses = load_objects("responses/*.yml", VERBOSE) + response_tasks = load_objects("response_tasks/*.yml", VERBOSE) + deployments = load_objects("deployments/*.yml", VERBOSE) try: + if VERBOSE: + print("generating Mitre lookups") generate_mitre_lookup() except: print("WARNING: Generation of Mitre lookup failed.") From 6b966dd4e371197a6bedcbede741b72077de7b7f Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 10:44:29 +0200 Subject: [PATCH 66/93] merged with develop --- requirements.txt | 21 +++------------------ 1 file changed, 3 insertions(+), 18 deletions(-) diff --git a/requirements.txt b/requirements.txt index a1a4cfaf4b..be21fe40d5 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,18 +7,11 @@ cfgv==2.0.1 chardet==3.0.4 configparser==4.0.2 contextlib2==0.6.0.post1 -<<<<<<< HEAD -identify==1.4.8 -idna==2.9 -importlib-metadata==1.2.0 -importlib-resources==1.0.2 -Jinja2==2.10.3 -======= identify==1.4.16 +idna==2.9 importlib-metadata==1.6.0 importlib-resources==1.5.0 Jinja2==2.11.2 ->>>>>>> develop jsonschema==3.2.0 MarkupSafe==1.1.1 more-itertools==8.0.2 @@ -31,23 +24,15 @@ pytz==2019.3 PyYAML==5.3.1 requests==2.23.0 scandir==1.10.0 -<<<<<<< HEAD -semantic-version==2.8.3 -simplejson==3.17.0 -======= semantic-version==2.8.5 ->>>>>>> develop +simplejson==3.17.0 six==1.14.0 stix2==1.4.0 stix2-patterns==1.3.0 taxii2-client==2.0.0 toml==0.10.0 typing==3.7.4.1 -<<<<<<< HEAD urllib3==1.25.9 -virtualenv==16.7.8 -zipp==0.6.0 -======= virtualenv==20.0.20 +zipp==0.6.0 zipp==3.1.0 ->>>>>>> develop From 052a7d787230e1e2291eda8e218732b6277b1a55 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 10:46:40 +0200 Subject: [PATCH 67/93] run generate --- lookups/mitre_enrichment.csv | 130 +++++++++++------------ package/default/analytic_stories.conf | 140 ++++++++++++------------- package/default/es_investigations.conf | 120 ++++++++++----------- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 2 +- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 128 +++++++++++----------- 7 files changed, 262 insertions(+), 262 deletions(-) diff --git a/lookups/mitre_enrichment.csv b/lookups/mitre_enrichment.csv index bb5180d7ae..f31d264442 100644 --- a/lookups/mitre_enrichment.csv +++ b/lookups/mitre_enrichment.csv @@ -47,91 +47,91 @@ T1222,File and Directory Permissions Modification,Defense Evasion,APT32 T1221,Template Injection,Defense Evasion,APT28|Tropic Trooper|Dragonfly 2.0|DarkHydrus T1220,XSL Script Processing,Defense Evasion|Execution,Cobalt Group T1197,BITS Jobs,Defense Evasion|Persistence,Leviathan +T1217,Browser Bookmark Discovery,Discovery,no T1191,CMSTP,Defense Evasion|Execution,Cobalt Group|MuddyWater T1196,Control Panel Items,Defense Evasion|Execution,no T1214,Credentials in Registry,Credential Access,Soft Cell T1207,DCShadow,Defense Evasion,no -T1217,Browser Bookmark Discovery,Discovery,no T1213,Data from Information Repositories,Collection,Ke3chang|APT28 -T1189,Drive-by Compromise,Initial Access,Darkhotel|APT38|Lazarus Group|Leafminer|Dragonfly 2.0|BRONZE BUTLER|Threat Group-3390|Dark Caracal|APT19|APT32|Elderwood|APT37|Patchwork|PLATINUM -T1203,Exploitation for Client Execution,Execution,APT41|admin@338|Threat Group-3390|APT12|The White Company|APT33|APT32|APT28|Tropic Trooper|BRONZE BUTLER|Lazarus Group|Cobalt Group|APT37|Leviathan|APT29|Patchwork|TA459|Elderwood -T1212,Exploitation for Credential Access,Credential Access,no -T1202,Indirect Command Execution,Defense Evasion,no +T1189,Drive-by Compromise,Initial Access,Darkhotel|APT38|Lazarus Group|Dragonfly 2.0|BRONZE BUTLER|Leafminer|Dark Caracal|APT32|Threat Group-3390|APT19|Elderwood|APT37|Patchwork|PLATINUM T1190,Exploit Public-Facing Application,Initial Access,Soft Cell|Night Dragon|Axiom -T1210,Exploitation of Remote Services,Lateral Movement,Threat Group-3390|APT28 +T1212,Exploitation for Credential Access,Credential Access,no T1211,Exploitation for Defense Evasion,Defense Evasion,APT28 +T1203,Exploitation for Client Execution,Execution,APT41|admin@338|Threat Group-3390|APT12|The White Company|APT33|APT32|APT28|Tropic Trooper|BRONZE BUTLER|Lazarus Group|Cobalt Group|APT37|APT29|Patchwork|Leviathan|Elderwood|TA459 +T1210,Exploitation of Remote Services,Lateral Movement,Threat Group-3390|APT28 T1200,Hardware Additions,Initial Access,no +T1202,Indirect Command Execution,Defense Evasion,no T1208,Kerberoasting,Credential Access,no T1215,Kernel Modules and Extensions,Persistence,no -T1198,SIP and Trust Provider Hijacking,Defense Evasion|Persistence,no -T1194,Spearphishing via Service,Initial Access,FIN6|OilRig|Dark Caracal|Magic Hound -T1195,Supply Chain Compromise,Initial Access,APT41|Elderwood -T1192,Spearphishing Link,Initial Access,Machete|Kimsuky|TA505|Stolen Pencil|APT39|FIN4|APT32|Night Dragon|APT28|Cobalt Group|Turla|OilRig|Dragonfly 2.0|APT33|Elderwood|APT29|Leviathan|Patchwork|Magic Hound|FIN8 -T1206,Sudo Caching,Privilege Escalation,no -T1199,Trusted Relationship,Initial Access,APT28|menuPass T1201,Password Policy Discovery,Discovery,OilRig T1205,Port Knocking,Defense Evasion|Persistence|Command And Control,no -T1218,Signed Binary Proxy Execution,Defense Evasion|Execution,TA505|Rancor|Cobalt Group T1219,Remote Access Tools,Command And Control,Kimsuky|Night Dragon|Thrip|Cobalt Group|Carbanak +T1198,SIP and Trust Provider Hijacking,Defense Evasion|Persistence,no +T1218,Signed Binary Proxy Execution,Defense Evasion|Execution,TA505|Rancor|Cobalt Group T1216,Signed Script Proxy Execution,Defense Evasion|Execution,APT32 -T1193,Spearphishing Attachment,Initial Access,APT41|Machete|admin@338|Kimsuky|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Tropic Trooper|Turla|Gorgon Group|Rancor|DarkHydrus|Lazarus Group|Cobalt Group|OilRig|FIN7|APT19|BRONZE BUTLER|Dragonfly 2.0|APT32|MuddyWater|TA459|FIN8|APT28|Patchwork|APT29|Elderwood|APT37|Leviathan|Magic Hound|menuPass|PLATINUM +T1193,Spearphishing Attachment,Initial Access,APT41|Machete|admin@338|Kimsuky|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Tropic Trooper|Turla|Gorgon Group|Rancor|DarkHydrus|Lazarus Group|Cobalt Group|BRONZE BUTLER|OilRig|FIN7|APT19|Dragonfly 2.0|APT32|FIN8|MuddyWater|APT28|TA459|Elderwood|APT29|APT37|Patchwork|Leviathan|Magic Hound|menuPass|PLATINUM +T1194,Spearphishing via Service,Initial Access,FIN6|OilRig|Dark Caracal|Magic Hound +T1192,Spearphishing Link,Initial Access,Machete|Kimsuky|TA505|Stolen Pencil|APT39|FIN4|APT32|Night Dragon|APT28|Turla|Cobalt Group|Dragonfly 2.0|OilRig|APT33|Elderwood|Patchwork|Magic Hound|APT29|Leviathan|FIN8 +T1206,Sudo Caching,Privilege Escalation,no +T1195,Supply Chain Compromise,Initial Access,APT41|Elderwood T1209,Time Providers,Persistence,no -T1204,User Execution,Execution,Machete|admin@338|APT12|TA505|Silence|The White Company|APT39|FIN4|Night Dragon|Darkhotel|Gallmaker|APT33|Dragonfly 2.0|Cobalt Group|APT19|BRONZE BUTLER|Dark Caracal|FIN7|DarkHydrus|Turla|Gorgon Group|Lazarus Group|APT32|OilRig|MuddyWater|Patchwork|Rancor|APT37|APT29|FIN8|APT28|menuPass|TA459|Elderwood|Leviathan|Magic Hound|PLATINUM +T1199,Trusted Relationship,Initial Access,APT28|menuPass +T1204,User Execution,Execution,Machete|admin@338|APT12|TA505|Silence|The White Company|APT39|FIN4|Night Dragon|Darkhotel|Gallmaker|Dragonfly 2.0|APT19|BRONZE BUTLER|APT33|Dark Caracal|Cobalt Group|FIN7|DarkHydrus|Patchwork|Turla|Gorgon Group|Lazarus Group|APT32|Rancor|OilRig|MuddyWater|APT37|APT28|APT29|FIN8|menuPass|Elderwood|PLATINUM|Magic Hound|TA459|Leviathan T1182,AppCert DLLs,Persistence|Privilege Escalation,Honeybee T1176,Browser Extensions,Persistence,Kimsuky|Stolen Pencil T1175,Component Object Model and Distributed COM,Lateral Movement|Execution,MuddyWater -T1181,Extra Window Memory Injection,Defense Evasion|Privilege Escalation,no -T1179,Hooking,Persistence|Privilege Escalation|Credential Access,PLATINUM -T1183,Image File Execution Options Injection,Privilege Escalation|Persistence|Defense Evasion,TEMP.Veles T1172,Domain Fronting,Command And Control,APT29 T1173,Dynamic Data Exchange,Execution,TA505|MuddyWater|Gallmaker|Patchwork|Cobalt Group|APT37|APT28|FIN7 +T1181,Extra Window Memory Injection,Defense Evasion|Privilege Escalation,no T1187,Forced Authentication,Credential Access,DarkHydrus|Dragonfly 2.0 +T1179,Hooking,Persistence|Privilege Escalation|Credential Access,PLATINUM +T1183,Image File Execution Options Injection,Privilege Escalation|Persistence|Defense Evasion,TEMP.Veles T1171,LLMNR/NBT-NS Poisoning and Relay,Credential Access,no -T1188,Multi-hop Proxy,Command And Control,FIN4|APT29 T1177,LSASS Driver,Execution|Persistence,no -T1174,Password Filter DLL,Credential Access,no T1185,Man in the Browser,Collection,no -T1184,SSH Hijacking,Lateral Movement,no -T1180,Screensaver,Persistence,no -T1178,SID-History Injection,Privilege Escalation,no T1170,Mshta,Defense Evasion|Execution,Kimsuky|APT32|MuddyWater|FIN7 +T1188,Multi-hop Proxy,Command And Control,FIN4|APT29 +T1174,Password Filter DLL,Credential Access,no T1186,Process Doppelgänging,Defense Evasion,no +T1184,SSH Hijacking,Lateral Movement,no +T1178,SID-History Injection,Privilege Escalation,no +T1180,Screensaver,Persistence,no T1156,.bash_profile and .bashrc,Persistence,no T1134,Access Token Manipulation,Defense Evasion|Privilege Escalation,Turla|Lazarus Group|APT28 T1155,AppleScript,Execution|Lateral Movement,no T1138,Application Shimming,Persistence|Privilege Escalation,FIN7 -T1146,Clear Command History,Defense Evasion,APT41 T1139,Bash History,Credential Access,no +T1146,Clear Command History,Defense Evasion,APT41 T1136,Create Account,Persistence,APT41|Soft Cell|Dragonfly 2.0|Leafminer|APT3 T1140,Deobfuscate/Decode Files or Information,Defense Evasion,Turla|WIRTE|Darkhotel|Tropic Trooper|Honeybee|menuPass|Gorgon Group|Threat Group-3390|APT19|Leviathan|MuddyWater|APT28|OilRig|BRONZE BUTLER T1157,Dylib Hijacking,Persistence|Privilege Escalation,no -T1148,HISTCONTROL,Defense Evasion,no T1144,Gatekeeper Bypass,Defense Evasion,no -T1158,Hidden Files and Directories,Defense Evasion|Persistence,APT32|Tropic Trooper|APT28|Lazarus Group +T1148,HISTCONTROL,Defense Evasion,no T1147,Hidden Users,Defense Evasion,no +T1158,Hidden Files and Directories,Defense Evasion|Persistence,APT32|Tropic Trooper|APT28|Lazarus Group T1143,Hidden Window,Defense Evasion,Gorgon Group|Deep Panda|DarkHydrus|CopyKittens|APT19|APT32|APT28|APT3|Magic Hound T1141,Input Prompt,Credential Access,FIN4 +T1142,Keychain,Credential Access,no T1149,LC_MAIN Hijacking,Defense Evasion,no +T1161,LC_LOAD_DYLIB Addition,Persistence,no +T1159,Launch Agent,Persistence,no T1152,Launchctl,Defense Evasion|Execution|Persistence,no T1168,Local Job Scheduling,Persistence|Execution,no -T1161,LC_LOAD_DYLIB Addition,Persistence,no T1160,Launch Daemon,Persistence|Privilege Escalation,no +T1162,Login Item,Persistence,no +T1135,Network Share Discovery,Discovery,APT41|Tropic Trooper|APT1|Dragonfly 2.0|Sowbug +T1137,Office Application Startup,Persistence,APT32|APT28 T1150,Plist Modification,Defense Evasion|Persistence|Privilege Escalation,no T1145,Private Keys,Credential Access,no -T1162,Login Item,Persistence,no -T1153,Source,Execution,no -T1137,Office Application Startup,Persistence,APT32|APT28 +T1163,Rc.common,Persistence,no +T1164,Re-opened Applications,Persistence,no T1167,Securityd Memory,Credential Access,no T1166,Setuid and Setgid,Privilege Escalation|Persistence,no -T1165,Startup Items,Persistence|Privilege Escalation,no -T1163,Rc.common,Persistence,no +T1153,Source,Execution,no T1151,Space after Filename,Defense Evasion|Execution,no -T1154,Trap,Execution|Persistence,no -T1142,Keychain,Credential Access,no -T1159,Launch Agent,Persistence,no -T1135,Network Share Discovery,Discovery,APT41|Tropic Trooper|APT1|Dragonfly 2.0|Sowbug -T1164,Re-opened Applications,Persistence,no +T1165,Startup Items,Persistence|Privilege Escalation,no T1169,Sudo,Privilege Escalation,no +T1154,Trap,Execution|Persistence,no T1133,External Remote Services,Persistence|Initial Access,APT41|Soft Cell|TEMP.Veles|Night Dragon|OilRig|Ke3chang|Dragonfly 2.0|FIN5|Threat Group-3390|APT18 T1132,Data Encoding,Command And Control,APT33|APT19|Lazarus Group|BRONZE BUTLER|Patchwork T1131,Authentication Package,Persistence,no @@ -148,22 +148,22 @@ T1121,Regsvcs/Regasm,Defense Evasion|Execution,no T1120,Peripheral Device Discovery,Discovery,APT37|Gamaredon Group|Equation|APT28 T1119,Automated Collection,Collection,APT1|APT28|Patchwork|OilRig|FIN5|Threat Group-3390|FIN6 T1118,InstallUtil,Defense Evasion|Execution,no -T1117,Regsvr32,Defense Evasion|Execution,WIRTE|Cobalt Group|APT19|Leviathan|APT32|Deep Panda -T1116,Code Signing,Defense Evasion,APT41|FIN6|TA505|FIN7|Honeybee|APT37|Leviathan|CopyKittens|Winnti Group|Suckfly|Molerats|Darkhotel +T1117,Regsvr32,Defense Evasion|Execution,WIRTE|APT19|Cobalt Group|Leviathan|APT32|Deep Panda +T1116,Code Signing,Defense Evasion,APT41|FIN6|TA505|FIN7|Honeybee|Leviathan|APT37|CopyKittens|Winnti Group|Suckfly|Molerats|Darkhotel T1115,Clipboard Data,Collection,APT38 -T1114,Email Collection,Collection,FIN4|Dragonfly 2.0|APT28|Ke3chang|Magic Hound|Leafminer|APT1 +T1114,Email Collection,Collection,FIN4|APT28|Dragonfly 2.0|Magic Hound|Ke3chang|Leafminer|APT1 T1113,Screen Capture,Collection,Silence|MuddyWater|OilRig|Dragonfly 2.0|FIN7|Dark Caracal|BRONZE BUTLER|Magic Hound|Group5|APT28 -T1112,Modify Registry,Defense Evasion,APT41|Turla|APT32|APT38|Dragonfly 2.0|Patchwork|APT19|Threat Group-3390|Gorgon Group|Honeybee|FIN8 +T1112,Modify Registry,Defense Evasion,APT41|Turla|APT32|APT38|Dragonfly 2.0|APT19|Gorgon Group|Patchwork|Threat Group-3390|Honeybee|FIN8 T1111,Two-Factor Authentication Interception,Credential Access,no -T1110,Brute Force,Credential Access,APT41|APT33|Leafminer|OilRig|Dragonfly 2.0|APT3|Lazarus Group|Turla +T1110,Brute Force,Credential Access,APT41|APT33|Leafminer|Dragonfly 2.0|OilRig|APT3|Lazarus Group|Turla T1109,Component Firmware,Defense Evasion|Persistence,Equation -T1108,Redundant Access,Defense Evasion|Persistence,Stolen Pencil|Cobalt Group|Leafminer|APT3|OilRig|FIN5|Threat Group-3390 -T1107,File Deletion,Defense Evasion,APT41|Kimsuky|Silence|The White Company|TEMP.Veles|APT32|APT38|Patchwork|Honeybee|Cobalt Group|menuPass|Dragonfly 2.0|FIN8|FIN5|OilRig|Magic Hound|BRONZE BUTLER|APT3|APT28|FIN10|Threat Group-3390|Group5|Lazarus Group|APT18|APT29 +T1108,Redundant Access,Defense Evasion|Persistence,Stolen Pencil|Cobalt Group|Leafminer|APT3|FIN5|OilRig|Threat Group-3390 +T1107,File Deletion,Defense Evasion,APT41|Kimsuky|Silence|The White Company|TEMP.Veles|APT32|APT38|Honeybee|Patchwork|Cobalt Group|Dragonfly 2.0|menuPass|FIN8|OilRig|FIN5|BRONZE BUTLER|Magic Hound|APT3|FIN10|APT28|Threat Group-3390|Group5|Lazarus Group|APT18|APT29 T1106,Execution through API,Execution,Turla|Silence|APT37|Gorgon Group -T1105,Remote File Copy,Command And Control|Lateral Movement,Soft Cell|TA505|WIRTE|APT33|MuddyWater|APT18|APT38|Turla|Gorgon Group|Cobalt Group|Rancor|Dragonfly 2.0|OilRig|FIN8|APT37|PLATINUM|Leviathan|Elderwood|Magic Hound|APT3|APT32|BRONZE BUTLER|FIN7|menuPass|FIN10|Gamaredon Group|Patchwork|Lazarus Group|Threat Group-3390|APT28 +T1105,Remote File Copy,Command And Control|Lateral Movement,Soft Cell|TA505|WIRTE|APT33|MuddyWater|APT18|APT38|Cobalt Group|Rancor|Turla|Gorgon Group|OilRig|Dragonfly 2.0|APT37|FIN8|Leviathan|PLATINUM|Elderwood|Magic Hound|APT3|BRONZE BUTLER|APT32|menuPass|FIN7|FIN10|Gamaredon Group|Patchwork|Lazarus Group|Threat Group-3390|APT28 T1104,Multi-Stage Channels,Command And Control,MuddyWater|APT3 T1103,AppInit DLLs,Persistence|Privilege Escalation,no -T1102,Web Service,Command And Control|Defense Evasion,APT41|APT12|FIN6|Turla|FIN7|BRONZE BUTLER|Leviathan|APT37|Magic Hound|RTM|Patchwork|Carbanak +T1102,Web Service,Command And Control|Defense Evasion,APT41|APT12|FIN6|Turla|FIN7|BRONZE BUTLER|APT37|Leviathan|Magic Hound|RTM|Patchwork|Carbanak T1101,Security Support Provider,Persistence,no T1100,Web Shell,Persistence|Privilege Escalation,Soft Cell|Threat Group-3390|TEMP.Veles|Leviathan|APT39|Dragonfly 2.0|APT32|OilRig|Deep Panda T1099,Timestomp,Defense Evasion,TEMP.Veles|APT32|Lazarus Group|APT28 @@ -177,12 +177,12 @@ T1092,Communication Through Removable Media,Command And Control,APT28 T1091,Replication Through Removable Media,Lateral Movement|Initial Access,Darkhotel|APT28 T1090,Connection Proxy,Command And Control|Defense Evasion,APT41|Soft Cell|Turla|APT39|MuddyWater|APT3|Lazarus Group|menuPass|Strider|APT28 T1089,Disabling Security Tools,Defense Evasion,Kimsuky|Turla|Night Dragon|Dragonfly 2.0|Gorgon Group|Threat Group-3390|Lazarus Group|Putter Panda|Carbanak -T1088,Bypass User Account Control,Defense Evasion|Privilege Escalation,APT37|MuddyWater|Honeybee|Threat Group-3390|Cobalt Group|BRONZE BUTLER|Patchwork|APT29 +T1088,Bypass User Account Control,Defense Evasion|Privilege Escalation,APT37|MuddyWater|Honeybee|Cobalt Group|Threat Group-3390|BRONZE BUTLER|Patchwork|APT29 T1087,Account Discovery,Discovery,APT32|APT1|Dragonfly 2.0|BRONZE BUTLER|OilRig|Threat Group-3390|menuPass|FIN6|Poseidon Group|APT3|admin@338|Ke3chang -T1086,PowerShell,Execution,APT41|Kimsuky|Soft Cell|TA505|WIRTE|TEMP.Veles|APT33|Gallmaker|Turla|DarkHydrus|Dragonfly 2.0|APT19|Thrip|Cobalt Group|APT28|Gorgon Group|Leviathan|TA459|MuddyWater|FIN8|CopyKittens|OilRig|Magic Hound|BRONZE BUTLER|APT32|FIN10|FIN7|Threat Group-3390|menuPass|Patchwork|Stealth Falcon|FIN6|Poseidon Group|APT3|APT29|Deep Panda +T1086,PowerShell,Execution,APT41|Kimsuky|Soft Cell|TA505|WIRTE|TEMP.Veles|APT33|Gallmaker|Turla|Thrip|APT19|DarkHydrus|Dragonfly 2.0|Cobalt Group|APT28|Gorgon Group|Leviathan|TA459|MuddyWater|FIN8|CopyKittens|OilRig|Magic Hound|BRONZE BUTLER|APT32|FIN10|FIN7|Threat Group-3390|menuPass|Patchwork|Stealth Falcon|FIN6|Poseidon Group|APT3|APT29|Deep Panda T1085,Rundll32,Defense Evasion|Execution,TA505|MuddyWater|APT29|APT19|CopyKittens|APT3|Carbanak|APT28 T1084,Windows Management Instrumentation Event Subscription,Persistence,Turla|Leviathan|APT29 -T1083,File and Directory Discovery,Discovery,Kimsuky|APT32|MuddyWater|APT18|Dragonfly 2.0|Dark Caracal|Leafminer|Honeybee|Sowbug|BRONZE BUTLER|APT3|Magic Hound|APT28|Patchwork|Lazarus Group|Dust Storm|admin@338|Turla|Ke3chang +T1083,File and Directory Discovery,Discovery,Kimsuky|APT32|MuddyWater|APT18|Leafminer|Dragonfly 2.0|Dark Caracal|Honeybee|Magic Hound|APT3|BRONZE BUTLER|Sowbug|APT28|Patchwork|Lazarus Group|Dust Storm|admin@338|Turla|Ke3chang T1082,System Information Discovery,Discovery,Kimsuky|Tropic Trooper|Darkhotel|MuddyWater|APT18|APT37|Honeybee|APT19|APT32|OilRig|Magic Hound|APT3|Sowbug|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|admin@338|Turla|Ke3chang T1081,Credentials in Files,Credential Access,OilRig|Kimsuky|Turla|TA505|Stolen Pencil|MuddyWater|APT3 T1080,Taint Shared Content,Lateral Movement,Darkhotel @@ -191,35 +191,35 @@ T1078,Valid Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Ac T1077,Windows Admin Shares,Lateral Movement,APT32|Orangeworm|FIN8|APT3|Lazarus Group|Threat Group-1314|Turla|Deep Panda|Ke3chang T1076,Remote Desktop Protocol,Lateral Movement,APT41|TEMP.Veles|Leviathan|APT39|Stolen Pencil|Cobalt Group|Dragonfly 2.0|FIN8|APT3|OilRig|menuPass|FIN10|Patchwork|FIN6|Lazarus Group|APT1|Axiom T1075,Pass the Hash,Lateral Movement,Soft Cell|APT32|Night Dragon|APT28|APT1 -T1074,Data Staged,Collection,Machete|Soft Cell|TEMP.Veles|Night Dragon|Patchwork|Honeybee|Dragonfly 2.0|Leviathan|FIN8|APT3|FIN5|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT28 +T1074,Data Staged,Collection,Machete|Soft Cell|TEMP.Veles|Night Dragon|Honeybee|Patchwork|Dragonfly 2.0|Leviathan|FIN8|APT3|FIN5|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT28 T1073,DLL Side-Loading,Defense Evasion,APT41|Soft Cell|Tropic Trooper|Patchwork|APT19|APT32|APT3|menuPass|Threat Group-3390 T1072,Third-party Software,Execution|Lateral Movement,Threat Group-1314 -T1071,Standard Application Layer Protocol,Command And Control,APT41|Machete|WIRTE|APT33|FIN4|Night Dragon|APT18|SilverTerrier|APT38|Dragonfly 2.0|APT19|Cobalt Group|FIN7|APT37|Threat Group-3390|Turla|Honeybee|Rancor|Orangeworm|Ke3chang|Dark Caracal|Lazarus Group|BRONZE BUTLER|OilRig|APT32|Magic Hound|Gamaredon Group|Stealth Falcon|FIN6|APT28 +T1071,Standard Application Layer Protocol,Command And Control,APT41|Machete|WIRTE|APT33|FIN4|Night Dragon|APT18|SilverTerrier|APT38|Dragonfly 2.0|APT19|Cobalt Group|FIN7|Threat Group-3390|APT37|Orangeworm|Turla|Rancor|Honeybee|Ke3chang|Dark Caracal|Lazarus Group|BRONZE BUTLER|OilRig|APT32|Magic Hound|Gamaredon Group|Stealth Falcon|FIN6|APT28 T1070,Indicator Removal on Host,Defense Evasion,APT41|APT29|APT38|Dragonfly 2.0|APT32|FIN8|FIN5|APT28 T1069,Permission Groups Discovery,Discovery,FIN6|Dragonfly 2.0|OilRig|APT3|admin@338|Ke3chang T1068,Exploitation for Privilege Escalation,Privilege Escalation,APT33|Cobalt Group|PLATINUM|FIN8|APT32|Threat Group-3390|FIN6|APT28 T1067,Bootkit,Persistence,APT41|Lazarus Group|APT28 T1066,Indicator Removal from Tools,Defense Evasion,Soft Cell|TEMP.Veles|Patchwork|APT3|Turla|OilRig|Deep Panda T1065,Uncommonly Used Port,Command And Control,TEMP.Veles|APT33|APT32|Gorgon Group|Magic Hound|Group5|Lazarus Group|APT3 -T1064,Scripting,Defense Evasion|Execution,Machete|Turla|TA505|Silence|WIRTE|APT39|FIN4|APT32|Darkhotel|Gallmaker|Dark Caracal|Lazarus Group|menuPass|APT19|Leafminer|Rancor|Dragonfly 2.0|Cobalt Group|Honeybee|Ke3chang|APT37|FIN7|Patchwork|Gorgon Group|MuddyWater|Leviathan|TA459|FIN8|APT28|Magic Hound|OilRig|BRONZE BUTLER|FIN5|FIN10|Gamaredon Group|Stealth Falcon|FIN6|APT3|APT29|Deep Panda|APT1 +T1064,Scripting,Defense Evasion|Execution,Machete|Turla|TA505|Silence|WIRTE|APT39|FIN4|APT32|Darkhotel|Gallmaker|Dark Caracal|Lazarus Group|menuPass|APT19|Dragonfly 2.0|APT37|Gorgon Group|Leafminer|Rancor|Cobalt Group|FIN7|Honeybee|Ke3chang|Patchwork|MuddyWater|Leviathan|FIN8|TA459|APT28|Magic Hound|OilRig|BRONZE BUTLER|FIN5|FIN10|Gamaredon Group|Stealth Falcon|FIN6|APT3|APT29|Deep Panda|APT1 T1063,Security Software Discovery,Discovery,The White Company|Cobalt Group|Darkhotel|MuddyWater|Tropic Trooper|FIN8|Patchwork|Naikon T1062,Hypervisor,Persistence,no T1061,Graphical User Interface,Execution,APT3 -T1060,Registry Run Keys / Startup Folder,Persistence,APT41|Machete|Kimsuky|APT33|APT39|APT32|APT18|Turla|APT19|Cobalt Group|Threat Group-3390|Honeybee|Dark Caracal|Ke3chang|Dragonfly 2.0|Gorgon Group|MuddyWater|APT37|Leviathan|APT3|BRONZE BUTLER|Magic Hound|FIN10|FIN7|Patchwork|FIN6|Lazarus Group|Putter Panda|APT29|Darkhotel -T1059,Command-Line Interface,Execution,APT41|Soft Cell|Turla|Silence|APT32|Cobalt Group|MuddyWater|APT18|APT38|APT28|Dragonfly 2.0|Gorgon Group|FIN7|Honeybee|Rancor|APT37|Leviathan|FIN8|Magic Hound|Sowbug|OilRig|BRONZE BUTLER|menuPass|Threat Group-3390|Suckfly|Patchwork|Lazarus Group|Threat Group-1314|APT3|admin@338|APT1|Ke3chang +T1060,Registry Run Keys / Startup Folder,Persistence,APT41|Machete|Kimsuky|APT33|APT39|APT32|APT18|Turla|APT19|Cobalt Group|Honeybee|Dark Caracal|Ke3chang|Threat Group-3390|Dragonfly 2.0|Gorgon Group|MuddyWater|APT37|Leviathan|BRONZE BUTLER|APT3|Magic Hound|FIN10|FIN7|Patchwork|FIN6|Lazarus Group|Putter Panda|APT29|Darkhotel +T1059,Command-Line Interface,Execution,APT41|Soft Cell|Turla|Silence|APT32|Cobalt Group|MuddyWater|APT18|APT38|Dragonfly 2.0|Gorgon Group|APT28|FIN7|Rancor|Honeybee|Leviathan|APT37|FIN8|Magic Hound|Sowbug|OilRig|BRONZE BUTLER|menuPass|Threat Group-3390|Suckfly|Patchwork|Lazarus Group|Threat Group-1314|APT3|admin@338|APT1|Ke3chang T1058,Service Registry Permissions Weakness,Persistence|Privilege Escalation,no T1057,Process Discovery,Discovery,Darkhotel|MuddyWater|APT1|APT38|Tropic Trooper|APT37|Honeybee|OilRig|APT3|Magic Hound|APT28|Winnti Group|Stealth Falcon|Poseidon Group|Lazarus Group|Molerats|Turla|Deep Panda|Ke3chang T1056,Input Capture,Collection|Credential Access,APT41|Kimsuky|menuPass|Stolen Pencil|FIN4|APT38|OilRig|Ke3chang|PLATINUM|Sowbug|Magic Hound|Group5|Lazarus Group|Threat Group-3390|APT3|Darkhotel|APT28 -T1055,Process Injection,Defense Evasion|Privilege Escalation,APT41|Kimsuky|Tropic Trooper|Gorgon Group|Threat Group-3390|APT37|Turla|Cobalt Group|Honeybee|Lazarus Group|PLATINUM|Putter Panda +T1055,Process Injection,Defense Evasion|Privilege Escalation,APT41|Kimsuky|Tropic Trooper|Gorgon Group|Turla|Threat Group-3390|APT37|Cobalt Group|Honeybee|Lazarus Group|PLATINUM|Putter Panda T1054,Indicator Blocking,Defense Evasion,no -T1053,Scheduled Task,Execution|Persistence|Privilege Escalation,APT41|Machete|Soft Cell|Silence|TEMP.Veles|APT33|APT39|Dragonfly 2.0|Cobalt Group|OilRig|Rancor|Patchwork|FIN8|BRONZE BUTLER|FIN10|menuPass|APT32|FIN7|Stealth Falcon|FIN6|Threat Group-3390|APT18|APT3|APT29 +T1053,Scheduled Task,Execution|Persistence|Privilege Escalation,APT41|Machete|Soft Cell|Silence|TEMP.Veles|APT33|APT39|Cobalt Group|Dragonfly 2.0|OilRig|Rancor|Patchwork|FIN8|BRONZE BUTLER|menuPass|FIN10|APT32|FIN7|Stealth Falcon|FIN6|Threat Group-3390|APT18|APT3|APT29 T1052,Exfiltration Over Physical Medium,Exfiltration,no T1051,Shared Webroot,Lateral Movement,no -T1050,New Service,Persistence|Privilege Escalation,Kimsuky|Tropic Trooper|Cobalt Group|FIN7|Threat Group-3390|Ke3chang|APT32|APT3|Lazarus Group|Carbanak +T1050,New Service,Persistence|Privilege Escalation,Kimsuky|Tropic Trooper|Cobalt Group|Ke3chang|FIN7|APT32|Threat Group-3390|APT3|Lazarus Group|Carbanak T1049,System Network Connections Discovery,Discovery,APT41|APT38|Soft Cell|APT32|APT1|OilRig|APT3|menuPass|Threat Group-3390|Poseidon Group|admin@338|Turla|Ke3chang T1048,Exfiltration Over Alternative Protocol,Exfiltration,Turla|APT33|Thrip|FIN8|OilRig|Lazarus Group T1047,Windows Management Instrumentation,Execution,APT41|FIN6|Soft Cell|APT32|MuddyWater|OilRig|Threat Group-3390|Leviathan|FIN8|menuPass|Stealth Falcon|Lazarus Group|APT29|Deep Panda -T1046,Network Service Scanning,Discovery,APT41|Tropic Trooper|APT39|APT32|Cobalt Group|OilRig|Leafminer|menuPass|Suckfly|FIN6|Threat Group-3390 +T1046,Network Service Scanning,Discovery,APT41|Tropic Trooper|APT39|APT32|Leafminer|Cobalt Group|OilRig|menuPass|Suckfly|FIN6|Threat Group-3390 T1045,Software Packing,Defense Evasion,Soft Cell|The White Company|APT39|APT38|Dark Caracal|Elderwood|APT3|Group5|Patchwork|APT29|Night Dragon T1044,File System Permissions Weakness,Persistence|Privilege Escalation,no T1043,Commonly Used Port,Command And Control,Machete|OilRig|APT28|TEMP.Veles|APT33|APT32|Night Dragon|APT29|APT18|Tropic Trooper|APT19|FIN7|Dragonfly 2.0|FIN8|APT37|Magic Hound|APT3|Lazarus Group|Threat Group-3390 @@ -232,18 +232,18 @@ T1037,Logon Scripts,Lateral Movement|Persistence,Cobalt Group|APT28 T1036,Masquerading,Defense Evasion,APT41|Soft Cell|PLATINUM|Ke3chang|Scarlet Mimic|menuPass|FIN6|TEMP.Veles|Dragonfly 2.0|MuddyWater|BRONZE BUTLER|Sowbug|FIN7|APT32|Patchwork|Poseidon Group|admin@338|Carbanak|APT1 T1035,Service Execution,Execution,Silence|FIN6|APT32|Honeybee|Ke3chang T1034,Path Interception,Persistence|Privilege Escalation,no -T1033,System Owner/User Discovery,Discovery,APT41|Soft Cell|Tropic Trooper|APT39|MuddyWater|APT37|APT32|APT19|Dragonfly 2.0|Magic Hound|OilRig|FIN10|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|APT3 +T1033,System Owner/User Discovery,Discovery,APT41|Soft Cell|Tropic Trooper|APT39|MuddyWater|APT32|APT37|APT19|Dragonfly 2.0|Magic Hound|OilRig|FIN10|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|APT3 T1032,Standard Cryptographic Protocol,Command And Control,Machete|APT33|Tropic Trooper|Cobalt Group|OilRig|FIN8|BRONZE BUTLER|Stealth Falcon|FIN6|Lazarus Group|Taidoor T1031,Modify Existing Service,Persistence,APT41|APT32|Honeybee|APT19 T1030,Data Transfer Size Limits,Exfiltration,Threat Group-3390 T1029,Scheduled Transfer,Exfiltration,no T1028,Windows Remote Management,Execution|Lateral Movement,Threat Group-3390 -T1027,Obfuscated Files or Information,Defense Evasion,Machete|Soft Cell|Turla|TA505|Silence|APT33|Night Dragon|Darkhotel|Gallmaker|APT29|APT18|Tropic Trooper|menuPass|Honeybee|Leafminer|Patchwork|Cobalt Group|APT37|Threat Group-3390|Dark Caracal|APT19|FIN8|BlackOasis|Leviathan|Elderwood|MuddyWater|FIN7|APT3|Magic Hound|OilRig|APT32|Group5|Dust Storm|Lazarus Group|Putter Panda|APT28 +T1027,Obfuscated Files or Information,Defense Evasion,Machete|Soft Cell|Turla|TA505|Silence|APT33|Night Dragon|Darkhotel|Gallmaker|APT29|APT18|Tropic Trooper|menuPass|Patchwork|Leafminer|Cobalt Group|APT37|Threat Group-3390|APT19|Honeybee|Dark Caracal|FIN8|BlackOasis|Elderwood|Leviathan|MuddyWater|FIN7|APT3|Magic Hound|OilRig|APT32|Group5|Dust Storm|Lazarus Group|Putter Panda|APT28 T1026,Multiband Communication,Command And Control,Lazarus Group T1025,Data from Removable Media,Collection,Machete|Turla|Gamaredon Group|APT28 T1024,Custom Cryptographic Protocol,Command And Control,APT28|BRONZE BUTLER|Lazarus Group -T1023,Shortcut Modification,Persistence,APT39|Darkhotel|APT29|FIN7|Gorgon Group|Dragonfly 2.0|Leviathan|Lazarus Group -T1022,Data Encrypted,Exfiltration,Kimsuky|Soft Cell|Turla|menuPass|APT32|Patchwork|Honeybee|CopyKittens|BRONZE BUTLER|FIN6|Lazarus Group|Threat Group-3390|Ke3chang +T1023,Shortcut Modification,Persistence,APT39|Darkhotel|APT29|Gorgon Group|FIN7|Dragonfly 2.0|Leviathan|Lazarus Group +T1022,Data Encrypted,Exfiltration,Kimsuky|Soft Cell|Turla|menuPass|APT32|Patchwork|Honeybee|BRONZE BUTLER|CopyKittens|FIN6|Lazarus Group|Threat Group-3390|Ke3chang T1021,Remote Services,Lateral Movement,TEMP.Veles|Leviathan|APT39|OilRig|menuPass|GCMAN T1020,Automated Exfiltration,Exfiltration,Honeybee T1019,System Firmware,Persistence,no @@ -260,8 +260,8 @@ T1009,Binary Padding,Defense Evasion,Patchwork|APT32|Leviathan|BRONZE BUTLER|Moa T1008,Fallback Channels,Command And Control,APT41|OilRig|Lazarus Group T1007,System Service Discovery,Discovery,APT1|OilRig|Poseidon Group|admin@338|Turla|Ke3chang T1006,File System Logical Offsets,Defense Evasion,no -T1005,Data from Local System,Collection,Kimsuky|Soft Cell|Turla|menuPass|Dark Caracal|Dragonfly 2.0|Honeybee|APT37|APT28|APT3|BRONZE BUTLER|Patchwork|Stealth Falcon|Lazarus Group|Dust Storm|Threat Group-3390|APT1|Ke3chang +T1005,Data from Local System,Collection,Kimsuky|Soft Cell|Turla|menuPass|Dragonfly 2.0|Dark Caracal|Honeybee|APT37|APT28|APT3|BRONZE BUTLER|Patchwork|Stealth Falcon|Lazarus Group|Dust Storm|Threat Group-3390|APT1|Ke3chang T1004,Winlogon Helper DLL,Persistence,Tropic Trooper|Turla -T1003,Credential Dumping,Credential Access,APT41|Soft Cell|TEMP.Veles|APT33|Leviathan|APT39|Stolen Pencil|APT32|Night Dragon|Dragonfly 2.0|Leafminer|Lazarus Group|Magic Hound|PLATINUM|APT37|MuddyWater|FIN8|Sowbug|BRONZE BUTLER|OilRig|FIN5|menuPass|Strider|Patchwork|Stealth Falcon|Suckfly|FIN6|Poseidon Group|Threat Group-3390|APT3|Molerats|APT28|APT1|Ke3chang|Cleaver|Axiom -T1002,Data Compressed,Exfiltration,APT41|Soft Cell|Gallmaker|APT33|APT32|APT39|MuddyWater|Honeybee|APT28|Magic Hound|Dragonfly 2.0|FIN8|BRONZE BUTLER|CopyKittens|Sowbug|APT3|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT1|Ke3chang +T1003,Credential Dumping,Credential Access,APT41|Soft Cell|TEMP.Veles|APT33|Leviathan|APT39|Stolen Pencil|APT32|Night Dragon|Dragonfly 2.0|Leafminer|Lazarus Group|Magic Hound|APT37|MuddyWater|PLATINUM|FIN8|Sowbug|BRONZE BUTLER|FIN5|OilRig|menuPass|Strider|Patchwork|Suckfly|Stealth Falcon|FIN6|Poseidon Group|Threat Group-3390|APT3|Molerats|APT28|APT1|Ke3chang|Cleaver|Axiom +T1002,Data Compressed,Exfiltration,APT41|Soft Cell|Gallmaker|APT33|APT32|APT39|MuddyWater|Honeybee|Magic Hound|APT28|Dragonfly 2.0|FIN8|BRONZE BUTLER|CopyKittens|Sowbug|APT3|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT1|Ke3chang T1001,Data Obfuscation,Command And Control,APT28|Axiom diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 6c8e822641..73a618e0be 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-20T08:17:41 UTC +# On Date: 2020-05-25T08:45:24 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] data_models = [] providing_technologies = none @@ -34,7 +34,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] support_searches = ["ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none @@ -53,8 +53,8 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] -support_searches = ["ESCU - Baseline of Network ACL Activity by ARN", "ESCU - Baseline of blocked outbound traffic from AWS"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of Network ACL Activity by ARN"] data_models = [] providing_technologies = none description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] data_models = [] providing_technologies = none @@ -86,8 +86,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] -support_searches = ["ESCU - Baseline of Security Group Activity by ARN", "ESCU - Baseline of API Calls per User ARN", "ESCU - Previously seen API call per user roles in CloudTrail", "ESCU - Create a list of approved AWS service accounts"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] +support_searches = ["ESCU - Create a list of approved AWS service accounts", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Previously seen API call per user roles in CloudTrail", "ESCU - Baseline of API Calls per User ARN"] data_models = [] providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. @@ -105,7 +105,7 @@ version = 1 reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] support_searches = ["ESCU - Count of assets by category"] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,8 +184,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region"] -support_searches = ["ESCU - Previously Seen Cloud Regions", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Instance Types"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] +support_searches = ["ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Regions"] data_models = ["Cloud_Infrastructure"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,7 +239,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations"] +investigative_searches = ["ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,7 +307,7 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,7 +383,7 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,8 +415,8 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Add Prohibited Processes to Enterprise Security"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. @@ -433,8 +433,8 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic"] -support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = ["ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint"] providing_technologies = none @@ -592,7 +592,7 @@ version = 1 reference = ["https://learn.cisecurity.org/20-controls-download"] detection_searches = ["ESCU - No Windows Updates in a time frame - Rule"] mappings = {"cis20": ["CIS 18"], "nist": ["PR.MA"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Updates"] providing_technologies = none @@ -610,7 +610,7 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -627,7 +627,7 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none @@ -670,8 +670,8 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,8 +729,8 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -762,7 +762,7 @@ version = 1 reference = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] detection_searches = ["ESCU - SQL Injection with Long URLs - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "mitre_attack": ["T1043"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] data_models = ["Vulnerabilities"] providing_technologies = none @@ -816,7 +816,7 @@ version = 1 reference = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] detection_searches = ["ESCU - Open Redirect in Splunk Web - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = [] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -860,7 +860,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] support_searches = ["ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen AWS Regions"] data_models = [] providing_technologies = none @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of S3 Bucket deletion activity by ARN", "ESCU - Previously seen S3 bucket access by remote IP"] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none @@ -929,8 +929,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,8 +981,8 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] -support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] support_searches = ["ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index f00281d581..173e425e83 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -3,79 +3,79 @@ label = AWS Cross Account Activity description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_source_user"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_aws_investigate_user_activities_by_source_user", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_aws_cryptomining] label = AWS Cryptomining description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_aws_network_acl_activity] label = AWS Network ACL Activity description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_aws_suspicious_provisioning_activities] label = AWS Suspicious Provisioning Activities description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_country", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] +panels = ["panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_country", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_region"] [panel_group://workbench_panel_group_aws_user_monitoring] label = AWS User Monitoring description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_user_activities_by_user_field"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_user_activities_by_user_field", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_account_monitoring_and_controls] label = Account Monitoring and Controls description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_apache_struts_vulnerability] label = Apache Struts Vulnerability description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. disabled = 0 -panels = ["panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_asset_tracking] label = Asset Tracking description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. disabled = 0 -panels = ["panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_brand_monitoring] label = Brand Monitoring description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. disabled = 0 -panels = ["panel://workbench_panel_get_email_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_cloud_cryptomining] label = Cloud Cryptomining description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_coldroot_macos_rat] label = ColdRoot MacOS RAT description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_collection_and_staging] label = Collection and Staging description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_command_and_control] label = Command and Control description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_common_phishing_frameworks] label = Common Phishing Frameworks @@ -93,19 +93,19 @@ panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activit label = Credential Dumping description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. disabled = 0 -panels = ["panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_ticket_attempts", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations"] +panels = ["panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_ticket_attempts", "panel://workbench_panel_investigate_pass_the_hash_attempts"] [panel_group://workbench_panel_group_dhs_report_ta18_074a] label = DHS Report TA18-074A description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. disabled = 0 -panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_dns_amplification_attacks] label = DNS Amplification Attacks description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_dns_hijacking] label = DNS Hijacking @@ -117,91 +117,91 @@ panels = ["panel://workbench_panel_get_dns_server_history_for_a_host"] label = Data Protection description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. disabled = 0 -panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_disabling_security_tools] label = Disabling Security Tools description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_dynamic_dns] label = Dynamic DNS description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. disabled = 0 -panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_emotet_malware__dhs_report_ta18_201a_] label = Emotet Malware DHS Report TA18-201A description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_hidden_cobra_malware] label = Hidden Cobra Malware description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. disabled = 0 -panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_host_redirection] label = Host Redirection description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. disabled = 0 -panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_jboss_vulnerability] label = JBoss Vulnerability description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_kubernetes_scanning_activity] label = Kubernetes Scanning Activity description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. disabled = 0 -panels = ["panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_lateral_movement] label = Lateral Movement description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_malicious_powershell] label = Malicious PowerShell description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_monitor_backup_solution] label = Monitor Backup Solution description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. disabled = 0 -panels = ["panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_monitor_for_unauthorized_software] label = Monitor for Unauthorized Software description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_monitor_for_updates] label = Monitor for Updates description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_netsh_abuse] label = Netsh Abuse description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_orangeworm_attack_group] label = Orangeworm Attack Group description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_phishing_payloads] label = Phishing Payloads @@ -213,61 +213,61 @@ panels = ["panel://workbench_panel_get_parent_process_info"] label = Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_prohibited_traffic_allowed_or_protocol_mismatch] label = Prohibited Traffic Allowed or Protocol Mismatch description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. disabled = 0 -panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_ransomware] label = Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_router_and_infrastructure_security] label = Router and Infrastructure Security description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_sql_injection] label = SQL Injection description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_samsam_ransomware] label = SamSam Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. disabled = 0 -panels = ["panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] label = Spectre And Meltdown Vulnerabilities description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability] label = Splunk Enterprise Vulnerability description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability_cve_2018_11409] label = Splunk Enterprise Vulnerability CVE-2018-11409 description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_investigate_web_activity_from_src_ip"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_aws_ec2_activities] label = Suspicious AWS EC2 Activities description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_ec2_launch_details", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_suspicious_aws_login_activities] label = Suspicious AWS Login Activities @@ -279,115 +279,115 @@ panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] label = Suspicious AWS S3 Activities description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. disabled = 0 -panels = ["panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_aws_traffic] label = Suspicious AWS Traffic description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_info", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_all_aws_activity_from_ip_address"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_command_line_executions] label = Suspicious Command-Line Executions description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_dns_traffic] label = Suspicious DNS Traffic description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. disabled = 0 -panels = ["panel://workbench_panel_get_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_emails] label = Suspicious Emails description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_email_info", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_mshta_activity] label = Suspicious MSHTA Activity description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_okta_activity] label = Suspicious Okta Activity description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. disabled = 0 -panels = ["panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_user_activities_in_okta"] +panels = ["panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_user_activities_in_okta"] [panel_group://workbench_panel_group_suspicious_wmi_use] label = Suspicious WMI Use description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_suspicious_windows_registry_activities] label = Suspicious Windows Registry Activities description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_unusual_aws_ec2_modifications] label = Unusual AWS EC2 Modifications description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_unusual_processes] label = Unusual Processes description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_use_of_cleartext_protocols] label = Use of Cleartext Protocols description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. disabled = 0 -panels = ["panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_web_fraud_detection] label = Web Fraud Detection description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. disabled = 0 -panels = ["panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_web_session_information_via_session_id"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_windows_defense_evasion_tactics] label = Windows Defense Evasion Tactics description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_windows_file_extension_and_association_abuse] label = Windows File Extension and Association Abuse description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_windows_log_manipulation] label = Windows Log Manipulation description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_windows_persistence_techniques] label = Windows Persistence Techniques description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_windows_privilege_escalation] label = Windows Privilege Escalation description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] [panel_group://workbench_panel_group_windows_service_abuse] label = Windows Service Abuse description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. disabled = 0 -panels = ["panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] diff --git a/package/default/macros.conf b/package/default/macros.conf index aa1d7832dc..16b0ab22c0 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-20T08:17:41 UTC +# On Date: 2020-05-25T08:45:24 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 05186e0dd4..9dbfbdfd8a 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-20T08:17:41 UTC +# On Date: 2020-05-25T08:45:24 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/transforms.conf b/package/default/transforms.conf index ffe9d86a7d..d122fef295 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-20T08:17:41 UTC +# On Date: 2020-05-25T08:45:24 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index cb60b4f8f4..8d74cd44ae 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-20T08:17:41 UTC +# On Date: 2020-05-25T08:45:24 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By Source User"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field"] +searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -78,7 +78,7 @@ version = 1 references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate User Activities In Single Cloud Region"] +searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get User Information from Identity Table", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Failed Logins for Multiple Destinations"] +searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Local Admin account - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Registry Activity", "ESCU - Get Registry Activities", "ESCU - Get Process File Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS record changed - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Responsible For The DNS Traffic"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Windows hosts file modification - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -435,7 +435,7 @@ version = 1 references = ["https://learn.cisecurity.org/20-controls-download"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - No Windows Updates in a time frame - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Monitor your enterprise to ensure that your endpoints are being patched and updated. Adversaries notoriously exploit known vulnerabilities that could be mitigated by applying routine security patches. narrative = It is a common best practice to ensure that endpoints are being patched and updated in a timely manner, in order to reduce the risk of compromise via a publicly disclosed vulnerability. Timely application of updates/patches is important to eliminate known vulnerabilities that may be exploited by various threat actors.\ Searches in this analytic story are designed to help analysts monitor endpoints for system patches and/or updates. This helps analysts identify any systems that are not successfully updated in a timely matter.\ @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Processes created by netsh - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -565,7 +565,7 @@ version = 1 references = ["https://capec.mitre.org/data/definitions/66.html", "https://www.incapsula.com/web-application-security/sql-injection.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint"] +searches = ["ESCU - SQL Injection with Long URLs - Rule", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Use the searches in this Analytic Story to help you detect structured query language (SQL) injection attempts characterized by long URLs that contain malicious parameters. narrative = It is very common for attackers to inject SQL parameters into vulnerable web applications, which then interpret the malicious SQL statements.\ This Analytic Story contains a search designed to identify attempts by attackers to leverage this technique to compromise a host and gain a foothold in the target environment. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -604,7 +604,7 @@ version = 1 references = ["http://www.splunk.com/view/SP-CAAAPQ6#announce", "https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2016-4859"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info"] +searches = ["ESCU - Open Redirect in Splunk Web - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = Keeping your Splunk deployment up to date is critical and may help you reduce the risk of CVE-2016-4859, an open-redirection vulnerability within some older versions of Splunk Enterprise. The detection search will help ensure that users are being properly authenticated and not being redirected to malicious domains. narrative = This Analytic Story is associated with CVE-2016-4859, an open-redirect vulnerability in the following versions of Splunk Enterprise:\ \ @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Investigate Network Traffic From src ip", "ESCU - Investigate Web Activity From src ip"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get EC2 Launch Details", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate AWS activities via region name", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Info", "ESCU - AWS Network Interface details via resourceId", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get All AWS Activity From IP Address"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Get Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Get Email Info", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - WMI Temporary Event Subscription - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id"] +searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Reg exe Process - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Shim Database File Creation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Registry Activities", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Parent Process Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable History", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User"] +searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. From 729419b24de559cd438ea3b829442e4b5f4df0d7 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 11:06:36 +0200 Subject: [PATCH 68/93] Updated searches --- baselines/baseline_of_command_line_length___mltk.yml | 2 +- baselines/baseline_of_smb_traffic___mltk.yml | 2 +- baselines/dnstwist_domain_names.yml | 2 +- ...iously_seen_aws_provisioning_activity_sources.yml | 4 ++-- baselines/previously_seen_command_line_arguments.yml | 2 +- baselines/previously_seen_users_in_cloudtrail.yml | 2 +- .../update_previously_seen_users_in_cloudtrail.yml | 2 +- ...attempt_to_add_certificate_to_untrusted_store.yml | 2 +- ...ll_execution_policy_to_unrestricted_or_bypass.yml | 2 +- .../clients_connecting_to_multiple_dns_servers.yml | 6 +++--- detections/common_ransomware_notes.yml | 2 +- .../create_local_admin_accounts_using_net_exe.yml | 10 +++++----- ...create_or_delete_windows_shares_using_net_exe.yml | 3 +-- detections/create_remote_thread_into_lsass.yml | 2 +- detections/deleting_shadow_copies.yml | 2 +- ...tackers_scanning_for_vulnerable_jboss_servers.yml | 2 +- ..._hosts_connecting_to_dynamic_domain_providers.yml | 4 ++-- detections/detect_long_dns_txt_record_response.yml | 2 +- ...t_malicious_requests_to_exploit_jboss_servers.yml | 2 +- ...ike_in_blocked_outbound_traffic_from_your_aws.yml | 2 +- ..._use_of_cmd_exe_to_launch_script_interpreters.yml | 2 +- detections/detection_of_dns_tunnels.yml | 2 +- detections/disabling_remote_user_account_control.yml | 2 +- detections/dns_query_length_outliers___mltk.yml | 2 +- ...dns_query_length_with_high_standard_deviation.yml | 2 +- ...requests_resolved_by_unauthorized_dns_servers.yml | 6 +++--- detections/email_attachments_with_lots_of_spaces.yml | 2 +- detections/excessive_dns_failures.yml | 2 +- detections/first_time_seen_command_line_argument.yml | 6 +++--- .../hiding_files_and_directories_with_attrib_exe.yml | 4 ++-- ...cess___connect_to_internet_with_hidden_window.yml | 2 +- detections/monitor_email_for_brand_abuse.yml | 2 +- detections/okta_account_lockout_events.yml | 2 +- detections/okta_failed_sso_attempts.yml | 2 +- detections/okta_user_logins_from_multiple_cities.yml | 2 +- detections/prohibited_network_traffic_allowed.yml | 4 ++-- detections/prohibited_software_on_endpoint.yml | 4 ++-- detections/protocol_or_port_mismatch.yml | 2 +- ...e_manipulating_windows_services_registry_keys.yml | 12 ++++++------ ...d_to_hide_files_directories_via_registry_keys.yml | 2 +- detections/registry_keys_used_for_persistence.yml | 8 ++++---- detections/remote_registry_key_modifications.yml | 2 +- detections/sc_exe_manipulating_windows_services.yml | 4 ++-- detections/smb_traffic_spike.yml | 2 +- detections/smb_traffic_spike___mltk.yml | 2 +- .../suspicious_email_attachment_extensions.yml | 2 +- detections/suspicious_reg_exe_process.yml | 2 +- ...ystem_processes_run_from_unexpected_locations.yml | 2 +- detections/tor_traffic.yml | 4 ++-- detections/unsigned_image_loaded_by_LSASS.yml | 2 +- detections/unusually_long_command_line.yml | 8 ++++---- detections/unusually_long_command_line___mltk.yml | 4 ++-- detections/web_fraud___account_harvesting.yml | 4 ++-- .../investigate_pass_the_ticket_attempts.yml | 6 ++++-- 54 files changed, 87 insertions(+), 86 deletions(-) diff --git a/baselines/baseline_of_command_line_length___mltk.yml b/baselines/baseline_of_command_line_length___mltk.yml index f5068fa341..28205e56d9 100644 --- a/baselines/baseline_of_command_line_length___mltk.yml +++ b/baselines/baseline_of_command_line_length___mltk.yml @@ -31,5 +31,5 @@ tags: - Suspicious MSHTA Activity - Unusual Processes detections: - - Unusually Long Command Line - MLTK - Detect Prohibited Applications Spawning cmd.exe + - Unusually Long Command Line - MLTK diff --git a/baselines/baseline_of_smb_traffic___mltk.yml b/baselines/baseline_of_smb_traffic___mltk.yml index f852ea17ce..e5b850a63c 100644 --- a/baselines/baseline_of_smb_traffic___mltk.yml +++ b/baselines/baseline_of_smb_traffic___mltk.yml @@ -36,5 +36,5 @@ tags: - Netsh Abuse - Ransomware detections: - - SMB Traffic Spike - MLTK - Processes launching netsh + - SMB Traffic Spike - MLTK diff --git a/baselines/dnstwist_domain_names.yml b/baselines/dnstwist_domain_names.yml index 7955295932..dde08528b5 100644 --- a/baselines/dnstwist_domain_names.yml +++ b/baselines/dnstwist_domain_names.yml @@ -17,5 +17,5 @@ tags: - Suspicious Emails detections: - Monitor Email For Brand Abuse - - Monitor Web Traffic For Brand Abuse - Monitor DNS For Brand Abuse + - Monitor Web Traffic For Brand Abuse diff --git a/baselines/previously_seen_aws_provisioning_activity_sources.yml b/baselines/previously_seen_aws_provisioning_activity_sources.yml index 24fad13984..c4eec20fd3 100644 --- a/baselines/previously_seen_aws_provisioning_activity_sources.yml +++ b/baselines/previously_seen_aws_provisioning_activity_sources.yml @@ -17,7 +17,7 @@ tags: analytics_story: - AWS Suspicious Provisioning Activities detections: - - AWS Cloud Provisioning From Previously Unseen City - AWS Cloud Provisioning From Previously Unseen IP Address - - AWS Cloud Provisioning From Previously Unseen Region + - AWS Cloud Provisioning From Previously Unseen City - AWS Cloud Provisioning From Previously Unseen Country + - AWS Cloud Provisioning From Previously Unseen Region diff --git a/baselines/previously_seen_command_line_arguments.yml b/baselines/previously_seen_command_line_arguments.yml index 32d364cc1e..8b15521edb 100644 --- a/baselines/previously_seen_command_line_arguments.yml +++ b/baselines/previously_seen_command_line_arguments.yml @@ -25,6 +25,6 @@ tags: - Suspicious Command-Line Executions - Suspicious MSHTA Activity detections: + - Detect Prohibited Applications Spawning cmd.exe - Processes launching netsh - First time seen command line argument - - Detect Prohibited Applications Spawning cmd.exe diff --git a/baselines/previously_seen_users_in_cloudtrail.yml b/baselines/previously_seen_users_in_cloudtrail.yml index 6f5a11191f..0a75480cd8 100644 --- a/baselines/previously_seen_users_in_cloudtrail.yml +++ b/baselines/previously_seen_users_in_cloudtrail.yml @@ -20,6 +20,6 @@ tags: - Suspicious AWS Login Activities detections: - Detect AWS Console Login by User from New Country - - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Region + - Detect AWS Console Login by User from New City - Detect new user AWS Console Login diff --git a/baselines/update_previously_seen_users_in_cloudtrail.yml b/baselines/update_previously_seen_users_in_cloudtrail.yml index ca2d520640..cc8a111d73 100644 --- a/baselines/update_previously_seen_users_in_cloudtrail.yml +++ b/baselines/update_previously_seen_users_in_cloudtrail.yml @@ -21,6 +21,6 @@ tags: - Suspicious AWS Login Activities detections: - Detect AWS Console Login by User from New Country - - Detect AWS Console Login by User from New City - Detect AWS Console Login by User from New Region + - Detect AWS Console Login by User from New City - Detect new user AWS Console Login diff --git a/detections/attempt_to_add_certificate_to_untrusted_store.yml b/detections/attempt_to_add_certificate_to_untrusted_store.yml index 1a65a56c62..9ed273f5fc 100644 --- a/detections/attempt_to_add_certificate_to_untrusted_store.yml +++ b/detections/attempt_to_add_certificate_to_untrusted_store.yml @@ -14,7 +14,7 @@ author: Rico Valdez, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process - Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` + Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `attempt_to_add_certificate_to_untrusted_store_filter`' known_false_positives: There may be legitimate reasons for administrators to add a certificate to the untrusted certificate store. In such cases, this will typically diff --git a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml index 20db8405eb..96e9e04f15 100644 --- a/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml +++ b/detections/attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass.yml @@ -17,7 +17,7 @@ search: "| tstats `security_content_summariesonly` count min(_time) as firstTime \ (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass)\ \ by Registry.registry_path Registry.registry_key_name Registry.registry_value_name\ \ Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`|\ - \ `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` " + \ `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter`\_" known_false_positives: Administrators may attempt to change the default execution policy on a system for a variety of reasons. However, setting the policy to "unrestricted" or "bypass" as this search is designed to identify, would be unusual. Hits should diff --git a/detections/clients_connecting_to_multiple_dns_servers.yml b/detections/clients_connecting_to_multiple_dns_servers.yml index 3de2319de0..b3f12496ec 100644 --- a/detections/clients_connecting_to_multiple_dns_servers.yml +++ b/detections/clients_connecting_to_multiple_dns_servers.yml @@ -27,10 +27,10 @@ known_false_positives: It's possible that an enterprise has more than five DNS s that are configured in a round-robin rotation. Please customize the search, as appropriate. tags: analytics_story: - - Command and Control - - Host Redirection - - Suspicious DNS Traffic - DNS Hijacking + - Command and Control + - Suspicious DNS Traffic + - Host Redirection mitre_attack_id: - T1048 kill_chain_phases: diff --git a/detections/common_ransomware_notes.yml b/detections/common_ransomware_notes.yml index a73dd745c8..4b8b8c9c48 100644 --- a/detections/common_ransomware_notes.yml +++ b/detections/common_ransomware_notes.yml @@ -15,7 +15,7 @@ author: David Dorsey, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` - | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`|`ransomware_notes`| + | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `ransomware_notes` | `common_ransomware_notes_filter`' known_false_positives: It's possible that a legitimate file could be created with the same name used by ransomware note files. diff --git a/detections/create_local_admin_accounts_using_net_exe.yml b/detections/create_local_admin_accounts_using_net_exe.yml index 236489d1d2..dd96f19f68 100644 --- a/detections/create_local_admin_accounts_using_net_exe.yml +++ b/detections/create_local_admin_accounts_using_net_exe.yml @@ -14,11 +14,11 @@ references: [] author: Bhavin Patel, Splunk search: '| tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime - max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe - OR Processes.process_name=net1.exe) by Processes.process Processes.process_name - Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* - OR process=*user*) |`create_local_admin_accounts_using_net_exe_filter` ' + max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=net.exe + OR Processes.process_name=net1.exe) AND (Processes.process=*localgroup* OR Processes.process=*/add* + OR Processes.process=*user*) by Processes.process Processes.process_name Processes.dest + | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` + |`create_local_admin_accounts_using_net_exe_filter` ' known_false_positives: Administrators often leverage net.exe to create admin accounts. tags: analytics_story: diff --git a/detections/create_or_delete_windows_shares_using_net_exe.yml b/detections/create_or_delete_windows_shares_using_net_exe.yml index 9eb576fe3a..5e66d89735 100644 --- a/detections/create_or_delete_windows_shares_using_net_exe.yml +++ b/detections/create_or_delete_windows_shares_using_net_exe.yml @@ -19,8 +19,7 @@ search: '| tstats `security_content_summariesonly` count values(Processes.user) max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| - `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) - | `create_or_delete_windows_shares_using_net_exe_filter` ' + `security_content_ctime(lastTime)` | search process=*share* | `create_or_delete_windows_shares_using_net_exe_filter` ' known_false_positives: Administrators often leverage net.exe to create or delete network shares. You should verify that the activity was intentional and is legitimate. tags: diff --git a/detections/create_remote_thread_into_lsass.yml b/detections/create_remote_thread_into_lsass.yml index 380b6d6eb5..ed579f304e 100644 --- a/detections/create_remote_thread_into_lsass.yml +++ b/detections/create_remote_thread_into_lsass.yml @@ -16,7 +16,7 @@ author: Patrick Bareiss, Splunk search: '`sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as firstTime max(_time) as lastTime by Computer, EventCode, TargetImage, TargetProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - |`create_remote_thread_into_lsass_filter`' + | `create_remote_thread_into_lsass_filter`' known_false_positives: Other tools can access LSASS for legitimate reasons and generate an event. In these cases, tweaking the search may help eliminate noise. tags: diff --git a/detections/deleting_shadow_copies.yml b/detections/deleting_shadow_copies.yml index c04ba7e5a8..62f95fe846 100644 --- a/detections/deleting_shadow_copies.yml +++ b/detections/deleting_shadow_copies.yml @@ -24,8 +24,8 @@ known_false_positives: vssadmin.exe and wmic.exe are standard applications shipp delete old backup copies, although this is typically rare. tags: analytics_story: - - SamSam Ransomware - Windows Log Manipulation + - SamSam Ransomware - Ransomware kill_chain_phases: - Actions on Objectives diff --git a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml index 7b7dfec741..9cc94a66ce 100644 --- a/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml +++ b/detections/detect_attackers_scanning_for_vulnerable_jboss_servers.yml @@ -19,8 +19,8 @@ known_false_positives: It's possible for legitimate HTTP requests to be made to containing the suspicious paths. tags: analytics_story: - - SamSam Ransomware - JBoss Vulnerability + - SamSam Ransomware mitre_attack_id: - T1082 kill_chain_phases: diff --git a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml index 71f1c02a11..8c3fcfa8fb 100644 --- a/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml +++ b/detections/detect_hosts_connecting_to_dynamic_domain_providers.yml @@ -44,12 +44,12 @@ known_false_positives: Some users and applications may leverage Dynamic DNS to r however this activity must be verified. tags: analytics_story: + - Data Protection - Prohibited Traffic Allowed or Protocol Mismatch - - Suspicious DNS Traffic - DNS Hijacking + - Suspicious DNS Traffic - Dynamic DNS - Command and Control - - Data Protection kill_chain_phases: - Command and Control - Actions on Objectives diff --git a/detections/detect_long_dns_txt_record_response.yml b/detections/detect_long_dns_txt_record_response.yml index b335fa7f35..12a52379a4 100644 --- a/detections/detect_long_dns_txt_record_response.yml +++ b/detections/detect_long_dns_txt_record_response.yml @@ -28,8 +28,8 @@ known_false_positives: It's possible that legitimate TXT record responses can be to help mitigate false positives. tags: analytics_story: - - Command and Control - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml index 49be7121db..ba130244e6 100644 --- a/detections/detect_malicious_requests_to_exploit_jboss_servers.yml +++ b/detections/detect_malicious_requests_to_exploit_jboss_servers.yml @@ -20,8 +20,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: No known false positives for this detection. tags: analytics_story: - - SamSam Ransomware - JBoss Vulnerability + - SamSam Ransomware kill_chain_phases: - Delivery cis20: diff --git a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml index e06ea84b01..fcdd2fdaa9 100644 --- a/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml +++ b/detections/detect_spike_in_blocked_outbound_traffic_from_your_aws.yml @@ -41,9 +41,9 @@ known_false_positives: The false-positive rate may vary based on the values of`d of blocked outbound connections. tags: analytics_story: - - Command and Control - AWS Network ACL Activity - Suspicious AWS Traffic + - Command and Control kill_chain_phases: - Actions on Objectives - Command and Control diff --git a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml index 37fac4086e..d261e24136 100644 --- a/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml +++ b/detections/detect_use_of_cmd_exe_to_launch_script_interpreters.yml @@ -22,8 +22,8 @@ search: '| tstats `security_content_summariesonly` count values(Processes.proces known_false_positives: Some legitimate applications may exhibit this behavior. tags: analytics_story: - - Suspicious Command-Line Executions - 'Emotet Malware DHS Report TA18-201A ' + - Suspicious Command-Line Executions mitre_attack_id: - T1059 kill_chain_phases: diff --git a/detections/detection_of_dns_tunnels.yml b/detections/detection_of_dns_tunnels.yml index b5cb9d2b95..2027a04314 100644 --- a/detections/detection_of_dns_tunnels.yml +++ b/detections/detection_of_dns_tunnels.yml @@ -39,9 +39,9 @@ known_false_positives: It's possible that normal DNS traffic will exhibit this b can also be modified to better suit your environment. tags: analytics_story: - - Command and Control - Data Protection - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/disabling_remote_user_account_control.yml b/detections/disabling_remote_user_account_control.yml index 878a50c013..ecb9b0b969 100644 --- a/detections/disabling_remote_user_account_control.yml +++ b/detections/disabling_remote_user_account_control.yml @@ -21,8 +21,8 @@ known_false_positives: This registry key may be modified via administrators to i a change in system policy. This type of change should be a very rare occurrence. tags: analytics_story: - - Suspicious Windows Registry Activities - Windows Defense Evasion Tactics + - Suspicious Windows Registry Activities mitre_attack_id: - T1112 kill_chain_phases: diff --git a/detections/dns_query_length_outliers___mltk.yml b/detections/dns_query_length_outliers___mltk.yml index 960bc2a820..6f1bab7aa8 100644 --- a/detections/dns_query_length_outliers___mltk.yml +++ b/detections/dns_query_length_outliers___mltk.yml @@ -47,9 +47,9 @@ known_false_positives: If you are seeing more results than desired, you may cons the support search to re-build the ML model on the latest data. tags: analytics_story: - - Command and Control - Hidden Cobra Malware - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/dns_query_length_with_high_standard_deviation.yml b/detections/dns_query_length_with_high_standard_deviation.yml index 1d612a5ac3..1d658defc6 100644 --- a/detections/dns_query_length_with_high_standard_deviation.yml +++ b/detections/dns_query_length_with_high_standard_deviation.yml @@ -18,9 +18,9 @@ search: '| tstats `security_content_summariesonly` count from datamodel=Network_ known_false_positives: It's possible there can be long domain names that are legitimate. tags: analytics_story: - - Command and Control - Hidden Cobra Malware - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml index 1ea4c64a62..67fba352f1 100644 --- a/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml +++ b/detections/dns_query_requests_resolved_by_unauthorized_dns_servers.yml @@ -18,10 +18,10 @@ known_false_positives: Legitimate DNS activity can be detected in this search. I verify and update the list of authorized DNS servers as appropriate. tags: analytics_story: - - Command and Control - - Host Redirection - - Suspicious DNS Traffic - DNS Hijacking + - Command and Control + - Suspicious DNS Traffic + - Host Redirection kill_chain_phases: - Command and Control cis20: diff --git a/detections/email_attachments_with_lots_of_spaces.yml b/detections/email_attachments_with_lots_of_spaces.yml index 90ffc1cc0d..cf550ea395 100644 --- a/detections/email_attachments_with_lots_of_spaces.yml +++ b/detections/email_attachments_with_lots_of_spaces.yml @@ -29,8 +29,8 @@ search: '| tstats `security_content_summariesonly` count values(All_Email.recipi known_false_positives: None at this time tags: analytics_story: - - Suspicious Emails - 'Emotet Malware DHS Report TA18-201A ' + - Suspicious Emails kill_chain_phases: - Delivery cis20: diff --git a/detections/excessive_dns_failures.yml b/detections/excessive_dns_failures.yml index 6289c61f59..d2e6d34058 100644 --- a/detections/excessive_dns_failures.yml +++ b/detections/excessive_dns_failures.yml @@ -21,8 +21,8 @@ known_false_positives: It is possible legitimate traffic can trigger this rule. to better suit your environment. tags: analytics_story: - - Command and Control - Suspicious DNS Traffic + - Command and Control mitre_attack_id: - T1048 - T1043 diff --git a/detections/first_time_seen_command_line_argument.yml b/detections/first_time_seen_command_line_argument.yml index b15dcdd2a9..4e65aa9096 100644 --- a/detections/first_time_seen_command_line_argument.yml +++ b/detections/first_time_seen_command_line_argument.yml @@ -34,11 +34,11 @@ known_false_positives: Legitimate programs can also use command-line arguments t macro to exclude legitimate parent_process_name tags: analytics_story: - - Suspicious Command-Line Executions - - Hidden Cobra Malware - DHS Report TA18-074A - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Suspicious Command-Line Executions - Orangeworm Attack Group + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Hidden Cobra Malware mitre_attack_id: - T1064 - T1059 diff --git a/detections/hiding_files_and_directories_with_attrib_exe.yml b/detections/hiding_files_and_directories_with_attrib_exe.yml index 3cbb39cf58..84db36db2f 100644 --- a/detections/hiding_files_and_directories_with_attrib_exe.yml +++ b/detections/hiding_files_and_directories_with_attrib_exe.yml @@ -17,14 +17,14 @@ author: Bhavin Patel, Splunk search: '| tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user - | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| + Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `hiding_files_and_directories_with_attrib_exe_filter` ' known_false_positives: 'Some applications and users may legitimately use attrib.exe to interact with the files. ' tags: analytics_story: - - Windows Persistence Techniques - Windows Defense Evasion Tactics + - Windows Persistence Techniques kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml index 2217d8c5f7..c1b4b686bc 100644 --- a/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml +++ b/detections/malicious_powershell_process___connect_to_internet_with_hidden_window.yml @@ -26,8 +26,8 @@ known_false_positives: Legitimate process can have this combination of command-l options, but it's not common. tags: analytics_story: - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Malicious PowerShell + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns mitre_attack_id: - T1086 - T1064 diff --git a/detections/monitor_email_for_brand_abuse.yml b/detections/monitor_email_for_brand_abuse.yml index 7889964dfc..aa409d05fa 100644 --- a/detections/monitor_email_for_brand_abuse.yml +++ b/detections/monitor_email_for_brand_abuse.yml @@ -21,8 +21,8 @@ search: '| tstats `security_content_summariesonly` values(All_Email.recipient) a known_false_positives: None at this time tags: analytics_story: - - Suspicious Emails - Brand Monitoring + - Suspicious Emails kill_chain_phases: - Delivery cis20: diff --git a/detections/okta_account_lockout_events.yml b/detections/okta_account_lockout_events.yml index 1b6c01b38a..162e5d18a4 100644 --- a/detections/okta_account_lockout_events.yml +++ b/detections/okta_account_lockout_events.yml @@ -9,7 +9,7 @@ type: ESCU author: Rico Valdez, Splunk search: '`okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city - as city | table _time, user, country, state, city, src_ip |`okta_account_lockout_events_filter` ' + as city | table _time, user, country, state, city, src_ip | `okta_account_lockout_events_filter` ' known_false_positives: None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor. diff --git a/detections/okta_failed_sso_attempts.yml b/detections/okta_failed_sso_attempts.yml index 2bb6d30ae0..9f1b9c370e 100644 --- a/detections/okta_failed_sso_attempts.yml +++ b/detections/okta_failed_sso_attempts.yml @@ -9,7 +9,7 @@ type: ESCU author: Rico Valdez, Splunk search: '`okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, - src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempts_filter` ' + src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `okta_failed_sso_attempts_filter` ' known_false_positives: There may be a faulty config preventing legitmate users from accessing apps they should have access to. tags: diff --git a/detections/okta_user_logins_from_multiple_cities.yml b/detections/okta_user_logins_from_multiple_cities.yml index b2257e06f6..416cf29617 100644 --- a/detections/okta_user_logins_from_multiple_cities.yml +++ b/detections/okta_user_logins_from_multiple_cities.yml @@ -12,7 +12,7 @@ search: '`okta` displayMessage="User login to Okta" client.geographicalContext.c | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - |`okta_user_logins_from_multiple_cities_filter`| search locations > 1' + | `okta_user_logins_from_multiple_cities_filter` | search locations > 1' known_false_positives: Users in your enviornment may legitmately be travelling and loggin in from different locations. This search is useful for those users that should *not* be travelling for some reason, such as the COVID-19 pandemic. The search also diff --git a/detections/prohibited_network_traffic_allowed.yml b/detections/prohibited_network_traffic_allowed.yml index 4f5c2efa47..abcba4ef5b 100644 --- a/detections/prohibited_network_traffic_allowed.yml +++ b/detections/prohibited_network_traffic_allowed.yml @@ -23,9 +23,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Command and Control - - Ransomware - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Command and Control mitre_attack_id: - T1043 - T1048 diff --git a/detections/prohibited_software_on_endpoint.yml b/detections/prohibited_software_on_endpoint.yml index 4394c1a7d1..b402bc90bb 100644 --- a/detections/prohibited_software_on_endpoint.yml +++ b/detections/prohibited_software_on_endpoint.yml @@ -24,9 +24,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - SamSam Ransomware - - 'Emotet Malware DHS Report TA18-201A ' - Monitor for Unauthorized Software + - 'Emotet Malware DHS Report TA18-201A ' + - SamSam Ransomware kill_chain_phases: - Installation - Command and Control diff --git a/detections/protocol_or_port_mismatch.yml b/detections/protocol_or_port_mismatch.yml index 315424a182..0753a62007 100644 --- a/detections/protocol_or_port_mismatch.yml +++ b/detections/protocol_or_port_mismatch.yml @@ -26,8 +26,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Command and Control - Prohibited Traffic Allowed or Protocol Mismatch + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/reg_exe_manipulating_windows_services_registry_keys.yml b/detections/reg_exe_manipulating_windows_services_registry_keys.yml index 23ce39e78b..d2aca8b976 100644 --- a/detections/reg_exe_manipulating_windows_services_registry_keys.yml +++ b/detections/reg_exe_manipulating_windows_services_registry_keys.yml @@ -13,11 +13,11 @@ references: [] author: Rico Valdez, Splunk search: '| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) - as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name - = reg.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` - | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join - [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path - count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" + as parent_process_name values(Processes.user) as user FROM datamodel=Endpoint.Processes + where Processes.process_name = reg.exe by Processes.process_id Processes.dest | + `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` + | join [| tstats `security_content_summariesonly` values(Registry.registry_path) + as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path] | `reg_exe_manipulating_windows_services_registry_keys_filter`' known_false_positives: It is unusual for a service to be created or modified by directly @@ -25,8 +25,8 @@ known_false_positives: It is unusual for a service to be created or modified by It is important to validate and investigate, as appropriate. tags: analytics_story: - - Windows Persistence Techniques - Windows Service Abuse + - Windows Persistence Techniques mitre_attack_id: - T1050 - T1031 diff --git a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml index fafe061d48..212df8aefb 100644 --- a/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml +++ b/detections/reg_exe_used_to_hide_files_directories_via_registry_keys.yml @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` values(Processes.process) as known_false_positives: None at the moment tags: analytics_story: + - Windows Defense Evasion Tactics - Suspicious Windows Registry Activities - Windows Persistence Techniques - - Windows Defense Evasion Tactics kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/registry_keys_used_for_persistence.yml b/detections/registry_keys_used_for_persistence.yml index e9119259f3..f99bb6c5c0 100644 --- a/detections/registry_keys_used_for_persistence.yml +++ b/detections/registry_keys_used_for_persistence.yml @@ -28,12 +28,12 @@ known_false_positives: There are many legitimate applications that must execute tags: analytics_story: - Suspicious Windows Registry Activities - - Windows Persistence Techniques - - 'Emotet Malware DHS Report TA18-201A ' - - Ransomware + - Suspicious MSHTA Activity - DHS Report TA18-074A - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - - Suspicious MSHTA Activity + - Ransomware + - Windows Persistence Techniques + - 'Emotet Malware DHS Report TA18-201A ' mitre_attack_id: - T1103 - T1131 diff --git a/detections/remote_registry_key_modifications.yml b/detections/remote_registry_key_modifications.yml index c900953e4f..3f7f0f342c 100644 --- a/detections/remote_registry_key_modifications.yml +++ b/detections/remote_registry_key_modifications.yml @@ -20,9 +20,9 @@ known_false_positives: This technique may be legitimately used by administrators modify remote registries, so it's important to filter these events out. tags: analytics_story: + - Windows Defense Evasion Tactics - Suspicious Windows Registry Activities - Windows Persistence Techniques - - Windows Defense Evasion Tactics kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/sc_exe_manipulating_windows_services.yml b/detections/sc_exe_manipulating_windows_services.yml index 955142e712..78563ec4a4 100644 --- a/detections/sc_exe_manipulating_windows_services.yml +++ b/detections/sc_exe_manipulating_windows_services.yml @@ -23,11 +23,11 @@ known_false_positives: Using sc.exe to manipulate Windows services is uncommon. and investigate as appropriate. tags: analytics_story: - - Windows Persistence Techniques - Windows Service Abuse - - Disabling Security Tools - DHS Report TA18-074A - Orangeworm Attack Group + - Windows Persistence Techniques + - Disabling Security Tools mitre_attack_id: - T1050 - T1031 diff --git a/detections/smb_traffic_spike.yml b/detections/smb_traffic_spike.yml index c43de1b40b..013f2661fc 100644 --- a/detections/smb_traffic_spike.yml +++ b/detections/smb_traffic_spike.yml @@ -21,9 +21,9 @@ known_false_positives: A file server may experience high-demand loads that could this analytic to trigger. tags: analytics_story: - - Ransomware - 'Emotet Malware DHS Report TA18-201A ' - Hidden Cobra Malware + - Ransomware - DHS Report TA18-074A mitre_attack_id: - T1043 diff --git a/detections/smb_traffic_spike___mltk.yml b/detections/smb_traffic_spike___mltk.yml index f848ea5e7e..8cc00847f4 100644 --- a/detections/smb_traffic_spike___mltk.yml +++ b/detections/smb_traffic_spike___mltk.yml @@ -42,9 +42,9 @@ known_false_positives: If you are seeing more results than desired, you may cons the `smb_traffic_spike_mltk_filter` macro to filter out false positive results tags: analytics_story: - - Ransomware - 'Emotet Malware DHS Report TA18-201A ' - Hidden Cobra Malware + - Ransomware - DHS Report TA18-074A mitre_attack_id: - T1043 diff --git a/detections/suspicious_email_attachment_extensions.yml b/detections/suspicious_email_attachment_extensions.yml index 8614d04a60..0df813263e 100644 --- a/detections/suspicious_email_attachment_extensions.yml +++ b/detections/suspicious_email_attachment_extensions.yml @@ -26,8 +26,8 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None identified tags: analytics_story: - - Suspicious Emails - 'Emotet Malware DHS Report TA18-201A ' + - Suspicious Emails kill_chain_phases: - Delivery cis20: diff --git a/detections/suspicious_reg_exe_process.yml b/detections/suspicious_reg_exe_process.yml index 39ce10bfee..c60be0872b 100644 --- a/detections/suspicious_reg_exe_process.yml +++ b/detections/suspicious_reg_exe_process.yml @@ -29,8 +29,8 @@ known_false_positives: It's possible for system administrators to write scripts to filter them out. tags: analytics_story: - - Disabling Security Tools - Windows Defense Evasion Tactics + - Disabling Security Tools - DHS Report TA18-074A mitre_attack_id: - T1112 diff --git a/detections/system_processes_run_from_unexpected_locations.yml b/detections/system_processes_run_from_unexpected_locations.yml index 4e7d43fa11..7e77f9ed36 100644 --- a/detections/system_processes_run_from_unexpected_locations.yml +++ b/detections/system_processes_run_from_unexpected_locations.yml @@ -21,8 +21,8 @@ known_false_positives: None identified tags: analytics_story: - Suspicious Command-Line Executions - - Ransomware - Unusual Processes + - Ransomware mitre_attack_id: - T1036 kill_chain_phases: diff --git a/detections/tor_traffic.yml b/detections/tor_traffic.yml index 83feca13ac..ae0ccd1df0 100644 --- a/detections/tor_traffic.yml +++ b/detections/tor_traffic.yml @@ -21,9 +21,9 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime known_false_positives: None at this time tags: analytics_story: - - Command and Control - - Ransomware - Prohibited Traffic Allowed or Protocol Mismatch + - Ransomware + - Command and Control mitre_attack_id: - T1043 kill_chain_phases: diff --git a/detections/unsigned_image_loaded_by_LSASS.yml b/detections/unsigned_image_loaded_by_LSASS.yml index e9646fe171..d614857984 100644 --- a/detections/unsigned_image_loaded_by_LSASS.yml +++ b/detections/unsigned_image_loaded_by_LSASS.yml @@ -16,7 +16,7 @@ author: Patrick Bareiss, Splunk search: '`sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` - | `unsigned_image_loaded_by_lsass_filter` ' + | `unsigned_image_loaded_by_LSAS`unsigned_image_loaded_by_lsass_filter` ' known_false_positives: Other tools could load images into LSASS for legitimate reason. But enterprise tools should always use signed DLLs. tags: diff --git a/detections/unusually_long_command_line.yml b/detections/unusually_long_command_line.yml index f3f2c703fa..434cd4e457 100644 --- a/detections/unusually_long_command_line.yml +++ b/detections/unusually_long_command_line.yml @@ -16,16 +16,16 @@ search: '| tstats `security_content_summariesonly` count min(_time) as firstTime Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) - as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| - `unusually_long_command_line_filter` eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process | + `unusually_long_command_line_filter` | eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost)' known_false_positives: Some legitimate applications start with long command lines. tags: analytics_story: - - Ransomware - Suspicious Command-Line Executions - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Unusual Processes + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Ransomware kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/unusually_long_command_line___mltk.yml b/detections/unusually_long_command_line___mltk.yml index 9f50cca4cf..dea463a213 100644 --- a/detections/unusually_long_command_line___mltk.yml +++ b/detections/unusually_long_command_line___mltk.yml @@ -35,10 +35,10 @@ known_false_positives: Some legitimate applications use long command lines for i build the associated model. tags: analytics_story: - - Ransomware - Suspicious Command-Line Executions - - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns - Unusual Processes + - Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns + - Ransomware kill_chain_phases: - Actions on Objectives cis20: diff --git a/detections/web_fraud___account_harvesting.yml b/detections/web_fraud___account_harvesting.yml index d02cf467a3..e3a7425763 100644 --- a/detections/web_fraud___account_harvesting.yml +++ b/detections/web_fraud___account_harvesting.yml @@ -19,8 +19,8 @@ references: author: Jim Apger, Splunk search: '`stream_http` http_content_type=text* uri="/magento2/customer/account/loginPost/" | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" - | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) - as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> + | search Username=* | rex field=Username "@(?.*)" | stats dc(Username) + as UniqueUsernames list(Username) as src_user by email_domain | where UniqueUsernames> 25 | `web_fraud___account_harvesting_filter`' known_false_positives: As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosely written detections diff --git a/response_tasks/investigate_pass_the_ticket_attempts.yml b/response_tasks/investigate_pass_the_ticket_attempts.yml index e6de16dd57..7ca5f470c9 100644 --- a/response_tasks/investigate_pass_the_ticket_attempts.yml +++ b/response_tasks/investigate_pass_the_ticket_attempts.yml @@ -12,8 +12,10 @@ how_to_implement: To successfully implement this search you need to be ingesting author: Patrick Bareiss, Splunk inputs: - dest -search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) - AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2' +search: '`wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user + "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) + AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 + | rename new_user AS user' tags: analytics_story: - Credential Dumping From f86d1cd590e85209479ddafd70030afb3f2a6f4d Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 11:09:44 +0200 Subject: [PATCH 69/93] dry run master api update --- .circleci/config.yml | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 9d9b290652..14957a5741 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -127,7 +127,7 @@ jobs: python bin/generate.py --path . --output package -v # make a copy of use_case_lib in order to have ES work :-( cp package/default/use_case_library.conf package/default/analyticstories.conf - - run: + - run: name: copy lookups .csv files command: | cd security-content @@ -244,7 +244,7 @@ jobs: - run: *apt-install - aws-cli/setup: profile-name: default - - run: + - run: name: update community api sources command: | cd security-content @@ -334,7 +334,7 @@ jobs: - run: name: sync latest ESCU to the Attack Range S3 bucket for apps command: | - aws s3 cp ~/DA-ESS-ContentUpdate-latest.tar.gz s3://attack-range-appbinaries/ + aws s3 cp ~/DA-ESS-ContentUpdate-latest.tar.gz s3://attack-range-appbinaries/ # make the file public since it is not by default aws s3api put-object-acl --bucket attack-range-appbinaries --key DA-ESS-ContentUpdate-latest.tar.gz --acl public-read master-api-update: @@ -351,17 +351,18 @@ jobs: - run: *apt-install - aws-cli/setup: profile-name: default - - run: + - run: name: update api sources command: | cd security-content aws s3 cp stories s3://security-content/stories --recursive --exclude "*" --include "*.yml" aws s3 cp baselines s3://security-content/baselines --recursive --exclude "*" --include "*.yml" aws s3 cp detections s3://security-content/detections --recursive --exclude "*" --include "*.yml" - aws s3 cp investigations s3://security-content/investigations --recursive --exclude "*" --include "*.yml" + aws s3 cp response_tasks s3://security-content/response_tasks --recursive --exclude "*" --include "*.yml" aws s3 cp responses s3://security-content/responses --recursive --exclude "*" --include "*.yml" aws s3 cp lookups s3://security-content/lookups --recursive --exclude "*" --include "*.yml" aws s3 cp macros s3://security-content/macros --recursive --exclude "*" --include "*.yml" + aws s3 cp deployments s3://security-content/deployments --recursive --exclude "*" --include "*.yml" workflows: version: 2.1 validate-and-build: @@ -456,6 +457,4 @@ workflows: - attack-range-update filters: tags: - only: /^v.*/ - branches: - ignore: /.*/ + only: /.*/ From 7b1d282ca71a3227759112f89155e98d088a18a3 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 11:11:27 +0200 Subject: [PATCH 70/93] dry run master api update --- requirements.txt | 1 - 1 file changed, 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index be21fe40d5..33cd21ab39 100644 --- a/requirements.txt +++ b/requirements.txt @@ -34,5 +34,4 @@ toml==0.10.0 typing==3.7.4.1 urllib3==1.25.9 virtualenv==20.0.20 -zipp==0.6.0 zipp==3.1.0 From 27244b14f6f857068561f28fa9224b3cf337f0d2 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 11:15:15 +0200 Subject: [PATCH 71/93] broken link --- stories/account_monitoring_and_controls.yml | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/stories/account_monitoring_and_controls.yml b/stories/account_monitoring_and_controls.yml index f03fe46e46..97aa2c5e63 100644 --- a/stories/account_monitoring_and_controls.yml +++ b/stories/account_monitoring_and_controls.yml @@ -15,8 +15,7 @@ narrative: Monitoring user accounts within your enterprise is a critical analyti or co-opted, leading to suspicious or malicious activity. author: David Dorsey, Splunk type: ESCU -references: -- https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf +references: [] tags: analytics_story: Account Monitoring and Controls usecase: Security Monitoring From 8977f7b02b92ec63bb5f38f25b3be17e8f890057 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 11:23:28 +0200 Subject: [PATCH 72/93] dry run master api update --- .circleci/config.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 14957a5741..80a1f5db23 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -457,4 +457,6 @@ workflows: - attack-range-update filters: tags: - only: /.*/ + only: /^v.*/ + branches: + ignore: /.*/ From 16463076153cf9fd447346aa1379ec543bbc4f76 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 11:33:25 +0200 Subject: [PATCH 73/93] dry run master api update --- .circleci/config.yml | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 80a1f5db23..7a38ecf088 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -361,6 +361,7 @@ jobs: aws s3 cp response_tasks s3://security-content/response_tasks --recursive --exclude "*" --include "*.yml" aws s3 cp responses s3://security-content/responses --recursive --exclude "*" --include "*.yml" aws s3 cp lookups s3://security-content/lookups --recursive --exclude "*" --include "*.yml" + aws s3 cp lookups s3://security-content/lookups --recursive --exclude "*" --include "*.csv" aws s3 cp macros s3://security-content/macros --recursive --exclude "*" --include "*.yml" aws s3 cp deployments s3://security-content/deployments --recursive --exclude "*" --include "*.yml" workflows: @@ -457,6 +458,4 @@ workflows: - attack-range-update filters: tags: - only: /^v.*/ - branches: - ignore: /.*/ + only: /.*/ From 4fc0b7555b4add09661a8d27040bdac6b9af4445 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 11:42:58 +0200 Subject: [PATCH 74/93] dry run master api update --- .circleci/config.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 7a38ecf088..042eb1ef9d 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -458,4 +458,6 @@ workflows: - attack-range-update filters: tags: - only: /.*/ + only: /^v.*/ + branches: + ignore: /.*/ From f229e1e6a4eb1caa66a9035e9df5c36c9c29d4c3 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 12:47:10 +0200 Subject: [PATCH 75/93] updated README --- README.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 13ccf44315..d1cd29ba69 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ - - - + + + # Splunk Security Content ![security-content](docs/static/logo.png) ===== @@ -28,7 +28,7 @@ curl -s https://content.splunkresearch.com | jq } ``` -#### GitHub Workflow +#### [GitHub Workflow](https://github.com/splunk/security-content/wiki/2.-Installation-and-Usage) Create your customized version of Security Content by forking this project and following this guide. # What's in an Analytic Story? @@ -40,7 +40,7 @@ Manifests contain a number of mandatory and optional fields. You can see the ful After release [1.0.46](https://github.com/splunk/security-content/releases) we introduced a concept of **input(pre-filter)** and **output(post-filter)** macros for each of our detection search. The intention behind introducing these macros is primarily to help our users to update the macro definition “once” and those changes will be applicable across all detections that leverage that macro and local to your Splunk Environment. -**input(pre-filter):** This macro is to specify your environment-specific configurations (index, source, sourcetype, etc.) to get the specific data sources that you would like to bring in. Replace the macro definition with configurations for your Splunk environment. For example the [sysmon](macros/sysmon.yml) **input macro** can be modified to the local splunk deployments index or sourcetype. +**input(pre-filter):** This macro is to specify your environment-specific configurations (index, source, sourcetype, etc.) to get the specific data sources that you would like to bring in. Replace the macro definition with configurations for your Splunk environment. For example the [sysmon](macros/sysmon.yml) **input macro** can be modified to the local splunk deployments index or sourcetype. **output(post-filter):** This macro is to specify your environment-specific values (eg: dest, user), to filter out known false positives.. Replace the macro definition with values that you’d like to exclude from detection results. Think of this as a whitelisting/blacklisting using macros. A good example @@ -51,16 +51,16 @@ After release [1.0.46](https://github.com/splunk/security-content/releases) we i Download and install the latest version of [Splunk Analytic Story Execution] (https://github.com/splunk/analytic_story_execution/releases). This Splunk application will help the user do the following: ======= -Download and install the latest version of [Splunk Analytic Story Execution] +Download and install the latest version of [Splunk Analytic Story Execution] (https://github.com/splunk/analytic_story_execution/releases). This Splunk application will help the user do the following: 1. Execute an analytic story in an adhoc mode and view the results. 2. Schedule all the detection searches in an analytic story. 3. Update security-content via an API - + # Writing Content -Before you begin, follow the steps to install **dependencies and pre-commit hooks** under ["Developing"](https://github.com/splunk/security-content#developing). +Before you begin, follow the steps to install **dependencies and pre-commit hooks** under ["Developing"](https://github.com/splunk/security-content#developing). >>>>>>> develop 1. Execute an analytic story in an adhoc mode and view the results. From 086209ae4260fb0f7a30186b24f9db52d889d33c Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 12:50:48 +0200 Subject: [PATCH 76/93] updated README --- README.md | 9 --------- 1 file changed, 9 deletions(-) diff --git a/README.md b/README.md index d1cd29ba69..64f9750747 100644 --- a/README.md +++ b/README.md @@ -47,10 +47,6 @@ After release [1.0.46](https://github.com/splunk/security-content/releases) we i # Execute an Analytic Story -<<<<<<< HEAD -Download and install the latest version of [Splunk Analytic Story Execution] -(https://github.com/splunk/analytic_story_execution/releases). This Splunk application will help the user do the following: -======= Download and install the latest version of [Splunk Analytic Story Execution] (https://github.com/splunk/analytic_story_execution/releases). This Splunk application will help the user do the following: @@ -61,11 +57,6 @@ Download and install the latest version of [Splunk Analytic Story Execution] # Writing Content Before you begin, follow the steps to install **dependencies and pre-commit hooks** under ["Developing"](https://github.com/splunk/security-content#developing). ->>>>>>> develop - -1. Execute an analytic story in an adhoc mode and view the results. -2. Schedule all the detection searches in an analytic story. -3. Update security-content via an API # Security Content From fd024fb4c098d8664e67971c0f7a3fcd451baae2 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 16:46:38 +0200 Subject: [PATCH 77/93] small bug --- bin/jinja2_templates/use_case_library.j2 | 2 +- lookups/mitre_enrichment.csv | 118 ++--- package/default/analytic_stories.conf | 150 +++--- ...l_investigate_pass_the_ticket_attempts.xml | 2 +- package/default/es_investigations.conf | 114 ++-- package/default/macros.conf | 2 +- package/default/savedsearches.conf | 106 ++-- package/default/transforms.conf | 2 +- package/default/use_case_library.conf | 488 +++++++++--------- 9 files changed, 492 insertions(+), 492 deletions(-) diff --git a/bin/jinja2_templates/use_case_library.j2 b/bin/jinja2_templates/use_case_library.j2 index 1aa262ca2b..a47e922985 100644 --- a/bin/jinja2_templates/use_case_library.j2 +++ b/bin/jinja2_templates/use_case_library.j2 @@ -29,7 +29,7 @@ narrative = {{ story.narrative }} {% for detection in detections %} [savedsearch://ESCU - {{ detection.name }} - Rule] type = detection -asset_type = {{ detection.asset_type }} +asset_type = {{ detection.tags.asset_type }} confidence = medium explanation = {{ detection.description }} {% if detection.how_to_implement is defined %} diff --git a/lookups/mitre_enrichment.csv b/lookups/mitre_enrichment.csv index f31d264442..2ee84a99fd 100644 --- a/lookups/mitre_enrichment.csv +++ b/lookups/mitre_enrichment.csv @@ -44,58 +44,58 @@ T1482,Domain Trust Discovery,Discovery,no T1480,Execution Guardrails,Defense Evasion,APT33|Equation T1223,Compiled HTML File,Defense Evasion|Execution,APT41|Silence|Lazarus Group|Dark Caracal|OilRig T1222,File and Directory Permissions Modification,Defense Evasion,APT32 -T1221,Template Injection,Defense Evasion,APT28|Tropic Trooper|Dragonfly 2.0|DarkHydrus T1220,XSL Script Processing,Defense Evasion|Execution,Cobalt Group +T1221,Template Injection,Defense Evasion,APT28|Tropic Trooper|Dragonfly 2.0|DarkHydrus T1197,BITS Jobs,Defense Evasion|Persistence,Leviathan -T1217,Browser Bookmark Discovery,Discovery,no T1191,CMSTP,Defense Evasion|Execution,Cobalt Group|MuddyWater T1196,Control Panel Items,Defense Evasion|Execution,no T1214,Credentials in Registry,Credential Access,Soft Cell T1207,DCShadow,Defense Evasion,no T1213,Data from Information Repositories,Collection,Ke3chang|APT28 -T1189,Drive-by Compromise,Initial Access,Darkhotel|APT38|Lazarus Group|Dragonfly 2.0|BRONZE BUTLER|Leafminer|Dark Caracal|APT32|Threat Group-3390|APT19|Elderwood|APT37|Patchwork|PLATINUM -T1190,Exploit Public-Facing Application,Initial Access,Soft Cell|Night Dragon|Axiom T1212,Exploitation for Credential Access,Credential Access,no -T1211,Exploitation for Defense Evasion,Defense Evasion,APT28 -T1203,Exploitation for Client Execution,Execution,APT41|admin@338|Threat Group-3390|APT12|The White Company|APT33|APT32|APT28|Tropic Trooper|BRONZE BUTLER|Lazarus Group|Cobalt Group|APT37|APT29|Patchwork|Leviathan|Elderwood|TA459 +T1217,Browser Bookmark Discovery,Discovery,no +T1190,Exploit Public-Facing Application,Initial Access,Soft Cell|Night Dragon|Axiom T1210,Exploitation of Remote Services,Lateral Movement,Threat Group-3390|APT28 T1200,Hardware Additions,Initial Access,no -T1202,Indirect Command Execution,Defense Evasion,no +T1189,Drive-by Compromise,Initial Access,Darkhotel|APT38|Lazarus Group|Dragonfly 2.0|BRONZE BUTLER|Leafminer|APT19|Dark Caracal|Threat Group-3390|APT32|Elderwood|Patchwork|APT37|PLATINUM +T1211,Exploitation for Defense Evasion,Defense Evasion,APT28 +T1203,Exploitation for Client Execution,Execution,APT41|admin@338|Threat Group-3390|APT12|The White Company|APT33|APT32|APT28|Tropic Trooper|BRONZE BUTLER|Lazarus Group|Cobalt Group|APT37|APT29|Patchwork|Leviathan|TA459|Elderwood T1208,Kerberoasting,Credential Access,no T1215,Kernel Modules and Extensions,Persistence,no T1201,Password Policy Discovery,Discovery,OilRig T1205,Port Knocking,Defense Evasion|Persistence|Command And Control,no -T1219,Remote Access Tools,Command And Control,Kimsuky|Night Dragon|Thrip|Cobalt Group|Carbanak T1198,SIP and Trust Provider Hijacking,Defense Evasion|Persistence,no T1218,Signed Binary Proxy Execution,Defense Evasion|Execution,TA505|Rancor|Cobalt Group -T1216,Signed Script Proxy Execution,Defense Evasion|Execution,APT32 -T1193,Spearphishing Attachment,Initial Access,APT41|Machete|admin@338|Kimsuky|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Tropic Trooper|Turla|Gorgon Group|Rancor|DarkHydrus|Lazarus Group|Cobalt Group|BRONZE BUTLER|OilRig|FIN7|APT19|Dragonfly 2.0|APT32|FIN8|MuddyWater|APT28|TA459|Elderwood|APT29|APT37|Patchwork|Leviathan|Magic Hound|menuPass|PLATINUM +T1202,Indirect Command Execution,Defense Evasion,no T1194,Spearphishing via Service,Initial Access,FIN6|OilRig|Dark Caracal|Magic Hound -T1192,Spearphishing Link,Initial Access,Machete|Kimsuky|TA505|Stolen Pencil|APT39|FIN4|APT32|Night Dragon|APT28|Turla|Cobalt Group|Dragonfly 2.0|OilRig|APT33|Elderwood|Patchwork|Magic Hound|APT29|Leviathan|FIN8 -T1206,Sudo Caching,Privilege Escalation,no T1195,Supply Chain Compromise,Initial Access,APT41|Elderwood +T1219,Remote Access Tools,Command And Control,Kimsuky|Night Dragon|Thrip|Cobalt Group|Carbanak +T1216,Signed Script Proxy Execution,Defense Evasion|Execution,APT32 +T1193,Spearphishing Attachment,Initial Access,APT41|Machete|admin@338|Kimsuky|APT12|TA505|Silence|The White Company|APT39|FIN4|Darkhotel|Gallmaker|Tropic Trooper|Turla|Gorgon Group|Rancor|DarkHydrus|Lazarus Group|Cobalt Group|OilRig|APT19|FIN7|BRONZE BUTLER|Dragonfly 2.0|APT32|FIN8|MuddyWater|APT28|TA459|Elderwood|APT29|APT37|Patchwork|Leviathan|menuPass|Magic Hound|PLATINUM T1209,Time Providers,Persistence,no +T1204,User Execution,Execution,Machete|admin@338|APT12|TA505|Silence|The White Company|APT39|FIN4|Night Dragon|Darkhotel|Gallmaker|Dragonfly 2.0|APT33|APT19|BRONZE BUTLER|Dark Caracal|Cobalt Group|FIN7|DarkHydrus|Turla|Gorgon Group|OilRig|MuddyWater|Patchwork|Lazarus Group|APT32|Rancor|APT37|APT28|APT29|menuPass|FIN8|TA459|Elderwood|Leviathan|Magic Hound|PLATINUM +T1192,Spearphishing Link,Initial Access,Machete|Kimsuky|TA505|Stolen Pencil|APT39|FIN4|APT32|Night Dragon|APT28|Turla|Cobalt Group|Dragonfly 2.0|OilRig|APT33|Elderwood|APT29|Leviathan|Patchwork|Magic Hound|FIN8 +T1206,Sudo Caching,Privilege Escalation,no T1199,Trusted Relationship,Initial Access,APT28|menuPass -T1204,User Execution,Execution,Machete|admin@338|APT12|TA505|Silence|The White Company|APT39|FIN4|Night Dragon|Darkhotel|Gallmaker|Dragonfly 2.0|APT19|BRONZE BUTLER|APT33|Dark Caracal|Cobalt Group|FIN7|DarkHydrus|Patchwork|Turla|Gorgon Group|Lazarus Group|APT32|Rancor|OilRig|MuddyWater|APT37|APT28|APT29|FIN8|menuPass|Elderwood|PLATINUM|Magic Hound|TA459|Leviathan T1182,AppCert DLLs,Persistence|Privilege Escalation,Honeybee T1176,Browser Extensions,Persistence,Kimsuky|Stolen Pencil T1175,Component Object Model and Distributed COM,Lateral Movement|Execution,MuddyWater -T1172,Domain Fronting,Command And Control,APT29 -T1173,Dynamic Data Exchange,Execution,TA505|MuddyWater|Gallmaker|Patchwork|Cobalt Group|APT37|APT28|FIN7 T1181,Extra Window Memory Injection,Defense Evasion|Privilege Escalation,no -T1187,Forced Authentication,Credential Access,DarkHydrus|Dragonfly 2.0 T1179,Hooking,Persistence|Privilege Escalation|Credential Access,PLATINUM -T1183,Image File Execution Options Injection,Privilege Escalation|Persistence|Defense Evasion,TEMP.Veles +T1172,Domain Fronting,Command And Control,APT29 +T1187,Forced Authentication,Credential Access,DarkHydrus|Dragonfly 2.0 +T1173,Dynamic Data Exchange,Execution,TA505|MuddyWater|Gallmaker|Patchwork|Cobalt Group|APT37|APT28|FIN7 +T1188,Multi-hop Proxy,Command And Control,FIN4|APT29 T1171,LLMNR/NBT-NS Poisoning and Relay,Credential Access,no T1177,LSASS Driver,Execution|Persistence,no -T1185,Man in the Browser,Collection,no -T1170,Mshta,Defense Evasion|Execution,Kimsuky|APT32|MuddyWater|FIN7 -T1188,Multi-hop Proxy,Command And Control,FIN4|APT29 T1174,Password Filter DLL,Credential Access,no -T1186,Process Doppelgänging,Defense Evasion,no -T1184,SSH Hijacking,Lateral Movement,no -T1178,SID-History Injection,Privilege Escalation,no T1180,Screensaver,Persistence,no +T1183,Image File Execution Options Injection,Privilege Escalation|Persistence|Defense Evasion,TEMP.Veles +T1170,Mshta,Defense Evasion|Execution,Kimsuky|APT32|MuddyWater|FIN7 +T1184,SSH Hijacking,Lateral Movement,no +T1185,Man in the Browser,Collection,no +T1186,Process Doppelgänging,Defense Evasion,no +T1178,SID-History Injection,Privilege Escalation,no T1156,.bash_profile and .bashrc,Persistence,no T1134,Access Token Manipulation,Defense Evasion|Privilege Escalation,Turla|Lazarus Group|APT28 T1155,AppleScript,Execution|Lateral Movement,no @@ -103,35 +103,35 @@ T1138,Application Shimming,Persistence|Privilege Escalation,FIN7 T1139,Bash History,Credential Access,no T1146,Clear Command History,Defense Evasion,APT41 T1136,Create Account,Persistence,APT41|Soft Cell|Dragonfly 2.0|Leafminer|APT3 -T1140,Deobfuscate/Decode Files or Information,Defense Evasion,Turla|WIRTE|Darkhotel|Tropic Trooper|Honeybee|menuPass|Gorgon Group|Threat Group-3390|APT19|Leviathan|MuddyWater|APT28|OilRig|BRONZE BUTLER +T1140,Deobfuscate/Decode Files or Information,Defense Evasion,Turla|WIRTE|Darkhotel|Tropic Trooper|Gorgon Group|Honeybee|menuPass|Threat Group-3390|APT19|Leviathan|MuddyWater|APT28|OilRig|BRONZE BUTLER T1157,Dylib Hijacking,Persistence|Privilege Escalation,no -T1144,Gatekeeper Bypass,Defense Evasion,no T1148,HISTCONTROL,Defense Evasion,no T1147,Hidden Users,Defense Evasion,no -T1158,Hidden Files and Directories,Defense Evasion|Persistence,APT32|Tropic Trooper|APT28|Lazarus Group T1143,Hidden Window,Defense Evasion,Gorgon Group|Deep Panda|DarkHydrus|CopyKittens|APT19|APT32|APT28|APT3|Magic Hound -T1141,Input Prompt,Credential Access,FIN4 -T1142,Keychain,Credential Access,no +T1144,Gatekeeper Bypass,Defense Evasion,no +T1158,Hidden Files and Directories,Defense Evasion|Persistence,APT32|Tropic Trooper|APT28|Lazarus Group T1149,LC_MAIN Hijacking,Defense Evasion,no -T1161,LC_LOAD_DYLIB Addition,Persistence,no -T1159,Launch Agent,Persistence,no T1152,Launchctl,Defense Evasion|Execution|Persistence,no T1168,Local Job Scheduling,Persistence|Execution,no -T1160,Launch Daemon,Persistence|Privilege Escalation,no +T1141,Input Prompt,Credential Access,FIN4 T1162,Login Item,Persistence,no -T1135,Network Share Discovery,Discovery,APT41|Tropic Trooper|APT1|Dragonfly 2.0|Sowbug T1137,Office Application Startup,Persistence,APT32|APT28 T1150,Plist Modification,Defense Evasion|Persistence|Privilege Escalation,no T1145,Private Keys,Credential Access,no T1163,Rc.common,Persistence,no +T1142,Keychain,Credential Access,no +T1159,Launch Agent,Persistence,no +T1151,Space after Filename,Defense Evasion|Execution,no +T1161,LC_LOAD_DYLIB Addition,Persistence,no +T1160,Launch Daemon,Persistence|Privilege Escalation,no +T1153,Source,Execution,no +T1154,Trap,Execution|Persistence,no +T1135,Network Share Discovery,Discovery,APT41|Tropic Trooper|APT1|Dragonfly 2.0|Sowbug T1164,Re-opened Applications,Persistence,no +T1169,Sudo,Privilege Escalation,no T1167,Securityd Memory,Credential Access,no T1166,Setuid and Setgid,Privilege Escalation|Persistence,no -T1153,Source,Execution,no -T1151,Space after Filename,Defense Evasion|Execution,no T1165,Startup Items,Persistence|Privilege Escalation,no -T1169,Sudo,Privilege Escalation,no -T1154,Trap,Execution|Persistence,no T1133,External Remote Services,Persistence|Initial Access,APT41|Soft Cell|TEMP.Veles|Night Dragon|OilRig|Ke3chang|Dragonfly 2.0|FIN5|Threat Group-3390|APT18 T1132,Data Encoding,Command And Control,APT33|APT19|Lazarus Group|BRONZE BUTLER|Patchwork T1131,Authentication Package,Persistence,no @@ -149,21 +149,21 @@ T1120,Peripheral Device Discovery,Discovery,APT37|Gamaredon Group|Equation|APT28 T1119,Automated Collection,Collection,APT1|APT28|Patchwork|OilRig|FIN5|Threat Group-3390|FIN6 T1118,InstallUtil,Defense Evasion|Execution,no T1117,Regsvr32,Defense Evasion|Execution,WIRTE|APT19|Cobalt Group|Leviathan|APT32|Deep Panda -T1116,Code Signing,Defense Evasion,APT41|FIN6|TA505|FIN7|Honeybee|Leviathan|APT37|CopyKittens|Winnti Group|Suckfly|Molerats|Darkhotel +T1116,Code Signing,Defense Evasion,APT41|FIN6|TA505|FIN7|Honeybee|APT37|Leviathan|CopyKittens|Winnti Group|Suckfly|Molerats|Darkhotel T1115,Clipboard Data,Collection,APT38 -T1114,Email Collection,Collection,FIN4|APT28|Dragonfly 2.0|Magic Hound|Ke3chang|Leafminer|APT1 -T1113,Screen Capture,Collection,Silence|MuddyWater|OilRig|Dragonfly 2.0|FIN7|Dark Caracal|BRONZE BUTLER|Magic Hound|Group5|APT28 -T1112,Modify Registry,Defense Evasion,APT41|Turla|APT32|APT38|Dragonfly 2.0|APT19|Gorgon Group|Patchwork|Threat Group-3390|Honeybee|FIN8 +T1114,Email Collection,Collection,FIN4|Dragonfly 2.0|APT28|Magic Hound|Ke3chang|Leafminer|APT1 +T1113,Screen Capture,Collection,Silence|MuddyWater|OilRig|Dragonfly 2.0|Dark Caracal|FIN7|BRONZE BUTLER|Magic Hound|Group5|APT28 +T1112,Modify Registry,Defense Evasion,APT41|Turla|APT32|APT38|Dragonfly 2.0|Threat Group-3390|Patchwork|APT19|Honeybee|Gorgon Group|FIN8 T1111,Two-Factor Authentication Interception,Credential Access,no -T1110,Brute Force,Credential Access,APT41|APT33|Leafminer|Dragonfly 2.0|OilRig|APT3|Lazarus Group|Turla +T1110,Brute Force,Credential Access,APT41|APT33|Leafminer|OilRig|Dragonfly 2.0|APT3|Lazarus Group|Turla T1109,Component Firmware,Defense Evasion|Persistence,Equation T1108,Redundant Access,Defense Evasion|Persistence,Stolen Pencil|Cobalt Group|Leafminer|APT3|FIN5|OilRig|Threat Group-3390 -T1107,File Deletion,Defense Evasion,APT41|Kimsuky|Silence|The White Company|TEMP.Veles|APT32|APT38|Honeybee|Patchwork|Cobalt Group|Dragonfly 2.0|menuPass|FIN8|OilRig|FIN5|BRONZE BUTLER|Magic Hound|APT3|FIN10|APT28|Threat Group-3390|Group5|Lazarus Group|APT18|APT29 +T1107,File Deletion,Defense Evasion,APT41|Kimsuky|Silence|The White Company|TEMP.Veles|APT32|APT38|Honeybee|Patchwork|Dragonfly 2.0|menuPass|Cobalt Group|FIN8|OilRig|FIN5|BRONZE BUTLER|Magic Hound|APT3|FIN10|Threat Group-3390|APT28|Group5|Lazarus Group|APT18|APT29 T1106,Execution through API,Execution,Turla|Silence|APT37|Gorgon Group -T1105,Remote File Copy,Command And Control|Lateral Movement,Soft Cell|TA505|WIRTE|APT33|MuddyWater|APT18|APT38|Cobalt Group|Rancor|Turla|Gorgon Group|OilRig|Dragonfly 2.0|APT37|FIN8|Leviathan|PLATINUM|Elderwood|Magic Hound|APT3|BRONZE BUTLER|APT32|menuPass|FIN7|FIN10|Gamaredon Group|Patchwork|Lazarus Group|Threat Group-3390|APT28 +T1105,Remote File Copy,Command And Control|Lateral Movement,Soft Cell|TA505|WIRTE|APT33|MuddyWater|APT18|APT38|Turla|Rancor|Gorgon Group|Cobalt Group|Dragonfly 2.0|OilRig|APT37|FIN8|PLATINUM|Leviathan|Elderwood|Magic Hound|APT3|APT32|BRONZE BUTLER|FIN7|FIN10|menuPass|Gamaredon Group|Patchwork|Lazarus Group|Threat Group-3390|APT28 T1104,Multi-Stage Channels,Command And Control,MuddyWater|APT3 T1103,AppInit DLLs,Persistence|Privilege Escalation,no -T1102,Web Service,Command And Control|Defense Evasion,APT41|APT12|FIN6|Turla|FIN7|BRONZE BUTLER|APT37|Leviathan|Magic Hound|RTM|Patchwork|Carbanak +T1102,Web Service,Command And Control|Defense Evasion,APT41|APT12|FIN6|Turla|FIN7|BRONZE BUTLER|Leviathan|APT37|Magic Hound|RTM|Patchwork|Carbanak T1101,Security Support Provider,Persistence,no T1100,Web Shell,Persistence|Privilege Escalation,Soft Cell|Threat Group-3390|TEMP.Veles|Leviathan|APT39|Dragonfly 2.0|APT32|OilRig|Deep Panda T1099,Timestomp,Defense Evasion,TEMP.Veles|APT32|Lazarus Group|APT28 @@ -177,36 +177,36 @@ T1092,Communication Through Removable Media,Command And Control,APT28 T1091,Replication Through Removable Media,Lateral Movement|Initial Access,Darkhotel|APT28 T1090,Connection Proxy,Command And Control|Defense Evasion,APT41|Soft Cell|Turla|APT39|MuddyWater|APT3|Lazarus Group|menuPass|Strider|APT28 T1089,Disabling Security Tools,Defense Evasion,Kimsuky|Turla|Night Dragon|Dragonfly 2.0|Gorgon Group|Threat Group-3390|Lazarus Group|Putter Panda|Carbanak -T1088,Bypass User Account Control,Defense Evasion|Privilege Escalation,APT37|MuddyWater|Honeybee|Cobalt Group|Threat Group-3390|BRONZE BUTLER|Patchwork|APT29 +T1088,Bypass User Account Control,Defense Evasion|Privilege Escalation,APT37|MuddyWater|Honeybee|Threat Group-3390|Cobalt Group|BRONZE BUTLER|Patchwork|APT29 T1087,Account Discovery,Discovery,APT32|APT1|Dragonfly 2.0|BRONZE BUTLER|OilRig|Threat Group-3390|menuPass|FIN6|Poseidon Group|APT3|admin@338|Ke3chang -T1086,PowerShell,Execution,APT41|Kimsuky|Soft Cell|TA505|WIRTE|TEMP.Veles|APT33|Gallmaker|Turla|Thrip|APT19|DarkHydrus|Dragonfly 2.0|Cobalt Group|APT28|Gorgon Group|Leviathan|TA459|MuddyWater|FIN8|CopyKittens|OilRig|Magic Hound|BRONZE BUTLER|APT32|FIN10|FIN7|Threat Group-3390|menuPass|Patchwork|Stealth Falcon|FIN6|Poseidon Group|APT3|APT29|Deep Panda +T1086,PowerShell,Execution,APT41|Kimsuky|Soft Cell|TA505|WIRTE|TEMP.Veles|APT33|Gallmaker|Turla|DarkHydrus|APT19|APT28|Thrip|Dragonfly 2.0|Cobalt Group|Gorgon Group|Leviathan|TA459|MuddyWater|FIN8|CopyKittens|OilRig|Magic Hound|BRONZE BUTLER|APT32|FIN10|FIN7|Threat Group-3390|menuPass|Patchwork|Stealth Falcon|FIN6|Poseidon Group|APT3|APT29|Deep Panda T1085,Rundll32,Defense Evasion|Execution,TA505|MuddyWater|APT29|APT19|CopyKittens|APT3|Carbanak|APT28 T1084,Windows Management Instrumentation Event Subscription,Persistence,Turla|Leviathan|APT29 -T1083,File and Directory Discovery,Discovery,Kimsuky|APT32|MuddyWater|APT18|Leafminer|Dragonfly 2.0|Dark Caracal|Honeybee|Magic Hound|APT3|BRONZE BUTLER|Sowbug|APT28|Patchwork|Lazarus Group|Dust Storm|admin@338|Turla|Ke3chang -T1082,System Information Discovery,Discovery,Kimsuky|Tropic Trooper|Darkhotel|MuddyWater|APT18|APT37|Honeybee|APT19|APT32|OilRig|Magic Hound|APT3|Sowbug|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|admin@338|Turla|Ke3chang +T1083,File and Directory Discovery,Discovery,Kimsuky|APT32|MuddyWater|APT18|Leafminer|Dragonfly 2.0|Honeybee|Dark Caracal|Magic Hound|APT3|Sowbug|BRONZE BUTLER|APT28|Patchwork|Lazarus Group|Dust Storm|admin@338|Turla|Ke3chang +T1082,System Information Discovery,Discovery,Kimsuky|Tropic Trooper|Darkhotel|MuddyWater|APT18|APT37|Honeybee|APT19|APT32|Magic Hound|OilRig|APT3|Sowbug|Gamaredon Group|Patchwork|Stealth Falcon|Lazarus Group|admin@338|Turla|Ke3chang T1081,Credentials in Files,Credential Access,OilRig|Kimsuky|Turla|TA505|Stolen Pencil|MuddyWater|APT3 T1080,Taint Shared Content,Lateral Movement,Darkhotel T1079,Multilayer Encryption,Command And Control,no -T1078,Valid Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,APT41|Soft Cell|TEMP.Veles|APT39|Stolen Pencil|FIN4|Night Dragon|Dragonfly 2.0|FIN8|APT33|Leviathan|APT3|FIN5|OilRig|menuPass|APT28|APT32|FIN10|Suckfly|FIN6|Threat Group-1314|Threat Group-3390|APT18|PittyTiger|Carbanak +T1078,Valid Accounts,Defense Evasion|Persistence|Privilege Escalation|Initial Access,APT41|Soft Cell|TEMP.Veles|APT39|Stolen Pencil|FIN4|Night Dragon|Dragonfly 2.0|FIN8|Leviathan|APT33|APT3|FIN5|OilRig|menuPass|APT28|FIN10|APT32|Suckfly|FIN6|Threat Group-1314|Threat Group-3390|APT18|PittyTiger|Carbanak T1077,Windows Admin Shares,Lateral Movement,APT32|Orangeworm|FIN8|APT3|Lazarus Group|Threat Group-1314|Turla|Deep Panda|Ke3chang T1076,Remote Desktop Protocol,Lateral Movement,APT41|TEMP.Veles|Leviathan|APT39|Stolen Pencil|Cobalt Group|Dragonfly 2.0|FIN8|APT3|OilRig|menuPass|FIN10|Patchwork|FIN6|Lazarus Group|APT1|Axiom T1075,Pass the Hash,Lateral Movement,Soft Cell|APT32|Night Dragon|APT28|APT1 T1074,Data Staged,Collection,Machete|Soft Cell|TEMP.Veles|Night Dragon|Honeybee|Patchwork|Dragonfly 2.0|Leviathan|FIN8|APT3|FIN5|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT28 T1073,DLL Side-Loading,Defense Evasion,APT41|Soft Cell|Tropic Trooper|Patchwork|APT19|APT32|APT3|menuPass|Threat Group-3390 T1072,Third-party Software,Execution|Lateral Movement,Threat Group-1314 -T1071,Standard Application Layer Protocol,Command And Control,APT41|Machete|WIRTE|APT33|FIN4|Night Dragon|APT18|SilverTerrier|APT38|Dragonfly 2.0|APT19|Cobalt Group|FIN7|Threat Group-3390|APT37|Orangeworm|Turla|Rancor|Honeybee|Ke3chang|Dark Caracal|Lazarus Group|BRONZE BUTLER|OilRig|APT32|Magic Hound|Gamaredon Group|Stealth Falcon|FIN6|APT28 +T1071,Standard Application Layer Protocol,Command And Control,APT41|Machete|WIRTE|APT33|FIN4|Night Dragon|APT18|SilverTerrier|APT38|Dragonfly 2.0|APT19|Cobalt Group|FIN7|Threat Group-3390|Turla|APT37|Rancor|Orangeworm|Honeybee|Ke3chang|Dark Caracal|Lazarus Group|BRONZE BUTLER|APT32|OilRig|Magic Hound|Gamaredon Group|Stealth Falcon|FIN6|APT28 T1070,Indicator Removal on Host,Defense Evasion,APT41|APT29|APT38|Dragonfly 2.0|APT32|FIN8|FIN5|APT28 T1069,Permission Groups Discovery,Discovery,FIN6|Dragonfly 2.0|OilRig|APT3|admin@338|Ke3chang T1068,Exploitation for Privilege Escalation,Privilege Escalation,APT33|Cobalt Group|PLATINUM|FIN8|APT32|Threat Group-3390|FIN6|APT28 T1067,Bootkit,Persistence,APT41|Lazarus Group|APT28 T1066,Indicator Removal from Tools,Defense Evasion,Soft Cell|TEMP.Veles|Patchwork|APT3|Turla|OilRig|Deep Panda T1065,Uncommonly Used Port,Command And Control,TEMP.Veles|APT33|APT32|Gorgon Group|Magic Hound|Group5|Lazarus Group|APT3 -T1064,Scripting,Defense Evasion|Execution,Machete|Turla|TA505|Silence|WIRTE|APT39|FIN4|APT32|Darkhotel|Gallmaker|Dark Caracal|Lazarus Group|menuPass|APT19|Dragonfly 2.0|APT37|Gorgon Group|Leafminer|Rancor|Cobalt Group|FIN7|Honeybee|Ke3chang|Patchwork|MuddyWater|Leviathan|FIN8|TA459|APT28|Magic Hound|OilRig|BRONZE BUTLER|FIN5|FIN10|Gamaredon Group|Stealth Falcon|FIN6|APT3|APT29|Deep Panda|APT1 +T1064,Scripting,Defense Evasion|Execution,Machete|Turla|TA505|Silence|WIRTE|APT39|FIN4|APT32|Darkhotel|Gallmaker|Dark Caracal|Lazarus Group|menuPass|APT19|Dragonfly 2.0|Leafminer|Rancor|Honeybee|APT37|Ke3chang|Cobalt Group|Patchwork|FIN7|Gorgon Group|MuddyWater|Leviathan|FIN8|TA459|APT28|Magic Hound|OilRig|FIN5|BRONZE BUTLER|FIN10|Gamaredon Group|Stealth Falcon|FIN6|APT3|APT29|Deep Panda|APT1 T1063,Security Software Discovery,Discovery,The White Company|Cobalt Group|Darkhotel|MuddyWater|Tropic Trooper|FIN8|Patchwork|Naikon T1062,Hypervisor,Persistence,no T1061,Graphical User Interface,Execution,APT3 -T1060,Registry Run Keys / Startup Folder,Persistence,APT41|Machete|Kimsuky|APT33|APT39|APT32|APT18|Turla|APT19|Cobalt Group|Honeybee|Dark Caracal|Ke3chang|Threat Group-3390|Dragonfly 2.0|Gorgon Group|MuddyWater|APT37|Leviathan|BRONZE BUTLER|APT3|Magic Hound|FIN10|FIN7|Patchwork|FIN6|Lazarus Group|Putter Panda|APT29|Darkhotel -T1059,Command-Line Interface,Execution,APT41|Soft Cell|Turla|Silence|APT32|Cobalt Group|MuddyWater|APT18|APT38|Dragonfly 2.0|Gorgon Group|APT28|FIN7|Rancor|Honeybee|Leviathan|APT37|FIN8|Magic Hound|Sowbug|OilRig|BRONZE BUTLER|menuPass|Threat Group-3390|Suckfly|Patchwork|Lazarus Group|Threat Group-1314|APT3|admin@338|APT1|Ke3chang +T1060,Registry Run Keys / Startup Folder,Persistence,APT41|Machete|Kimsuky|APT33|APT39|APT32|APT18|Turla|APT19|Dark Caracal|Ke3chang|Dragonfly 2.0|Cobalt Group|Honeybee|Threat Group-3390|Gorgon Group|MuddyWater|APT37|Leviathan|BRONZE BUTLER|APT3|Magic Hound|FIN10|FIN7|Patchwork|FIN6|Lazarus Group|Putter Panda|APT29|Darkhotel +T1059,Command-Line Interface,Execution,APT41|Soft Cell|Turla|Silence|APT32|Cobalt Group|MuddyWater|APT18|APT38|Dragonfly 2.0|Gorgon Group|APT28|FIN7|Rancor|Honeybee|APT37|Leviathan|FIN8|Magic Hound|Sowbug|OilRig|BRONZE BUTLER|menuPass|Threat Group-3390|Suckfly|Patchwork|Lazarus Group|Threat Group-1314|APT3|admin@338|APT1|Ke3chang T1058,Service Registry Permissions Weakness,Persistence|Privilege Escalation,no T1057,Process Discovery,Discovery,Darkhotel|MuddyWater|APT1|APT38|Tropic Trooper|APT37|Honeybee|OilRig|APT3|Magic Hound|APT28|Winnti Group|Stealth Falcon|Poseidon Group|Lazarus Group|Molerats|Turla|Deep Panda|Ke3chang T1056,Input Capture,Collection|Credential Access,APT41|Kimsuky|menuPass|Stolen Pencil|FIN4|APT38|OilRig|Ke3chang|PLATINUM|Sowbug|Magic Hound|Group5|Lazarus Group|Threat Group-3390|APT3|Darkhotel|APT28 @@ -238,18 +238,18 @@ T1031,Modify Existing Service,Persistence,APT41|APT32|Honeybee|APT19 T1030,Data Transfer Size Limits,Exfiltration,Threat Group-3390 T1029,Scheduled Transfer,Exfiltration,no T1028,Windows Remote Management,Execution|Lateral Movement,Threat Group-3390 -T1027,Obfuscated Files or Information,Defense Evasion,Machete|Soft Cell|Turla|TA505|Silence|APT33|Night Dragon|Darkhotel|Gallmaker|APT29|APT18|Tropic Trooper|menuPass|Patchwork|Leafminer|Cobalt Group|APT37|Threat Group-3390|APT19|Honeybee|Dark Caracal|FIN8|BlackOasis|Elderwood|Leviathan|MuddyWater|FIN7|APT3|Magic Hound|OilRig|APT32|Group5|Dust Storm|Lazarus Group|Putter Panda|APT28 +T1027,Obfuscated Files or Information,Defense Evasion,Machete|Soft Cell|Turla|TA505|Silence|APT33|Night Dragon|Darkhotel|Gallmaker|APT29|APT18|Tropic Trooper|menuPass|Patchwork|Leafminer|Cobalt Group|APT37|Threat Group-3390|Honeybee|Dark Caracal|APT19|FIN8|BlackOasis|Elderwood|Leviathan|MuddyWater|FIN7|Magic Hound|APT3|OilRig|APT32|Group5|Dust Storm|Lazarus Group|Putter Panda|APT28 T1026,Multiband Communication,Command And Control,Lazarus Group T1025,Data from Removable Media,Collection,Machete|Turla|Gamaredon Group|APT28 T1024,Custom Cryptographic Protocol,Command And Control,APT28|BRONZE BUTLER|Lazarus Group -T1023,Shortcut Modification,Persistence,APT39|Darkhotel|APT29|Gorgon Group|FIN7|Dragonfly 2.0|Leviathan|Lazarus Group -T1022,Data Encrypted,Exfiltration,Kimsuky|Soft Cell|Turla|menuPass|APT32|Patchwork|Honeybee|BRONZE BUTLER|CopyKittens|FIN6|Lazarus Group|Threat Group-3390|Ke3chang +T1023,Shortcut Modification,Persistence,APT39|Darkhotel|APT29|FIN7|Gorgon Group|Dragonfly 2.0|Leviathan|Lazarus Group +T1022,Data Encrypted,Exfiltration,Kimsuky|Soft Cell|Turla|menuPass|APT32|Patchwork|Honeybee|CopyKittens|BRONZE BUTLER|FIN6|Lazarus Group|Threat Group-3390|Ke3chang T1021,Remote Services,Lateral Movement,TEMP.Veles|Leviathan|APT39|OilRig|menuPass|GCMAN T1020,Automated Exfiltration,Exfiltration,Honeybee T1019,System Firmware,Persistence,no -T1018,Remote System Discovery,Discovery,Soft Cell|APT32|Threat Group-3390|Dragonfly 2.0|Deep Panda|Ke3chang|Leafminer|FIN8|FIN5|APT3|BRONZE BUTLER|menuPass|FIN6|Turla +T1018,Remote System Discovery,Discovery,Soft Cell|APT32|Threat Group-3390|Dragonfly 2.0|Deep Panda|Ke3chang|Leafminer|FIN8|APT3|FIN5|BRONZE BUTLER|menuPass|FIN6|Turla T1017,Application Deployment Software,Lateral Movement,APT32 -T1016,System Network Configuration Discovery,Discovery,APT41|Soft Cell|APT39|APT32|Darkhotel|MuddyWater|APT1|APT19|Dragonfly 2.0|Magic Hound|OilRig|menuPass|Threat Group-3390|Stealth Falcon|Lazarus Group|APT3|Naikon|admin@338|Turla|Ke3chang +T1016,System Network Configuration Discovery,Discovery,APT41|Soft Cell|APT39|APT32|Darkhotel|MuddyWater|APT1|APT19|Dragonfly 2.0|OilRig|Magic Hound|menuPass|Threat Group-3390|Stealth Falcon|Lazarus Group|APT3|Naikon|admin@338|Turla|Ke3chang T1015,Accessibility Features,Persistence|Privilege Escalation,APT41|APT3|APT29|Deep Panda|Axiom T1014,Rootkit,Defense Evasion,APT41|APT28|Winnti Group T1013,Port Monitors,Persistence|Privilege Escalation,no @@ -262,6 +262,6 @@ T1007,System Service Discovery,Discovery,APT1|OilRig|Poseidon Group|admin@338|Tu T1006,File System Logical Offsets,Defense Evasion,no T1005,Data from Local System,Collection,Kimsuky|Soft Cell|Turla|menuPass|Dragonfly 2.0|Dark Caracal|Honeybee|APT37|APT28|APT3|BRONZE BUTLER|Patchwork|Stealth Falcon|Lazarus Group|Dust Storm|Threat Group-3390|APT1|Ke3chang T1004,Winlogon Helper DLL,Persistence,Tropic Trooper|Turla -T1003,Credential Dumping,Credential Access,APT41|Soft Cell|TEMP.Veles|APT33|Leviathan|APT39|Stolen Pencil|APT32|Night Dragon|Dragonfly 2.0|Leafminer|Lazarus Group|Magic Hound|APT37|MuddyWater|PLATINUM|FIN8|Sowbug|BRONZE BUTLER|FIN5|OilRig|menuPass|Strider|Patchwork|Suckfly|Stealth Falcon|FIN6|Poseidon Group|Threat Group-3390|APT3|Molerats|APT28|APT1|Ke3chang|Cleaver|Axiom +T1003,Credential Dumping,Credential Access,APT41|Soft Cell|TEMP.Veles|APT33|Leviathan|APT39|Stolen Pencil|APT32|Night Dragon|Dragonfly 2.0|Leafminer|Lazarus Group|Magic Hound|APT37|MuddyWater|PLATINUM|FIN8|Sowbug|BRONZE BUTLER|FIN5|OilRig|menuPass|Strider|Patchwork|Stealth Falcon|Suckfly|FIN6|Poseidon Group|Threat Group-3390|APT3|Molerats|APT28|APT1|Ke3chang|Cleaver|Axiom T1002,Data Compressed,Exfiltration,APT41|Soft Cell|Gallmaker|APT33|APT32|APT39|MuddyWater|Honeybee|Magic Hound|APT28|Dragonfly 2.0|FIN8|BRONZE BUTLER|CopyKittens|Sowbug|APT3|menuPass|FIN6|Lazarus Group|Threat Group-3390|APT1|Ke3chang T1001,Data Obfuscation,Command And Control,APT28|Axiom diff --git a/package/default/analytic_stories.conf b/package/default/analytic_stories.conf index 73a618e0be..c53d061c85 100644 --- a/package/default/analytic_stories.conf +++ b/package/default/analytic_stories.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-25T08:45:24 UTC +# On Date: 2020-05-25T14:45:46 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -16,7 +16,7 @@ version = 1 reference = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] detection_searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] support_searches = ["ESCU - Previously Seen AWS Cross Account Activity"] data_models = [] providing_technologies = none @@ -34,8 +34,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen EC2 AMIs", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +support_searches = ["ESCU - Previously Seen EC2 Launches By User", "ESCU - Previously Seen AWS Regions", "ESCU - Previously Seen EC2 Instance Types", "ESCU - Previously Seen EC2 AMIs"] data_models = [] providing_technologies = none description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -53,7 +53,7 @@ version = 2 reference = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] detection_searches = ["ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11", "CIS 12"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of Network ACL Activity by ARN"] data_models = [] providing_technologies = none @@ -69,7 +69,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] +investigative_searches = ["ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City"] support_searches = ["ESCU - Previously Seen AWS Provisioning Activity Sources"] data_models = [] providing_technologies = none @@ -86,8 +86,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] detection_searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule"] mappings = {"cis20": ["CIS 1", "CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "ID.AM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] -support_searches = ["ESCU - Create a list of approved AWS service accounts", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Previously seen API call per user roles in CloudTrail", "ESCU - Baseline of API Calls per User ARN"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] +support_searches = ["ESCU - Baseline of API Calls per User ARN", "ESCU - Baseline of Security Group Activity by ARN", "ESCU - Previously seen API call per user roles in CloudTrail", "ESCU - Create a list of approved AWS service accounts"] data_models = [] providing_technologies = none description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. @@ -102,10 +102,10 @@ creation_date = 2017-09-06 modification_date = 2017-09-06 id = 8892a655-6205-55f7-abba-06460e38c8ae version = 1 -reference = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] +reference = [] detection_searches = ["ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078", "T1136"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change"] providing_technologies = none @@ -121,7 +121,7 @@ version = 1 reference = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] detection_searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule"] mappings = {"cis20": ["CIS 12", "CIS 18", "CIS 3", "CIS 4"], "kill_chain_phases": ["Actions on Objectives", "Delivery", "Exploitation"], "mitre_attack": ["T1082"], "nist": ["DE.AE", "DE.CM", "ID.RA", "PR.IP", "PR.MA", "PR.PT", "RS.MI"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -150,7 +150,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] detection_searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule"] mappings = {"cis20": ["CIS 1"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] support_searches = ["ESCU - Count of assets by category"] data_models = ["Network_Sessions"] providing_technologies = none @@ -166,7 +166,7 @@ version = 1 reference = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] detection_searches = ["ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor Web Traffic For Brand Abuse - Rule"] mappings = {"cis20": ["CIS 7"], "kill_chain_phases": ["Actions on Objectives", "Delivery"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "Network_Resolution", "Web"] providing_technologies = none @@ -184,8 +184,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Compute Instance Types", "ESCU - Previously Seen Cloud Regions"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +support_searches = ["ESCU - Previously Seen Cloud Compute Images", "ESCU - Previously Seen Cloud Regions", "ESCU - Previously Seen Cloud Compute Creations By User", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen Cloud Compute Instance Types"] data_models = ["Cloud_Infrastructure"] providing_technologies = none description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. @@ -203,7 +203,7 @@ version = 1 reference = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] detection_searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule"] mappings = {"cis20": ["CIS 4", "CIS 8"], "kill_chain_phases": ["Command and Control"], "nist": ["DE.DP", "PR.PT"]} -investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = [] providing_technologies = none @@ -221,7 +221,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] detection_searches = ["ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule"] mappings = {"cis20": ["CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1043", "T1074", "T1114"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -239,8 +239,8 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 1", "CIS 11", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048", "T1095"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of blocked outbound traffic from AWS"] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS", "ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. @@ -289,7 +289,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] detection_searches = ["ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1003", "T1064", "T1086"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts"] +investigative_searches = ["ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -307,8 +307,8 @@ version = 2 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] detection_searches = ["ESCU - Create local admin accounts using net exe - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 2", "CIS 3", "CIS 5", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1043", "T1050", "T1053", "T1059", "T1064", "T1078", "T1086", "T1089", "T1103", "T1112", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.AT", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. @@ -326,7 +326,7 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] detection_searches = ["ESCU - Large Volume of DNS ANY Queries - Rule"] mappings = {"cis20": ["CIS 12"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -367,7 +367,7 @@ version = 1 reference = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] detection_searches = ["ESCU - Detect USB device insertion - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043"], "nist": ["DE.AE", "DE.CM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Change_Analysis", "Network_Resolution"] providing_technologies = none @@ -383,8 +383,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] detection_searches = ["ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1089", "T1112"], "nist": ["DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. @@ -399,7 +399,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule"] mappings = {"cis20": ["CIS 13", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1041"], "nist": ["DE.CM", "DE.DP", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Web"] providing_technologies = none @@ -415,8 +415,8 @@ version = 1 reference = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 2", "CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Exploitation", "Installation"], "mitre_attack": ["T1043", "T1059", "T1072", "T1087", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] -support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security", "ESCU - Baseline of SMB Traffic - MLTK"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Email", "Endpoint", "Network_Traffic"] providing_technologies = none description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. @@ -433,8 +433,8 @@ version = 2 reference = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] detection_searches = ["ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Suspicious File Write - Rule"] mappings = {"cis20": ["CIS 12", "CIS 16", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1059", "T1064", "T1076"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of DNS Query Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint", "Network_Resolution", "Network_Traffic"] providing_technologies = none description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. @@ -452,7 +452,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8"], "kill_chain_phases": ["Command and Control"], "mitre_attack": ["T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.AC", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution"] providing_technologies = none @@ -468,7 +468,7 @@ version = 1 reference = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] detection_searches = ["ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery", "Reconnaissance"], "mitre_attack": ["T1082"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info"] support_searches = [] data_models = ["Web"] providing_technologies = none @@ -498,7 +498,7 @@ version = 1 reference = ["https://github.com/splunk/cloud-datamodel-security-research"] detection_searches = ["ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - GCP Kubernetes cluster scan detection - Rule"] mappings = {"kill_chain_phases": ["Reconnaissance"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -514,7 +514,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] detection_searches = ["ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Schtasks scheduling job on remote system - Rule"] mappings = {"cis20": ["CIS 16", "CIS 3", "CIS 9"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1053", "T1075", "T1076"], "nist": ["DE.AE", "PR.AC", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none @@ -534,7 +534,7 @@ version = 4 reference = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1064", "T1086"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -559,7 +559,7 @@ version = 1 reference = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] detection_searches = ["ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Unsuccessful Netbackup backups - Rule"] mappings = {"cis20": ["CIS 10"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +investigative_searches = ["ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host"] support_searches = ["ESCU - Monitor Successful Backups", "ESCU - Monitor Unsuccessful Backups"] data_models = [] providing_technologies = none @@ -575,7 +575,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] detection_searches = ["ESCU - Prohibited Software On Endpoint - Rule"] mappings = {"cis20": ["CIS 2"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint"] providing_technologies = none @@ -610,8 +610,8 @@ version = 1 reference = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] detection_searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1059", "T1089"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of SMB Traffic - MLTK"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. @@ -627,8 +627,8 @@ version = 2 reference = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1031", "T1050", "T1059", "T1064", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Previously Seen Running Windows Services"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] +support_searches = ["ESCU - Previously Seen Running Windows Services", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. @@ -670,8 +670,8 @@ version = 1 reference = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] detection_searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 7", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1059", "T1064", "T1086", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. @@ -713,7 +713,7 @@ version = 1 reference = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] detection_searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule"] mappings = {"cis20": ["CIS 12", "CIS 13", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Resolution", "Network_Traffic"] providing_technologies = none @@ -729,8 +729,8 @@ version = 1 reference = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] detection_searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 3", "CIS 5", "CIS 6", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery"], "mitre_attack": ["T1036", "T1043", "T1047", "T1048", "T1053", "T1070", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] -support_searches = ["ESCU - Baseline of SMB Traffic - MLTK", "ESCU - Baseline of Command Line Length - MLTK"] +investigative_searches = ["ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Baseline of SMB Traffic - MLTK"] data_models = ["Endpoint", "Network_Traffic"] providing_technologies = none description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. @@ -745,7 +745,7 @@ version = 1 reference = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] detection_searches = ["ESCU - Detect New Login Attempts to Routers - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Authentication"] providing_technologies = none @@ -779,7 +779,7 @@ version = 1 reference = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] detection_searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Spike in File Writes - Rule"] mappings = {"cis20": ["CIS 10", "CIS 12", "CIS 16", "CIS 18", "CIS 2", "CIS 3", "CIS 4", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Delivery", "Installation", "Reconnaissance"], "mitre_attack": ["T1059", "T1076", "T1082"], "nist": ["DE.AE", "DE.CM", "ID.AM", "ID.RA", "PR.AC", "PR.DS", "PR.IP", "PR.MA", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Add Prohibited Processes to Enterprise Security"] data_models = ["Endpoint", "Network_Traffic", "Web"] providing_technologies = none @@ -800,7 +800,7 @@ version = 1 reference = ["https://meltdownattack.com/"] detection_searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule"] mappings = {"cis20": ["CIS 4"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Systems Ready for Spectre-Meltdown Windows Patch"] data_models = ["Vulnerabilities"] providing_technologies = none @@ -841,7 +841,7 @@ version = 1 reference = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] detection_searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule"] mappings = {"cis20": ["CIS 18"], "kill_chain_phases": ["Delivery"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info"] support_searches = [] data_models = [] providing_technologies = none @@ -860,8 +860,8 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP", "ID.AM"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] -support_searches = ["ESCU - Previously Seen EC2 Launches By User", "ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen AWS Regions"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] +support_searches = ["ESCU - Baseline of Excessive AWS Instances Terminated by User - MLTK", "ESCU - Previously Seen AWS Regions", "ESCU - Baseline of Excessive AWS Instances Launched by User - MLTK", "ESCU - Previously Seen EC2 Launches By User"] data_models = [] providing_technologies = none description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. @@ -877,7 +877,7 @@ reference = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integr detection_searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule"] mappings = {"cis20": ["CIS 16"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.AE", "DE.DP"]} investigative_searches = ["ESCU - AWS Investigate User Activities By ARN"] -support_searches = ["ESCU - Previously seen users in CloudTrail", "ESCU - Update previously seen users in CloudTrail"] +support_searches = ["ESCU - Update previously seen users in CloudTrail", "ESCU - Previously seen users in CloudTrail"] data_models = [] providing_technologies = none description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. @@ -892,7 +892,7 @@ version = 2 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] detection_searches = ["ESCU - Detect New Open S3 buckets - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule"] mappings = {"cis20": ["CIS 13", "CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["DE.CM", "DE.DP", "PR.AC", "PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName"] support_searches = ["ESCU - Baseline of S3 Bucket deletion activity by ARN", "ESCU - Previously seen S3 bucket access by remote IP"] data_models = [] providing_technologies = none @@ -910,7 +910,7 @@ version = 1 reference = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] detection_searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule"] mappings = {"cis20": ["CIS 11"], "kill_chain_phases": ["Command and Control"], "nist": ["PR.AC"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Baseline of blocked outbound traffic from AWS"] data_models = [] providing_technologies = none @@ -929,8 +929,8 @@ version = 2 reference = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Exploitation"], "mitre_attack": ["T1036", "T1059", "T1064"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. @@ -945,7 +945,7 @@ version = 1 reference = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] detection_searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Excessive DNS Failures - Rule"] mappings = {"cis20": ["CIS 1", "CIS 12", "CIS 13", "CIS 3", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Command and Control"], "mitre_attack": ["T1043", "T1048"], "nist": ["DE.AE", "DE.CM", "ID.AM", "PR.DS", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Baseline of DNS Query Length - MLTK"] data_models = ["Network_Resolution"] providing_technologies = none @@ -961,7 +961,7 @@ version = 1 reference = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] detection_searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule"] mappings = {"cis20": ["CIS 12", "CIS 3", "CIS 7"], "kill_chain_phases": ["Delivery"], "nist": ["DE.AE", "PR.IP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - DNSTwist Domain Names"] data_models = ["Email", "UEBA"] providing_technologies = none @@ -981,8 +981,8 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] detection_searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1059", "T1103", "T1131"], "nist": ["DE.AE", "DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] -support_searches = ["ESCU - Previously seen command line arguments", "ESCU - Baseline of Command Line Length - MLTK"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] +support_searches = ["ESCU - Baseline of Command Line Length - MLTK", "ESCU - Previously seen command line arguments"] data_models = ["Endpoint"] providing_technologies = none description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. @@ -999,7 +999,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] detection_searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule"] mappings = {"cis20": ["CIS 16"], "mitre_attack": ["T1078"], "nist": ["DE.CM"]} -investigative_searches = ["ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] +investigative_searches = ["ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app"] support_searches = [] data_models = [] providing_technologies = none @@ -1017,7 +1017,7 @@ version = 2 reference = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] detection_searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1047", "T1084"], "nist": ["PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1035,7 +1035,7 @@ version = 1 reference = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1015", "T1042", "T1103", "T1112", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1053,7 +1053,7 @@ version = 1 reference = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] detection_searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule"] mappings = {"cis20": ["CIS 1"], "nist": ["ID.AM"]} -investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] support_searches = ["ESCU - Previously Seen EC2 Modifications By User"] data_models = [] providing_technologies = none @@ -1070,7 +1070,7 @@ version = 2 reference = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] detection_searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Command and Control", "Installation"], "mitre_attack": ["T1015", "T1036", "T1085"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Baseline of Command Line Length - MLTK"] data_models = ["Endpoint"] providing_technologies = none @@ -1088,7 +1088,7 @@ version = 1 reference = ["https://www.monkey.org/~dugsong/dsniff/"] detection_searches = ["ESCU - Protocols passing authentication in cleartext - Rule"] mappings = {"cis20": ["CIS 14"], "kill_chain_phases": ["Actions on Objectives"], "nist": ["PR.DS"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Network_Traffic"] providing_technologies = none @@ -1104,7 +1104,7 @@ version = 1 reference = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] detection_searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule"] mappings = {"cis20": ["CIS 16", "CIS 6"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1078", "T1136"], "nist": ["DE.AE", "DE.CM", "DE.DP"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Web Session Information via session id"] support_searches = [] data_models = [] providing_technologies = none @@ -1125,7 +1125,7 @@ version = 1 reference = ["https://attack.mitre.org/wiki/Defense_Evasion"] detection_searches = ["ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule"] mappings = {"cis20": ["CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1089", "T1112"], "nist": ["DE.CM", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1141,7 +1141,7 @@ version = 1 reference = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] detection_searches = ["ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule"] mappings = {"cis20": ["CIS 3", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1042"], "nist": ["DE.CM", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1161,7 +1161,7 @@ version = 2 reference = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] detection_searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Windows Event Log Cleared - Rule"] mappings = {"cis20": ["CIS 10", "CIS 3", "CIS 5", "CIS 6", "CIS 8"], "kill_chain_phases": ["Actions on Objectives"], "mitre_attack": ["T1070"], "nist": ["DE.AE", "DE.CM", "DE.DP", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1178,7 +1178,7 @@ version = 2 reference = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] detection_searches = ["ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1053", "T1089", "T1103", "T1131", "T1138"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1194,7 +1194,7 @@ version = 2 reference = ["https://attack.mitre.org/tactics/TA0004/"] detection_searches = ["ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule"] mappings = {"cis20": ["CIS 2", "CIS 8"], "kill_chain_phases": ["Actions on Objectives", "Exploitation"], "mitre_attack": ["T1015", "T1068"], "nist": ["DE.CM", "ID.AM", "PR.DS", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] support_searches = [] data_models = ["Endpoint"] providing_technologies = none @@ -1210,7 +1210,7 @@ version = 3 reference = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] detection_searches = ["ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule"] mappings = {"cis20": ["CIS 3", "CIS 5", "CIS 8", "CIS 9"], "kill_chain_phases": ["Actions on Objectives", "Installation"], "mitre_attack": ["T1031", "T1050", "T1089"], "nist": ["DE.AE", "DE.CM", "PR.AC", "PR.AT", "PR.IP", "PR.PT"]} -investigative_searches = ["ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +investigative_searches = ["ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] support_searches = ["ESCU - Previously Seen Running Windows Services"] data_models = ["Endpoint"] providing_technologies = none diff --git a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml index 3f5dff58ab..02d2dff20d 100644 --- a/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml +++ b/package/default/data/ui/panels/workbench_panel_investigate_pass_the_ticket_attempts.xml @@ -1,7 +1,7 @@
- `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 + `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user diff --git a/package/default/es_investigations.conf b/package/default/es_investigations.conf index 173e425e83..8811fa4b84 100644 --- a/package/default/es_investigations.conf +++ b/package/default/es_investigations.conf @@ -3,79 +3,79 @@ label = AWS Cross Account Activity description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid", "panel://workbench_panel_aws_investigate_user_activities_by_source_user", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_source_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_aws_investigate_user_activities_by_accesskeyid"] [panel_group://workbench_panel_group_aws_cryptomining] label = AWS Cryptomining description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_aws_network_acl_activity] label = AWS Network ACL Activity description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_aws_suspicious_provisioning_activities] label = AWS Suspicious Provisioning Activities description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. disabled = 0 -panels = ["panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_country", "panel://workbench_panel_get_all_aws_activity_from_city", "panel://workbench_panel_get_all_aws_activity_from_region"] +panels = ["panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_all_aws_activity_from_region", "panel://workbench_panel_get_all_aws_activity_from_country", "panel://workbench_panel_get_all_aws_activity_from_city"] [panel_group://workbench_panel_group_aws_user_monitoring] label = AWS User Monitoring description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_investigate_aws_user_activities_by_user_field", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_aws_user_activities_by_user_field"] [panel_group://workbench_panel_group_account_monitoring_and_controls] label = Account Monitoring and Controls description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_logon_rights_modifications_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_logon_rights_modifications_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_apache_struts_vulnerability] label = Apache Struts Vulnerability description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_suspicious_strings_in_http_header", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_posts_from_src", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_asset_tracking] label = Asset Tracking description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_first_occurrence_and_last_occurrence_of_a_mac_address"] [panel_group://workbench_panel_group_brand_monitoring] label = Brand Monitoring description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_email_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_cloud_cryptomining] label = Cloud Cryptomining description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_investigate_user_activities_in_single_cloud_region", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_user_activities_in_all_cloud_regions", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_cloud_compute_instance_activities", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_coldroot_macos_rat] label = ColdRoot MacOS RAT description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. disabled = 0 -panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_collection_and_staging] label = Collection and Staging description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_command_and_control] label = Command and Control description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_common_phishing_frameworks] label = Common Phishing Frameworks @@ -93,19 +93,19 @@ panels = ["panel://workbench_panel_investigate_aws_ecr_container_listing_activit label = Credential Dumping description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. disabled = 0 -panels = ["panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_pass_the_ticket_attempts", "panel://workbench_panel_investigate_pass_the_hash_attempts"] +panels = ["panel://workbench_panel_investigate_failed_logins_for_multiple_destinations", "panel://workbench_panel_investigate_previous_unseen_user", "panel://workbench_panel_investigate_pass_the_hash_attempts", "panel://workbench_panel_investigate_pass_the_ticket_attempts"] [panel_group://workbench_panel_group_dhs_report_ta18_074a] label = DHS Report TA18-074A description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_registry_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_process_file_activity", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_dns_amplification_attacks] label = DNS Amplification Attacks description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] [panel_group://workbench_panel_group_dns_hijacking] label = DNS Hijacking @@ -117,73 +117,73 @@ panels = ["panel://workbench_panel_get_dns_server_history_for_a_host"] label = Data Protection description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_disabling_security_tools] label = Disabling Security Tools description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_dynamic_dns] label = Dynamic DNS description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_emotet_malware__dhs_report_ta18_201a_] label = Emotet Malware DHS Report TA18-201A description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_hidden_cobra_malware] label = Hidden Cobra Malware description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_host_redirection] label = Host Redirection description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_jboss_vulnerability] label = JBoss Vulnerability description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_kubernetes_scanning_activity] label = Kubernetes Scanning Activity description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_gcp_kubernetes_activity_by_src_ip", "panel://workbench_panel_amazon_eks_kubernetes_activity_by_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_lateral_movement] label = Lateral Movement description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_malicious_powershell] label = Malicious PowerShell description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_monitor_backup_solution] label = Monitor Backup Solution description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. disabled = 0 -panels = ["panel://workbench_panel_all_backup_logs_for_host", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint"] +panels = ["panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_all_backup_logs_for_host"] [panel_group://workbench_panel_group_monitor_for_unauthorized_software] label = Monitor for Unauthorized Software description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_monitor_for_updates] label = Monitor for Updates @@ -195,13 +195,13 @@ panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_g label = Netsh Abuse description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_orangeworm_attack_group] label = Orangeworm Attack Group description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_phishing_payloads] label = Phishing Payloads @@ -213,25 +213,25 @@ panels = ["panel://workbench_panel_get_parent_process_info"] label = Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_prohibited_traffic_allowed_or_protocol_mismatch] label = Prohibited Traffic Allowed or Protocol Mismatch description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_ransomware] label = Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_router_and_infrastructure_security] label = Router and Infrastructure Security description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_sql_injection] label = SQL Injection @@ -243,13 +243,13 @@ panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_g label = SamSam Ransomware description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_investigate_successful_remote_desktop_authentications", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_update_logs_for_endpoint", "panel://workbench_panel_get_backup_logs_for_endpoint", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_spectre_and_meltdown_vulnerabilities] label = Spectre And Meltdown Vulnerabilities description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_splunk_enterprise_vulnerability] label = Splunk Enterprise Vulnerability @@ -261,13 +261,13 @@ panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_g label = Splunk Enterprise Vulnerability CVE-2018-11409 description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_investigate_network_traffic_from_src_ip", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_investigate_web_activity_from_src_ip", "panel://workbench_panel_get_notable_info"] [panel_group://workbench_panel_group_suspicious_aws_ec2_activities] label = Suspicious AWS EC2 Activities description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_launch_details"] +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_ec2_launch_details"] [panel_group://workbench_panel_group_suspicious_aws_login_activities] label = Suspicious AWS Login Activities @@ -279,115 +279,115 @@ panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn"] label = Suspicious AWS S3 Activities description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_investigate_aws_activities_via_region_name", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_aws_s3_bucket_details_via_bucketname"] [panel_group://workbench_panel_group_suspicious_aws_traffic] label = Suspicious AWS Traffic description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_aws_network_acl_details_from_id", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_all_aws_activity_from_ip_address", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_aws_network_interface_details_via_resourceid", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_suspicious_command_line_executions] label = Suspicious Command-Line Executions description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_suspicious_dns_traffic] label = Suspicious DNS Traffic description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_dns_server_history_for_a_host", "panel://workbench_panel_get_process_responsible_for_the_dns_traffic", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_dns_traffic_ratio", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_suspicious_emails] label = Suspicious Emails description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_email_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_email_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_suspicious_mshta_activity] label = Suspicious MSHTA Activity description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_suspicious_okta_activity] label = Suspicious Okta Activity description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. disabled = 0 -panels = ["panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_okta_activity_by_app", "panel://workbench_panel_investigate_user_activities_in_okta"] +panels = ["panel://workbench_panel_investigate_user_activities_in_okta", "panel://workbench_panel_investigate_okta_activity_by_ip_address", "panel://workbench_panel_investigate_okta_activity_by_app"] [panel_group://workbench_panel_group_suspicious_wmi_use] label = Suspicious WMI Use description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_sysmon_wmi_activity_for_host", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_suspicious_windows_registry_activities] label = Suspicious Windows Registry Activities description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_unusual_aws_ec2_modifications] label = Unusual AWS EC2 Modifications description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. disabled = 0 -panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_ec2_instance_details_by_instanceid", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_aws_investigate_user_activities_by_arn", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_ec2_instance_details_by_instanceid"] [panel_group://workbench_panel_group_unusual_processes] label = Unusual Processes description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_use_of_cleartext_protocols] label = Use of Cleartext Protocols description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_process_information_for_port_activity", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_web_fraud_detection] label = Web Fraud Detection description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_web_session_information_via_session_id", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_emails_from_specific_sender", "panel://workbench_panel_get_web_session_information_via_session_id"] [panel_group://workbench_panel_group_windows_defense_evasion_tactics] label = Windows Defense Evasion Tactics description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_windows_file_extension_and_association_abuse] label = Windows File Extension and Association Abuse description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_windows_log_manipulation] label = Windows Log Manipulation description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_vulnerability_logs_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] [panel_group://workbench_panel_group_windows_persistence_techniques] label = Windows Persistence Techniques description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_windows_privilege_escalation] label = Windows Privilege Escalation description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_registry_activities", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_investigate_web_activity_from_host", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_registry_activities"] [panel_group://workbench_panel_group_windows_service_abuse] label = Windows Service Abuse description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. disabled = 0 -panels = ["panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_user_information_from_identity_table", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_notable_history"] +panels = ["panel://workbench_panel_get_parent_process_info", "panel://workbench_panel_get_notable_history", "panel://workbench_panel_get_process_info", "panel://workbench_panel_get_risk_modifiers_for_user", "panel://workbench_panel_get_risk_modifiers_for_endpoint", "panel://workbench_panel_get_notable_info", "panel://workbench_panel_get_authentication_logs_for_endpoint", "panel://workbench_panel_get_user_information_from_identity_table"] diff --git a/package/default/macros.conf b/package/default/macros.conf index 16b0ab22c0..53e8b92870 100644 --- a/package/default/macros.conf +++ b/package/default/macros.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-25T08:45:24 UTC +# On Date: 2020-05-25T14:45:46 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/savedsearches.conf b/package/default/savedsearches.conf index 9dbfbdfd8a..f402d27b79 100644 --- a/package/default/savedsearches.conf +++ b/package/default/savedsearches.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-25T08:45:24 UTC +# On Date: 2020-05-25T14:45:46 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -605,7 +605,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)` | `attempt_to_add_certificate_to_untrusted_store_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=certutil.exe (Processes.process=*-addstore* AND Processes.process=*disallowed* ) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` |`security_content_ctime(lastTime)` | `attempt_to_add_certificate_to_untrusted_store_filter` [ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule] action.escu = 0 @@ -645,7 +645,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Registry where Registry.registry_path=*Software\\Microsoft\\Powershell\\1\\ShellIds\\Microsoft.PowerShell* Registry.registry_key_name=ExecutionPolicy (Registry.registry_value_name=Unrestricted OR Registry.registry_value_name=Bypass) by Registry.registry_path Registry.registry_key_name Registry.registry_value_name Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `attempt_to_set_default_powershell_execution_policy_to_unrestricted_or_bypass_filter` [ESCU - Attempt To Stop Security Service - Rule] action.escu = 0 @@ -824,7 +824,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Clients Connecting to Multiple DNS Servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Host Redirection", "Suspicious DNS Traffic", "DNS Hijacking"] +action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1091,7 +1091,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)`|`ransomware_notes`| `common_ransomware_notes_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Filesystem.user) as user values(Filesystem.dest) as dest values(Filesystem.file_path) as file_path from datamodel=Endpoint.Filesystem by Filesystem.file_name | `drop_dm_object_name(Filesystem)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `ransomware_notes` | `common_ransomware_notes_filter` [ESCU - Create Remote Thread into LSASS - Rule] action.escu = 0 @@ -1131,7 +1131,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as firstTime max(_time) as lastTime by Computer, EventCode, TargetImage, TargetProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`create_remote_thread_into_lsass_filter` +search = `sysmon` EventID=8 TargetImage=*lsass.exe | stats count min(_time) as firstTime max(_time) as lastTime by Computer, EventCode, TargetImage, TargetProcessId | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `create_remote_thread_into_lsass_filter` [ESCU - Create local admin accounts using net exe - Rule] action.escu = 0 @@ -1171,7 +1171,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*localgroup* OR process=*/add* OR process=*user*) |`create_local_admin_accounts_using_net_exe_filter` +search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processes.process_name=net.exe OR Processes.process_name=net1.exe) AND (Processes.process=*localgroup* OR Processes.process=*/add* OR Processes.process=*user*) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`create_local_admin_accounts_using_net_exe_filter` [ESCU - Create or delete windows shares using net exe - Rule] action.escu = 0 @@ -1211,7 +1211,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search (process=*share* AND process=*delete*) | `create_or_delete_windows_shares_using_net_exe_filter` +search = | tstats `security_content_summariesonly` count values(Processes.user) as user values(Processes.parent_process) as parent_process min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where (Processs.process_name=net.exe OR Processes.process_name=net1.exe) by Processes.process Processes.process_name Processes.dest | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | search process=*share* | `create_or_delete_windows_shares_using_net_exe_filter` [ESCU - Creation of Shadow Copy - Rule] action.escu = 0 @@ -1394,7 +1394,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length Outliers - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] +action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1434,7 +1434,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Length With High Standard Deviation - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Hidden Cobra Malware", "Suspicious DNS Traffic"] +action.escu.analytic_story = ["Hidden Cobra Malware", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1473,7 +1473,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Host Redirection", "Suspicious DNS Traffic", "DNS Hijacking"] +action.escu.analytic_story = ["DNS Hijacking", "Command and Control", "Suspicious DNS Traffic", "Host Redirection"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -1557,7 +1557,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Deleting Shadow Copies - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Windows Log Manipulation", "Ransomware"] +action.escu.analytic_story = ["Windows Log Manipulation", "SamSam Ransomware", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2056,7 +2056,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Long DNS TXT Record Response - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] +action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2745,7 +2745,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "AWS Network ACL Activity", "Suspicious AWS Traffic"] +action.escu.analytic_story = ["AWS Network ACL Activity", "Suspicious AWS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2863,7 +2863,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Suspicious Command-Line Executions"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2903,7 +2903,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "JBoss Vulnerability"] +action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2949,7 +2949,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect hosts connecting to dynamic domain providers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Suspicious DNS Traffic", "DNS Hijacking", "Dynamic DNS", "Command and Control", "Data Protection"] +action.escu.analytic_story = ["Data Protection", "Prohibited Traffic Allowed or Protocol Mismatch", "DNS Hijacking", "Suspicious DNS Traffic", "Dynamic DNS", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -2988,7 +2988,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detect malicious requests to exploit JBoss servers - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "JBoss Vulnerability"] +action.escu.analytic_story = ["JBoss Vulnerability", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3230,7 +3230,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Detection of DNS Tunnels - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Data Protection", "Suspicious DNS Traffic"] +action.escu.analytic_story = ["Data Protection", "Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3310,7 +3310,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Disabling Remote User Account Control - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Defense Evasion Tactics"] +action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3590,7 +3590,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Email Attachments With Lots Of Spaces - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Suspicious Emails"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3708,7 +3708,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Excessive DNS Failures - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Suspicious DNS Traffic"] +action.escu.analytic_story = ["Suspicious DNS Traffic", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -3947,7 +3947,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - First time seen command line argument - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Hidden Cobra Malware", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Orangeworm Attack Group"] +action.escu.analytic_story = ["DHS Report TA18-074A", "Suspicious Command-Line Executions", "Orangeworm Attack Group", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Hidden Cobra Malware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4065,7 +4065,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Hiding Files And Directories With Attrib exe - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Defense Evasion Tactics"] +action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4073,7 +4073,7 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Hiding Files And Directories With Attrib exe - Rule schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = ['user'] +action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = Attackers leverage an existing Windows binary, attrib.exe, to mark specific as hidden by using specific flags so that the victim does not see the file. The search looks for specific command-line arguments to detect the use of attrib.exe to hide files. action.notable.param.rule_title = Hiding Files And Directories With Attrib exe action.notable.param.security_domain = endpoint @@ -4088,7 +4088,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `hiding_files_and_directories_with_attrib_exe_filter` +search = | tstats `security_content_summariesonly` count min(_time) values(Processes.process) as process max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.process_name=attrib.exe (Processes.process=*+h*) by Processes.parent_process Processes.process_name Processes.user Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`|`security_content_ctime(lastTime)`| `hiding_files_and_directories_with_attrib_exe_filter` [ESCU - Hosts receiving high volume of network traffic from email server - Rule] action.escu = 0 @@ -4262,7 +4262,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Malicious PowerShell"] +action.escu.analytic_story = ["Malicious PowerShell", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4501,7 +4501,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Monitor Email For Brand Abuse - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails", "Brand Monitoring"] +action.escu.analytic_story = ["Brand Monitoring", "Suspicious Emails"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -4761,7 +4761,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip |`okta_account_lockout_events_filter` +search = `okta` displayMessage="Max sign in attempts exceeded" | rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city | table _time, user, country, state, city, src_ip | `okta_account_lockout_events_filter` [ESCU - Okta Failed SSO Attempts - Rule] action.escu = 0 @@ -4800,7 +4800,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`|`okta_failed_sso_attempts_filter` +search = `okta` displayMessage="User attempted unauthorized access to app" | stats min(_time) as firstTime max(_time) as lastTime values(app) as Apps count by user, result ,displayMessage, src_ip | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `okta_failed_sso_attempts_filter` [ESCU - Okta User Logins From Multiple Cities - Rule] action.escu = 0 @@ -4840,7 +4840,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `okta` displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` |`okta_user_logins_from_multiple_cities_filter`| search locations > 1 +search = `okta` displayMessage="User login to Okta" client.geographicalContext.city!=null | stats min(_time) as firstTime max(_time) as lastTime dc(client.geographicalContext.city) as locations values(client.geographicalContext.city) as cities values(client.geographicalContext.state) as states by user | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `okta_user_logins_from_multiple_cities_filter` | search locations > 1 [ESCU - Open Redirect in Splunk Web - Rule] action.escu = 0 @@ -5134,7 +5134,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Network Traffic Allowed - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Ransomware", "Prohibited Traffic Allowed or Protocol Mismatch"] +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5173,7 +5173,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Prohibited Software On Endpoint - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["SamSam Ransomware", "Emotet Malware DHS Report TA18-201A ", "Monitor for Unauthorized Software"] +action.escu.analytic_story = ["Monitor for Unauthorized Software", "Emotet Malware DHS Report TA18-201A ", "SamSam Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5213,7 +5213,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Protocol or Port Mismatch - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Prohibited Traffic Allowed or Protocol Mismatch"] +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5292,7 +5292,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Service Abuse"] +action.escu.analytic_story = ["Windows Service Abuse", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5300,7 +5300,7 @@ action.correlationsearch.enabled = 1 action.correlationsearch.label = ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule schedule_window = auto action.notable = 1 -action.notable.param.nes_fields = ['dest'] +action.notable.param.nes_fields = ['user', 'dest'] action.notable.param.rule_description = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. action.notable.param.rule_title = Reg exe Manipulating Windows Services Registry Keys action.notable.param.security_domain = endpoint @@ -5315,7 +5315,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path] | `reg_exe_manipulating_windows_services_registry_keys_filter` +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(Processes.process_name) as process_name values(Processes.parent_process_name) as parent_process_name values(Processes.user) as user FROM datamodel=Endpoint.Processes where Processes.process_name = reg.exe by Processes.process_id Processes.dest | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | join [| tstats `security_content_summariesonly` values(Registry.registry_path) as registry_path count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\services\\*" by Registry.process_id Registry.dest | `drop_dm_object_name("Registry")` | table process_id dest registry_path] | `reg_exe_manipulating_windows_services_registry_keys_filter` [ESCU - Reg exe used to hide files directories via registry keys - Rule] action.escu = 0 @@ -5332,7 +5332,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Reg exe used to hide files directories via registry keys - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Windows Defense Evasion Tactics"] +action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5372,7 +5372,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Registry Keys Used For Persistence - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A ", "Ransomware", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Suspicious MSHTA Activity"] +action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Suspicious MSHTA Activity", "DHS Report TA18-074A", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware", "Windows Persistence Techniques", "Emotet Malware DHS Report TA18-201A "] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5651,7 +5651,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Remote Registry Key modifications - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Windows Registry Activities", "Windows Persistence Techniques", "Windows Defense Evasion Tactics"] +action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Suspicious Windows Registry Activities", "Windows Persistence Techniques"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5771,7 +5771,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "DHS Report TA18-074A"] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Ransomware", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5814,7 +5814,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - SMB Traffic Spike - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "DHS Report TA18-074A"] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Hidden Cobra Malware", "Ransomware", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -5934,7 +5934,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Sc exe Manipulating Windows Services - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Windows Persistence Techniques", "Windows Service Abuse", "Disabling Security Tools", "DHS Report TA18-074A", "Orangeworm Attack Group"] +action.escu.analytic_story = ["Windows Service Abuse", "DHS Report TA18-074A", "Orangeworm Attack Group", "Windows Persistence Techniques", "Disabling Security Tools"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6534,7 +6534,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Email Attachment Extensions - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Emails", "Emotet Malware DHS Report TA18-201A "] +action.escu.analytic_story = ["Emotet Malware DHS Report TA18-201A ", "Suspicious Emails"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6693,7 +6693,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Suspicious Reg exe Process - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Disabling Security Tools", "Windows Defense Evasion Tactics", "DHS Report TA18-074A"] +action.escu.analytic_story = ["Windows Defense Evasion Tactics", "Disabling Security Tools", "DHS Report TA18-074A"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6852,7 +6852,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - System Processes Run From Unexpected Locations - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Suspicious Command-Line Executions", "Ransomware", "Unusual Processes"] +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Unusual Processes", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -6892,7 +6892,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - TOR Traffic - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Command and Control", "Ransomware", "Prohibited Traffic Allowed or Protocol Mismatch"] +action.escu.analytic_story = ["Prohibited Traffic Allowed or Protocol Mismatch", "Ransomware", "Command and Control"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -7074,7 +7074,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `unsigned_image_loaded_by_lsass_filter` +search = `sysmon` EventID=7 Image=*lsass.exe Signed=false | stats count min(_time) as firstTime max(_time) as lastTime by Computer, Image, ImageLoaded, Signed, SHA1 | rename Computer as dest | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)` | `unsigned_image_loaded_by_LSAS`unsigned_image_loaded_by_lsass_filter` [ESCU - Unsuccessful Netbackup backups - Rule] action.escu = 0 @@ -7130,7 +7130,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Suspicious Command-Line Executions", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Unusual Processes", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -7153,7 +7153,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process| `unusually_long_command_line_filter` eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost) +search = | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Processes by Processes.user Processes.dest Processes.process_name Processes.process | `drop_dm_object_name("Processes")` | `security_content_ctime(firstTime)`| `security_content_ctime(lastTime)`| eval processlen=len(process) | eventstats stdev(processlen) as stdev, avg(processlen) as avg by dest | stats max(processlen) as maxlen, values(stdev) as stdevperhost, values(avg) as avgperhost by dest, user, process_name, process | `unusually_long_command_line_filter` |eval threshold = 10 | where maxlen > ((threshold*stdevperhost) + avgperhost) [ESCU - Unusually Long Command Line - MLTK - Rule] action.escu = 0 @@ -7170,7 +7170,7 @@ action.escu.confidence = high action.escu.full_search_name = ESCU - Unusually Long Command Line - MLTK - Rule action.escu.search_type = detection action.escu.providing_technologies = [] -action.escu.analytic_story = ["Ransomware", "Suspicious Command-Line Executions", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Unusual Processes"] +action.escu.analytic_story = ["Suspicious Command-Line Executions", "Unusual Processes", "Possible Backdoor Activity Associated With MUDCARP Espionage Campaigns", "Ransomware"] cron_schedule = */30 * * * * dispatch.earliest_time = -30m dispatch.latest_time = now @@ -7391,7 +7391,7 @@ relation = greater than quantity = 0 realtime_schedule = 0 is_visible = false -search = `stream_http` http_content_type=text* uri="/magento2/customer/account/loginPost/" | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" | search Username=* | rex field=Username "@(?.*)"|stats dc(Username) as UniqueUsernames list(Username) as src_user by email_domain|where UniqueUsernames> 25 | `web_fraud___account_harvesting_filter` +search = `stream_http` http_content_type=text* uri="/magento2/customer/account/loginPost/" | rex field=cookie "form_key=(?\w+)" | rex field=form_data "login\[username\]=(?[^&|^$]+)" | search Username=* | rex field=Username "@(?.*)" | stats dc(Username) as UniqueUsernames list(Username) as src_user by email_domain | where UniqueUsernames> 25 | `web_fraud___account_harvesting_filter` [ESCU - Web Fraud - Anomalous User Clickspeed - Rule] action.escu = 0 @@ -9536,7 +9536,7 @@ action.escu.known_false_positives = None at this time disabled = true schedule_window = auto is_visible = false -search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | stats count BY user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY user, dest | where sum_count/max_count!=2 +search = `wineventlog_security` EventCode=4768 OR EventCode=4769 | rex field=user "(?[^\@]+)" | stats count BY new_user, dest, EventCode | stats max(count) AS max_count sum(count) AS sum_count BY new_user, dest | where sum_count/max_count!=2 | rename new_user AS user [ESCU - Investigate Previous Unseen User - Response Task] action.escu = 0 diff --git a/package/default/transforms.conf b/package/default/transforms.conf index d122fef295..e3e880572b 100644 --- a/package/default/transforms.conf +++ b/package/default/transforms.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-25T08:45:24 UTC +# On Date: 2020-05-25T14:45:46 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# diff --git a/package/default/use_case_library.conf b/package/default/use_case_library.conf index 8d74cd44ae..06455a4bae 100644 --- a/package/default/use_case_library.conf +++ b/package/default/use_case_library.conf @@ -1,6 +1,6 @@ ############# # Automatically generated by generator.py in splunk/security-content -# On Date: 2020-05-25T08:45:24 UTC +# On Date: 2020-05-25T14:45:46 UTC # Author: Splunk Security Research # Contact: research@splunk.com ############# @@ -14,7 +14,7 @@ version = 1 references = ["https://aws.amazon.com/blogs/security/aws-cloudtrail-now-tracks-cross-account-activity-to-its-origin/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By AccessKeyId", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History"] +searches = ["ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule", "ESCU - AWS Investigate User Activities By Source User", "ESCU - Get Notable History", "ESCU - AWS Investigate User Activities By AccessKeyId"] description = Track when a user assumes an IAM role in another AWS account to obtain cross-account access to services and resources in that account. Accessing new roles could be an indication of malicious activity. narrative = Amazon Web Services (AWS) admins manage access to AWS resources and services across the enterprise using AWS's Identity and Access Management (IAM) functionality. IAM provides the ability to create and manage AWS users, groups, and roles-each with their own unique set of privileges and defined access to specific resources (such as EC2 instances, the AWS Management Console, API, or the command-line interface). Unlike conventional (human) users, IAM roles are assumable by anyone in the organization. They provide users with dynamically created temporary security credentials that expire within a set time period.\ Herein lies the rub. In between the time between when the temporary credentials are issued and when they expire is a period of opportunity, where a user could leverage the temporary credentials to wreak havoc-spin up or remove instances, create new users, elevate privileges, and other malicious activities-throughout the environment.\ @@ -27,7 +27,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule", "ESCU - EC2 Instance Started With Previously Unseen AMI - Rule", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] description = Monitor your AWS EC2 instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or EC2 instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS). It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -41,7 +41,7 @@ version = 2 references = ["https://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/VPC_Appendix_NACLs.html", "https://aws.amazon.com/blogs/security/how-to-help-prepare-for-ddos-attacks-by-reducing-your-attack-surface/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network Access Control List Deleted - Rule", "ESCU - Detect Spike in Network ACL Activity - Rule", "ESCU - AWS Network Access Control List Created with All Open Ports - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor your AWS network infrastructure for bad configurations and malicious activity. Investigative searches help you probe deeper, when the facts warrant it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and operational/risk auditing of your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Management Console, AWS Command Line Interface, and AWS SDKs and APIs to ensure that your servers are not vulnerable to attacks. This analytic story contains detection searches that leverage CloudTrail logs from AWS to check for bad configurations and malicious activity in your AWS network access controls. @@ -52,7 +52,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City", "ESCU - Get All AWS Activity From Region"] +searches = ["ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule", "ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get All AWS Activity From Region", "ESCU - Get All AWS Activity From Country", "ESCU - Get All AWS Activity From City"] description = Monitor your AWS provisioning activities for behaviors originating from unfamiliar or unusual locations. These behaviors may indicate that malicious activities are occurring somewhere within your network. narrative = Because most enterprise AWS activities originate from familiar geographic locations, monitoring for activity from unknown or unusual regions is an important security measure. This indicator can be especially useful in environments where it is impossible to whitelist specific IPs (because they vary).\ This Analytic Story was designed to provide you with flexibility in the precision you employ in specifying legitimate geographic regions. It can be as specific as an IP address or a city, or as broad as a region (think state) or an entire country. By determining how precise you want your geographical locations to be and monitoring for new locations that haven't previously accessed your environment, you can detect adversaries as they begin to probe your environment. Since there are legitimate reasons for activities from unfamiliar locations, this is not a standalone indicator. Nevertheless, location can be a relevant piece of information that you may wish to investigate further. @@ -64,7 +64,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://redlock.io/blog/cryptojacking-tesla"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Get Notable Info", "ESCU - Investigate AWS User Activities by user field", "ESCU - Get Notable History"] +searches = ["ESCU - Detect API activity from users without MFA - Rule", "ESCU - Detect Spike in AWS API Activity - Rule", "ESCU - Detect Spike in Security Group Activity - Rule", "ESCU - Detect new API calls from user roles - Rule", "ESCU - Detect AWS API Activities From Unapproved Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Investigate AWS User Activities by user field"] description = Detect and investigate dormant user accounts for your AWS environment that have become active again. Because inactive and ad-hoc accounts are common attack targets, it's critical to enable governance within your environment. narrative = It seems obvious that it is critical to monitor and control the users who have access to your cloud infrastructure. Nevertheless, it's all too common for enterprises to lose track of ad-hoc accounts, leaving their servers vulnerable to attack. In fact, this was the very oversight that led to Tesla's cryptojacking attack in February, 2018.\ In addition to compromising the security of your data, when bad actors leverage your compute resources, it can incur monumental costs, since you will be billed for any new EC2 instances and increased bandwidth usage. \ @@ -75,10 +75,10 @@ The detection searches in this Analytic Story are designed to help you uncover A category = Best Practices last_updated = 2017-09-06 version = 1 -references = ["https://www.sans.org/media/critical-security-controls/critical-controls-poster-2016.pdf"] +references = [] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Excessive User Account Lockouts - Rule", "ESCU - Detect Excessive Account Lockouts From Endpoint - Rule", "ESCU - Identify New User Accounts - Rule", "ESCU - Short Lived Windows Accounts - Rule", "ESCU - Get Logon Rights Modifications For Endpoint", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Logon Rights Modifications For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = A common attack technique is to leverage user accounts to gain unauthorized access to the target's network. This Analytic Story minimizes opportunities for attack by helping you actively manage creation/use/dormancy/deletion--the lifecycle of system and application accounts. narrative = Monitoring user accounts within your enterprise is a critical analytic function that helps ensure that credential and access policies/procedures are properly implemented and are being enforced. Proactive ad-hoc hunting, as well as routine monitoring, can ensure user or system accounts are not being abused by unauthorized individuals or processes. In the event of a network event or breach, user-authentication logs are a key resource in determining if or how an account might have been compromised or co-opted, leading to suspicious or malicious activity. @@ -89,7 +89,7 @@ version = 1 references = ["https://github.com/SpiderLabs/owasp-modsecurity-crs/blob/v3.2/dev/rules/REQUEST-944-APPLICATION-ATTACK-JAVA.conf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate Web POSTs From src", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Notable History"] +searches = ["ESCU - Suspicious Java Classes - Rule", "ESCU - Web Servers Executing Suspicious Processes - Rule", "ESCU - Unusually Long Content-Type Length - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Suspicious Strings in HTTP Header", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web POSTs From src", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activities--such as unusually long `Content-Type` length, suspicious java classes and web servers executing suspicious processes--consistent with attempts to exploit Apache Struts vulnerabilities. narrative = In March of 2017, a remote code-execution vulnerability in the Jakarta Multipart parser in Apache Struts, a widely used open-source framework for creating Java web applications, was disclosed and assigned to CVE-2017-5638. About two months later, hackers exploited the flaw to carry out the world's 5th largest data breach. The target, credit giant Equifax, told investigators that it had become aware of the vulnerability two months before the attack. \ The exploit involved manipulating the `Content-Type HTTP` header to execute commands embedded in the header.\ @@ -113,7 +113,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/inventory-of-authorized-and-unauthorized-devices/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Unauthorized Assets by MAC address - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get First Occurrence and Last Occurrence of a MAC Address"] description = Keep a careful inventory of every asset on your network to make it easier to detect rogue devices. Unauthorized/unmanaged devices could be an indication of malicious behavior that should be investigated further. narrative = This Analytic Story is designed to help you develop a better understanding of what authorized and unauthorized devices are part of your enterprise. This story can help you better categorize and classify assets, providing critical business context and awareness of their assets during an incident. Information derived from this Analytic Story can be used to better inform and support other analytic stories. For successful detection, you will need to leverage the Assets and Identity Framework from Enterprise Security to populate your known assets. @@ -124,7 +124,7 @@ version = 1 references = ["https://www.zerofox.com/blog/what-is-digital-risk-monitoring/", "https://securingtomorrow.mcafee.com/consumer/family-safety/what-is-typosquatting/", "https://blog.malwarebytes.com/cybercrime/2016/06/explained-typosquatting/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Monitor Web Traffic For Brand Abuse - Rule", "ESCU - Monitor DNS For Brand Abuse - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table"] description = Detect and investigate activity that may indicate that an adversary is using faux domains to mislead users into interacting with malicious infrastructure. Monitor DNS, email, and web traffic for permutations of your brand name. narrative = While you can educate your users and customers about the risks and threats posed by typosquatting, phishing, and corporate espionage, human error is a persistent fact of life. Of course, your adversaries are all too aware of this reality and will happily leverage it for nefarious purposes whenever possible3phishing with lookalike addresses, embedding faux command-and-control domains in malware, and hosting malicious content on domains that closely mimic your corporate servers. This is where brand monitoring comes in.\ You can use our adaptation of `DNSTwist`, together with the support searches in this Analytic Story, to generate permutations of specified brands and external domains. Splunk can monitor email, DNS requests, and web traffic for these permutations and provide you with early warnings and situational awareness--powerful elements of an effective defense.\ @@ -137,7 +137,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule", "ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule", "ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Investigate User Activities In Single Cloud Region", "ESCU - Get Notable History", "ESCU - Investigate User Activities In All Cloud Regions", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate Cloud Compute Instance Activities", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] description = Monitor your cloud compute instances for activities related to cryptojacking/cryptomining. New instances that originate from previously unseen regions, users who launch abnormally high numbers of instances, or compute instances started by previously unseen users are just a few examples of potentially malicious behavior. narrative = Cryptomining is an intentionally difficult, resource-intensive business. Its complexity was designed into the process to ensure that the number of blocks mined each day would remain steady. So, it's par for the course that ambitious, but unscrupulous, miners make amassing the computing power of large enterprises--a practice known as cryptojacking--a top priority. \ Cryptojacking has attracted an increasing amount of media attention since its explosion in popularity in the fall of 2017. The attacks have moved from in-browser exploits and mobile phones to enterprise cloud services, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Azure. It's difficult to determine exactly how widespread the practice has become, since bad actors continually evolve their ability to escape detection, including employing unlisted endpoints, moderating their CPU usage, and hiding the mining pool's IP address behind a free CDN. \ @@ -151,7 +151,7 @@ version = 1 references = ["https://www.intego.com/mac-security-blog/osxcoldroot-and-the-rat-invasion/", "https://objective-see.com/blog/blog_0x2A.html", "https://www.bleepingcomputer.com/news/security/coldroot-rat-still-undetectable-despite-being-uploaded-on-github-two-years-ago/"] maintainers = "Jose Hernandez, Splunk" spec_version = 3 -searches = ["ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Osquery pack - ColdRoot detection - Rule", "ESCU - Processes Tapping Keyboard Events - Rule", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that relate to the ColdRoot Remote Access Trojan that affects MacOS. An example of some of these activities are changing sensative binaries in the MacOS sub-system, detecting process names and executables associated with the RAT, detecting when a keyboard tab is installed on a MacOS machine and more. narrative = Conventional wisdom holds that Apple's MacOS operating system is significantly less vulnerable to attack than Windows machines. While that point is debatable, it is true that attacks against MacOS systems are much less common. However, this fact does not mean that Macs are impervious to breaches. To the contrary, research has shown that that Mac malware is increasing at an alarming rate. According to AV-test, in 2018, there were 86,865 new MacOS malware variants, up from 27,338 the year before—a 31% increase. In contrast, the independent research firm found that new Windows malware had increased from 65.17M to 76.86M during that same period, less than half the rate of growth. The bottom line is that while the numbers look a lot smaller than Windows, it's definitely time to take Mac security more seriously.\ This Analytic Story addresses the ColdRoot remote access trojan (RAT), which was uploaded to Github in 2016, but was still escaping detection by the first quarter of 2018, when a new, more feature-rich variant was discovered masquerading as an Apple audio driver. Among other capabilities, the Pascal-based ColdRoot can heist passwords from users' keychains and remotely control infected machines without detection. In the initial report of his findings, Patrick Wardle, Chief Research Officer for Digita Security, explained that the new ColdRoot RAT could start and kill processes on the breached system, spawn new remote-desktop sessions, take screen captures and assemble them into a live stream of the victim's desktop, and more.\ @@ -164,7 +164,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Collection", "https://attack.mitre.org/wiki/Technique/T1074"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Hosts receiving high volume of network traffic from email server - Rule", "ESCU - Email servers sending high volume traffic to hosts - Rule", "ESCU - Suspicious writes to windows Recycle Bin - Rule", "ESCU - Suspicious writes to System Volume Information - Rule", "ESCU - Email files written outside of the Outlook directory - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities--such as suspicious writes to the Windows Recycling Bin or email servers sending high amounts of traffic to specific hosts, for example--that may indicate that an adversary is harvesting and exfiltrating sensitive data. narrative = A common adversary goal is to identify and exfiltrate data of value from a target organization. This data may include email conversations and addresses, confidential company information, links to network design/infrastructure, important dates, and so on.\ Attacks are composed of three activities: identification, collection, and staging data for exfiltration. Identification typically involves scanning systems and observing user activity. Collection can involve the transfer of large amounts of data from various repositories. Staging/preparation includes moving data to a central location and compressing (and optionally encoding and/or encrypting) it. All of these activities provide opportunities for defenders to identify their presence. \ @@ -177,7 +177,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Command_and_Control", "https://searchsecurity.techtarget.com/feature/Command-and-control-servers-The-puppet-masters-that-govern-malware"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - TOR Traffic - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect Large Outbound ICMP Packets - Rule", "ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures leveraged by attackers to establish and operate command and control channels. Implants installed by attackers on compromised endpoints use these channels to receive instructions and send data back to the malicious operators. narrative = Threat actors typically architect and implement an infrastructure to use in various ways during the course of their attack campaigns. In some cases, they leverage this infrastructure for scanning and performing reconnaissance activities. In others, they may use this infrastructure to launch actual attacks. One of the most important functions of this infrastructure is to establish servers that will communicate with implants on compromised endpoints. These servers establish a command and control channel that is used to proxy data between the compromised endpoint and the attacker. These channels relay commands from the attacker to the compromised endpoint and the output of those commands back to the attacker.\ Because this communication is so critical for an adversary, they often use techniques designed to hide the true nature of the communications. There are many different techniques used to establish and communicate over these channels. This Analytic Story provides searches that look for a variety of the techniques used for these channels, as well as indications that these channels are active, by examining logs associated with border control devices and network-access control lists. @@ -212,7 +212,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1003", "https://cyberwardog.blogspot.com/2017/03/chronicles-of-threat-hunter-hunting-for.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Pass the Ticket Attempts", "ESCU - Investigate Pass the Hash Attempts"] +searches = ["ESCU - Credential Dumping via Symlink to Shadow Copy - Rule", "ESCU - Dump LSASS via comsvcs DLL - Rule", "ESCU - Access LSASS Memory for Dump Creation - Rule", "ESCU - Creation of Shadow Copy with wmic and powershell - Rule", "ESCU - Detect Credential Dumping through LSASS access - Rule", "ESCU - Detect Mimikatz Using Loaded Images - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Creation of Shadow Copy - Rule", "ESCU - Create Remote Thread into LSASS - Rule", "ESCU - Attempted Credential Dump From Registry via Reg exe - Rule", "ESCU - Unsigned Image Loaded by LSASS - Rule", "ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule", "ESCU - Investigate Failed Logins for Multiple Destinations", "ESCU - Investigate Previous Unseen User", "ESCU - Investigate Pass the Hash Attempts", "ESCU - Investigate Pass the Ticket Attempts"] description = Uncover activity consistent with credential dumping, a technique wherein attackers compromise systems and attempt to obtain and exfiltrate passwords. The threat actors use these pilfered credentials to further escalate privileges and spread throughout a target environment. The included searches in this Analytic Story are designed to identify attempts to credential dumping. narrative = Credential dumping—gathering credentials from a target system, often hashed or encrypted—is a common attack technique. Even though the credentials may not be in plain text, an attacker can still exfiltrate the data and set to cracking it offline, on their own systems. The threat actors target a variety of sources to extract them, including the Security Accounts Manager (SAM), Local Security Authority (LSA), NTDS from Domain Controllers, or the Group Policy Preference (GPP) files.\ Once attackers obtain valid credentials, they use them to move throughout a target network with ease, discovering new systems and identifying assets of interest. Credentials obtained in this manner typically include those of privileged users, which may provide access to more sensitive information and system operations.\ @@ -225,7 +225,7 @@ version = 2 references = ["https://www.us-cert.gov/ncas/alerts/TA18-074A"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process File Activity", "ESCU - Get Process Registry Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule", "ESCU - Single Letter Process On Endpoint - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Create local admin accounts using net exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule", "ESCU - Detect New Local Admin account - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Registry Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Process File Activity", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor for suspicious activities associated with DHS Technical Alert US-CERT TA18-074A. Some of the activities that adversaries used in these compromises included spearfishing attacks, malware, watering-hole domains, many and more. narrative = The frequency of nation-state cyber attacks has increased significantly over the last decade. Employing numerous tactics and techniques, these attacks continue to escalate in complexity. \ There is a wide range of motivations for these state-sponsored hacks, including stealing valuable corporate, military, or diplomatic dataѿall of which could confer advantages in various arenas. They may also target critical infrastructure. \ @@ -239,7 +239,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA13-088A", "https://www.imperva.com/learn/application-security/dns-amplification/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Large Volume of DNS ANY Queries - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] description = DNS poses a serious threat as a Denial of Service (DOS) amplifier, if it responds to `ANY` queries. This Analytic Story can help you detect attackers who may be abusing your company's DNS infrastructure to launch amplification attacks, causing Denial of Service to other victims. narrative = The Domain Name System (DNS) is the protocol used to map domain names to IP addresses. It has been proven to work very well for its intended function. However if DNS is misconfigured, servers can be abused by attackers to levy amplification or redirection attacks against victims. Because DNS responses to `ANY` queries are so much larger than the queries themselves--and can be made with a UDP packet, which does not require a handshake--attackers can spoof the source address of the packet and cause much more data to be sent to the victim than if they sent the traffic themselves. The `ANY` requests are will be larger than normal DNS server requests, due to the fact that the server provides significant details, such as MX records and associated IP addresses. A large volume of this traffic can result in a DOS on the victim's machine. This misconfiguration leads to two possible victims, the first being the DNS servers participating in an attack and the other being the hosts that are the targets of the DOS attack.\ The search in this story can help you to detect if attackers are abusing your company's DNS infrastructure to launch DNS amplification attacks causing Denial of Service to other victims. @@ -251,7 +251,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - DNS record changed - Rule", "ESCU - Get DNS Server History for a host"] description = Secure your environment against DNS hijacks with searches that help you detect and investigate unauthorized changes to DNS records. narrative = Dubbed the Achilles heel of the Internet (see https://www.f5.com/labs/articles/threat-intelligence/dns-is-still-the-achilles-heel-of-the-internet-25613), DNS plays a critical role in routing web traffic but is notoriously vulnerable to attack. One reason is its distributed nature. It relies on unstructured connections between millions of clients and servers over inherently insecure protocols.\ The gravity and extent of the importance of securing DNS from attacks is undeniable. The fallout of compromised DNS can be disastrous. Not only can hackers bring down an entire business, they can intercept confidential information, emails, and login credentials, as well. \ @@ -270,7 +270,7 @@ version = 1 references = ["https://www.cisecurity.org/controls/data-protection/", "https://www.sans.org/reading-room/whitepapers/dns/splunk-detect-dns-tunneling-37022", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect USB device insertion - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Fortify your data-protection arsenal--while continuing to ensure data confidentiality and integrity--with searches that monitor for and help you investigate possible signs of data exfiltration. narrative = Attackers can leverage a variety of resources to compromise or exfiltrate enterprise data. Common exfiltration techniques include remote-access channels via low-risk, high-payoff active-collections operations and close-access operations using insiders and removable media. While this Analytic Story is not a comprehensive listing of all the methods by which attackers can exfiltrate data, it provides a useful starting point. @@ -281,7 +281,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1089", "https://blog.malwarebytes.com/cybercrime/2015/11/vonteera-adware-uses-certificates-to-disable-anti-malware/", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Tools-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Processes launching netsh - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Unload Sysmon Filter Driver - Rule", "ESCU - Attempt To Stop Security Service - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Attempt To Add Certificate To Untrusted Store - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Looks for activities and techniques associated with the disabling of security tools on a Windows system, such as suspicious `reg.exe` processes, processes launching netsh, and many others. narrative = Attackers employ a variety of tactics in order to avoid detection and operate without barriers. This often involves modifying the configuration of security tools to get around them or explicitly disabling them to prevent them from running. This Analytic Story includes searches that look for activity consistent with attackers attempting to disable various security mechanisms. Such activity may involve monitoring for suspicious registry activity, as this is where much of the configuration for Windows and various other programs reside, or explicitly attempting to shut down security-related services. Other times, attackers attempt various tricks to prevent specific programs from running, such as adding the certificates with which the security tools are signed to a blacklist (which would prevent them from running). @@ -292,7 +292,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/09/apt33-insights-into-iranian-cyber-espionage.html", "https://umbrella.cisco.com/blog/2013/04/15/on-the-trail-of-malicious-dynamic-dns-domains/", "http://www.noip.com/blog/2014/07/11/dynamic-dns-can-use-2/", "https://www.splunk.com/blog/2015/08/04/detecting-dynamic-dns-domains-in-splunk.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From src ip", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Detect web traffic to dynamic domain providers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect and investigate hosts in your environment that may be communicating with dynamic domain providers. Attackers may leverage these services to help them avoid firewall blocks and blacklists. narrative = Dynamic DNS services (DDNS) are legitimate low-cost or free services that allow users to rapidly update domain resolutions to IP infrastructure. While their usage can be benign, malicious actors can abuse DDNS to host harmful payloads or interactive-command-and-control infrastructure. These attackers will manually update or automate domain resolution changes by routing dynamic domains to IP addresses that circumvent firewall blocks and blacklists and frustrate a network defender's analytic and investigative processes. These searches will look for DNS queries made from within your infrastructure to suspicious dynamic domains and then investigate more deeply, when appropriate. While this list of top-level dynamic domains is not exhaustive, it can be dynamically updated as new suspicious dynamic domains are identified. @@ -303,7 +303,7 @@ version = 1 references = ["https://www.us-cert.gov/ncas/alerts/TA18-201A", "https://www.first.org/resources/papers/conf2017/Advanced-Incident-Detection-and-Threat-Hunting-using-Sysmon-and-Splunk.pdf", "https://www.vkremez.com/2017/05/emotet-banking-trojan-malware-analysis.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Detection of tools built by NirSoft - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Detect rarely used executables, specific registry paths that may confer malware survivability and persistence, instances where cmd.exe is used to launch script interpreters, and other indicators that the Emotet financial malware has compromised your environment. narrative = The trojan downloader known as Emotet first surfaced in 2014, when it was discovered targeting the banking industry to steal credentials. However, according to a joint technical alert (TA) issued by three government agencies (https://www.us-cert.gov/ncas/alerts/TA18-201A), Emotet has evolved far beyond those beginnings to become what a ThreatPost article called a threat-delivery service(see https://threatpost.com/emotet-malware-evolves-beyond-banking-to-threat-delivery-service/134342/). For example, in early 2018, Emotet was found to be using its loader function to spread the Quakbot and Ransomware variants. \ According to the TA, the the malware continues to be among the most costly and destructive malware affecting the private and public sectors. Researchers have linked it to the threat group Mealybug, which has also been on the security communitys radar since 2014.\ @@ -316,7 +316,7 @@ version = 2 references = ["https://www.us-cert.gov/HIDDEN-COBRA-North-Korean-Malicious-Cyber-Activity", "https://www.operationblockbuster.com/wp-content/uploads/2016/02/Operation-Blockbuster-Destructive-Malware-Report.pdf"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Outbound SMB Traffic - Rule", "ESCU - Create or delete windows shares using net exe - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Suspicious File Write - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Monitor for and investigate activities, including the creation or deletion of hidden shares and file writes, that may be evidence of infiltration by North Korean government-sponsored cybercriminals. Details of this activity were reported in DHS Report TA-18-149A. narrative = North Korea's government-sponsored "cyber army" has been slowly building momentum and gaining sophistication over the last 15 years or so. As a result, the group's activity, which the US government refers to as "Hidden Cobra," has surreptitiously crept onto the collective radar as a preeminent global threat.\ These state-sponsored actors are thought to be responsible for everything from a hack on a South Korean nuclear plant to an attack on Sony in anticipation of its release of the movie "The Interview" at the end of 2014. They're also notorious for cyberespionage. In recent years, the group seems to be focused on financial crimes, such as cryptojacking.\ @@ -330,7 +330,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2016/09/hosts-file-hijacks/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History"] +searches = ["ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Windows hosts file modification - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect evidence of tactics used to redirect traffic from a host to a destination other than the one intended--potentially one that is part of an adversary's attack infrastructure. An example is redirecting communications regarding patches and updates or misleading users into visiting a malicious website. narrative = Attackers will often attempt to manipulate client communications for nefarious purposes. In some cases, an attacker may endeavor to modify a local host file to redirect communications with resources (such as antivirus or system-update services) to prevent clients from receiving patches or updates. In other cases, an attacker might use this tactic to have the client connect to a site that looks like the intended site, but instead installs malware or collects information from the victim. Additionally, an attacker may redirect a victim in order to execute a MITM attack and observe communications. @@ -341,7 +341,7 @@ version = 1 references = ["http://www.deependresearch.org/2016/04/jboss-exploits-view-from-victim.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From Host", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Get Notable History", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info"] description = In March of 2016, adversaries were seen using JexBoss--an open-source utility used for testing and exploiting JBoss application servers. These searches help detect evidence of these attacks, such as network connections to external resources or web services spawning atypical child processes, among others. narrative = This Analytic Story looks for probing and exploitation attempts targeting JBoss application servers. While the vulnerabilities associated with this story are rather dated, they were leveraged in a spring 2016 campaign in connection with the Samsam ransomware variant. Incidents involving this ransomware are unique, in that they begin with attacks against vulnerable services, rather than the phishing or drive-by attacks more common with ransomware. In this case, vulnerable JBoss applications appear to be the target of choice.\ It is helpful to understand how often a notable event generated by this story occurs, as well as the commonalities between some of these events, both of which may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. It may also help to understand whether the issue is restricted to a single user/system or whether it is broader in scope.\ @@ -366,7 +366,7 @@ version = 1 references = ["https://github.com/splunk/cloud-datamodel-security-research"] maintainers = "Rod Soto, Splunk" spec_version = 3 -searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Get Notable Info", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History"] +searches = ["ESCU - GCP Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes cluster scan detection - Rule", "ESCU - Amazon EKS Kubernetes Pod scan detection - Rule", "ESCU - GCP Kubernetes activity by src ip", "ESCU - Amazon EKS Kubernetes activity by src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info"] description = This story addresses detection against Kubernetes cluster fingerprint scan and attack by providing information on items such as source ip, user agent, cluster names. narrative = Kubernetes is the most used container orchestration platform, this orchestration platform contains sensitve information and management priviledges of production workloads, microservices and applications. These searches allow operator to detect suspicious unauthenticated requests from the internet to kubernetes cluster. @@ -377,7 +377,7 @@ version = 2 references = ["https://www.fireeye.com/blog/executive-perspective/2015/08/malware_lateral_move.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Schtasks scheduling job on remote system - Rule", "ESCU - Detect Activity Related to Pass the Hash Attacks - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Remote Desktop Process Running On System - Rule", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect and investigate tactics, techniques, and procedures around how attackers move laterally within the enterprise. Because lateral movement can expose the adversary to detection, it should be an important focus for security analysts. narrative = Once attackers gain a foothold within an enterprise, they will seek to expand their accesses and leverage techniques that facilitate lateral movement. Attackers will often spend quite a bit of time and effort moving laterally. Because lateral movement renders an attacker the most vulnerable to detection, it's an excellent focus for detection and investigation.\ Indications of lateral movement can include the abuse of system utilities (such as `psexec.exe`), unauthorized use of remote desktop services, `file/admin$` shares, WMI, PowerShell, pass-the-hash, or the abuse of scheduled tasks. Organizations must be extra vigilant in detecting lateral movement techniques and look for suspicious activity in and around high-value strategic network assets, such as Active Directory, which are often considered the primary target or "crown jewels" to a persistent threat actor.\ @@ -392,7 +392,7 @@ version = 4 references = ["https://blogs.mcafee.com/mcafee-labs/malware-employs-powershell-to-infect-systems/", "https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule", "ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule", "ESCU - Malicious PowerShell Process - Encoded Command - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Attackers are finding stealthy ways "live off the land," leveraging utilities and tools that come standard on the endpoint--such as PowerShell--to achieve their goals without downloading binary files. These searches can help you detect and investigate PowerShell command-line options that may be indicative of malicious intent. narrative = The searches in this Analytic Story monitor for parameters often used for malicious purposes. It is helpful to understand how often the notable events generated by this story occur, as well as the commonalities between some of these events. These factors may provide clues about whether this is a common occurrence of minimal concern or a rare event that may require more extensive investigation. Likewise, it is important to determine whether the issue is restricted to a single user/system or is broader in scope.\ The following factors may assist you in determining whether the event is malicious: \ @@ -412,7 +412,7 @@ version = 1 references = ["https://www.carbonblack.com/2016/03/04/tracking-locky-ransomware-using-carbon-black/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - All backup logs for host", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint"] +searches = ["ESCU - Unsuccessful Netbackup backups - Rule", "ESCU - Extended Period Without Successful Netbackup Backups - Rule", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - All backup logs for host"] description = Address common concerns when monitoring your backup processes. These searches can help you reduce risks from ransomware, device theft, or denial of physical access to a host by backing up data on endpoints. narrative = Having backups is a standard best practice that helps ensure continuity of business operations. Having mature backup processes can also help you reduce the risks of many security-related incidents and streamline your response processes. The detection searches in this Analytic Story will help you identify systems that have backup failures, as well as systems that have not been backed up for an extended period of time. The story will also return the notable event history and all of the backup logs for an endpoint. @@ -423,7 +423,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Identify and investigate prohibited/unauthorized software or processes that may be concealing malicious behavior within your environment. narrative = It is critical to identify unauthorized software and processes running on enterprise endpoints and determine whether they are likely to be malicious. This Analytic Story requires the user to populate the Interesting Processes table within Enterprise Security with prohibited processes. An included support search will augment this data, adding information on processes thought to be malicious. This search requires data from endpoint detection-and-response solutions, endpoint data sources (such as Sysmon), or Windows Event Logs--assuming that the Active Directory administrator has enabled process tracking within the System Event Audit Logs.\ It is important to investigate any software identified as suspicious, in order to understand how it was installed or executed. Analyzing authentication logs or any historic notable events might elicit additional investigative leads of interest. For best results, schedule the search to run every two weeks. @@ -448,7 +448,7 @@ version = 1 references = ["https://technet.microsoft.com/library/bb490939.aspx", "https://htmlpreview.github.io/?https://github.com/MatthewDemaske/blogbackup/blob/master/netshell.html", "http://blog.jpcert.or.jp/2016/01/windows-commands-abused-by-attackers.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Processes created by netsh - Rule", "ESCU - Processes launching netsh - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the abuse of `netsh.exe`, which can disable local firewall settings or set up a remote connection to a host from an infected system. narrative = It is a common practice for attackers of all types to leverage native Windows tools and functionality to execute commands for malicious reasons. One such tool on Windows OS is `netsh.exe`,a command-line scripting utility that allows you to--either locally or remotely--display or modify the network configuration of a computer that is currently running. `Netsh.exe` can be used to discover and disable local firewall settings. It can also be used to set up a remote connection to a host from an infected system.\ To get started, run the detection search to identify parent processes of `netsh.exe`. @@ -460,7 +460,7 @@ version = 2 references = ["https://www.symantec.com/blogs/threat-intelligence/orangeworm-targets-healthcare-us-europe-asia", "https://www.infosecurity-magazine.com/news/healthcare-targeted-by-hacker/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - First time seen command line argument - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect activities and various techniques associated with the Orangeworm Attack Group, a group that frequently targets the healthcare industry. narrative = In May of 2018, the attack group Orangeworm was implicated for installing a custom backdoor called Trojan.Kwampirs within large international healthcare corporations in the United States, Europe, and Asia. This malware provides the attackers with remote access to the target system, decrypting and extracting a copy of its main DLL payload from its resource section. Before writing the payload to disk, it inserts a randomly generated string into the middle of the decrypted payload in an attempt to evade hash-based detections.\ Awareness of the Orangeworm group first surfaced in January, 2015. It has conducted targeted attacks against related industries, as well, such as pharmaceuticals and healthcare IT solution providers.\ @@ -475,7 +475,7 @@ version = 1 references = ["https://www.fireeye.com/blog/threat-research/2019/04/spear-phishing-campaign-targets-ukraine-government.html"] maintainers = "Splunk Research Team, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Get Parent Process Info"] +searches = ["ESCU - Detect Oulook exe writing a zip file - Rule", "ESCU - Suspicious LNK file launching a process - Rule", "ESCU - Get Parent Process Info"] description = Detect signs of malicious payloads that may indicate that your environment has been breached via a phishing attack. narrative = Despite its simplicity, phishing remains the most pervasive and dangerous cyberthreat. In fact, research shows that as many as [91% of all successful attacks](https://digitalguardian.com/blog/91-percent-cyber-attacks-start-phishing-email-heres-how-protect-against-phishing) are initiated via a phishing email. \ As most people know, these emails use fraudulent domains, [email scraping](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), familiar contact names inserted as senders, and other tactics to lure targets into clicking a malicious link, opening an attachment with a [nefarious payload](https://www.cyberscoop.com/emotet-trojan-phishing-scraping-templates-cofense-geodo/), or entering sensitive personal information that perpetrators may intercept. This attack technique requires a relatively low level of skill and allows adversaries to easily cast a wide net. Worse, because its success relies on the gullibility of humans, it's impossible to completely "automate" it out of your environment. However, you can use ES and ESCU to detect and investigate potentially malicious payloads injected into your environment subsequent to a phishing attack. \ @@ -493,7 +493,7 @@ version = 1 references = ["https://www.infosecurity-magazine.com/news/scope-of-mudcarp-attacks-highlight-1/", "http://blog.amossys.fr/badflick-is-not-so-bad.html"] maintainers = "iDefense Cyber Espionage Team, iDefense" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor your environment for suspicious behaviors that resemble the techniques employed by the MUDCARP threat group. narrative = This story was created as a joint effort between iDefense and Splunk.\ iDefense analysts have recently discovered a Windows executable file that, upon execution, spoofs a decryption tool and then drops a file that appears to be the custom-built javascript backdoor, "Orz," which is associated with the threat actors known as MUDCARP (as well as "temp.Periscope" and "Leviathan"). The file is executed using Wscript.\ @@ -531,7 +531,7 @@ version = 1 references = ["http://www.novetta.com/2015/02/advanced-methods-to-detect-advanced-cyber-attacks-protocol-abuse/"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Protocol or Port Mismatch - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Detect instances of prohibited network traffic allowed in the environment, as well as protocols running on non-standard ports. Both of these types of behaviors typically violate policy and can be leveraged by attackers. narrative = A traditional security best practice is to control the ports, protocols, and services allowed within your environment. By limiting the services and protocols to those explicitly approved by policy, administrators can minimize the attack surface. The combined effect allows both network defenders and security controls to focus and not be mired in superfluous traffic or data types. Looking for deviations to policy can identify attacker activity that abuses services and protocols to run on alternate or non-standard ports in the attempt to avoid detection or frustrate forensic analysts. @@ -542,7 +542,7 @@ version = 1 references = ["https://www.carbonblack.com/2017/06/28/carbon-black-threat-research-technical-analysis-petya-notpetya-ransomware/", "https://www.splunk.com/blog/2017/06/27/closing-the-detection-to-mitigation-gap-or-to-petya-or-notpetya-whocares-.html"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Common Ransomware Extensions - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - SMB Traffic Spike - MLTK - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - TOR Traffic - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Scheduled tasks used in BadRabbit ransomware - Rule", "ESCU - SMB Traffic Spike - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Prohibited Network Traffic Allowed - Rule", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to ransomware--spikes in SMB traffic, suspicious wevtutil usage, the presence of common ransomware extensions, and system processes run from unexpected locations, and many others. narrative = Ransomware is an ever-present risk to the enterprise, wherein an infected host encrypts business-critical data, holding it hostage until the victim pays the attacker a ransom. There are many types and varieties of ransomware that can affect an enterprise. Attackers can deploy ransomware to enterprises through spearphishing campaigns and driveby downloads, as well as through traditional remote service-based exploitation. In the case of the WannaCry campaign, there was self-propagating wormable functionality that was used to maximize infection. Fortunately, organizations can apply several techniques--such as those in this Analytic Story--to detect and or mitigate the effects of ransomware. @@ -553,7 +553,7 @@ version = 1 references = ["https://www.fireeye.com/blog/executive-perspective/2015/09/the_new_route_toper.html", "https://www.cisco.com/c/en/us/about/security-center/event-response/synful-knock.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect New Login Attempts to Routers - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Validate the security configuration of network infrastructure and verify that only authorized users and systems are accessing critical assets. Core routing and switching infrastructure are common strategic targets for attackers. narrative = Networking devices, such as routers and switches, are often overlooked as resources that attackers will leverage to subvert an enterprise. Advanced threats actors have shown a proclivity to target these critical assets as a means to siphon and redirect network traffic, flash backdoored operating systems, and implement cryptographic weakened algorithms to more easily decrypt network traffic.\ This Analytic Story helps you gain a better understanding of how your network devices are interacting with your hosts. By compromising your network devices, attackers can obtain direct access to the company's internal infrastructure— effectively increasing the attack surface and accessing private services/data. @@ -577,7 +577,7 @@ version = 1 references = ["https://www.crowdstrike.com/blog/an-in-depth-analysis-of-samsam-ransomware-and-boss-spider/", "https://nakedsecurity.sophos.com/2018/07/31/samsam-the-almost-6-million-ransomware/", "https://thehackernews.com/2018/07/samsam-ransomware-attacks.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Batch File Write to System32 - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Detect PsExec With accepteula Flag - Rule", "ESCU - Common Ransomware Extensions - Rule", "ESCU - Samsam Test File Write - Rule", "ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule", "ESCU - Common Ransomware Notes - Rule", "ESCU - Remote Desktop Network Bruteforce - Rule", "ESCU - Remote Desktop Network Traffic - Rule", "ESCU - File with Samsam Extension - Rule", "ESCU - Spike in File Writes - Rule", "ESCU - Detect malicious requests to exploit JBoss servers - Rule", "ESCU - Prohibited Software On Endpoint - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Batch File Write to System32 - Rule", "ESCU - Investigate Successful Remote Desktop Authentications", "ESCU - Get Parent Process Info", "ESCU - Get Update Logs For Endpoint", "ESCU - Get Backup Logs For Endpoint", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Leverage searches that allow you to detect and investigate unusual activities that might relate to the SamSam ransomware, including looking for file writes associated with SamSam, RDP brute force attacks, the presence of files with SamSam ransomware extensions, suspicious psexec use, and more. narrative = The first version of the SamSam ransomware (a.k.a. Samas or SamsamCrypt) was launched in 2015 by a group of Iranian threat actors. The malicious software has affected and continues to affect thousands of victims and has raised almost $6M in ransom.\ Although categorized under the heading of ransomware, SamSam campaigns have some importance distinguishing characteristics. Most notable is the fact that conventional ransomware is a numbers game. Perpetrators use a "spray-and-pray" approach with phishing campaigns or other mechanisms, charging a small ransom (typically under $1,000). The goal is to find a large number of victims willing to pay these mini-ransoms, adding up to a lucrative payday. They use relatively simple methods for infecting systems.\ @@ -593,7 +593,7 @@ version = 1 references = ["https://meltdownattack.com/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Spectre and Meltdown Vulnerable Systems - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Assess and mitigate your systems' vulnerability to Spectre and Meltdown exploitation with the searches in this Analytic Story. narrative = Meltdown and Spectre exploit critical vulnerabilities in modern CPUs that allow unintended access to data in memory. This Analytic Story will help you identify the systems can be patched for these vulnerabilities, as well as those that still need to be patched. @@ -624,7 +624,7 @@ version = 1 references = ["https://nvd.nist.gov/vuln/detail/CVE-2018-11409", "https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings", "https://www.exploit-db.com/exploits/44865/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Get Notable Info", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History"] +searches = ["ESCU - Splunk Enterprise Information Disclosure - Rule", "ESCU - Investigate Network Traffic From src ip", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Investigate Web Activity From src ip", "ESCU - Get Notable Info"] description = Reduce the risk of CVE-2018-11409, an information disclosure vulnerability within some older versions of Splunk Enterprise, with searches designed to help ensure that your Splunk system does not leak information to authenticated users. narrative = Although there have been no reports of it being exploited, Splunk Enterprise versions through 7.0.1 reportedly have a vulnerability that may expose information through a REST endpoint (read more here: https://www.splunk.com/view/SP-CAAAP5E#VulnerabilityDescriptionsandRatings). NIST has included it in its vulnerability database (read more here: https://nvd.nist.gov/vuln/detail/CVE-2018-11409). The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Customers should upgrade to the latest version to reduce the risk of this vulnerability.\ Splunk Enterprise exposes partial information about the host operating system, hardware, and Splunk license. Splunk Enterprise before 6.6.0 exposes this information without authentication. Splunk Enterprise 6.6.0 and later exposes this information only to authenticated Splunk users. Based on the information exposure, Splunk characterizes this issue as a low severity impact.\ @@ -638,7 +638,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Launch Details"] +searches = ["ESCU - EC2 Instance Started With Previously Unseen User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - Rule", "ESCU - EC2 Instance Started In Previously Unseen Region - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - Rule", "ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule", "ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable Info", "ESCU - Get EC2 Launch Details"] description = Use the searches in this Analytic Story to monitor your AWS EC2 instances for evidence of anomalous activity and suspicious behaviors, such as EC2 instances that originate from unusual locations or those launched by previously unseen users (among others). Included investigative searches will help you probe more deeply, when the information warrants it. narrative = AWS CloudTrail is an AWS service that helps you enable governance, compliance, and risk auditing within your AWS account. Actions taken by a user, role, or an AWS service are recorded as events in CloudTrail. It is crucial for a company to monitor events and actions taken in the AWS Console, AWS command-line interface, and AWS SDKs and APIs to ensure that your EC2 instances are not vulnerable to attacks. This Analytic Story identifies suspicious activities in your AWS EC2 instances and helps you respond and investigate those activities. @@ -649,7 +649,7 @@ version = 1 references = ["https://docs.aws.amazon.com/IAM/latest/UserGuide/cloudtrail-integration.html"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - AWS Investigate User Activities By ARN"] +searches = ["ESCU - Detect AWS Console Login by User from New City - Rule", "ESCU - Detect AWS Console Login by User from New Region - Rule", "ESCU - Detect new user AWS Console Login - Rule", "ESCU - Detect AWS Console Login by User from New Country - Rule", "ESCU - AWS Investigate User Activities By ARN"] description = Monitor your AWS authentication events using your CloudTrail logs. Searches within this Analytic Story will help you stay aware of and investigate suspicious logins. narrative = It is important to monitor and control who has access to your AWS infrastructure. Detecting suspicious logins to your AWS infrastructure will provide good starting points for investigations. Abusive behaviors caused by compromised credentials can lead to direct monetary costs, as you will be billed for any EC2 instances created by the attacker. @@ -660,7 +660,7 @@ version = 2 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf", "https://www.tripwire.com/state-of-security/security-data-protection/cloud/public-aws-s3-buckets-writable/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - AWS S3 Bucket details via bucketName", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History"] +searches = ["ESCU - Detect S3 access from a new IP - Rule", "ESCU - Detect Spike in S3 Bucket deletion - Rule", "ESCU - Detect New Open S3 buckets - Rule", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Investigate AWS activities via region name", "ESCU - Get Notable History", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get Notable Info", "ESCU - AWS S3 Bucket details via bucketName"] description = Use the searches in this Analytic Story to monitor your AWS S3 buckets for evidence of anomalous activity and suspicious behaviors, such as detecting open S3 buckets and buckets being accessed from a new IP. The contextual and investigative searches will give you more information, when required. narrative = As cloud computing has exploded, so has the number of creative attacks on virtual environments. And as the number-two cloud-service provider, Amazon Web Services (AWS) has certainly had its share.\ Amazon's "shared responsibility" model dictates that the company has responsibility for the environment outside of the VM and the customer is responsible for the security inside of the S3 container. As such, it's important to stay vigilant for activities that may belie suspicious behavior inside of your environment.\ @@ -673,7 +673,7 @@ version = 1 references = ["https://rhinosecuritylabs.com/aws/hiding-cloudcobalt-strike-beacon-c2-using-amazon-apis/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - AWS Network ACL Details from ID", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule", "ESCU - AWS Network ACL Details from ID", "ESCU - Get DNS Server History for a host", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get All AWS Activity From IP Address", "ESCU - Get DNS traffic ratio", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - AWS Network Interface details via resourceId", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Leverage these searches to monitor your AWS network traffic for evidence of anomalous activity and suspicious behaviors, such as a spike in blocked outbound traffic in your virtual private cloud (VPC). narrative = A virtual private cloud (VPC) is an on-demand managed cloud-computing service that isolates computing resources for each client. Inside the VPC container, the environment resembles a physical network. \ Amazon's VPC service enables you to launch EC2 instances and leverage other Amazon resources. The traffic that flows in and out of this VPC can be controlled via network access-control rules and security groups. Amazon also has a feature called VPC Flow Logs that enables you to log IP traffic going to and from the network interfaces in your VPC. This data is stored using Amazon CloudWatch Logs.\ @@ -687,7 +687,7 @@ version = 2 references = ["https://attack.mitre.org/wiki/Technique/T1059", "https://www.microsoft.com/en-us/wdsi/threats/macro-malware", "https://www.fireeye.com/content/dam/fireeye-www/services/pdfs/mandiant-apt1-report.pdf"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - First time seen command line argument - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Leveraging the Windows command-line interface (CLI) is one of the most common attack techniques--one that is also detailed in the MITRE ATT&CK framework. Use this Analytic Story to help you identify unusual or suspicious use of the CLI on Windows systems. narrative = The ability to execute arbitrary commands via the Windows CLI is a primary goal for the adversary. With access to the shell, an attacker can easily run scripts and interact with the target system. Often, attackers may only have limited access to the shell or may obtain access in unusual ways. In addition, malware may execute and interact with the CLI in ways that would be considered unusual and inconsistent with typical user activity. This provides defenders with opportunities to identify suspicious use and investigate, as appropriate. This Analytic Story contains various searches to help identify this suspicious activity, as well as others to aid you in deeper investigation. @@ -698,7 +698,7 @@ version = 1 references = ["http://blogs.splunk.com/2015/10/01/random-words-on-entropy-and-dns/", "http://www.darkreading.com/analytics/security-monitoring/got-malware-three-signs-revealed-in-dns-traffic/d/d-id/1139680", "https://live.paloaltonetworks.com/t5/Threat-Vulnerability-Articles/What-are-suspicious-DNS-queries/ta-p/71454"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect hosts connecting to dynamic domain providers - Rule", "ESCU - DNS Query Length Outliers - MLTK - Rule", "ESCU - Detection of DNS Tunnels - Rule", "ESCU - DNS Query Length With High Standard Deviation - Rule", "ESCU - Detect Long DNS TXT Record Response - Rule", "ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule", "ESCU - Excessive DNS Failures - Rule", "ESCU - Clients Connecting to Multiple DNS Servers - Rule", "ESCU - Get DNS Server History for a host", "ESCU - Get Process Responsible For The DNS Traffic", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get DNS traffic ratio", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Attackers often attempt to hide within or otherwise abuse the domain name system (DNS). You can thwart attempts to manipulate this omnipresent protocol by monitoring for these types of abuses. narrative = Although DNS is one of the fundamental underlying protocols that make the Internet work, it is often ignored (perhaps because of its complexity and effectiveness). However, attackers have discovered ways to abuse the protocol to meet their objectives. One potential abuse involves manipulating DNS to hijack traffic and redirect it to an IP address under the attacker's control. This could inadvertently send users intending to visit google.com, for example, to an unrelated malicious website. Another technique involves using the DNS protocol for command-and-control activities with the attacker's malicious code or to covertly exfiltrate data. The searches within this Analytic Story look for these types of abuses. @@ -709,7 +709,7 @@ version = 1 references = ["https://www.splunk.com/blog/2015/06/26/phishing-hits-a-new-level-of-quality/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Emails From Specific Sender", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Email Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Notable History"] +searches = ["ESCU - Email Attachments With Lots Of Spaces - Rule", "ESCU - Suspicious Email - UBA Anomaly - Rule", "ESCU - Suspicious Email Attachment Extensions - Rule", "ESCU - Monitor Email For Brand Abuse - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Email Info", "ESCU - Get User Information from Identity Table"] description = Email remains one of the primary means for attackers to gain an initial foothold within the modern enterprise. Detect and investigate suspicious emails in your environment with the help of the searches in this Analytic Story. narrative = It is a common practice for attackers of all types to leverage targeted spearphishing campaigns and mass mailers to deliver weaponized email messages and attachments. Fortunately, there are a number of ways to monitor email data in Splunk to detect suspicious content.\ Once a phishing message has been detected, the next steps are to answer the following questions: \ @@ -724,7 +724,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5", "https://attack.mitre.org/wiki/Technique/T1170"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect Prohibited Applications Spawning cmd exe - Rule", "ESCU - Detect mshta exe running scripts in command-line arguments - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor and detect techniques used by attackers who leverage the mshta.exe process to execute malicious code. narrative = One common adversary tactic is to bypass application white-listing solutions via the mshta.exe process, which executes Microsoft HTML applications with the .hta suffix. In these cases, attackers use the trusted Windows utility to eproxy execution of malicious files, whether an .hta application, javascript, or VBScript.\ One example of a notable mshta.exe attack was the Kovter malware (https://medium.com/@mbromileyDFIR/malware-monday-aebb456356c5) that was implicated in ransomware and click-fraud attacks. Kovter utilized .hta to execute a series of javascript commands, each progressively more dangerous. According to the Mitre Parternship Network (https://attack.mitre.org/wiki/Technique/T1170), FIN7 has leveraged mshta.exe, as has the MuddyWater group, who used it to execute its POWERSTATS payload (which then used the utility to execute additional payloads).\ @@ -737,7 +737,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Technique/T1078", "https://owasp.org/www-community/attacks/Credential_stuffing", "https://searchsecurity.techtarget.com/answer/What-is-a-password-spraying-attack-and-how-does-it-work"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app", "ESCU - Investigate User Activities In Okta"] +searches = ["ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule", "ESCU - Okta Failed SSO Attempts - Rule", "ESCU - Okta Account Lockout Events - Rule", "ESCU - Okta User Logins From Multiple Cities - Rule", "ESCU - Investigate User Activities In Okta", "ESCU - Investigate Okta Activity by IP Address", "ESCU - Investigate Okta Activity by app"] description = Monitor your Okta environment for suspicious activities. Due to the Covid outbreak, many users are migrating over to leverage cloud services more and more. Okta is a popular tool to manage multiple users and the web-based applications they need to stay productive. The searches in this story will help monitor your Okta environment for suspicious activities and associated user behaviors. narrative = Okta is the leading single sign on (SSO) provider, allowing users to authenticate once to Okta, and from there access a variety of web-based applications. These applications are assigned to users and allow administrators to centrally manage which users are allowed to access which applications. It also provides centralized logging to help understand how the applications are used and by whom. \ While SSO is a major convenience for users, it also provides attackers with an opportunity. If the attacker can gain access to Okta, they can access a variety of applications. As such monitoring the environment is important. \ @@ -750,7 +750,7 @@ version = 2 references = ["https://www.blackhat.com/docs/us-15/materials/us-15-Graeber-Abusing-Windows-Management-Instrumentation-WMI-To-Build-A-Persistent%20Asynchronous-And-Fileless-Backdoor-wp.pdf", "https://www.fireeye.com/blog/threat-research/2017/03/wmimplant_a_wmi_ba.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Process Execution via WMI - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Process Execution via WMI - Rule", "ESCU - Script Execution via WMI - Rule", "ESCU - Remote WMI Command Attempt - Rule", "ESCU - Remote Process Instantiation via WMI - Rule", "ESCU - WMI Permanent Event Subscription - Sysmon - Rule", "ESCU - WMI Temporary Event Subscription - Rule", "ESCU - WMI Permanent Event Subscription - Rule", "ESCU - Get Sysmon WMI Activity for Host", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Attackers are increasingly abusing Windows Management Instrumentation (WMI), a framework and associated utilities available on all modern Windows operating systems. Because WMI can be leveraged to manage both local and remote systems, it is important to identify the processes executed and the user context within which the activity occurred. narrative = WMI is a Microsoft infrastructure for management data and operations on Windows operating systems. It includes of a set of utilities that can be leveraged to manage both local and remote Windows systems. Attackers are increasingly turning to WMI abuse in their efforts to conduct nefarious tasks, such as reconnaissance, detection of antivirus and virtual machines, code execution, lateral movement, persistence, and data exfiltration. \ The detection searches included in this Analytic Story are used to look for suspicious use of WMI commands that attackers may leverage to interact with remote systems. The searches specifically look for the use of WMI to run processes on remote systems.\ @@ -763,7 +763,7 @@ version = 1 references = ["https://redcanary.com/blog/windows-registry-attacks-threat-detection/", "https://attack.mitre.org/wiki/Technique/T1112"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor and detect registry changes initiated from remote locations, which can be a sign that an attacker has infiltrated your system. narrative = Attackers are developing increasingly sophisticated techniques for hijacking target servers, while evading detection. One such technique that has become progressively more common is registry modification.\ The registry is a key component of the Windows operating system. It has a hierarchical database called "registry" that contains settings, options, and values for executables. Once the threat actor gains access to a machine, they can use reg.exe to modify their account to obtain administrator-level privileges, maintain persistence, and move laterally within the environment.\ @@ -776,7 +776,7 @@ version = 1 references = ["https://d0.awsstatic.com/whitepapers/aws-security-best-practices.pdf"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get EC2 Instance Details by instanceId", "ESCU - Get Notable History"] +searches = ["ESCU - EC2 Instance Modified With Previously Unseen User - Rule", "ESCU - AWS Investigate User Activities By ARN", "ESCU - Get Notable History", "ESCU - Get EC2 Instance Details by instanceId"] description = Identify unusual changes to your AWS EC2 instances that may indicate malicious activity. Modifications to your EC2 instances by previously unseen users is an example of an activity that may warrant further investigation. narrative = A common attack technique is to infiltrate a cloud instance and make modifications. The adversary can then secure access to your infrastructure or hide their activities. So it's important to stay alert to changes that may indicate that your environment has been compromised. \ Searches within this Analytic Story can help you detect the presence of a threat by monitoring for EC2 instances that have been created or changed--either by users that have never previously performed these activities or by known users who modify or create instances in a way that have not been done before. This story also provides investigative searches that help you go deeper once you detect suspicious behavior. @@ -788,7 +788,7 @@ version = 2 references = ["https://www.fireeye.com/blog/threat-research/2017/08/monitoring-windows-console-activity-part-two.html", "https://www.splunk.com/pdfs/technical-briefs/advanced-threat-detection-and-response-tech-brief.pdf", "https://www.sans.org/reading-room/whitepapers/logging/detecting-security-incidents-windows-workstation-event-logs-34262"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Detect Rare Executables - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Detect processes used for System Network Configuration Discovery - Rule", "ESCU - System Processes Run From Unexpected Locations - Rule", "ESCU - Detect Rare Executables - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Unusually Long Command Line - MLTK - Rule", "ESCU - Unusually Long Command Line - Rule", "ESCU - RunDLL Loading DLL By Ordinal - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Quickly identify systems running new or unusual processes in your environment that could be indicators of suspicious activity. Processes run from unusual locations, those with conspicuously long command lines, and rare executables are all examples of activities that may warrant deeper investigation. narrative = Being able to profile a host's processes within your environment can help you more quickly identify processes that seem out of place when compared to the rest of the population of hosts or asset types.\ This Analytic Story lets you identify processes that are either a) not typically seen running or b) have some sort of suspicious command-line arguments associated with them. This Analytic Story will also help you identify the user running these processes and the associated process activity on the host.\ @@ -801,7 +801,7 @@ version = 1 references = ["https://www.monkey.org/~dugsong/dsniff/"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Notable History"] +searches = ["ESCU - Protocols passing authentication in cleartext - Rule", "ESCU - Get Notable History", "ESCU - Get Risk Modifiers For User", "ESCU - Get Process Information For Port Activity", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table"] description = Leverage searches that detect cleartext network protocols that may leak credentials or should otherwise be encrypted. narrative = Various legacy protocols operate by default in the clear, without the protections of encryption. This potentially leaks sensitive information that can be exploited by passively sniffing network traffic. Depending on the protocol, this information could be highly sensitive, or could allow for session hijacking. In addition, these protocols send authentication information, which would allow for the harvesting of usernames and passwords that could potentially be used to authenticate and compromise secondary systems. @@ -812,7 +812,7 @@ version = 1 references = ["https://www.fbi.gov/scams-and-safety/common-fraud-schemes/internet-fraud", "https://www.fbi.gov/news/stories/2017-internet-crime-report-released-050718"] maintainers = "Jim Apger, Splunk" spec_version = 3 -searches = ["ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get Web Session Information via session id", "ESCU - Get Emails From Specific Sender", "ESCU - Get Notable History"] +searches = ["ESCU - Web Fraud - Anomalous User Clickspeed - Rule", "ESCU - Web Fraud - Account Harvesting - Rule", "ESCU - Web Fraud - Password Sharing Across Accounts - Rule", "ESCU - Get Notable Info", "ESCU - Get Notable History", "ESCU - Get Emails From Specific Sender", "ESCU - Get Web Session Information via session id"] description = Monitor your environment for activity consistent with common attack techniques bad actors use when attempting to compromise web servers or other web-related assets. narrative = The Federal Bureau of Investigations (FBI) defines Internet fraud as the use of Internet services or software with Internet access to defraud victims or to otherwise take advantage of them. According to the Bureau, Internet crime schemes are used to steal millions of dollars each year from victims and continue to plague the Internet through various methods. The agency includes phishing scams, data breaches, Denial of Service (DOS) attacks, email account compromise, malware, spoofing, and ransomware in this category.\ These crimes are not the fraud itself, but rather the attack techniques commonly employed by fraudsters in their pursuit of data that enables them to commit malicious actssuch as obtaining and using stolen credit cards. They represent a serious problem that is steadily increasing and not likely to go away anytime soon.\ @@ -828,7 +828,7 @@ version = 1 references = ["https://attack.mitre.org/wiki/Defense_Evasion"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Suspicious Reg exe Process - Rule", "ESCU - Disabling Remote User Account Control - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Detect tactics used by malware to evade defenses on Windows endpoints. A few of these include suspicious `reg.exe` processes, files hidden with `attrib.exe` and disabling user-account control, among many others narrative = Defense evasion is a tactic--identified in the MITRE ATT&CK framework--that adversaries employ in a variety of ways to bypass or defeat defensive security measures. There are many techniques enumerated by the MITRE ATT&CK framework that are applicable in this context. This Analytic Story includes searches designed to identify the use of such techniques on Windows platforms. @@ -839,7 +839,7 @@ version = 1 references = ["https://blog.malwarebytes.com/cybercrime/2013/12/file-extensions-2/", "https://attack.mitre.org/wiki/Technique/T1042"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Execution of File with Multiple Extensions - Rule", "ESCU - Suspicious Changes to File Associations - Rule", "ESCU - Execution of File With Spaces Before Extension - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Detect and investigate suspected abuse of file extensions and Windows file associations. Some of the malicious behaviors involved may include inserting spaces before file extensions or prepending the file extension with a different one, among other techniques. narrative = Attackers use a variety of techniques to entice users to run malicious code or to persist on an endpoint. One way to accomplish these goals is to leverage file extensions and the mechanism Windows uses to associate files with specific applications. \ Since its earliest days, Windows has used extensions to identify file types. Users have become familiar with these extensions and their application associations. For example, if users see that a file ends in `.doc` or `.docx`, they will assume that it is a Microsoft Word document and expect that double-clicking will open it using `winword.exe`. The user will typically also presume that the `.docx` file is safe. \ @@ -854,7 +854,7 @@ version = 2 references = ["https://www.crowdstrike.com/blog/bears-midst-intrusion-democratic-national-committee/", "https://zeltser.com/security-incident-log-review-checklist/", "http://journeyintoir.blogspot.com/2013/01/re-introducing-usnjrnl.html"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable History"] +searches = ["ESCU - Windows Event Log Cleared - Rule", "ESCU - USN Journal Deletion - Rule", "ESCU - Deleting Shadow Copies - Rule", "ESCU - Suspicious wevtutil Usage - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Vulnerability Logs For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Adversaries often try to cover their tracks by manipulating Windows logs. Use these searches to help you monitor for suspicious activity surrounding log files--an essential component of an effective defense. narrative = Because attackers often modify system logs to cover their tracks and/or to thwart the investigative process, log monitoring is an industry-recognized best practice. While there are legitimate reasons to manipulate system logs, it is still worthwhile to keep track of who manipulated the logs, when they manipulated them, and in what way they manipulated them (determining which accesses, tools, or utilities were employed). Even if no malicious activity is detected, the knowledge of an attempt to manipulate system logs may be indicative of a broader security risk that should be thoroughly investigated.\ The Analytic Story gives users two different ways to detect manipulation of Windows Event Logs and one way to detect deletion of the Update Sequence Number (USN) Change Journal. The story helps determine the history of the host and the users who have accessed it. Finally, the story aides in investigation by retrieving all the information on the process that caused these events (if the process has been identified). @@ -866,7 +866,7 @@ version = 2 references = ["http://www.fuzzysecurity.com/tutorials/19.html", "https://www.fireeye.com/blog/threat-research/2010/07/malware-persistence-windows-registry.html", "http://resources.infosecinstitute.com/common-malware-persistence-mechanisms/", "https://www.fireeye.com/blog/threat-research/2017/05/fin7-shim-databases-persistence.html", "https://www.youtube.com/watch?v=dq2Hv7J9fvk"] maintainers = "Bhavin Patel, Splunk" spec_version = 3 -searches = ["ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Registry Keys for Creating SHIM Databases - Rule", "ESCU - Detect Path Interception By Creation Of program exe - Rule", "ESCU - Reg exe used to hide files directories via registry keys - Rule", "ESCU - Monitor Registry Keys for Print Monitors - Rule", "ESCU - Schtasks used for forcing a reboot - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Registry Keys Used For Persistence - Rule", "ESCU - Hiding Files And Directories With Attrib exe - Rule", "ESCU - Shim Database File Creation - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Shim Database Installation With Suspicious Parameters - Rule", "ESCU - Remote Registry Key modifications - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor for activities and techniques associated with maintaining persistence on a Windows system--a sign that an adversary may have compromised your environment. narrative = Maintaining persistence is one of the first steps taken by attackers after the initial compromise. Attackers leverage various custom and built-in tools to ensure survivability and persistent access within a compromised enterprise. This Analytic Story provides searches to help you identify various behaviors used by attackers to maintain persistent access to a Windows environment. @@ -877,7 +877,7 @@ version = 2 references = ["https://attack.mitre.org/tactics/TA0004/"] maintainers = "David Dorsey, Splunk" spec_version = 3 -searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Registry Activities", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Investigate Web Activity From Host", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Overwriting Accessibility Binaries - Rule", "ESCU - Registry Keys Used For Privilege Escalation - Rule", "ESCU - Uncommon Processes On Endpoint - Rule", "ESCU - Child Processes of Spoolsv exe - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Investigate Web Activity From Host", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table", "ESCU - Get Registry Activities"] description = Monitor for and investigate activities that may be associated with a Windows privilege-escalation attack, including unusual processes running on endpoints, modified registry keys, and more. narrative = Privilege escalation is a "land-and-expand" technique, wherein an adversary gains an initial foothold on a host and then exploits its weaknesses to increase his privileges. The motivation is simple: certain actions on a Windows machine--such as installing software--may require higher-level privileges than those the attacker initially acquired. By increasing his privilege level, the attacker can gain the control required to carry out his malicious ends. This Analytic Story provides searches to detect and investigate behaviors that attackers may use to elevate their privileges in your environment. @@ -888,7 +888,7 @@ version = 3 references = ["https://attack.mitre.org/wiki/Technique/T1050", "https://attack.mitre.org/wiki/Technique/T1031"] maintainers = "Rico Valdez, Splunk" spec_version = 3 -searches = ["ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Notable Info", "ESCU - Get User Information from Identity Table", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get Risk Modifiers For User", "ESCU - Get Parent Process Info", "ESCU - Get Process Info", "ESCU - Get Notable History"] +searches = ["ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule", "ESCU - Sc exe Manipulating Windows Services - Rule", "ESCU - First Time Seen Running Windows Service - Rule", "ESCU - Get Parent Process Info", "ESCU - Get Notable History", "ESCU - Get Process Info", "ESCU - Get Risk Modifiers For User", "ESCU - Get Risk Modifiers For Endpoint", "ESCU - Get Notable Info", "ESCU - Get Authentication Logs For Endpoint", "ESCU - Get User Information from Identity Table"] description = Windows services are often used by attackers for persistence and the ability to load drivers or otherwise interact with the Windows kernel. This Analytic Story helps you monitor your environment for indications that Windows services are being modified or created in a suspicious manner. narrative = The Windows operating system uses a services architecture to allow for running code in the background, similar to a UNIX daemon. Attackers will often leverage Windows services for persistence, hiding in plain sight, seeking the ability to run privileged code that can interact with the kernel. In many cases, attackers will create a new service to host their malicious code. Attackers have also been observed modifying unnecessary or unused services to point to their own code, as opposed to what was intended. In these cases, attackers often use tools to create or modify services in ways that are not typical for most environments, providing opportunities for detection. @@ -898,7 +898,7 @@ narrative = The Windows operating system uses a services architecture to allow f [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen City - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen cities. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. @@ -909,7 +909,7 @@ providing_technologies = none [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen Country - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen countries. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. @@ -920,7 +920,7 @@ providing_technologies = none [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen IP Address - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen IP addresses. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. @@ -931,7 +931,7 @@ providing_technologies = none [savedsearch://ESCU - AWS Cloud Provisioning From Previously Unseen Region - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for AWS provisioning activities from previously unseen regions. Region in this context is similar to a state in the United States. Provisioning activities are defined broadly as any event that begins with "Run" or "Create." how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen AWS Provisioning Activity Sources" support search once to create a history of previously seen locations that have provisioned AWS resources. @@ -942,7 +942,7 @@ providing_technologies = none [savedsearch://ESCU - AWS Cross Account Activity From Previously Unseen Account - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the `Previously Seen AWS Cross Account Activity` support search only once to create the baseline of previously seen cross account activity. Thanks to Pablo Vega at Recurly for suggesting improvements to the search. @@ -952,7 +952,7 @@ providing_technologies = none [savedsearch://ESCU - AWS Network Access Control List Created with All Open Ports - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = The search looks for CloudTrail events to detect if any network ACLs were created with all the ports open to a specified CIDR. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS, version 4.4.0 or later, and configure your CloudTrail inputs. @@ -962,7 +962,7 @@ providing_technologies = none [savedsearch://ESCU - AWS Network Access Control List Deleted - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = Enforcing network-access controls is one of the defensive mechanisms used by cloud administrators to restrict access to a cloud instance. After the attacker has gained control of the AWS console by compromising an admin account, they can delete a network ACL and gain access to the instance from anywhere. This search will query the CloudTrail logs to detect users deleting network ACLs. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. @@ -972,7 +972,7 @@ providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Launched by User - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. @@ -982,7 +982,7 @@ providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Launched by User - MLTK - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events where a user successfully launches an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. @@ -992,7 +992,7 @@ providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Terminated by User - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events where an abnormally high number of instances were successfully terminated by a user in a 10-minute window how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. @@ -1002,7 +1002,7 @@ providing_technologies = none [savedsearch://ESCU - Abnormally High AWS Instances Terminated by User - MLTK - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events where a user successfully terminates an abnormally high number of instances. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. The threshold value should be tuned to your environment. @@ -1012,7 +1012,7 @@ providing_technologies = none [savedsearch://ESCU - Access LSASS Memory for Dump Creation - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = Detect memory dumping of the LSASS process. how_to_implement = This search requires Sysmon Logs and a Sysmon configuration, which includes EventCode 10 for lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. @@ -1022,7 +1022,7 @@ providing_technologies = none [savedsearch://ESCU - Amazon EKS Kubernetes Pod scan detection - Rule] type = detection -asset_type = +asset_type = Amazon EKS Kubernetes cluster Pod confidence = medium explanation = This search provides detection information on unauthenticated requests against Kubernetes' Pods API how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on forAWS (version 4.4.0 or later), then configure your AWS CloudWatch EKS Logs.Please also customize the `kubernetes_pods_aws_scan_fingerprint_detection` macro to filter out the false positives. @@ -1032,7 +1032,7 @@ providing_technologies = none [savedsearch://ESCU - Amazon EKS Kubernetes cluster scan detection - Rule] type = detection -asset_type = +asset_type = Amazon EKS Kubernetes cluster confidence = medium explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster in AWS how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudWatch EKS Logs inputs. @@ -1042,7 +1042,7 @@ providing_technologies = none [savedsearch://ESCU - Attempt To Add Certificate To Untrusted Store - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Attempt to add a certificate to the untrusted certificate store how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1052,7 +1052,7 @@ providing_technologies = none [savedsearch://ESCU - Attempt To Set Default PowerShell Execution Policy To Unrestricted or Bypass - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Monitor for changes of the ExecutionPolicy in the registry to the values "unrestricted" or "bypass," which allows the execution of malicious scripts. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Registry node. You must also be ingesting logs with the fields registry_path, registry_key_name, and registry_value_name from your endpoints. @@ -1062,7 +1062,7 @@ providing_technologies = none [savedsearch://ESCU - Attempt To Stop Security Service - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for attempts to stop security-related services on the endpoint. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. The search is shipped with a lookup file, `security_services.csv`, that can be edited to update the list of services to monitor. This lookup file can be edited directly where it lives in `$SPLUNK_HOME/etc/apps/DA-ESS-ContentUpdate/lookups`, or via the Splunk console. You should add the names of services an attacker might use on the command line and surround with asterisks (*****), so that they work properly when searching the command line. The file should be updated with the names of any services you would like to monitor for attempts to stop the service., @@ -1072,7 +1072,7 @@ providing_technologies = none [savedsearch://ESCU - Attempted Credential Dump From Registry via Reg exe - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Monitor for execution of reg.exe with parameters specifying an export of keys that contain hashed credentials that attackers may try to crack offline. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1082,7 +1082,7 @@ providing_technologies = none [savedsearch://ESCU - Batch File Write to System32 - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for a batch file (.bat) written to the Windows system directory tree. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -1092,7 +1092,7 @@ providing_technologies = none [savedsearch://ESCU - Child Processes of Spoolsv exe - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for child processes of spoolsv.exe. This activity is associated with a POC privilege-escalation exploit associated with CVE-2018-8440. Spoolsv.exe is the process associated with the Print Spooler service in Windows and typically runs as SYSTEM. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. Update the `children_of_spoolsv_filter` macro to filter out legitimate child processes spawned by spoolsv.exe. @@ -1102,7 +1102,7 @@ providing_technologies = none [savedsearch://ESCU - Clients Connecting to Multiple DNS Servers - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search. how_to_implement = This search requires that DNS data is being ingested and populating the `Network_Resolution` data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.\ @@ -1114,7 +1114,7 @@ providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Created By Previously Unseen User - Rule] type = detection -asset_type = +asset_type = Cloud Compute Instance confidence = medium explanation = This search looks for cloud compute instances created by users who have not created them before. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Creations By User" support search to create of baseline of previously seen users. @@ -1124,7 +1124,7 @@ providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Created With Previously Unseen Image - Rule] type = detection -asset_type = +asset_type = Cloud Compute Instance confidence = medium explanation = This search looks for cloud compute instances being created with previously unseen image IDs. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the "Previously Seen Cloud Compute Images" support search to create a baseline of previously seen images. @@ -1134,7 +1134,7 @@ providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Created With Previously Unseen Instance Type - Rule] type = detection -asset_type = +asset_type = Cloud Compute Instance confidence = medium explanation = Find EC2 instances being created with previously unseen instance types. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the " Previously Seen Cloud Compute Instance Types" support search to create a baseline of previously seen regions. @@ -1144,7 +1144,7 @@ providing_technologies = none [savedsearch://ESCU - Cloud Compute Instance Started In Previously Unused Region - Rule] type = detection -asset_type = +asset_type = Cloud Compute Instance confidence = medium explanation = This search looks at cloud-infrastructure events where an instance is created in any region within the last hour and then compares it to a lookup file of previously seen regions where instances have been created. how_to_implement = You must be ingesting the appropriate cloud-infrastructure logs and have the Security Research cloud data model (https://github.com/splunk/cloud-datamodel-security-research/) installed. Run the \"Previously Seen Cloud Compute Instance Types\" support search to create a baseline of previously seen regions. @@ -1154,7 +1154,7 @@ providing_technologies = none [savedsearch://ESCU - Common Ransomware Extensions - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for file modifications with extensions commonly used by Ransomware how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data.\ @@ -1168,7 +1168,7 @@ providing_technologies = none [savedsearch://ESCU - Common Ransomware Notes - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for files created with names matching those typically used in ransomware notes that tell the victim how to get their data back. how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint Filesystem data-model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. @@ -1178,7 +1178,7 @@ providing_technologies = none [savedsearch://ESCU - Create Remote Thread into LSASS - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = Detect remote thread creation into LSASS consistent with credential dumping. how_to_implement = This search needs Sysmon Logs with a Sysmon configuration, which includes EventCode 8 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. @@ -1188,7 +1188,7 @@ providing_technologies = none [savedsearch://ESCU - Create local admin accounts using net exe - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the creation of local administrator accounts using net.exe. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1198,7 +1198,7 @@ providing_technologies = none [savedsearch://ESCU - Create or delete windows shares using net exe - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the creation or deletion of hidden shares using net.exe. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1208,7 +1208,7 @@ providing_technologies = none [savedsearch://ESCU - Creation of Shadow Copy - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Monitor for signs that Ntdsutil, Vssadmin, or Wmic has been used to create a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1218,7 +1218,7 @@ providing_technologies = none [savedsearch://ESCU - Creation of Shadow Copy with wmic and powershell - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search detects the use of wmic and Powershell to create a shadow copy. how_to_implement = You must enable Powershell scriptblock logging in order to detect this attack.This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. @@ -1228,7 +1228,7 @@ providing_technologies = none [savedsearch://ESCU - Credential Dumping via Copy Command from Shadow Copy - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search detects credential dumping using copy command from a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1238,7 +1238,7 @@ providing_technologies = none [savedsearch://ESCU - Credential Dumping via Symlink to Shadow Copy - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search detects the creation of a symlink to a shadow copy. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1248,7 +1248,7 @@ providing_technologies = none [savedsearch://ESCU - DNS Query Length Outliers - MLTK - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search allows you to identify DNS requests that are unusually large for the record type being requested in your environment. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of DNS Query Length - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ @@ -1264,7 +1264,7 @@ providing_technologies = none [savedsearch://ESCU - DNS Query Length With High Standard Deviation - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. @@ -1274,7 +1274,7 @@ providing_technologies = none [savedsearch://ESCU - DNS Query Requests Resolved by Unauthorized DNS Servers - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search will detect DNS requests resolved by unauthorized DNS servers. Legitimate DNS servers should be identified in the Enterprise Security Assets and Identity Framework. how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the Network_Resolution data model. It also requires that your DNS servers are identified correctly in the Assets and Identity table of Enterprise Security. @@ -1284,7 +1284,7 @@ providing_technologies = none [savedsearch://ESCU - DNS record changed - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search takes the DNS records and their answers results of the discovered_dns_records lookup and finds if any records have changed by searching DNS response from the Network_Resolution datamodel across the last day. how_to_implement = To successfully implement this search you will need to ensure that DNS data is populating the `Network_Resolution` data model. It also requires that the `discover_dns_record` lookup table be populated by the included support search "Discover DNS record". \ @@ -1298,7 +1298,7 @@ providing_technologies = none [savedsearch://ESCU - Deleting Shadow Copies - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The vssadmin.exe utility is used to interact with the Volume Shadow Copy Service. Wmic is an interface to the Windows Management Instrumentation. This search looks for either of these tools being used to delete shadow copies. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1308,7 +1308,7 @@ providing_technologies = none [savedsearch://ESCU - Detect API activity from users without MFA - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events where a user logged into the AWS account, is making API calls and has not enabled Multi Factor authentication. Multi factor authentication adds a layer of security by forcing the users to type a unique authentication code from an approved authentication device when they access AWS websites or services. AWS Best Practices recommend that you enable MFA for privileged IAM users. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Leverage the support search `Create a list of approved AWS service accounts`: run it once every 30 days to create a list of service accounts and validate them.\ @@ -1324,7 +1324,7 @@ providing_technologies = none [savedsearch://ESCU - Detect AWS API Activities From Unapproved Accounts - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for successful CloudTrail activity by user accounts that are not listed in the identity table or `aws_service_accounts.csv`. It returns event names and count, as well as the first and last time a specific user or service is detected, grouped by users. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also populate the `identity_lookup_expanded` lookup shipped with the Asset and Identity framework to be able to look up users in your identity table in Enterprise Security (ES). Leverage the support search called "Create a list of approved AWS service accounts": run it once every 30 days to create and validate a list of service accounts.\ @@ -1340,7 +1340,7 @@ providing_technologies = none [savedsearch://ESCU - Detect AWS Console Login by User from New City - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. @@ -1350,7 +1350,7 @@ providing_technologies = none [savedsearch://ESCU - Detect AWS Console Login by User from New Country - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. @@ -1360,7 +1360,7 @@ providing_technologies = none [savedsearch://ESCU - Detect AWS Console Login by User from New Region - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. @@ -1370,7 +1370,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Activity Related to Pass the Hash Attacks - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for specific authentication events from the Windows Security Event logs to detect potential attempts at using the Pass-the-Hash technique. how_to_implement = To successfully implement this search, you must ingest your Windows Security Event logs and leverage the latest TA for Windows. @@ -1380,7 +1380,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Credential Dumping through LSASS access - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search looks for reading lsass memory consistent with credential dumping. how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 10 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. @@ -1390,7 +1390,7 @@ providing_technologies = none [savedsearch://ESCU - Detect DNS requests to Phishing Sites leveraging EvilGinx2 - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for DNS requests for phishing domains that are leveraging EvilGinx tools to mimic websites. how_to_implement = You need to ingest data from your DNS logs in the Network_Resolution datamodel. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You will have to add legitimate domain names to the `legit_domains.csv` file shipped with the app. \ @@ -1404,7 +1404,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Excessive Account Lockouts From Endpoint - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search identifies endpoints that have caused a relatively high number of account lockouts in a short period. how_to_implement = You must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. \ @@ -1418,7 +1418,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Excessive User Account Lockouts - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search detects user accounts that have been locked out a relatively high number of times in a short period. how_to_implement = ou must ingest your Windows security event logs in the `Change` datamodel under the nodename is `Account_Management`, for this search to execute successfully. Please consider updating the cron schedule and the count of lockouts you want to monitor, according to your environment. @@ -1428,7 +1428,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Large Outbound ICMP Packets - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for outbound ICMP packets with a packet size larger than 1,000 bytes. Various threat actors have been known to use ICMP as a command and control channel for their attack infrastructure. Large ICMP packets from an endpoint to a remote host may be indicative of this activity. how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have a good understanding of how your network segments are designed and that you are able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in the `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model @@ -1438,7 +1438,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Long DNS TXT Record Response - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search is used to detect attempts to use DNS tunneling, by calculating the length of responses to DNS TXT queries. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting unusually large volumes of DNS traffic. how_to_implement = To successfully implement this search you need to ingest data from your DNS logs, or monitor DNS traffic using Stream, Bro or something similar. Specifically, this query requires that the DNS data model is populated with information regarding the DNS record type that is being returned as well as the data in the answer section of the protocol. @@ -1448,7 +1448,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Mimikatz Using Loaded Images - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search looks for reading loaded Images unique to credential dumping with Mimikatz. how_to_implement = This search needs Sysmon Logs and a sysmon configuration, which includes EventCode 7 with powershell.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. @@ -1458,7 +1458,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Mimikatz Via PowerShell And EventCode 4703 - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search looks for PowerShell requesting privileges consistent with credential dumping. how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here: http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes. @@ -1468,7 +1468,7 @@ providing_technologies = none [savedsearch://ESCU - Detect New Local Admin account - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search looks for newly created accounts that have been elevated to local administrators. how_to_implement = You must be ingesting Windows Security logs. You must also enable the account change auditing here:http://docs.splunk.com/Documentation/Splunk/7.0.2/Data/MonitorWindowseventlogdata. Additionally, this search requires you to enable your Group Management Audit Logs in your Local Windows Security Policy and to be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/. Finally, please make sure that the local administrator group name is "Administrators" to be able to look for the right group membership changes.\ @@ -1484,7 +1484,7 @@ providing_technologies = none [savedsearch://ESCU - Detect New Login Attempts to Routers - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search queries the authentication logs for assets that are categorized as routers in the ES Assets and Identity Framework, to identify connections that have not been seen before in the last 30 days. how_to_implement = To successfully implement this search, you must ensure the network router devices are categorized as "router" in the Assets and identity table. You must also populate the Authentication data model with logs related to users authenticating to routing infrastructure. @@ -1494,7 +1494,7 @@ providing_technologies = none [savedsearch://ESCU - Detect New Open S3 buckets - Rule] type = detection -asset_type = +asset_type = S3 Bucket confidence = medium explanation = This search looks for CloudTrail events where a user has created an open/public S3 bucket. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), and then configure your CloudTrail inputs. The threshold value should be tuned to your environment. @@ -1504,7 +1504,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Oulook exe writing a zip file - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for execution of process `outlook.exe` where the process is writing a `.zip` file to the disk. how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. @@ -1514,7 +1514,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Outbound SMB Traffic - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for outbound SMB connections made by hosts within your network to the Internet. SMB traffic is used for Windows file-sharing activity. One of the techniques often used by attackers involves retrieving the credential hash using an SMB request made to a compromised server controlled by the threat actor. how_to_implement = In order to run this search effectively, we highly recommend that you leverage the Assets and Identity framework. It is important that you have good understanding of how your network segments are designed, and be able to distinguish internal from external address space. Add a category named `internal` to the CIDRs that host the company's assets in `assets_by_cidr.csv` lookup file, which is located in `$SPLUNK_HOME/etc/apps/SA-IdentityManagement/lookups/`. More information on updating this lookup can be found here: https://docs.splunk.com/Documentation/ES/5.0.0/Admin/Addassetandidentitydata. This search also requires you to be ingesting your network traffic and populating the Network_Traffic data model @@ -1534,7 +1534,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Prohibited Applications Spawning cmd exe - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for executions of cmd.exe spawned by a process that is often abused by attackers and that does not typically launch cmd.exe. how_to_implement = You must be ingesting data that records process activity from your hosts and populates the Endpoint data model with the resultant dataset. This search includes a lookup file, `prohibited_apps_launching_cmd.csv`, that contains a list of processes that should not be spawning cmd.exe. You can modify this lookup to better suit your environment. @@ -1544,7 +1544,7 @@ providing_technologies = none [savedsearch://ESCU - Detect PsExec With accepteula Flag - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for events where `PsExec.exe` is run with the `accepteula` flag in the command line. PsExec is a built-in Windows utility that enables you to execute processes on other systems. It is fully interactive for console applications. This tool is widely used for launching interactive command prompts on remote systems. Threat actors leverage this extensively for executing code on compromised systems. If an attacker is running PsExec for the first time, they will be prompted to accept the end-user license agreement (EULA), which can be passed as the argument `accepteula` within the command line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1554,7 +1554,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Rare Executables - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search will return a table of rare processes, the names of the systems running them, and the users who initiated each process. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts and populating the endpoint data model with the resultant dataset. The macro `filter_rare_process_whitelist` searches two lookup files to whitelist your processes. These consist of `rare_process_whitelist_default.csv` and `rare_process_whitelist_local.csv`. To add your own processes to the whitelist, add them to `rare_process_whitelist_local.csv`. If you wish to remove an entry from the default lookup file, you will have to modify the macro itself to set the whitelist value for that process to false. You can modify the limit parameter and search scheduling to better suit your environment. @@ -1564,7 +1564,7 @@ providing_technologies = none [savedsearch://ESCU - Detect S3 access from a new IP - Rule] type = detection -asset_type = +asset_type = S3 Bucket confidence = medium explanation = This search looks at S3 bucket-access logs and detects new or previously unseen remote IP addresses that have successfully accessed an S3 bucket. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your S3 access logs' inputs. This search works best when you run the "Previously Seen S3 Bucket Access by Remote IP" support search once to create a history of previously seen remote IPs and bucket names. @@ -1574,7 +1574,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Spike in AWS API Activity - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search will detect users creating spikes of API activity in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.\ @@ -1590,7 +1590,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Spike in Network ACL Activity - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search will detect users creating spikes in API activity related to network access-control lists (ACLs)in your AWS environment. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Network ACL Activity by ARN" support search once to create a lookup file of previously seen Network ACL Activity. To add or remove API event names related to network ACLs, edit the macro `network_acl_events`. @@ -1600,7 +1600,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Spike in S3 Bucket deletion - Rule] type = detection -asset_type = +asset_type = S3 Bucket confidence = medium explanation = This search detects users creating spikes in API activity related to deletion of S3 buckets in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of S3 Bucket deletion activity by ARN" support search once to create a baseline of previously seen S3 bucket-deletion activity. @@ -1610,7 +1610,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Spike in Security Group Activity - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search will detect users creating spikes in API activity related to security groups in your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the minimum number of data points required to have a statistically significant amount of data to determine. The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike.This search works best when you run the "Baseline of Security Group Activity by ARN" support search once to create a history of previously seen Security Group Activity. To add or remove API event names for security groups, edit the macro `security_group_api_calls`. @@ -1620,7 +1620,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Spike in blocked Outbound Traffic from your AWS - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search will detect spike in blocked outbound network connections originating from within your AWS environment. It will also update the cache file that factors in the latest data. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your VPC Flow logs. You can modify `dataPointThreshold` and `deviationThreshold` to better fit your environment. The `dataPointThreshold` variable is the number of data points required to meet the definition of "spike." The `deviationThreshold` variable is the number of standard deviations away from the mean that the value must be to be considered a spike. This search works best when you run the "Baseline of Blocked Outbound Connection" support search once to create a history of previously seen blocked outbound connections. @@ -1630,7 +1630,7 @@ providing_technologies = none [savedsearch://ESCU - Detect USB device insertion - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search is used to detect hosts that generate Windows Event ID 4663 for successful attempts to write to or read from a removable storage and Event ID 4656 for failures, which occurs when a USB drive is plugged in. In this scenario we are querying the Change_Analysis data model to look for Windows Event ID 4656 or 4663 where the priority of the affected host is marked as high in the ES Assets and Identity Framework. how_to_implement = To successfully implement this search, you must ingest Windows Security Event logs and track event code 4663 and 4656. Ensure that the field from the event logs is being mapped to the result_id field in the Change_Analysis data model. To minimize the alert volume, this search leverages the Assets and Identity framework to filter out events from those assets not marked high priority in the Enterprise Security Assets and Identity Framework. @@ -1640,7 +1640,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Unauthorized Assets by MAC address - Rule] type = detection -asset_type = +asset_type = Infrastructure confidence = medium explanation = By populating the organization's assets within the assets_by_str.csv, we will be able to detect unauthorized devices that are trying to connect with the organization's network by inspecting DHCP request packets, which are issued by devices when they attempt to obtain an IP address from the DHCP server. The MAC address associated with the source of the DHCP request is checked against the list of known devices, and reports on those that are not found. how_to_implement = This search uses the Network_Sessions data model shipped with Enterprise Security. It leverages the Assets and Identity framework to populate the assets_by_str.csv file located in SA-IdentityManagement, which will contain a list of known authorized organizational assets including their MAC addresses. Ensure that all inventoried systems have their MAC address populated. @@ -1650,7 +1650,7 @@ providing_technologies = none [savedsearch://ESCU - Detect Use of cmd exe to Launch Script Interpreters - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the execution of the cscript.exe or wscript.exe processes, with a parent of cmd.exe. The search will return the count, the first and last time this execution was seen on a machine, the user, and the destination of the machine how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -1660,7 +1660,7 @@ providing_technologies = none [savedsearch://ESCU - Detect attackers scanning for vulnerable JBoss servers - Rule] type = detection -asset_type = +asset_type = Web Server confidence = medium explanation = This search looks for specific GET or HEAD requests to web servers that are indicative of reconnaissance attempts to identify vulnerable JBoss servers. JexBoss is described as the exploit tool of choice for this malicious activity. how_to_implement = You must be ingesting data from the web server or network traffic that contains web specific information, and populating the Web data model. @@ -1670,7 +1670,7 @@ providing_technologies = none [savedsearch://ESCU - Detect hosts connecting to dynamic domain providers - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Malicious actors often abuse legitimate Dynamic DNS services to host malicious payloads or interactive command and control nodes. Attackers will automate domain resolution changes by routing dynamic domains to countless IP addresses to circumvent firewall blocks, blacklists as well as frustrate a network defenders analytic and investigative processes. This search will look for DNS queries made from within your infrastructure to suspicious dynamic domains. how_to_implement = First, you'll need to ingest data from your DNS operations. This can be done by ingesting logs from your server or data, collected passively by Splunk Stream or a similar solution. Specifically, data that contains the domain that is being queried and the IP of the host originating the request must be populating the `Network_Resolution` data model. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of Dynamic DNS providers. Please consider updating the local lookup periodically by adding new domains to the list of `dynamic_dns_providers_local.csv`.\ @@ -1686,7 +1686,7 @@ providing_technologies = none [savedsearch://ESCU - Detect malicious requests to exploit JBoss servers - Rule] type = detection -asset_type = +asset_type = Web Server confidence = medium explanation = This search is used to detect malicious HTTP requests crafted to exploit jmx-console in JBoss servers. The malicious requests have a long URL length, as the payload is embedded in the URL. how_to_implement = You must ingest data from the web server or capture network data that contains web specific information with solutions such as Bro or Splunk Stream, and populating the Web data model @@ -1696,7 +1696,7 @@ providing_technologies = none [savedsearch://ESCU - Detect mshta exe running scripts in command-line arguments - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the execution of "mshta.exe" with command-line arguments that launch a script. The search will return the first time and last time these command-line arguments were used for these executions, as well as the target system, the user, process "mshta.exe" and its parent process. how_to_implement = To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -1706,7 +1706,7 @@ providing_technologies = none [savedsearch://ESCU - Detect new API calls from user roles - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search detects new API calls that have either never been seen before or that have not been seen in the previous hour, where the identity type is `AssumedRole`. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously seen API call per user roles in CloudTrail" support search once to create a history of previously seen user roles. @@ -1716,7 +1716,7 @@ providing_technologies = none [savedsearch://ESCU - Detect new user AWS Console Login - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events wherein a console login event by a user was recorded within the last hour, then compares the event to a lookup file of previously seen users (by ARN values) who have logged into the console. The alert is fired if the user has logged into the console for the first time within the last hour how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen users in CloudTrail" support search only once to create a baseline of previously seen IAM users within the last 30 days. Run "Update previously seen users in CloudTrail" hourly (or more frequently depending on how often you run the detection searches) to refresh the baselines. @@ -1726,7 +1726,7 @@ providing_technologies = none [savedsearch://ESCU - Detect processes used for System Network Configuration Discovery - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for fast execution of processes used for system network configuration discovery on the endpoint. how_to_implement = You must be ingesting data that records registry activity from your hosts to populate the Endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report reads and writes to the registry or that are populated via Windows event logs, after enabling process tracking in your Windows audit settings. @@ -1736,7 +1736,7 @@ providing_technologies = none [savedsearch://ESCU - Detect web traffic to dynamic domain providers - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for web connections to dynamic DNS providers. how_to_implement = This search requires you to be ingesting web-traffic logs. You can obtain these logs from indexing data from a web proxy or by using a network-traffic-analysis tool, such as Bro or Splunk Stream. The web data model must contain the URL being requested, the IP address of the host initiating the request, and the destination IP. This search also leverages a lookup file, `dynamic_dns_providers_default.csv`, which contains a non-exhaustive list of dynamic DNS providers. Consider periodically updating this local lookup file with new domains.\ @@ -1748,7 +1748,7 @@ providing_technologies = none [savedsearch://ESCU - Detection of DNS Tunnels - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search is used to detect DNS tunneling, by calculating the sum of the length of DNS queries and DNS answers. The search also filters out potential false positives by filtering out queries made to internal systems and the queries originating from internal DNS, Web, and Email servers. Endpoints using DNS as a method of transmission for data exfiltration, command and control, or evasion of security controls can often be detected by noting an unusually large volume of DNS traffic. how_to_implement = To successfully implement this search, we must ensure that DNS data is being ingested and mapped to the appropriate fields in the Network_Resolution data model. Fields like src_category are automatically provided by the Assets and Identity Framework shipped with Splunk Enterprise Security. You will need to ensure you are using the Assets and Identity Framework and populating the src_category field. You will also need to enable the `cim_corporate_web_domain_search()` macro which will essentially filter out the DNS queries made to the corporate web domains to reduce alert fatigue. @@ -1758,7 +1758,7 @@ providing_technologies = none [savedsearch://ESCU - Detection of tools built by NirSoft - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for specific command-line arguments that may indicate the execution of tools made by Nirsoft, which are legitimate, but may be abused by attackers. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1768,7 +1768,7 @@ providing_technologies = none [savedsearch://ESCU - Disabling Remote User Account Control - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for modifications to registry keys that control the enforcement of Windows User Account Control (UAC). how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. @@ -1778,7 +1778,7 @@ providing_technologies = none [savedsearch://ESCU - Dump LSASS via comsvcs DLL - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Detect the usage of comsvcs.dll for dumping the lsass process. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints, to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -1788,7 +1788,7 @@ providing_technologies = none [savedsearch://ESCU - EC2 Instance Modified With Previously Unseen User - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for EC2 instances being modified by users who have not previously modified them. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. To add or remove APIs that modify an EC2 instance, edit the macro `ec2_modification_api_calls`. @@ -1798,7 +1798,7 @@ providing_technologies = none [savedsearch://ESCU - EC2 Instance Started In Previously Unseen Region - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for CloudTrail events where an instance is started in a particular region in the last one hour and then compares it to a lookup file of previously seen regions where an instance was started how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. Run the "Previously seen AWS Regions" support search only once to create of baseline of previously seen regions. @@ -1808,7 +1808,7 @@ providing_technologies = none [savedsearch://ESCU - EC2 Instance Started With Previously Unseen AMI - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for EC2 instances being created with previously unseen AMIs. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 AMIs" support search once to create a history of previously seen AMIs. @@ -1818,7 +1818,7 @@ providing_technologies = none [savedsearch://ESCU - EC2 Instance Started With Previously Unseen Instance Type - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for EC2 instances being created with previously unseen instance types. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Instance Types" support search once to create a history of previously seen instance types. @@ -1828,7 +1828,7 @@ providing_technologies = none [savedsearch://ESCU - EC2 Instance Started With Previously Unseen User - Rule] type = detection -asset_type = +asset_type = AWS Instance confidence = medium explanation = This search looks for EC2 instances being created by users who have not created them before. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. This search works best when you run the "Previously Seen EC2 Launches By User" support search once to create a history of previously seen ARNs. @@ -1838,7 +1838,7 @@ providing_technologies = none [savedsearch://ESCU - Email Attachments With Lots Of Spaces - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Attackers often use spaces as a means to obfuscate an attachment's file extension. This search looks for messages with email attachments that have many spaces within the file names. how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. The threshold ratio is set to 10%, but this value can be configured to suit each environment. \ @@ -1850,7 +1850,7 @@ providing_technologies = none [savedsearch://ESCU - Email files written outside of the Outlook directory - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks at the change-analysis data model and detects email files created outside the normal Outlook directory. how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. @@ -1860,7 +1860,7 @@ providing_technologies = none [savedsearch://ESCU - Email servers sending high volume traffic to hosts - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. @@ -1870,7 +1870,7 @@ providing_technologies = none [savedsearch://ESCU - Excessive DNS Failures - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences. how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. @@ -1880,7 +1880,7 @@ providing_technologies = none [savedsearch://ESCU - Execution of File With Spaces Before Extension - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for processes launched from files with at least five spaces in the name before the extension. This is typically done to obfuscate the file extension by pushing it outside of the default view. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -1890,7 +1890,7 @@ providing_technologies = none [savedsearch://ESCU - Execution of File with Multiple Extensions - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for processes launched from files that have double extensions in the file name. This is typically done to obscure the "real" file extension and make it appear as though the file being accessed is a data file, as opposed to executable content. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. @@ -1900,7 +1900,7 @@ providing_technologies = none [savedsearch://ESCU - Extended Period Without Successful Netbackup Backups - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search returns a list of hosts that have not successfully completed a backup in over a week. how_to_implement = To successfully implement this search you need to first obtain data from your backup solution, either from the backup logs on your hosts, or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your backup solution. Depending on how often you backup your systems, you may want to modify how far in the past to look for a successful backup, other than the default of seven days. @@ -1910,7 +1910,7 @@ providing_technologies = none [savedsearch://ESCU - File with Samsam Extension - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for file writes with extensions consistent with a SamSam ransomware attack. how_to_implement = You must be ingesting data that records file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -1920,7 +1920,7 @@ providing_technologies = none [savedsearch://ESCU - First Time Seen Running Windows Service - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the first time a Windows service is seen running in your environment. how_to_implement = While this search does not require you to adhere to Splunk CIM, you must be ingesting your Windows security-event logs in order for this search to execute successfully. The support search, `Previously Seen Running Windows Services`, should be run before this search to create the baseline of known Windows services. Please ensure that the Splunk Add-on for Microsoft Windows is version 5.0.0 or above. @@ -1930,7 +1930,7 @@ providing_technologies = none [savedsearch://ESCU - First time seen command line argument - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for command-line arguments that use a `/c` parameter to execute a command that has not previously been seen. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must be ingesting logs with both the process name and command line from your endpoints. The complete process name with command-line arguments are mapped to the "process" field in the Endpoint data model. Please make sure you run the support search "Previously seen command line arguments,"—which creates a lookup file called `previously_seen_cmd_line_arguments.csv`—a historical baseline of all command-line arguments. You must also validate this list. For the search to do accurate calculation, ensure the search scheduling is the same value as the `relative_time` evaluation function. @@ -1940,7 +1940,7 @@ providing_technologies = none [savedsearch://ESCU - GCP GCR container uploaded - Rule] type = detection -asset_type = +asset_type = GCP GCR Container confidence = medium explanation = This search show information on uploaded containers including source user, account, action, bucket name event name, http user agent, message and destination path. how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a subpub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_gcp_detection_filter` macro to filter out the false positives. @@ -1950,7 +1950,7 @@ providing_technologies = none [savedsearch://ESCU - GCP Kubernetes cluster scan detection - Rule] type = detection -asset_type = +asset_type = GCP Kubernetes cluster confidence = medium explanation = This search provides information of unauthenticated requests via user agent, and authentication data against Kubernetes cluster how_to_implement = You must install the GCP App for Splunk (version 2.0.0 or later), then configure stackdriver and set a Pub/Sub subscription to be imported to Splunk. You must also install Cloud Infrastructure data model.Customize the macro kubernetes_gcp_scan_fingerprint_attack_detection to filter out FPs. @@ -1970,7 +1970,7 @@ providing_technologies = none [savedsearch://ESCU - Hosts receiving high volume of network traffic from email server - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for an increase of data transfers from your email server to your clients. This could be indicative of a malicious actor collecting data using your email server. how_to_implement = This search requires you to be ingesting your network traffic and populating the Network_Traffic data model. Your email servers must be categorized as "email_server" for the search to work, as well. You may need to adjust the deviation_threshold and minimum_data_samples values based on the network traffic in your environment. The "deviation_threshold" field is a multiplying factor to control how much variation you're willing to tolerate. The "minimum_data_samples" field is the minimum number of connections of data samples required for the statistic to be valid. @@ -1980,7 +1980,7 @@ providing_technologies = none [savedsearch://ESCU - Identify New User Accounts - Rule] type = detection -asset_type = +asset_type = Domain Server confidence = medium explanation = This detection search will help profile user accounts in your environment by identifying newly created accounts that have been added to your network in the past week. how_to_implement = To successfully implement this search, you need to be populating the Enterprise Security Identity_Management data model in the assets and identity framework. @@ -1990,7 +1990,7 @@ providing_technologies = none [savedsearch://ESCU - Large Volume of DNS ANY Queries - Rule] type = detection -asset_type = +asset_type = DNS Servers confidence = medium explanation = The search is used to identify attempts to use your DNS Infrastructure for DDoS purposes via a DNS amplification attack leveraging ANY queries. how_to_implement = To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model. @@ -2000,7 +2000,7 @@ providing_technologies = none [savedsearch://ESCU - MacOS - Re-opened Applications - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for processes referencing the plist files that determine which applications are re-opened when a user reboots their machine. how_to_implement = In order to properly run this search, Splunk needs to ingest process data from your osquery deployed agents with the [splunk.conf](https://github.com/splunk/TA-osquery/blob/master/config/splunk.conf) pack enabled. Also the [TA-OSquery](https://github.com/splunk/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the data populate the Endpoint data model. @@ -2010,7 +2010,7 @@ providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Connect To Internet With Hidden Window - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for PowerShell processes started with parameters to modify the execution policy of the run, run in a hidden window, and connect to the Internet. This combination of command-line options is suspicious because it's overriding the default PowerShell execution policy, attempts to hide its activity from the user, and connects to the Internet. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2020,7 +2020,7 @@ providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Encoded Command - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for PowerShell processes that have encoded the script within the command-line. Malware has been seen using this parameter, as it obfuscates the code and makes it relatively easy to pass a script on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2030,7 +2030,7 @@ providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Execution Policy Bypass - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for PowerShell processes started with parameters used to bypass the local execution policy for scripts. These parameters are often observed in attacks leveraging PowerShell scripts as they override the default PowerShell execution policy. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2040,7 +2040,7 @@ providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process - Multiple Suspicious Command-Line Arguments - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for PowerShell processes started with a base64 encoded command-line passed to it, with parameters to modify the execution policy for the process, and those that prevent the display of an interactive prompt to the user. This combination of command-line options is suspicious because it overrides the default PowerShell execution policy, attempts to hide itself from the user, and passes an encoded script to be run on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2050,7 +2050,7 @@ providing_technologies = none [savedsearch://ESCU - Malicious PowerShell Process With Obfuscation Techniques - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for PowerShell processes launched with arguments that have characters indicative of obfuscation on the command-line. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2060,7 +2060,7 @@ providing_technologies = none [savedsearch://ESCU - Monitor DNS For Brand Abuse - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for DNS requests for faux domains similar to the domains that you want to have monitored for abuse. how_to_implement = You need to ingest data from your DNS logs. Specifically you must ingest the domain that is being queried and the IP of the host originating the request. Ideally, you should also be ingesting the answer to the query and the query type. This approach allows you to also create your own localized passive DNS capability which can aid you in future investigations. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -2070,7 +2070,7 @@ providing_technologies = none [savedsearch://ESCU - Monitor Email For Brand Abuse - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for emails claiming to be sent from a domain similar to one that you want to have monitored for abuse. how_to_implement = You need to ingest email header data. Specifically the sender's address (src_user) must be populated. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -2080,7 +2080,7 @@ providing_technologies = none [savedsearch://ESCU - Monitor Registry Keys for Print Monitors - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for registry activity associated with modifications to the registry key `HKLM\SYSTEM\CurrentControlSet\Control\Print\Monitors`. In this scenario, an attacker can load an arbitrary .dll into the print-monitor registry by giving the full path name to the after.dll. The system will execute the .dll with elevated (SYSTEM) permissions and will persist after reboot. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report registry modifications. @@ -2090,7 +2090,7 @@ providing_technologies = none [savedsearch://ESCU - Monitor Web Traffic For Brand Abuse - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for Web requests to faux domains similar to the one that you want to have monitored for abuse. how_to_implement = You need to ingest data from your web traffic. This can be accomplished by indexing data from a web proxy, or using a network traffic analysis tool, such as Bro or Splunk Stream. You also need to have run the search "ESCU - DNSTwist Domain Names", which creates the permutations of the domain that will be checked for. @@ -2100,7 +2100,7 @@ providing_technologies = none [savedsearch://ESCU - Multiple Okta Users With Invalid Credentails From The Same IP - Rule] type = detection -asset_type = +asset_type = Infrastructure confidence = medium explanation = This search detects Okta login failures due to bad credentials for multiple users originating from the same ip address. how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. @@ -2110,7 +2110,7 @@ providing_technologies = none [savedsearch://ESCU - New container uploaded to AWS ECR - Rule] type = detection -asset_type = +asset_type = AWS ECR container confidence = medium explanation = This searches show information on uploaded containers including source user, image id, source IP user type, http user agent, region, first time, last time of operation (PutImage). These searches are based on Cloud Infrastructure Data Model. how_to_implement = You must install the AWS App for Splunk (version 5.1.0 or later) and Splunk Add-on for AWS (version 4.4.0 or later), then configure your CloudTrail inputs. You must also install Cloud Infrastructure data model. Please also customize the `container_implant_aws_detection_filter` macro to filter out the false positives. @@ -2120,7 +2120,7 @@ providing_technologies = none [savedsearch://ESCU - No Windows Updates in a time frame - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for Windows endpoints that have not generated an event indicating a successful Windows update in the last 60 days. Windows updates are typically released monthly and applied shortly thereafter. An endpoint that has not successfully applied an update in this time frame indicates the endpoint is not regularly being patched for some reason. how_to_implement = To successfully implement this search, it requires that the 'Update' data model is being populated. This can be accomplished by ingesting Windows events or the Windows Update log via a universal forwarder on the Windows endpoints you wish to monitor. The Windows add-on should be also be installed and configured to properly parse Windows events in Splunk. There may be other data sources which can populate this data model, including vulnerability management systems. @@ -2130,7 +2130,7 @@ providing_technologies = none [savedsearch://ESCU - Okta Account Lockout Events - Rule] type = detection -asset_type = +asset_type = Infrastructure confidence = medium explanation = Detect Okta user lockout events how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. @@ -2140,7 +2140,7 @@ providing_technologies = none [savedsearch://ESCU - Okta Failed SSO Attempts - Rule] type = detection -asset_type = +asset_type = Infrastructure confidence = medium explanation = Detect failed Okta SSO events how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. @@ -2150,7 +2150,7 @@ providing_technologies = none [savedsearch://ESCU - Okta User Logins From Multiple Cities - Rule] type = detection -asset_type = +asset_type = Infrastructure confidence = medium explanation = This search detects logins from the same user from different states in a 24 hour period. how_to_implement = This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment. @@ -2160,7 +2160,7 @@ providing_technologies = none [savedsearch://ESCU - Open Redirect in Splunk Web - Rule] type = detection -asset_type = +asset_type = Splunk Server confidence = medium explanation = This search allows you to look for evidence of exploitation for CVE-2016-4859, the Splunk Open Redirect Vulnerability. how_to_implement = No extra steps needed to implement this search. @@ -2170,7 +2170,7 @@ providing_technologies = none [savedsearch://ESCU - Osquery pack - ColdRoot detection - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for ColdRoot events from the osx-attacks osquery pack. how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model @@ -2180,7 +2180,7 @@ providing_technologies = none [savedsearch://ESCU - Overwriting Accessibility Binaries - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = Microsoft Windows contains accessibility features that can be launched with a key combination before a user has logged in. An adversary can modify or replace these programs so they can get a command prompt or backdoor without logging in to the system. This search looks for modifications to these binaries. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -2190,7 +2190,7 @@ providing_technologies = none [savedsearch://ESCU - Process Execution via WMI - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for processes launched via WMI. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2200,7 +2200,7 @@ providing_technologies = none [savedsearch://ESCU - Processes Tapping Keyboard Events - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for processes in an MacOS system that is tapping keyboard events in MacOS, and essentially monitoring all keystrokes made by a user. This is a common technique used by RATs to log keystrokes from a victim, although it can also be used by legitimate processes like Siri to react on human input how_to_implement = In order to properly run this search, Splunk needs to ingest data from your osquery deployed agents with the [osx-attacks.conf](https://github.com/facebook/osquery/blob/experimental/packs/osx-attacks.conf#L599) pack enabled. Also the [TA-OSquery](https://github.com/d1vious/TA-osquery) must be deployed across your indexers and universal forwarders in order to have the osquery data populate the Alerts data model. @@ -2210,7 +2210,7 @@ providing_technologies = none [savedsearch://ESCU - Processes created by netsh - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for processes launching netsh.exe to execute various commands via the netsh command-line utility. Netsh.exe is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper .dll when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe that are executing commands via the command line. how_to_implement = To successfully implement this search, you must be ingesting logs with the process name, command-line arguments, and parent processes from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -2220,7 +2220,7 @@ providing_technologies = none [savedsearch://ESCU - Processes launching netsh - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for processes launching netsh.exe. Netsh is a command-line scripting utility that allows you to, either locally or remotely, display or modify the network configuration of a computer that is currently running. Netsh can be used as a persistence proxy technique to execute a helper DLL when netsh.exe is executed. In this search, we are looking for processes spawned by netsh.exe and executing commands via the command line. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model @@ -2230,7 +2230,7 @@ providing_technologies = none [savedsearch://ESCU - Prohibited Network Traffic Allowed - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for network traffic defined by port and transport layer protocol in the Enterprise Security lookup table "lookup_interesting_ports", that is marked as prohibited, and has an associated 'allow' action in the Network_Traffic data model. This could be indicative of a misconfigured network device. how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. @@ -2240,7 +2240,7 @@ providing_technologies = none [savedsearch://ESCU - Prohibited Software On Endpoint - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for applications on the endpoint that you have marked as prohibited. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is usually generated via logs that report process tracking in your Windows audit settings. In addition, you must also have only the `process_name` (not the entire process path) marked as "prohibited" in the Enterprise Security `interesting processes` table. To include the process names marked as "prohibited", which is included with ES Content Updates, run the included search Add Prohibited Processes to Enterprise Security. @@ -2250,7 +2250,7 @@ providing_technologies = none [savedsearch://ESCU - Protocol or Port Mismatch - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for network traffic on common ports where a higher layer protocol does not match the port that is being used. For example, this search should identify cases where protocols other than HTTP are running on TCP port 80. This can be used by attackers to circumvent firewall restrictions, or as an attempt to hide malicious communications over ports and protocols that are typically allowed and not well inspected. how_to_implement = Running this search properly requires a technology that can inspect network traffic and identify common protocols. Technologies such as Bro and Palo Alto Networks firewalls are two examples that will identify protocols via inspection, and not just assume a specific protocol based on the transport protocol and ports. @@ -2260,7 +2260,7 @@ providing_technologies = none [savedsearch://ESCU - Protocols passing authentication in cleartext - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for cleartext protocols at risk of leaking credentials. Currently, this consists of legacy protocols such as telnet, POP3, IMAP, and non-anonymous FTP sessions. While some of these protocols can be used over SSL, they typically run on different assigned ports in those cases. how_to_implement = This search requires you to be ingesting your network traffic, and populating the Network_Traffic data model. @@ -2270,7 +2270,7 @@ providing_technologies = none [savedsearch://ESCU - Reg exe Manipulating Windows Services Registry Keys - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for reg.exe modifying registry keys that define Windows services and their configurations. how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. @@ -2290,7 +2290,7 @@ providing_technologies = none [savedsearch://ESCU - Registry Keys Used For Persistence - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for modifications to registry keys that can be used to launch an application or service at system startup. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. @@ -2300,7 +2300,7 @@ providing_technologies = none [savedsearch://ESCU - Registry Keys Used For Privilege Escalation - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for modifications to registry keys that can be used to elevate privileges. The registry keys under "Image File Execution Options" are used to intercept calls to an executable and can be used to attach malicious binaries to benign system binaries. how_to_implement = To successfully implement this search, you must be ingesting data that records registry activity from your hosts to populate the endpoint data model in the registry node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. @@ -2310,7 +2310,7 @@ providing_technologies = none [savedsearch://ESCU - Registry Keys for Creating SHIM Databases - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for registry activity associated with application compatibility shims, which can be leveraged by attackers for various nefarious purposes. how_to_implement = To successfully implement this search, you must populate the Change_Analysis data model. This is typically populated via endpoint detection and response products, such as Carbon Black or other endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. @@ -2320,7 +2320,7 @@ providing_technologies = none [savedsearch://ESCU - Remote Desktop Network Bruteforce - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for RDP application network traffic and filters any source/destination pair generating more than twice the standard deviation of the average traffic. how_to_implement = You must ensure that your network traffic data is populating the Network_Traffic data model. @@ -2330,7 +2330,7 @@ providing_technologies = none [savedsearch://ESCU - Remote Desktop Network Traffic - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for network traffic on TCP/3389, the default port used by remote desktop. While remote desktop traffic is not uncommon on a network, it is usually associated with known hosts. This search allows for whitelisting both source and destination hosts to remove them from the output of the search so you can focus on the uncommon uses of remote desktop on your network. how_to_implement = To successfully implement this search you need to identify systems that commonly originate remote desktop traffic and that commonly receive remote desktop traffic. You can use the included support search "Identify Systems Creating Remote Desktop Traffic" to identify systems that originate the traffic and the search "Identify Systems Receiving Remote Desktop Traffic" to identify systems that receive a lot of remote desktop traffic. After identifying these systems, you will need to add the "common_rdp_source" or "common_rdp_destination" category to that system depending on the usage, using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in SA-IdentityManagement/lookups. @@ -2340,7 +2340,7 @@ providing_technologies = none [savedsearch://ESCU - Remote Desktop Process Running On System - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the remote desktop process mstsc.exe running on systems upon which it doesn't typically run. This is accomplished by filtering out all systems that are noted in the `common_rdp_source category` in the Assets and Identity framework. how_to_implement = To successfully implement this search, you must be ingesting data that records process activity from your hosts to populate the endpoint data model in the processes node. The search requires you to identify systems that do not commonly use remote desktop. You can use the included support search "Identify Systems Using Remote Desktop" to identify these systems. After identifying them, you will need to add the "common_rdp_source" category to that system using the Enterprise Security Assets and Identities framework. This can be done by adding an entry in the assets.csv file located in `SA-IdentityManagement/lookups`. @@ -2350,7 +2350,7 @@ providing_technologies = none [savedsearch://ESCU - Remote Process Instantiation via WMI - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for wmic.exe being launched with parameters to spawn a process on a remote system. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2360,7 +2360,7 @@ providing_technologies = none [savedsearch://ESCU - Remote Registry Key modifications - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search monitors for remote modifications to registry keys. how_to_implement = To successfully implement this search, you must populate the `Endpoint` data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the registry. @@ -2370,7 +2370,7 @@ providing_technologies = none [savedsearch://ESCU - Remote WMI Command Attempt - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for wmic.exe being launched with parameters to operate on remote systems. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2380,7 +2380,7 @@ providing_technologies = none [savedsearch://ESCU - RunDLL Loading DLL By Ordinal - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for DLLs under %AppData% being loaded by rundll32.exe that are calling the exported function at ordinal 2. Calling exported functions by ordinal is not as common as calling by exported name. There was a bug fixed in IDAPro on 2016-08-08 that would not display functions without names. Calling functions by ordinal would overcome the lack of name and make it harder for analyst to reverse engineer. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2390,7 +2390,7 @@ providing_technologies = none [savedsearch://ESCU - SMB Traffic Spike - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for spikes in the number of Server Message Block (SMB) traffic connections. how_to_implement = This search requires you to be ingesting your network traffic logs and populating the `Network_Traffic` data model. @@ -2400,7 +2400,7 @@ providing_technologies = none [savedsearch://ESCU - SMB Traffic Spike - MLTK - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search uses the Machine Learning Toolkit (MLTK) to identify spikes in the number of Server Message Block (SMB) connections. how_to_implement = To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, the Machine Learning Toolkit (MLTK) version 4.2 or greater must be installed on your search heads, along with any required dependencies. Finally, the support search "Baseline of SMB Traffic - MLTK" must be executed before this detection search, because it builds a machine-learning (ML) model over the historical data used by this search. It is important that this search is run in the same app context as the associated support search, so that the model created by the support search is available for use. You should periodically re-run the support search to rebuild the model with the latest data available in your environment.\ @@ -2413,7 +2413,7 @@ providing_technologies = none [savedsearch://ESCU - SQL Injection with Long URLs - Rule] type = detection -asset_type = +asset_type = Database Server confidence = medium explanation = This search looks for long URLs that have several SQL commands visible within them. how_to_implement = To successfully implement this search, you need to be monitoring network communications to your web servers or ingesting your HTTP logs and populating the Web data model. You must also identify your web servers in the Enterprise Security assets table. @@ -2423,7 +2423,7 @@ providing_technologies = none [savedsearch://ESCU - Samsam Test File Write - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for a file named "test.txt" written to the windows system directory tree, which is consistent with Samsam propagation. how_to_implement = You must be ingesting data that records the file-system activity from your hosts to populate the Endpoint file-system data-model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -2433,7 +2433,7 @@ providing_technologies = none [savedsearch://ESCU - Sc exe Manipulating Windows Services - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for arguments to sc.exe indicating the creation or modification of a Windows service. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2443,7 +2443,7 @@ providing_technologies = none [savedsearch://ESCU - Scheduled Task Name Used by Dragonfly Threat Actors - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a task name associated with the Dragonfly threat actor was created or deleted. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2453,7 +2453,7 @@ providing_technologies = none [savedsearch://ESCU - Scheduled tasks used in BadRabbit ransomware - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate that task names related to the execution of Bad Rabbit ransomware were created or deleted. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2463,7 +2463,7 @@ providing_technologies = none [savedsearch://ESCU - Schtasks scheduling job on remote system - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate a job is being scheduled on a remote system. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2473,7 +2473,7 @@ providing_technologies = none [savedsearch://ESCU - Schtasks used for forcing a reboot - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for flags passed to schtasks.exe on the command-line that indicate that a forced reboot of system is scheduled. how_to_implement = To successfully implement this search you need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -2483,7 +2483,7 @@ providing_technologies = none [savedsearch://ESCU - Script Execution via WMI - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for scripts launched via WMI. how_to_implement = You must be ingesting endpoint data that tracks process activity, including parent-child relationships from your endpoints to populate the Endpoint data model in the Processes node. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2493,7 +2493,7 @@ providing_technologies = none [savedsearch://ESCU - Shim Database File Creation - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for shim database files being written to default directories. The sdbinst.exe application is used to install shim database files (.sdb). According to Microsoft, a shim is a small library that transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. If you are using Sysmon, you will need a Splunk Universal Forwarder on each endpoint from which you want to collect data. @@ -2503,7 +2503,7 @@ providing_technologies = none [savedsearch://ESCU - Shim Database Installation With Suspicious Parameters - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search detects the process execution and arguments required to silently create a shim database. The sdbinst.exe application is used to install shim database files (.sdb). A shim is a small library which transparently intercepts an API, changes the parameters passed, handles the operation itself, or redirects the operation elsewhere. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2513,7 +2513,7 @@ providing_technologies = none [savedsearch://ESCU - Short Lived Windows Accounts - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search detects accounts that were created and deleted in a short time period. how_to_implement = This search requires you to have enabled your Group Management Audit Logs in your Local Windows Security Policy and be ingesting those logs. More information on how to enable them can be found here: http://whatevernetworks.com/auditing-group-membership-changes-in-active-directory/ @@ -2523,7 +2523,7 @@ providing_technologies = none [savedsearch://ESCU - Single Letter Process On Endpoint - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for process names that consist only of a single letter. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2533,7 +2533,7 @@ providing_technologies = none [savedsearch://ESCU - Spectre and Meltdown Vulnerable Systems - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search is used to detect systems that are still vulnerable to the Spectre and Meltdown vulnerabilities. how_to_implement = The search requires that you are ingesting your vulnerability-scanner data and that it reports the CVE of the vulnerability identified. @@ -2543,7 +2543,7 @@ providing_technologies = none [savedsearch://ESCU - Spike in File Writes - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for a sharp increase in the number of files written to a particular host how_to_implement = In order to implement this search, you must populate the Endpoint file-system data model node. This is typically populated via endpoint detection and response products, such as Carbon Black or endpoint data sources such as Sysmon. The data used for this search is typically generated via logs that report reads and writes to the file system. @@ -2553,7 +2553,7 @@ providing_technologies = none [savedsearch://ESCU - Splunk Enterprise Information Disclosure - Rule] type = detection -asset_type = +asset_type = Splunk Server confidence = medium explanation = This search allows you to look for evidence of exploitation for CVE-2018-11409, a Splunk Enterprise Information Disclosure Bug. how_to_implement = The REST endpoint that exposes system information is also necessary for the proper operation of Splunk clustering and instrumentation. Whitelisting your Splunk systems will reduce false positives. @@ -2563,7 +2563,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious Changes to File Associations - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for changes to registry values that control Windows file associations, executed by a process that is not typical for legitimate, routine changes to this area. how_to_implement = To successfully implement this search you need to be ingesting information on registry changes that include the name of the process responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Registry` nodes. @@ -2573,7 +2573,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious Email - UBA Anomaly - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA). how_to_implement = You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance. @@ -2583,7 +2583,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious Email Attachment Extensions - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for emails that have attachments with suspicious file extensions. how_to_implement = You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. \ @@ -2595,7 +2595,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious File Write - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for files created with names that have been linked to malicious activity. how_to_implement = You must be ingesting data that records the filesystem activity from your hosts to populate the Endpoint file-system data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or via other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file system reads and writes. In addition, this search leverages an included lookup file that contains the names of the files to watch for, as well as a note to communicate why that file name is being monitored. This lookup file can be edited to add or remove file the file names you want to monitor. @@ -2605,7 +2605,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious Java Classes - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for suspicious Java classes that are often used to exploit remote command execution in common Java frameworks, such as Apache Struts. how_to_implement = In order to properly run this search, Splunk needs to ingest data from your web-traffic appliances that serve or sit in the path of your Struts application servers. This can be accomplished by indexing data from a web proxy, or by using network traffic-analysis tools, such as Splunk Stream or Bro. @@ -2615,7 +2615,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious LNK file launching a process - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for a ``*.lnk` file under `C:\User*` or `*\Local\Temp\*` executing a process. This is common behavior used by various spear phishing tools. how_to_implement = You must be ingesting data that records filesystem and process activity from your hosts to populate the Endpoint data model. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or endpoint data sources, such as Sysmon. @@ -2625,7 +2625,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious Reg exe Process - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for reg.exe being launched from a command prompt not started by the user. When a user launches cmd.exe, the parent process is usually explorer.exe. This search filters out those instances. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2645,7 +2645,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious writes to System Volume Information - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search detects writes to the 'System Volume Information' folder by something other than the System process. how_to_implement = You need to be ingesting logs with both the process name and command-line from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. @@ -2655,7 +2655,7 @@ providing_technologies = none [savedsearch://ESCU - Suspicious writes to windows Recycle Bin - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search detects writes to the recycle bin by a process other than explorer.exe. how_to_implement = To successfully implement this search you need to be ingesting information on filesystem and process logs responsible for the changes from your endpoints into the `Endpoint` datamodel in the `Processes` and `Filesystem` nodes. @@ -2665,7 +2665,7 @@ providing_technologies = none [savedsearch://ESCU - System Processes Run From Unexpected Locations - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for system processes that normally run out of C:\Windows\System32\ or C:\Windows\SysWOW64 that are not run from that location. This can indicate a malicious process that is trying to hide as a legitimate process. how_to_implement = To successfully implement this search you need to ingest details about process execution from your hosts. Specifically, this search requires the process name and the full path to the process executable. @@ -2675,7 +2675,7 @@ providing_technologies = none [savedsearch://ESCU - TOR Traffic - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for network traffic identified as The Onion Router (TOR), a benign anonymity network which can be abused for a variety of nefarious purposes. how_to_implement = In order to properly run this search, Splunk needs to ingest data from firewalls or other network control devices that mediate the traffic allowed into an environment. This is necessary so that the search can identify an 'action' taken on the traffic of interest. The search requires the Network_Traffic data model be populated. @@ -2685,7 +2685,7 @@ providing_technologies = none [savedsearch://ESCU - USN Journal Deletion - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The fsutil.exe application is a legitimate Windows utility used to perform tasks related to the file allocation table (FAT) and NTFS file systems. The update sequence number (USN) change journal provides a log of all changes made to the files on the disk. This search looks for fsutil.exe deleting the USN journal. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. @@ -2695,7 +2695,7 @@ providing_technologies = none [savedsearch://ESCU - Uncommon Processes On Endpoint - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for applications on the endpoint that you have marked as uncommon. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. This search uses a lookup file `uncommon_processes_default.csv` to track various features of process names that are usually uncommon in most environments. Please consider updating `uncommon_processes_local.csv` to hunt for processes that are uncommon in your environment. @@ -2715,7 +2715,7 @@ providing_technologies = none [savedsearch://ESCU - Unsigned Image Loaded by LSASS - Rule] type = detection -asset_type = +asset_type = Windows confidence = medium explanation = This search detects loading of unsigned images by LSASS. how_to_implement = This search needs Sysmon Logs with a sysmon configuration, which includes EventCode 7 with lsass.exe. This search uses an input macro named `sysmon`. We strongly recommend that you specify your environment-specific configurations (index, source, sourcetype, etc.) for Windows Sysmon logs. Replace the macro definition with configurations for your Splunk environment. The search also uses a post-filter macro designed to filter out known false positives. @@ -2725,7 +2725,7 @@ providing_technologies = none [savedsearch://ESCU - Unsuccessful Netbackup backups - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search gives you the hosts where a backup was attempted and then failed. how_to_implement = To successfully implement this search you need to obtain data from your backup solution, either from the backup logs on your endpoints or from a central server responsible for performing the backups. If you do not use Netbackup, you can modify this search for your specific backup solution. @@ -2755,7 +2755,7 @@ providing_technologies = none [savedsearch://ESCU - Unusually Long Content-Type Length - Rule] type = detection -asset_type = +asset_type = Web Server confidence = medium explanation = This search looks for unusually long strings in the Content-Type http header that the client sends the server. how_to_implement = This particular search leverages data extracted from Stream:HTTP. You must configure the http stream using the Splunk Stream App on your Splunk Stream deployment server to extract the cs_content_type field. @@ -2765,7 +2765,7 @@ providing_technologies = none [savedsearch://ESCU - WMI Permanent Event Subscription - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the creation of WMI permanent event subscriptions. how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. @@ -2775,7 +2775,7 @@ providing_technologies = none [savedsearch://ESCU - WMI Permanent Event Subscription - Sysmon - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the creation of WMI permanent event subscriptions. how_to_implement = To successfully implement this search, you must be collecting Sysmon data using Sysmon version 6.1 or greater and have Sysmon configured to generate alerts for WMI activity. In addition, you must have at least version 6.0.4 of the Sysmon TA installed to properly parse the fields. @@ -2785,7 +2785,7 @@ providing_technologies = none [savedsearch://ESCU - WMI Temporary Event Subscription - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for the creation of WMI temporary event subscriptions. how_to_implement = To successfully implement this search, you must be ingesting the Windows WMI activity logs. This can be done by adding a stanza to inputs.conf on the system generating logs with a title of [WinEventLog://Microsoft-Windows-WMI-Activity/Operational]. @@ -2795,7 +2795,7 @@ providing_technologies = none [savedsearch://ESCU - Web Fraud - Account Harvesting - Rule] type = detection -asset_type = +asset_type = Account confidence = medium explanation = This search is used to identify the creation of multiple user accounts using the same email domain name. how_to_implement = We start with a dataset that provides visibility into the email address used for the account creation. In this example, we are narrowing our search down to the single web page that hosts the Magento2 e-commerce platform (via URI) used for account creation, the single http content-type to grab only the user's clicks, and the http field that provides the username (form_data), for performance reasons. After we have the username and email domain, we look for numerous account creations per email domain. Common data sources used for this detection are customized Apache logs or Splunk Stream. @@ -2805,7 +2805,7 @@ providing_technologies = none [savedsearch://ESCU - Web Fraud - Anomalous User Clickspeed - Rule] type = detection -asset_type = +asset_type = account confidence = medium explanation = This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session. how_to_implement = Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. @@ -2815,7 +2815,7 @@ providing_technologies = none [savedsearch://ESCU - Web Fraud - Password Sharing Across Accounts - Rule] type = detection -asset_type = +asset_type = account confidence = medium explanation = This search is used to identify user accounts that share a common password. how_to_implement = We need to start with a dataset that allows us to see the values of usernames and passwords that users are submitting to the website hosting the Magento2 e-commerce platform (commonly found in the HTTP form_data field). A tokenized or hashed value of a password is acceptable and certainly preferable to a clear-text password. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream. @@ -2825,7 +2825,7 @@ providing_technologies = none [savedsearch://ESCU - Web Servers Executing Suspicious Processes - Rule] type = detection -asset_type = +asset_type = Web Server confidence = medium explanation = This search looks for suspicious processes on all systems labeled as web servers. how_to_implement = You must be ingesting data that records process activity from your hosts to populate the Endpoint data model in the Processes node. You must also be ingesting logs with both the process name and command line from your endpoints. The command-line arguments are mapped to the "process" field in the Endpoint data model. In addition, web servers will need to be identified in the Assets and Identity Framework of Enterprise Security. @@ -2835,7 +2835,7 @@ providing_technologies = none [savedsearch://ESCU - Windows Event Log Cleared - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = This search looks for Windows events that indicate one of the Windows event logs has been purged. how_to_implement = To successfully implement this search, you need to be ingesting Windows event logs from your hosts. @@ -2845,7 +2845,7 @@ providing_technologies = none [savedsearch://ESCU - Windows hosts file modification - Rule] type = detection -asset_type = +asset_type = Endpoint confidence = medium explanation = The search looks for modifications to the hosts file on all Windows endpoints across your environment. how_to_implement = To successfully implement this search, you must be ingesting data that records the file-system activity from your hosts to populate the Endpoint.Filesystem data model node. This is typically populated via endpoint detection-and-response products, such as Carbon Black, or by other endpoint data sources, such as Sysmon. The data used for this search is typically generated via logs that report file-system reads and writes. From b9128cee7b0317b60d0a0fe0151bdee2203967cf Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 17:00:05 +0200 Subject: [PATCH 78/93] small bug --- bin/jinja2_templates/use_case_library.j2 | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bin/jinja2_templates/use_case_library.j2 b/bin/jinja2_templates/use_case_library.j2 index a47e922985..9a4166218d 100644 --- a/bin/jinja2_templates/use_case_library.j2 +++ b/bin/jinja2_templates/use_case_library.j2 @@ -39,7 +39,7 @@ how_to_implement = none {% endif %} annotations = {{ detection.mappings | tojson }} known_false_positives = {{ detection.known_false_positives }} -providing_technologies = none +providing_technologies = ["AWS"] {% endfor %} ### END DETECTIONS ### From 69e061606bda646cd37ff492f2983e9d28ea9fc0 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 17:10:08 +0200 Subject: [PATCH 79/93] test content api --- .circleci/config.yml | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 042eb1ef9d..7a38ecf088 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -458,6 +458,4 @@ workflows: - attack-range-update filters: tags: - only: /^v.*/ - branches: - ignore: /.*/ + only: /.*/ From d3ef1dabc4e27e0db6a4736122ba0a285b3c87a1 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 17:17:47 +0200 Subject: [PATCH 80/93] test content api --- .circleci/config.yml | 20 ++++++++++++-------- bin/jinja2_templates/use_case_library.j2 | 2 +- 2 files changed, 13 insertions(+), 9 deletions(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 7a38ecf088..371a2d0978 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -248,13 +248,15 @@ jobs: name: update community api sources command: | cd security-content - aws s3 cp stories s3://security-content-community/stories --recursive --exclude "*" --include "*.yml" - aws s3 cp baselines s3://security-content-community/baselines --recursive --exclude "*" --include "*.yml" - aws s3 cp detections s3://security-content-community/detections --recursive --exclude "*" --include "*.yml" - aws s3 cp investigations s3://security-content-community/investigations --recursive --exclude "*" --include "*.yml" - aws s3 cp responses s3://security-content-community/responses --recursive --exclude "*" --include "*.yml" - aws s3 cp lookups s3://security-content-community/lookups --recursive --exclude "*" --include "*.yml" - aws s3 cp macros s3://security-content-community/macros --recursive --exclude "*" --include "*.yml" + aws s3 cp stories s3://security-content/stories --recursive --exclude "*" --include "*.yml" + aws s3 cp baselines s3://security-content/baselines --recursive --exclude "*" --include "*.yml" + aws s3 cp detections s3://security-content/detections --recursive --exclude "*" --include "*.yml" + aws s3 cp response_tasks s3://security-content/response_tasks --recursive --exclude "*" --include "*.yml" + aws s3 cp responses s3://security-content/responses --recursive --exclude "*" --include "*.yml" + aws s3 cp lookups s3://security-content/lookups --recursive --exclude "*" --include "*.yml" + aws s3 cp lookups s3://security-content/lookups --recursive --exclude "*" --include "*.csv" + aws s3 cp macros s3://security-content/macros --recursive --exclude "*" --include "*.yml" + aws s3 cp deployments s3://security-content/deployments --recursive --exclude "*" --include "*.yml" - persist_to_workspace: root: ~/ paths: @@ -458,4 +460,6 @@ workflows: - attack-range-update filters: tags: - only: /.*/ + only: /^v.*/ + branches: + ignore: /.*/ diff --git a/bin/jinja2_templates/use_case_library.j2 b/bin/jinja2_templates/use_case_library.j2 index 9a4166218d..292ca19b92 100644 --- a/bin/jinja2_templates/use_case_library.j2 +++ b/bin/jinja2_templates/use_case_library.j2 @@ -39,7 +39,7 @@ how_to_implement = none {% endif %} annotations = {{ detection.mappings | tojson }} known_false_positives = {{ detection.known_false_positives }} -providing_technologies = ["AWS"] +providing_technologies = [] {% endfor %} ### END DETECTIONS ### From 3da73d36d0b1a334842c3c92a3ce9d3f46c6f9a6 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Mon, 25 May 2020 15:32:43 +0000 Subject: [PATCH 81/93] Bump six from 1.14.0 to 1.15.0 Bumps [six](https://github.com/benjaminp/six) from 1.14.0 to 1.15.0. - [Release notes](https://github.com/benjaminp/six/releases) - [Changelog](https://github.com/benjaminp/six/blob/master/CHANGES) - [Commits](https://github.com/benjaminp/six/compare/1.14.0...1.15.0) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 33cd21ab39..3eb6848391 100644 --- a/requirements.txt +++ b/requirements.txt @@ -26,7 +26,7 @@ requests==2.23.0 scandir==1.10.0 semantic-version==2.8.5 simplejson==3.17.0 -six==1.14.0 +six==1.15.0 stix2==1.4.0 stix2-patterns==1.3.0 taxii2-client==2.0.0 From d1e645e1832d89457c950d158f2c067146ce3c54 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Mon, 25 May 2020 15:32:43 +0000 Subject: [PATCH 82/93] Bump virtualenv from 20.0.20 to 20.0.21 Bumps [virtualenv](https://github.com/pypa/virtualenv) from 20.0.20 to 20.0.21. - [Release notes](https://github.com/pypa/virtualenv/releases) - [Changelog](https://github.com/pypa/virtualenv/blob/20.0.21/docs/changelog.rst) - [Commits](https://github.com/pypa/virtualenv/compare/20.0.20...20.0.21) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 33cd21ab39..17eef85471 100644 --- a/requirements.txt +++ b/requirements.txt @@ -33,5 +33,5 @@ taxii2-client==2.0.0 toml==0.10.0 typing==3.7.4.1 urllib3==1.25.9 -virtualenv==20.0.20 +virtualenv==20.0.21 zipp==3.1.0 From 0991f6498c451093262f5f85edb4d85b19eabc20 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Mon, 25 May 2020 15:32:43 +0000 Subject: [PATCH 83/93] Bump more-itertools from 8.2.0 to 8.3.0 Bumps [more-itertools](https://github.com/more-itertools/more-itertools) from 8.2.0 to 8.3.0. - [Release notes](https://github.com/more-itertools/more-itertools/releases) - [Commits](https://github.com/more-itertools/more-itertools/compare/v8.2.0...v8.3.0) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 33cd21ab39..49136b6186 100644 --- a/requirements.txt +++ b/requirements.txt @@ -14,7 +14,7 @@ importlib-resources==1.5.0 Jinja2==2.11.2 jsonschema==3.2.0 MarkupSafe==1.1.1 -more-itertools==8.0.2 +more-itertools==8.3.0 nodeenv==1.3.3 pathlib2==2.3.5 pre-commit==1.20.0 From e9c7ae28a585642b17bdcda5f21bb66af4dc8004 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 18:00:46 +0200 Subject: [PATCH 84/93] small bug bix --- .circleci/config.yml | 4 +--- ...1.yml => enterprise_security_deployment_configuration.yml} | 0 2 files changed, 1 insertion(+), 3 deletions(-) rename deployments/{deployment_example_1.yml => enterprise_security_deployment_configuration.yml} (100%) diff --git a/.circleci/config.yml b/.circleci/config.yml index 371a2d0978..892e563f32 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -460,6 +460,4 @@ workflows: - attack-range-update filters: tags: - only: /^v.*/ - branches: - ignore: /.*/ + only: /.*/ diff --git a/deployments/deployment_example_1.yml b/deployments/enterprise_security_deployment_configuration.yml similarity index 100% rename from deployments/deployment_example_1.yml rename to deployments/enterprise_security_deployment_configuration.yml From 32a9f80a5ba027e6078fdc0152a3b6369815e600 Mon Sep 17 00:00:00 2001 From: Patrick Bareiss Date: Mon, 25 May 2020 18:09:31 +0200 Subject: [PATCH 85/93] content api tested --- .circleci/config.yml | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.circleci/config.yml b/.circleci/config.yml index 892e563f32..371a2d0978 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -460,4 +460,6 @@ workflows: - attack-range-update filters: tags: - only: /.*/ + only: /^v.*/ + branches: + ignore: /.*/ From 95372f2a2f10a913340dd1e9a91d9005116f0c95 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Tue, 26 May 2020 14:12:55 +0000 Subject: [PATCH 86/93] Bump pytz from 2019.3 to 2020.1 Bumps [pytz](https://github.com/stub42/pytz) from 2019.3 to 2020.1. - [Release notes](https://github.com/stub42/pytz/releases) - [Commits](https://github.com/stub42/pytz/compare/release_2019.3...release_2020.1) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cb090fa6e8..fce129b1c8 100644 --- a/requirements.txt +++ b/requirements.txt @@ -20,7 +20,7 @@ pathlib2==2.3.5 pre-commit==1.20.0 pyrsistent==0.15.6 python-dateutil==2.8.1 -pytz==2019.3 +pytz==2020.1 PyYAML==5.3.1 requests==2.23.0 scandir==1.10.0 From 62f5042d7c5f3dce1d87741f6341211cfadb8eee Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Tue, 26 May 2020 14:13:17 +0000 Subject: [PATCH 87/93] Bump cfgv from 2.0.1 to 3.1.0 Bumps [cfgv](https://github.com/asottile/cfgv) from 2.0.1 to 3.1.0. - [Release notes](https://github.com/asottile/cfgv/releases) - [Commits](https://github.com/asottile/cfgv/compare/v2.0.1...v3.1.0) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index cb090fa6e8..7f79fd41e6 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,7 +3,7 @@ aspy.yaml==1.3.0 attackcti==0.3.2 attrs==19.3.0 certifi==2020.4.5.1 -cfgv==2.0.1 +cfgv==3.1.0 chardet==3.0.4 configparser==4.0.2 contextlib2==0.6.0.post1 From 19e17e99750d1eb758867494c2bc1e751270735c Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Tue, 26 May 2020 14:19:13 +0000 Subject: [PATCH 88/93] Bump pre-commit from 2.3.0 to 2.4.0 Bumps [pre-commit](https://github.com/pre-commit/pre-commit) from 2.3.0 to 2.4.0. - [Release notes](https://github.com/pre-commit/pre-commit/releases) - [Changelog](https://github.com/pre-commit/pre-commit/blob/master/CHANGELOG.md) - [Commits](https://github.com/pre-commit/pre-commit/compare/v2.3.0...v2.4.0) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 2704175567..bcbbcd44bb 100644 --- a/requirements.txt +++ b/requirements.txt @@ -17,7 +17,7 @@ MarkupSafe==1.1.1 more-itertools==8.3.0 nodeenv==1.3.3 pathlib2==2.3.5 -pre-commit==1.20.0 +pre-commit==2.4.0 pyrsistent==0.15.6 python-dateutil==2.8.1 pytz==2020.1 From a53e1aabb243207617ca70cd1abd9a6386b0e933 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Tue, 26 May 2020 14:19:14 +0000 Subject: [PATCH 89/93] Bump configparser from 4.0.2 to 5.0.0 Bumps [configparser](https://github.com/jaraco/configparser) from 4.0.2 to 5.0.0. - [Release notes](https://github.com/jaraco/configparser/releases) - [Changelog](https://github.com/jaraco/configparser/blob/master/CHANGES.rst) - [Commits](https://github.com/jaraco/configparser/compare/v4.0.2...v5.0.0) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 2704175567..e803933b0b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -5,7 +5,7 @@ attrs==19.3.0 certifi==2020.4.5.1 cfgv==3.1.0 chardet==3.0.4 -configparser==4.0.2 +configparser==5.0.0 contextlib2==0.6.0.post1 identify==1.4.16 idna==2.9 From d1d4044dd6ec8fb861e7ebbaaa3d5f590cf74301 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Tue, 26 May 2020 14:26:45 +0000 Subject: [PATCH 90/93] Bump pyrsistent from 0.15.6 to 0.16.0 Bumps [pyrsistent](https://github.com/tobgu/pyrsistent) from 0.15.6 to 0.16.0. - [Release notes](https://github.com/tobgu/pyrsistent/releases) - [Changelog](https://github.com/tobgu/pyrsistent/blob/master/CHANGES.txt) - [Commits](https://github.com/tobgu/pyrsistent/compare/v0.15.6...v0.16.0) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 4d18f2b621..91db7155cc 100644 --- a/requirements.txt +++ b/requirements.txt @@ -18,7 +18,7 @@ more-itertools==8.3.0 nodeenv==1.3.3 pathlib2==2.3.5 pre-commit==2.4.0 -pyrsistent==0.15.6 +pyrsistent==0.16.0 python-dateutil==2.8.1 pytz==2020.1 PyYAML==5.3.1 From 116b1dbb238772b88f7ec4eb7ba30642c2382b24 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Tue, 26 May 2020 14:33:11 +0000 Subject: [PATCH 91/93] Bump nodeenv from 1.3.3 to 1.3.5 Bumps [nodeenv](https://github.com/ekalinin/nodeenv) from 1.3.3 to 1.3.5. - [Release notes](https://github.com/ekalinin/nodeenv/releases) - [Changelog](https://github.com/ekalinin/nodeenv/blob/master/CHANGES) - [Commits](https://github.com/ekalinin/nodeenv/compare/1.3.3...1.3.5) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 91db7155cc..021ea66934 100644 --- a/requirements.txt +++ b/requirements.txt @@ -15,7 +15,7 @@ Jinja2==2.11.2 jsonschema==3.2.0 MarkupSafe==1.1.1 more-itertools==8.3.0 -nodeenv==1.3.3 +nodeenv==1.3.5 pathlib2==2.3.5 pre-commit==2.4.0 pyrsistent==0.16.0 From 788a09cdef8eaef0eacfd3a5e922adc763f8b840 Mon Sep 17 00:00:00 2001 From: Rico Valdez Date: Tue, 26 May 2020 14:33:08 -0600 Subject: [PATCH 92/93] fix as the strptime function wasn't correct --- ...ccount_activity_from_previously_unseen_account.yml | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/detections/aws_cross_account_activity_from_previously_unseen_account.yml b/detections/aws_cross_account_activity_from_previously_unseen_account.yml index 9873b76700..0856164363 100644 --- a/detections/aws_cross_account_activity_from_previously_unseen_account.yml +++ b/detections/aws_cross_account_activity_from_previously_unseen_account.yml @@ -1,6 +1,6 @@ name: AWS Cross Account Activity From Previously Unseen Account id: 64fbbddf-fabf-4edf-80b3-0cc36ef37727 -version: 2 +version: 3 date: '2018-11-02' description: This search looks for AssumeRole events where an IAM role in a different account is requested for the first time. @@ -15,12 +15,11 @@ author: David Dorsey, Splunk search: '`cloudtrail` eventName=AssumeRole | spath output=requestingAccountId path=userIdentity.accountId | spath output=requestedAccountId path=resources{}.accountId | search requestingAccountId=* | where requestingAccountId != requestedAccountId | inputlookup append=t previously_seen_aws_cross_account_activity - | multireport [| stats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d %H:%M:%S")))) - as firstTime max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), lastTime))) + | multireport [| stats min(eval(coalesce(firstTime, _time))) + as firstTime max(eval(coalesce(lastTime, _time))) as lastTime by requestingAccountId, requestedAccountId | outputlookup previously_seen_aws_cross_account_activity - | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, strptime(_time,"%Y-%m-%d - %H:%M:%S")))) as firstTime, max(eval(coalesce(strptime(_time,"%Y-%m-%d %H:%M:%S"), - lastTime))) as lastTime by requestingAccountId, requestedAccountId | where firstTime + | where fact=fiction] [| eventstats min(eval(coalesce(firstTime, _time))) as firstTime, + max(eval(coalesce(lastTime, _time))) as lastTime by requestingAccountId, requestedAccountId | where firstTime >= relative_time(now(), "-70m@m") AND isnotnull(_time) | spath output=accessKeyId path=responseElements.credentials.accessKeyId | spath output=requestingARN path=resources{}.ARN | stats values(awsRegion) as awsRegion values(firstTime) as firstTime values(lastTime) From 17fd0abcc9d252f815cc1986dbd830b7e75c3174 Mon Sep 17 00:00:00 2001 From: "dependabot-preview[bot]" <27856297+dependabot-preview[bot]@users.noreply.github.com> Date: Tue, 26 May 2020 21:22:11 +0000 Subject: [PATCH 93/93] Bump identify from 1.4.16 to 1.4.17 Bumps [identify](https://github.com/chriskuehl/identify) from 1.4.16 to 1.4.17. - [Release notes](https://github.com/chriskuehl/identify/releases) - [Commits](https://github.com/chriskuehl/identify/compare/v1.4.16...v1.4.17) Signed-off-by: dependabot-preview[bot] --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index 021ea66934..7964b28e3c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -7,7 +7,7 @@ cfgv==3.1.0 chardet==3.0.4 configparser==5.0.0 contextlib2==0.6.0.post1 -identify==1.4.16 +identify==1.4.17 idna==2.9 importlib-metadata==1.6.0 importlib-resources==1.5.0